Our research contributions in AI, optimization, and intelligent port systems.
BACKGROUND: F-FDG PET/CT examinations for staging and response assessment, raising concerns about cumulative radiation dose, particularly from the CT component. We propose SnapPET, a CT-sparing deep l...
The adoption of immersive virtual reality (IVR) for gamified rehabilitation is increasing. However, a significant challenge relates to perceptions of virtual environments as empty and isolating, poten...
Many studies have shown that collaborative tasks in immersive virtual reality (VR) and augmented reality (AR) environments can enhance collaborative outcomes in learning, training, and game-based cont...
This work investigates UAV viewpoint planning for high-quality 3D reconstruction and introduces DynaView, a framework that synergizes a learned reconstructability predictor with continuous optimizatio...
The rapid advancements in PET technology, coupled with the need for accurate and efficient imaging, necessitate the development of robust and generalizable methods for CT-free attenuation and scatter ...
• Integrates geo-fenced station planning with incentive-based inventory management. • Data-driven clustering optimizes station locations and capacities using historical riding data. • Designs optimal ...
This report presents a framework that enables the reproduction and extension of our empirical evaluations using Large Language Models (LLMs) for automated web-form-test generation. The framework inclu...
REpresentation State Transfer (REST) is an architectural style for designing web applications that enables scalable, stateless communication between clients and servers via common HTTP techniques. Web...
This paper introduces MeLA, a Metacognitive LLM-Driven Architecture that presents a new paradigm for Automatic Heuristic Design (AHD). Traditional nature evolutionary methods operate directly on heuri...
While visual reasoning for simple analogies has received significant attention, compositional visual relations (CVR) remain relatively unexplored due to their greater complexity. To solve CVR tasks, w...
Multi-objective optimization (MOO) has been widely studied in literature because of its versatility in human-centered decision making in real-life applications. Recently, demand for dynamic MOO is fas...
Random testing (RT) is an essential software testing strategy that selects test cases based on a random distribution. Adaptive RT (ART) encompasses a group of test‐case selection/generation methods th...
Recently, researchers have achieved significant results in the skeleton-based action recognition. To better model the skeleton sequences, we drive the encoder to learn more discriminative representati...
Sensors constitute a fundamental element of modern digital healthcare, acting as the primary interface for capturing physiological, environmental, and biomechanical data from patients and clinical set...
Medical image segmentation is essential for clinical diagnosis and treatment planning. Although transformer-based methods have achieved remarkable results, their high computational cost hinders clinic...
The Segment Anything Model 2 (SAM2) demonstrates remarkable universal segmentation capabilities on natural images. However, its performance on ultrasound images is significantly degraded due to domain...
Cognitive radio (CR) provides key technical support for the seamless communication of consumer electronic (CE) devices through distributed cooperative sensing and spectrum access. However, its opennes...
Insufficient training in firefighting techniques increases the risk of injuries and fatalities among firefighters. Human activity recognition methods show promising potential for performance monitorin...
ABSTRACT With the increasingly frequent attacks on software systems, software security is an issue that must be addressed. Within software security, automated detection of software vulnerabilities is ...
BACKGROUND: Breast tumor segmentation is crucial for the diagnosis of breast cancer, as it enables radiologists to rapidly identify areas of interest and facilitate subsequent analysis, diagnosis, and...
Identifying circRNA-miRNA associations is critical for understanding gene regulatory mechanisms, discovering new biomarkers, and developing therapeutic strategies. The ongoing advancement of autonomou...
Dynamic novel view synthesis (NVS) aims to render time-varying scenes from arbitrary viewpoints, balancing rendering quality and computational efficiency. While recent 4D Gaussian Splatting approaches...
Puzzle solving has recently become a popular research topic. Existing solvers often overlook puzzles with missing pieces. The missing pieces, together with gaps between pieces, pose significant challe...
Learning effective molecular representations is crucial for accurate property prediction in artificial intelligence (AI)-aided drug discovery. Graph and fingerprint representations have been widely us...
Simultaneous localization and mapping (SLAM) in indoor environments remains a critical challenge, especially in GPS-denied areas where real-time Performance, low cost, and robustness are required. Tra...
Large language models (LLMs) have rapidly become a powerful tool in automated code generation, yet most research has focused on their correctness and efficiency rather than the stylistic patterns of t...
Abstract visual reasoning (AVR) is a critical ability of humans, and it has been widely studied, but arithmetic visual reasoning, a unique task in AVR to reason over number sense, is less studied in t...
As autonomous vehicles (AVs) become increasingly widespread, the intelligent driving control and safety concerns have emerged. Recent advents in Internet of Things (IoTs) and 6G technologies have vast...
The universality of deep neural networks across different modalities and their generalization capabilities to unseen domains play an essential role in medical image segmentation. The recent segment an...
Executing neural networks on resource-constrained embedded devices faces challenges. Efforts have been made at the application and system levels to reduce the execution cost. Among them, the early-exi...
As consumer electronics (CEs) continue to become more intelligent and interconnected, end-edge-cloud collaborative computing is an essential paradigm to meet the demands of cross-application dependent...
Dynamic positron emission tomography (PET) parametric imaging typically requires a 60-minute acquisition period, causing patient discomfort and reducing clinical efficiency. This study explores the fe...
ABSTRACT We investigate the impact of firms' Environmental, Social and Governance (ESG) activities on stock price crash risk during crises. We use the US–China trade war as a negative external shock a...
Sequential recommendation is becoming more critical in a variety of e-commerce platforms. The aim of sequential recommender systems is to model the dynamic preferences of users based on their previous...
The Internet of Medical Things (IoMT) has transformed healthcare by integrating medical devices, wearables, and electronic medical records (EMRs). These technologies enable real-time diagnostics, pers...
Machine learning (ML) techniques are applied for profiling computing and processing resources data collected while running deep neural network models on edge devices. Adaptive deep neural network (DNN...
• Eco-friendly ultrasound-intensified continuous preparation of AgNPs was developed. • Key synthesis parameters governed the physicochemical properties of AgNPs. • 2–5 nm spherical AgNPs exhibited enh...
As the level of intelligence in agricultural consumer electronics continues to advance, data-driven devices are often faced with challenges such as resource shortages, high real-time requirements, and...
The increasing demand for accurate and accessible cancer detection has driven the development of AI-driven diagnostic systems on consumer-grade medical electronics. However, deploying large-scale deep...
University of Nottingham Ningbo China (UNNC) was the first Sino-foreign higher education institution (SfHEI). It has a history of innovation, including through collaborations with students in research...
Equality graphs (E-graphs) offer a compact representation for vast sets of equivalent implementations, proving invaluable in hardware synthesis and program optimization. Nevertheless, extracting the o...
The rapid development of Large Language Models (LLMs), such as ChatGPT and DeepSeek, has revolutionized software development, particularly in the domain of automated code generation. These models, bui...
The increasing complexity of deep learning models, especially in black-box scenarios, presents significant challenges to traditional software testing methods. Due to the lack of transparency in neural...
Recent advancements in immersive virtual reality (IVR) have highlighted its expanding potential in educational settings. However, the influence of learners’ interpersonal relationships on their prefer...
We identify that technology crowdfunding campaigns attracting more domestic investors have a higher probability of project success and examine the role of home bias in supporting online innovative ent...
Routing congestion prediction expedites the closure of FPGA placement and routing (PnR). Current prediction methods employ convolutional models, taking advantage of their capacity of dealing with imag...
The state-of-the-art YOLO detection algorithms still suffer from the issue of redundant extraction of similar features during feature propagation, and the simplistic stacking approach of connecting di...
Physics education often faces challenges in communicating abstract concepts effectively and maintaining student interest. This study explored the integration of immersive virtual reality (IVR) with ga...
Pedagogical agents (PAs) have been extensively employed in im-mersive virtual reality (IVR) educational settings, yet their specific attributes are not thoroughly investigated. This study explores the...
Edge computing (EC) represents a basic functionality to support the efficiency of the future Internet of intelligent things. The EC has promoted container adoption for deploying and managing applicati...
• A novel multi-modal Fusion-based Unified Security and Energy Efficiency approach for Industrial Systems (FUSE-IS) framework • FUSE-IS integrates deep learning, differential privacy, and carbon-aware...
Medical Consumer Electronics (MCE) have greatly facilitated people’s lives, allowing patients to obtain personal medical information including medical images. These medical images obtained from MCE ne...
Integrating natural language processing (NLP) with generative pre-trained transformer (GPT) models plays a pivotal role in enhancing the accuracy and efficiency of healthcare software, which is essent...
As the global population ages, sarcopenia—age-related muscle decline—demands innovative solutions. This paper introduces GRIPPY, a VR grip controller that transforms basic handgrip exercises into imme...
Web 3.0 is the next era in internet development, and it is characterized as being decentralization, semantic intelligence and user experience oriented. The previous eras focused on user-generated cont...
Ultrasound imaging is the most commonly used method for screening thyroid nodules due to its low cost and non-invasive nature. Thyroid nodule lesions have variable shapes, rich aspect ratios, unclear ...
China’s national academies have long served as barometers of academic development and scientific prestige. We use publicly available information to develop a dataset comprising 3,534 academy member pr...
This paper investigates the association between firm innovation and endowment-based fundamental factors through the lens of congruence and then examines the impact of a national-level industrial polic...
Context: This paper provides an in-depth examination of the generation and evaluation of Metamorphic Relations (MRs) using GPT models developed by OpenAI, with a particular focus on the capabilities o...
Video captioning, bridging computer vision and natural language, is crucial for various knowledge-based systems in the age of video streaming. Recent video captioning approaches have shown promise by ...
Testing web forms is an essential activity for ensuring the quality of web applications. It typically involves evaluating the interactions between users and forms. Automated test-case generation remai...
This paper examines the influence of syndicated investments involving governmental venture capital (GVC) and private venture capital firms (PVC) on the success of innovative companies in China. By ana...
Formal verification of heavily optimized multipliers is a critical yet challenging problem in both industry and academia. Current approaches suffer from fundamental limitations: Symbolic Computer Alge...
Empowered by Large Language Models (LLMs), substantial progress has been made in enhancing the EDA design flow in terms of high-level synthesis, such as direct translation from high-level language int...
We propose a comprehensive and practical framework for Chinese corporate fraud prediction which incorporates classifiers, class imbalance, population drift, segmented models, and model evaluation usin...
Medical image segmentation plays an important role in computer-aided diagnosis. Traditional convolution-based U-shape segmentation architectures are usually limited by the local receptive field. Exist...
In this work, we present a novel multi-modal, end-to-end, marker-free motion capture framework designed to estimate the six degrees of freedom (6-DoF) states of objects. Traditional motion capture sys...
Through Internet of Things (IoT) communication technology, collaborative perception enhances a vehicle’s capacity to discern its surroundings while driving by integrating and synchronizing sensor data...
ABSTRACT Metamorphic testing (MT) is an effective software quality assurance method; it uses metamorphic relations (MRs) to examine the inputs and outputs of multiple test cases. Metamorphic explorati...
The rapid changes in technology available for teaching and learning have led to a wide variety of potential tools that can be deployed to support a student's education experience. This article examine...
The Internet of Medical Things (IoMT) introduces complex security challenges as interconnected medical devices enlarge the attack surface and limit the effectiveness of traditional intrusion detection...
The robust segmentation of different targets in multiple modality images is challenging due to factors such as low contrast, variations in target size and shape, and interference from diseases, which ...
Urban land-use optimization plays a vital role in mitigating the escalating carbon emissions of rapidly growing cities. This study employs advanced computational intelligence to address urban carbon r...
Data-driven genetic programming (GP) has proven highly effective in solving combinatorial optimization problems under dynamic and uncertain environments. A central challenge lies in fast fitness evalu...
Formal verification of large-scale optimized integer multipliers remains a critical yet insufficiently addressed challenge in industry and academia. Current methods employ reference multiplier generat...
The International Workshop on NeuroPhysiological Approaches for Interactive Information Retrieval (NeuroPhysIIR'25), co-located with ACM SIGIR CHIIR 2025 in Naarm/Melbourne, Australia, included 19 par...
As an important way of assuring software quality, software testing generates and executes test cases to identify software failures. Many strategies have been proposed to guide test-case generation, su...
Autonomous Mobile Robots (AMRs) have garnered significant attention and widespread application due to their operational efficiency. However, in human-centered environments, such as warehouses, manufac...
Modern neural architecture search (NAS) is inherently multi-objective balancing trade-offs such as accuracy, parameter count, and computational cost. This complexity makes NAS computationally expensiv...
The exponential growth of sensitive patient information and diagnostic records in digital healthcare systems has increased the complexity of data protection, while frequent medical data breaches sever...
Sustaining patient engagement in physical rehabilitation for conditions of venous thromboembolism (VTE) prevention is often challenging due to factors such as the repetitive nature of the rehabilitati...
This paper examines the valuation impact of investigations related to the alleged infringement of American intellectual property (IP) rights, specifically Section 337 investigations, on Chinese techno...
The paper investigates the negative effect of the COVID-19 crisis on supply chain financing in China. It examines the role of blockchain adoption in mitigating such disruptions by using data from Chin...
The War for Chinese Talent in America: The Politics of Technology and Knowledge in Sino-U.S. Relations David Zweig. Ann Arbor, MI: Association for Asian Studies, 2024. xxiv + 222 pp. $26.00; £22.00 (p...
In this paper, we propose a reconfigurable intelligent surface (RIS)-aided wireless powered anti-jamming communication network (WPAJCN), where the RIS is utilized to participate in downlink wireless p...
Cancer remains a leading global health issue, where accurate and timely diagnosis is critical for effective treatment. The Internet of Medical Things (IoMT), an interconnected network of medical devic...
• Intelligence augmentation tool enhances the quality of empathic medical conversation. • EOPD enables empathic opportunity recognition, tailors personalized communication. • Multi-modal emotion data ...
Credit risk refers to the possibility that a borrower fails to meet contractual repayment obligations, posing potential losses to lenders. This study aims to enhance post-loan default prediction in cr...
Virtual Production (VP) is a novel approach to filmmaking that blends real-time computer graphics, live-action footage, and cutting-edge technologies (such as LED volumes and game engines like Unreal ...
The convergence of virtual reality live streaming and AI-driven avatars has emerged as a significant technological trend. However, current integration attempts remain in the proof-of-concept stage, wi...
In highway scenarios, factors such as high-speed vehicle movement, lighting conditions, and positional changes significantly affect the quality of trajectories in multi-object tracking. This, in turn,...
While brokerage role diversity draws attention from the network research community, the benefits and costs of being a diversified broker rarely being discussed. This paper examines the moderating effe...
Publishing papers in prestigious journals such as Nature , Science and PNAS is a great feat, like athletes winning Olympics Gold Medals. Under widespread global competition, the law of allocation may ...
The learning-based, passive, device-free wireless human activity recognition (WHAR) systems still face significant challenges, especially in real-world deployments. Environmental differences and domai...
Recent advancements in computational pathology have produced patch-level Multi-modal Large Language Models (MLLMs), but these models are limited by their inability to analyze whole slide images (WSIs)...
In regression analysis, methodologies range from black-box approaches like artificial neural networks to white-box techniques like symbolic regression. Renowned for its trans-parency and interpretabil...
Software quality evaluation is a challenging task in software engineering. A new group decision-making evaluation model is presented in this work. The new model is based on the Vlsekriterijumska optim...
The online bin packing problem is a well-known optimization challenge that finds application in a wide range of real-world scenarios. In the paper, we propose a novel algorithm called FuzzyPatternPack...
Software developers can only obtain a very small amount of information from the individual failure-causing inputs, which makes debugging difficult. Therefore, it is necessary to explore additional fai...
Venous thromboembolism (VTE) is an under-appreciated vascular disease that has been a growing global healthcare challenge, with increasing morbidity, mortality, and associated healthcare costs. Few wo...
Document Image Inpainting (DII) has been applied to degraded documents, including financial and historical documents, to enhance the legibility of images for: (1) human readers by providing high visua...
Robot-assisted catheterization offers a promising technique for cardiovascular interventions, addressing the limitations of manual interventional surgery, where precise tool manipulation is critical. ...
BACKGROUND: Stroke is a prevalent disease with a significant global impact. Effective assessment of stroke severity is vital for an accurate diagnosis, appropriate treatment, and optimal clinical outc...
Frontier scientific discoveries increasingly rely on big-science research infrastructures, such as supercolliders, synchrotron light sources, and space telescopes, whose construction and operation inv...
Semantic segmentation has recently achieved notable advances by exploiting “class-level” contextual information during learning, e.g., the Object Contextual Representation (OCR) and Context Prior (CPN...
Portfolio optimization is a strategic approach aiming at achieving an optimal balance between risk and returns through the judicious allocation of limited capital across various assets. In recent year...
Adversarial examples are security risks in the implementation of artificial intelligence (AI) in 6G Consumer Electronics. Deep learning models are highly susceptible to adversarial attacks, and defens...
Deep learning has gained significant popularity in recent years, particularly for tasks like image and speech recognition, natural language processing, and other intricate pattern recognition challeng...
The global economy faces a new complexity with slowing growth and persistent inflation, exacerbated by the pandemic, geopolitical disputes, and underlying structural factors. This paper first analyzes...
Abstract This study uses Trump's withdrawal from the Paris Accord as an exogenous policy shock and investigates its impact on crowdfunding outcomes. We find that this major policy change negatively af...
Although Convolutional Neural Networks (CNNs) have achieved remarkable success in image classification, most CNNs use image datasets in the Red-Green-Blue (RGB) color space (one of the most commonly u...
Purpose: This paper reports on an ongoing study examining the implementation of image-based generative AI in higher education to study the impacts and changes to learning behaviors and academic perfor...
To develop a cross-regional feature fusion model for the classification of cervical tumour subtypes using non-invasive magnetic resonance imaging (MRI), we aimed to explore feature representation in b...
This study presents an approach to identifying retinal structural biomarkers in ophthalmology, which is essential for accurate diagnosis and effective treatment of eye diseases. We develop a multi-mod...
Efficient truck dispatching is crucial for optimizing container terminal operations within dynamic and complex scenarios. Despite good progress being made recently with more advanced uncertainty-handl...
Survival models have become popular for credit risk estimation. Most current credit risk survival models use an underlying linear model. This is beneficial in terms of interpretability but is restrict...
Spatial-Temporal Local Binary Pattern (STLBP) has been widely used for dynamic texture (DT) recognition. Hashing Pixel-Difference Vectors (PDVs) into binary codes before forming histogram features has...
Abstract Recently, discriminative and robust identification information has played an increasingly critical role in Person Re-identification (Re-ID). It is a fact that the existing part-based methods ...
This paper presents a pilot study that examines the capacity of novice testers to generate Metamorphic Relations (MRs) for autonomous driving systems (ADSs), specifically fo-cusing on parking function...
This study introduces a website serving as an Open Educational Resource (OER), dedicated to Metamorphic Testing (MT) and Metamorphic Relation (MR) generation, with a specific focus on Autonomous Drivi...
Over the past decades, China has faced an increasingly severe fire issue, resulting in significant human and financial losses. Consequently, the importance of enhancing fire safety education for citiz...
Purpose This study aims to examine the effects on student motivation and perception of technological interventions within undergraduate mechanical engineering and product design and manufacture progra...
The shift towards transportation electrification, marked by the rising use of electric vehicles (EVs) and the development of fast charging stations (FCS), plays a crucial role in transport decarboniza...
Physics education posed challenges, with students' limited interest attributed to the subject's abstract nature as well as educators' struggles in conveying complex concepts effectively. To address th...
Immersive Virtual Reality (IVR) exergaming presents a promising avenue to integrate physical exercise with engaging virtual experiences, potentially encouraging sustained physical activity. However, m...
Infrared thermal imaging presents significant potential in various domains. However, the widespread development of this technology is hindered by the high cost associated with acquiring high-quality t...
Deep Reinforcement Learning (DRL)-based Dynamic Voltage Frequency Scaling (DVFS) has shown great promise for energy conservation in embedded systems. While many works were devoted to validating its ef...
We introduce a web-based SQL query visualisation tool aimed at improving students' understanding of SQL query execution. The tool, available as an Open Educational Resource (OER), allows users to visu...
This study examines the global–local corporate social responsibility (CSR) interface in the context of Confucian culture by analyzing four multinational corporation (MNC) subsidiaries in China. We col...
Existing surgical guidewire endpoint localization methods in X‐ray images face challenges owing to their small size, simple appearance, nonrigid nature of objects, low signal‐to‐noise ratio of X‐ray i...
Advances in computer vision research enable human-like high-dimensional perceptual induction over analogical visual reasoning problems, such as Raven's Progressive Matrices (RPMs). In this paper, we p...
This paper investigates whether international reward crowdfunding campaigns effectively attract global backers by testing the global market penetration level and explores the impact of home region ori...
Abstract Crowdfunding plays a key role in financial technology to provide individuals and enterprises with funding opportunities to establish start-ups and/or new business ventures. It is mainly used ...
Purpose Currently, owners find it difficult to manage their assets throughout their project life cycle. The fact that asset information models (AIMs) are mandatory as deliverables for building informa...
Technology integration in higher education (HE) provides educators with the opportunity to design stimulating learning environments, especially in design and engineering education (DEE) where it plays...
Although many of today’s object detectors (ODs) are fairly powerful and advanced, most of them still suffer from high detection failure rates. To address this issue, we have developed an innovative, m...
Agents have been applied to a wide variety of fields, including power systems and spacecraft. Belief-Desire-Intention (BDI) agents, as one of the most widely used and researched architectures, have th...
This paper presents a comprehensive investigation of traffic radar coverage efficiency under different placement strategies in collaboration with Zhejiang Communications Investment Group Company Limit...
Inadequate training poses a significant risk of injury among young firefighters. Although Human Activity Recognition (HAR) algorithms have shown potential in monitoring and evaluating performance, mos...
Abstract Distributed systems have been widely used in many safety‐critical areas. Any abnormalities (e.g., service interruption or service quality degradation) could lead to application crashes or dec...
Low-contrast medical image segmentation is a challenging task that requires full use of local details and global context. However, existing convolutional neural networks (CNNs) cannot fully exploit gl...
Segmenting vessels in magnetic resonance imaging (MRI) stands as a mainstream approach for evaluating cerebrovascular conditions.Due to the complex semantics and topology of cerebrovascular structures...
Path planning is the core of autonomous robot navigation, which helps the robot to find a collision-free path to the destination based on the environment information. Most current path planning method...
Metamorphic testing has become one mainstream technique to address the notorious oracle problem in software testing, thanks to its great successes in revealing real-life bugs in a wide variety of soft...
This paper explores the educational and practical impacts of integrating metamorphic testing (MT) into a software engineering project conducted by an intercultural group of students. The students desi...
This study reports on the development and implementation of the Interactive Design Research Toolkit (IDRT), a mobile application that supports the teaching and learning (T&L) of Human-Centered Design ...
Sequential decision making is an important part of robotic problems that is receiving unprecedented attention from both academia and industry. Recently, Deep Reinforcement Learning (DRL) has shown its...
ABSTRACT Metamorphic testing (MT) is effective in detecting software failures; it detects failures by examining the metamorphic relations (MRs) among source test cases (STCs), follow‐up test cases (FT...
Metamorphic Testing (MT) has been repeatedly proven effective in detecting software faults. MT detects faults by checking the Metamorphic Relations (MRs) among Source Test Cases (STCs) and Follow-up T...
Deep neural networks have been applied to audio spectrograms for respiratory sound classification. Existing models often treat the spectrogram as a synthetic image while overlooking its physical chara...
Ophthalmic Biomarkers, as an objective and quantifiable approach to identifying the ophthalmological disease process, are proven to be useful not only in assisting healthcare professionals in disease ...
Self-supervised representation learning (SSRL) has gained increasing attention in point cloud understanding, in addressing the challenges posed by 3D data scarcity and high annotation costs. This pape...
Although 2D radar signal representations, such as spectrograms and range-Doppler maps have been widely used for target recognition, 3D time-range-Doppler (TRD) has been less studied, partially because...
Summary When selecting services from a cloud center to build applications, the quality of service (QoS) is an important nonfunctional attribute to be considered. However, in actual application scenari...
Video-based gait recognition suffers from potential privacy issues and performance degradation due to dim environments, partial occlusions, or camera view changes. Radar has recently become increasing...
Formally verifying logic-optimized integer multipliers remains a crucial yet insufficiently addressed problem in both industry and academia, presenting significant verification challenges, particularl...
Financial fraud datasets typically exhibit a pro-nounced class imbalance, leading to elevated false positive rates when employing machine learning classifiers. To mitigate this issue, the Conditional ...
Object detection in aerial imagery presents a significant challenge due to large scale variations among objects. This paper proposes an evolutionary reinforcement learning agent, integrated within a c...
ABSTRACT The proliferation of driver‐assistance features in vehicles has resulted in a growing interest among the public in fully autonomous driving systems (ADSs). However, the integration of softwar...
The performance of metamorphic testing relates strongly to the quality of test cases. However, most related research has only focused on source test cases, ignoring follow-up test cases to some extent...
Visible-infrared image fusion is a technique that extracts information from different sensors. It could be used to enhance human visual perception of video surveillance under low-light conditions, and...
Three-dimensional cerebrovascular segmentation is crucial for accurate diagnosis and treatment planning of cerebrovascular diseases.However, the lack of high-quality publicly labelled datasets can lim...
Pedestrian detection plays a critical role in computer vision as it contributes to ensuring traffic safety. Existing methods that rely solely on RGB images suffer from performance degradation under lo...
Observational studies are widely used in Human-Computer Interaction (HCI) research to evaluate usability and user experience with technologies. However, the act of observation may influence participan...
Future airspace is expected to become more congested with additional in-service cargo and commercial flights. Pilots will face additional burdens in such an environment, given the increasing number of...
This paper briefly summarizes the current development status of the IoT ecosystem in Ningbo, China, overviews the challenges and difficulties faced by the IoT industry in the city, and predicts its fu...
Abstract This study investigates the relationship between corporate environmental performance, as captured by environmental investment, and firms’ access to trade credit. Using data from Chinese liste...
Graph Neural Networks (GNNs) have been widely used to model molecules with a graph representation. However, GNNs face inherent challenges in accurately modeling long-range atomic interactions and iden...
Artificial intelligence (AI) has revolutionized software engineering (SE) by enhancing software development efficiency. The advent of pre-trained models (PTMs) leveraging transfer learning has signifi...
Raven’s Progressive Matrices (RPMs) are frequently used in evaluating human’s visual reasoning ability. Researchers have made considerable efforts in developing systems to automatically solve the RPM ...
Unmanned Aerial Vehicle (UAV)-assisted Internet of Things application communication is an emerging concept that effectuates the foreknowledge of innovative technologies. With the accelerated advanceme...
The recent release of the Apple Vision Pro has reignited interest in the metaverse, showcasing the intensified efforts of technology giants in developing platforms and devices to facilitate its growth...
Rigid robots have found wide-ranging applications in manufacturing automation, owing to their high loading capacity, high speed, and high precision. Nevertheless, these robots typically feature joint-...
The COVID-19 pandemic rapidly accelerated the adoption of technology in educational environments. However, the technology initially employed during this period was limited in terms of interaction, eng...
A data-driven approach has been developed to classify indoor activities using only commonly available passive environmental sensors, such as CO2, temperature, humidity, and passive infrared (PIR). An ...
Weakly supervised salient object detection (WSOD) methods endeavor to boost sparse labels to get more salient cues in various ways. Among them, an effective approach is using pseudo labels from multip...
In recent years, deep reinforcement learning has shown great potential in solving computer games with sequential decision-making scenarios. Hyper-heuristic is a generic search framework, capable of in...
We propose a logic of east and west (LEW ) for points in 1D Euclidean space. It formalises primitive direction relations: east (E), west (W) and indeterminate east/west (Iew). It has a parameter τ ∈ N...
In many classification models, data is discretized to better estimate its distribution. Existing discretization methods often target at maximizing the discriminant power of discretized data, while ove...
Falling has become the leading cause of non-fatal and preventable injuries. The majority of existing fall detection systems (FDSs) rely on motion sensors. However, most of the applied feature extracti...
Recently, many improved naive Bayes methods have been developed with enhanced discrimination capabilities. Among them, regularized naive Bayes (RNB) produces excellent performance by balancing the dis...
Automated Guided Vehicles (AGVs) enhance transportation efficiency in different domains such as warehouses, factories, and container ports. Much research has been done into optimal scheduling and rout...
With the inherent algorithmic error resilience of conventional neural networks (CNNs) and the worst-case design methodologies of current electronic design automation tools, overclocking-based timing s...
Driver drowsiness is a major factor that leads to traffic accidents and loss of life. A popular drowsiness detection (DD) method is based on machine learning (ML) and monitoring electroencephalogram (...
The domestic pool of talent is deep, but international links are still crucial for maintaining the country’s role in the search for global solutions. The domestic pool of talent is deep, but internati...
Corporate fraud is becoming a vital concern of Chinese financial industry in recent years. However, manual investigation of certain suspicious companies could result in mass consumption of resources. ...
Sustainable urban infrastructure planning and maintenance require an integrated approach that considers various infrastructure assets (e.g., the ground, roads, and buried pipes) and their inter-linkag...
The demand for firefighting has significantly risen in recent decades, accompanied by increased risks faced by firefighters. Tragic incidents, such as the Shanghai factory fires, have resulted in the ...
In marine container terminals, truck dispatching optimization is often considered as the primary focus as it provides crucial synergy between the sea-side operations and yard-side activities and hence...
Prior literature shows that corporate culture matters for firm performance and enhance corporate resilience in crises. We construct a text-based measure of corporate culture for Chinese listed firms a...
The detail of the function PEO(.) in Section IV-B for this article was not available at the time of publication. It appears in Section IV-B as follows.
Memory scrubbing is a resource-efficient technique to ensure the high reliability of SRAM-based FPGAs by refreshing the configuration memory just before its execution. To maximize reliability, a scrub...
With the rapid development of short video platforms, providing accurate short video recommendations for users has become increasingly important. However, due to the multimodal nature of short videos, ...
Holography has attracted considerable attention from researchers due to its ability to store and recreate the wavefront emanating from a three-dimensional object. However, holographic video requires e...
Due to the phenomenon of "involution" in China, the current generation of college and university students are experiencing escalating levels of stress, both academically and within their families. Ext...
This paper provides an in-depth analysis of the current state of personal information storage and usage, as well as the existing issues in this domain. It proposes an architecture for building a decen...
University of Nottingham Ningbo China (UNNC) has been investigating the use of an augmented-reality (AR) educational game to aid in the teaching of Design for Manufacturing and Assembly (DfMA) theorie...
Conventional in-person teaching methods often restrict students’ critical thinking capabilities as they adhere to rigid instructions for information acquisition. The COVID-19 pandemic has accelerated ...
The Dual Foot Inertial Navigation System (DF-INS) shows promise as a practical approach for indoor location-based service (ILBS). Achieving accurate zero-velocity detection is crucial for optimal perf...
The class imbalance problem in finance fraud datasets often leads to biased prediction towards the nonfraud class, resulting in poor performance in the fraud class. This study explores the effects of ...
Concerns have been growing over fake news and its impact. Software that can automatically detect fake news is becoming more popular. However, the accuracy and reliability of such fake-news detection s...
The traditional offline teaching landscape has faced unprecedented challenges due to the COVID-19 pandemic, leading to the emergence of online teaching as a novel educational trend. However, online te...
This document 1 is an extended abstract of a Science of Computer Programming paper, "Candidate Test Set Reduction for Adaptive Random Testing: An Overheads Reduction Technique," presented as a J1C2 (J...
This paper empirically examines the representation of female venture capitalists (VCs) on boards and how they exert substantial influence on firm innovation performance in China. We first identify a p...
Indoor positioning in the firefighting ground shows promising application prospects for enhancing rescue safety and efficiency. Low visibility and signal interference caused by smoke pose significant ...
Some generative adversarial networks (GANs) have been developed to remove background noise in real-world audio recordings. MetricGAN and its variants focus on generating a clean spectrogram from a noi...
Visualization of endovascular tools like guidewire and catheter is essential for procedural success of endovascular interventions. This requires tracking the tool pixels and motion during catheterizat...
This paper proposes a visual focus of attention detection method based on the user’s 6D head pose estimation, which determines the content of the observer’s visual focus of attention according to the ...
Raven’s Progressive Matrices (RPMs) have been widely used to evaluate the visual reasoning ability of humans. To tackle the challenges of visual perception and logic reasoning on RPMs, we propose a Hi...
In clinical practice, the microscopic examination of urine sediment is considered an important in vitro examination with many broad applications. Measuring the amount of each type of urine sediment al...
Detecting 3D mask attacks to a face recognition system is challenging. Although genuine faces and 3D face masks show significantly different remote photoplethysmography (rPPG) signals, rPPG-based face...
As the complexity of autonomous driving systems (ADSs) increases, the question of how to organize testing in an efficient manner has become a serious issue. This study investigates the potential for m...
Automated Driving Systems (ADSs) have gained popularity recently. However, the unstable and unsafe ADSs have caused many traffic accidents and received widespread attention. One way to alleviate such ...
For an agent in a multi-agent environment, it is often beneficial to be able to predict what other agents will do next when deciding how to act. Previous work in multi-agent intention scheduling assum...
The disparity of sub-national institutions in transitional economies gradually comes into the spotlight, while less attention has been paid to the coexistence and interaction of different institutiona...
Oriented FAST and Rotating BRIEF (ORB) is a key technique for visual feature extraction and matching, which forms the foundation of the state-of-the-art ORB-SLAM systems. Due to the computational comp...
Contact-less or Device-less Human Activity Recognition (HAR) using IEEE 802.11 Wireless Local Area Network (WLAN) has garnered significant interest due to its ubiquitous coverage, convenience, and pri...
The wearable sensor applications and services are highly sensible to computation latency. The infrastructure that processes data closer to its source or end user named as multi-access edge computing (...
Salient object detection (SOD) aims to mimic the human visual system (HVS) and cognition mechanisms to identify and segment salient objects. However, due to the complexity of these mechanisms, current...
Falling is one of the primary causes of firefighter casualties. Therefore, early fall detection, followed by reliable and timely notification, is vital to ensure the survival of firefighters. However,...
This study is a driving analysis of the transfer data of container terminals based on simulation interactive modeling technology. In the context of a container yard, a model was established to analyze...
By generating prediction intervals (PIs) to quantify the uncertainty of each prediction in deep learning regression, the risk of wrong predictions can be effectively controlled. High-quality PIs need ...
Under pressure to reinvent itself, the CAS should concentrate on managing large-scale research infrastructures.
The quality of the cornea endothelial microscopy image is critical for clinical analysis. Although the noncontact specular microscope is more user-friendly than the contact confocal microscope, the im...
With the evolution of Internet of Things (IoT), some IoT nodes possess a certain degree of mobility, and the gains of the corresponding channels vary dramatically, incurring the energy supply problem ...
Jigsaw puzzle solving has recently become an emerging research area. The developed techniques have been widely used in applications beyond puzzle solving. This paper focuses on solving Jigsaw Puzzles ...
Great effort has been made to restructure the traditional monopolization of power industries to introduce fair competition.The deregulation of the electricity market allows the price of electricity to...
Purpose Since 2015, China has made efforts to reform its intellectual property rights (IPR) system to better protect and stimulate innovation. These reforms are a result of the demand for more stringe...
The segmentation of blurred cell boundaries in cornea endothelium microscope images is challenging, which affects the clinical parameter estimation accuracy. Existing deep learning methods only consid...
In the manufacturing process of industrial robots, the defect detection of raw materials includes two types of tasks, which makes the defect detection guarantee its accuracy. It also makes the defect ...
We construct a global financial inclusion index using data from the World Bank, IMF, and V-Lab and propose an inverted U-shaped relationship between financial inclusion and financial stability. The em...
There are a variety of reasons underlying the remarkable development of science and technology (S&T), and innovation in post-1978 China. This book seeks to achieve an understanding of such development...
In this study, we adopt case studies of four local corporations in China to explore how traditional Chinese culture (TCC) influences corporate social responsibility (CSR) in a more systematic and in-d...
Corneal endothelial cell segmentation of the microscope image is critical for clinical parameters quantification. However, the low-contrast regions are ambiguous and hard to segment. The uncertainty h...
Android compilers play a crucial role in Android app development. The correctness of the apps relies on the compilers because the source code of the app is translated into the target language by the c...
The large number of connected networks that underpin today’s IT ecosystem make them more vulnerable to cyber threats because of their connectivity, user diversity, amount of connected devices, and ser...
Visible light communication (VLC) is considered a new technology for interconnecting devices in 5G and beyond. VLC can provide additional bandwidth for communicating devices which can help to reduce t...
FPGA accelerators for lightweight neural networks, such as MobileNetv2, are of great need in edge computing applications with high throughput requirements. Dataflow architecture has been considered a ...
Since the outbreak of the COVID-19 pandemic, University of Nottingham Ningbo China (UNNC), the first Sino-foreign university in China, has been committed to digital transformation and increasing its t...
J1C2 Presentation Abstract at IEEE SERVICES 2022 for IEEE Transactions on Services Computing, 2022, 15(2):736-751. DOI: 10.1109/TSC.2019.2960496.
A competitive traveling salesmen problem is a variant of traveling salesman problem in that multiple agents compete with each other in visiting a number of cities. The agent who is the first one to vi...
One trend in the latest bottom-up approaches for arbitrary-shape scene text detection is to determine the links between text segments using Graph Convolutional Networks (GCNs). However, the performanc...
Naive Bayes has been widely used in many applications because of its simplicity and ability in handling both numerical data and categorical data. However, lack of modeling of correlations between feat...
The recent Facebook rebranding to Meta has drawn renewed attention to the metaverse. Technology giants, amongst others, are increasingly embracing the vision and opportunities of a hybrid social exper...
In a marine container terminal, truck dispatching is a crucial problem that impacts the operation efficiency of the whole port. Traditionally, this problem is formulated as an offline optimization pro...
Abstract Test case prioritization (TCP) aims at scheduling test case execution so that more important test cases are executed as early as possible. Many TCP techniques have been proposed, according to...
Spatial-temporal local binary pattern (STLBP) has been widely used in dynamic texture recognition. STLBP often encounters the high-dimension problem as its dimension increases exponentially, so that S...
Feature detection is essential to a large number of vision-based applications. Among the approaches available, keypoint detection-based ones, e.g., SIFT, SURF, and ORB, are very popular. In particular...
In the contemporary highly competitive business environment, employer branding is of greatest importance to talent attraction. However, studies on employer branding and talent recruitment are scattere...
Backscatter communications have been widely adopted in wireless networks for low-power IoT devices. For the devices which are powered by a battery or harvest energy from ambient signals, it is importa...
Recently, robotic catheterization has enhanced the outcomes of cardiovascular interventions. Meanwhile, the roles of operator’s natural behavior in the robot-assisted intravascular procedures need mor...
Voltage and frequency scaling (VFS) has been widely used to improve energy efficiency, lifespan, and system reliability by converting conservative timing margins into VddV_{\text {dd}}Vdd reduction...
Bin packing is a typical optimization problem with many real-world application scenarios. In the online bin packing problem, a sequence of items is revealed one at a time, and each item must be packed...
IEEE COMPSAC Workshops series is an established research event that complements the main focus of the IEEE COMPSAC conference, by focusing on specific topics that gain momentum in the research communi...
In this paper, we consider the testing of software whose input involves a data stream, such as in video analysis applications. To address the oracle problem in testing this kind of software, existing ...
This paper focuses on the problem of intelligent evacuation route planning for emergencies, including natural and human resource disasters and epidemic disasters, such as the COVID-19 pandemic. The go...
With the development of indoor location-based services (ILBS), the dual foot-mounted inertial navigation system (DF-INS) has been extensively used in many fields involving monitoring and direction-fin...
The dissolution test has become the most important quality index in the research and development of solid formulation, especially the evaluation of drug bioequivalence. However, it had low operability...
Bottom-up text detection methods play an important role in arbitrary-shape scene text detection but there are two restrictions preventing them from achieving their great potential, i.e., 1) the accumu...
Recent work in multi-agent intention scheduling has shown that enabling agents to predict the actions of other agents when choosing their own actions can be beneficial. However existing approaches to ...
Entity re-identification is the foundation of tracking- and matching-based computer vision tasks, which are widely employed in a variety of applications. However, when trained exclusively on clear ima...
Computing systems are becoming increasingly complex and sophisticated. Technologies such as artificial intelligence, big data, and autonomous vehicles are pushing the boundaries of system size, comple...
Applications with adaptability are widely available on the edge devices with energy harvesting capabilities. For their runtime quality optimization, however, current approaches cannot tackle the varia...
The consumption-based capital asset pricing model (CCAPM) is an attractive research field in finance, and extant studies have examined the impacts of different factors towards traditional CCAPM, inten...
Lane detection plays an essential role in autonomous driving. Using LiDAR data instead of RGB images makes lane detection a simple straight line, and curve fitting problem works for realtime applicati...
With the increasing popularity of open educational resources in the past few decades, more and more users watch online videos to gain knowledge. However, most educational videos only provide monotonou...
Indoor Location-Based Service (ILBS) shows great research promotions with wide applications e.g., indoor firefighting and cave exploration. Foot-mounted Inertial Navigation System (INS), one approach ...
This extended abstract presents an approach to enhance the Fixed-Sized-Candidate-Set Adaptive Random Testing (FSCS-ART) sampling strategy. SWFC-ART, the proposed approach, stores the previously-execut...
This study investigates whether and how family social capital influences borrowers' loan performance in informal financial markets. Using a unique dataset collected from an informal financial institut...
Metamorphic testing (MT) has been growing in pop-ularity, but it can still be quite challenging and time-consuming to assess its performance. Typical approaches to performance assessment can require a...
The weight information of an outbound container is often inaccurate, and it cannot be determined until its arrival at a port terminal. In order to fit all containers in a yard into the required loadin...
In indoor target tracking based on wireless sensor networks, the particle filtering algorithm has been widely used because of its outstanding performance in coping with highly non-linear problems. Res...
In this work, the impact of chemical additions, especially nano-particles (NPs), was quantitatively analyzed using our constructed artificial neural networks (ANNs)-response surface methodology (RSM) ...
Abstract This paper reports the molecular simulation of catalytic adsorption of the model compounds (simulated fatty acid and methanol) via the density functional theory (DFT) approach. The catalyst w...
In this research, we develop an affective computing method based on machine learning for emotion recognition using a wireless protocol and a wearable electroencephalography (EEG) custom-designed devic...
The Vehicle Routing Problem (VRP) is one of the most intensively studied combinatorial optimisation problems for which numerous models and algorithms have been proposed. To tackle the complexities, un...
Conformal predictors are machine learning algorithms that output prediction sets that have a guarantee of marginal validity for finite samples with minimal distributional assumptions. This is a proper...
Abstract Background Single-cell transcriptome (SCT) sequencing technology has reached the level of high-throughput technology where gene expression can be measured concurrently from large numbers of c...
Big data are potentially useful for environmental management planning and actions that can be directed toward pollution control. China is using big data approaches to help reduce its current levels of...
Interdisciplinarity is widely regarded as the future of Industry 4.0. It is at the core of the knowledge economy, and is key to solving complex real-world problems. Contemporary education therefore mu...
The rapid advancement of intelligent systems, especially robotics and autonomous driving, is highly reliant on low-complexity and high-accuracy stereo matching algorithms. However, the performance of ...
How cooperation emerges and persists in a population of selfish agents is a fundamental question in evolutionary game theory. The research shows that collective strategies with master-slave mechanism ...
Awareness of web accessibility issues is necessary for, amongst other things, good website design. Good website design can mean the difference between disabled users being able to access the website c...
Raven's Progressive Matrices (RPMs) are frequently used in testing human's visual reasoning ability. Recent advances of RPM-like datasets and solution models partially address the challenges of visual...
These labpackage files are open for interested readers and researchers to validate, replicate and extend our following paper: M. Iqbal, J. C. Han, Z. Q. Zhou, and D. Towey, “Enhancing Euro NCAP standa...
Abstract Deteriorating relations between the USA and China since 2018 have extended to education and scientific research arenas. We put the US–China science and education in a historical perspective a...
Visual localization estimation is highly depended on the quality of video frames or captured images. Estimation quality may be affected by the poor visibility, low background texture and overexposure....
Advanced Driver-Assistance Systems (ADASs) have become increasingly popular. To ensure safety, simulation testing is essential. In this research, we conducted a case study to investigate the fault-det...
Particle filter (PF) has been widely used in the target state and position estimations owing to its superiority in tackling the complicated nonlinear problems with arbitrary distributions. As an advan...
The current hydrogen generation technologies, especially biomass gasification using fluidized bed reactors (FBRs), were rigorously reviewed. There are involute operational parameters in a fluidized be...
) and the olefin to paraffin ratio (OPR) within acceptable uncertainties. With additional validation data sets (15 × 36 matrix with total 540 data sets), the uncertainties of using three different mod...
A machine learning approach has been applied to virtual screening for lysine specific demethylase 1 (LSD1) inhibitors. LSD1 is an important anti-cancer target. Machine learning models to predict activ...
Information is indispensable in modern society. People’s daily communication and work depend on information transmission. Unsafe storage or transmission of data may result in privacy and security prob...
Since the popularization of social media, news has entered our lives digitally. While news is spreading broader and faster, fake news is becoming an increasingly popular topic. Fake news detection is ...
Using the concepts of technology goal (T), effective organization (O), and market end-user (M), this paper proposes a TOM framework for analyzing the contextual characteristics of adoption of the MMRD...
This study considers the interaction effects of government subsidies, financial constraints, and ownership structure on the firm’s net research & development (R&D) based on a sample of 3440 Chinese-li...
Network scanning tools play an important role in network information gathering, which is the first step in penetration testing. They are tools that can help both hackers and security auditors to detec...
This paper presents an automated, domain-independent, metamorphic testing platform called MTKeras. In this paper, we report on an investigation demonstrating the effectiveness and usability of MTKeras...
COVID-19 has caused heart-break and disruption. The People's Republic of China (PRC) was one of the first severely-impacted countries, but also one of the first to attempt to return to normalcy. Educa...
Raven's Progressive Matrices (RPMs) are frequently used in evaluating human's visual reasoning ability. Researchers have made considerable effort in developing a system which could automatically solve...
Conformal predictors are an important class of algorithms that allow predictions to be made with a user-defined confidence level. They are able to do this by outputting prediction sets, rather than si...
We performed classification of healthy Peripheral Blood Mononuclear Cells cell types using four methods Artificial Neural Network (ANN), Profiles, Protein Markers (PMs), and RNA markers (RNAMs). Profi...
Abstract China’s rising capability in science, technology and innovation to a certain extent has to do with “a grand experiment” that started 15 years ago when the Chinese government released the Nati...
Background Single cell transcriptomics is a new technology that enables us to measure the expression levels of genes from an individual cell. The expression information reflects the activity of that i...
Gypsum (CaSO4·2H2O) with active catalytic performance was prepared from phosphorous rock through an improved clean wet process. The impact of the preparation conditions was extensively analyzed to ide...
In today’s digital era, the number of digital artefacts produced by students in universities around the world continues to rise. This paper describes a project that developed a digital artefacts platf...
Face spoofing detection against paper attack and video-replay attack has been well studied, whereas detecting 3D face mask attack remains challenging. Remote photoplethysmography (rPPG) signal is a re...
Abstract Purpose We attempt to find out whether OA or TA really affects the dissemination of scientific discoveries. Design/methodology/approach We design the indicators, hot-degree, and R-index to in...
During the past decade, falling has been one of the top three causes of death amongst firefighters in China. Even though there are many studies on fall-detection systems (FDSs), the majority use a sin...
Both parameter quantization and depthwise convolution are essential measures to provide high-accuracy, lightweight, and resource-friendly solutions when deploying deep neural networks (DNNs) onto edge...
The recent COVID-19 pandemic has presented challenges to post-secondary education, including that campuses have been closed, removing face-to-face instruction options. Meanwhile, this crisis has also ...
Taking a deep look at how China has transformed its capacity for scientific research and innovation provides a window into the country’s ambitions and possible paths in the future.
International and domestic maritime trade has been expanding dramatically in the last few decades, seaborne container transportation has become an indispensable part of maritime trade efficient and ea...
Urban infrastructure assets (e.g. roads, water pipes) perform critical functions to the health and well-being of society. Although it has been widely recognised that different infrastructure assets ar...
There is a lack of accurate and valid data provision during the construction project lifecycle, and throughout the in-use phase of building assets. Construction needs to adopt a new technology to supp...
We propose a logic of directions for points (LD) over 2D Euclidean space, which formalises primary direction relations east (E), west (W), and indeterminate east/west (Iew), north (N), south (S) and i...
Many real-life optimisation problems, including those in production and logistics, have uncertainties that pose considerable challenges for practitioners. In spite of considerable efforts, the current...
The Bayesian classification framework has been widely used in many fields, but the covariance matrix is usually difficult to estimate reliably. To alleviate the problem, many naive Bayes (NB) approach...
This paper describes an on-going project to develop a Virtual Reality platform to deliver phobia-inspired experiences. These experiences could induce a reaction in the user that may help the user over...
Accurate circuit delay measurement is essential for various purposes such as aging detection, health monitoring, and dynamic voltage and frequency scaling. State-of-the-art measurement techniques exhi...
Summary Web vulnerability scanners (WVSs) are tools that can detect security vulnerabilities in web services. Although both commercial and open‐source WVSs exist, their vulnerability detection capabil...
Fuzzing is a highly automated testing technique. It has been widely used in software vulnerability mining. American fuzzy lop (AFL) is one of the most effective fuzzing tools, with low resource consum...
In its simplest form, software testing consists of creating test cases from a defined input space, running them in the system-under-test (SUT), and evaluating the outputs with a mechanism for determin...
Recently, businesses and government bodies in the Architecture, Engineering, and Construction (AEC) sector have faced a key challenge to the delivery of effective project outcomes. Asset Information M...
This paper describes an on-going project to develop diagnostic profiling tools for healthcare professionals to identify potential speech and language developmental problems of Chinese-speaking childre...
The COVID-19 pandemic has caused staggering human and economic costs. We outline four key lessons learned from efforts to address the pandemic in China and the US. First, effective surveillance, repor...
Abstract Combinatorial interaction testing (CIT) aims at constructing a covering array (CA) of all value combinations at a specific interaction strength, to detect faults that are caused by the intera...
We propose an agent-based model (ABM) to simulate city-scale intra-urban activities and movements. We calibrate the ABM for New York City, using NYC Open Data trip diaries and taxi journeys. Model val...
In medical fields, text classification is one of the most important tasks that can significantly reduce human work-load through structured information digitization and intelligent decision support. De...
Purpose It is possible for civil engineering (CE) students to graduate from a degree programme without gaining experience on a construction site. The implementation of virtual field trips using virtua...
No abstract available.
Purpose This paper empirically investigates how cultural variations in individualism and tightness affected the containment of COVID-19 using data from 54 nations during a 30-day period of government ...
Abstract We examine science–industry collaborations by identifying how academician workstations – joint platforms by listed firms and academicians under provincial governments – influence corporate in...
Application-level approximate computing exploits inherent resilience of adaptive applications, and trades off application output quality for runtime system resources. Existing methods treat computing ...
To obtain high reliability but avoiding the huge area overhead of traditional triple modular redundancy (TMR) methods in SRAM-based FPGAs, scrubbing based methods reconfigure the configuration memory ...
Stochastic service network designs with uncertain demand represented by a set of scenarios can be modelled as a large-scale two-stage stochastic mixed-integer program (SMIP). The progressive hedging a...
Abstract On the one hand, accelerating convolution neural networks (CNNs) on FPGAs requires ever increasing high energy efficiency in the edge computing paradigm. On the other hand, unlike normal digi...
Adaptive random testing (ART) aims at enhancing the testing effectiveness of random testing (RT) by more evenly spreading test cases over the input domain. Many ART methods have been proposed, based o...
This paper reports on the use of program slicing concepts and partial execution tracing at Adobe Analytics to address a major limitation of differential testing --- namely, how to deal with the large ...
Stereo matching is a promising approach for smart vehicles to find the depth of nearby objects. Transforming a traditional stereo matching algorithm to its adaptive version has potential advantages to...
Internet hospital is a rising business thanks to recent advances in mobile web technology and high demand of health care services. Online medical services become increasingly popular and active. Accor...
Sign language was designed to allow hearing-impaired people to interact with others. Nonetheless, knowledge of sign language is uncommon in society, which leads to a communication barrier with the hea...
The recent COVID-19 pandemic has placed a huge strain on higher education institutions and educators around the world, which has included the closure of campuses, removal of face-to-face instruction a...
Purpose Social media have increasingly gained credibility as information sources in emergencies. Retweeting or resharing nature has made Twitter a popular medium of information dissemination. The purp...
Financial technology (fintech) is rapidly transforming the economy as well as the financial landscape in China. This paper attempts to shed light on its contributing factors, current state, economic i...
Random testing (RT) is a well-studied testing method that has been widely applied to the testing of many applications, including embedded software systems, SQL database systems, and Android applicatio...
This paper studies a real-life container transportation problem with a wide planning horizon divided into multiple shifts. The trucks in this problem do not return to depot after every single shift bu...
Abstract test cases (ATCs) have been widely used in practice, including in combinatorial testing and in software product line testing. When constructing a set of ATCs, due to limited testing resources...
Taxi GPS data offers an opportunity to discover behavioural patterns in urban populations. However, raw taxi journey data does not provide a link between outbound and return journeys of individual tra...
Blockchain technology, despite its origins as the underlying infrastructure for value transfer in the era of cryptocurrency, has been touted as the main disruptive force in modern businesses. Blockcha...
Motivated by recent developments in AR/VR technology and accessibility, an interdisciplinary team at a Sino-foreign Higher Education Institution in China have been engaged in the creation of a virtual...
Purpose Financial technologies, also known as “FinTech,” have brought disruptive changes to virtually every aspect of financial services and are becoming increasingly important in the world economic s...
In recent years, service oriented architecture (SOA) has been increasingly adopted to develop distributed applications in the context of the Internet. To develop reliable SOA-based applications, an im...
Purpose Embracing reflective practice and retrospection, with a goal of identifying commonalities, this paper aims to examine delivery of engineering subjects in both traditional higher education (THE...
While FPGA has been recognized as a promising platform to accelerate Convolutional Neural Networks (CNNs) in embedded computing given its high flexibility and power efficiency, two challenges still ha...
Global positioning system (GPS) data generated from taxi trips is a valuable source of information that offers an insight into travel behaviours of urban populations with high spatio-temporal resoluti...
Machine learning has been becoming increasingly popular and widely-used in various industry domains. The presence of the oracle problem, however, makes it difficult to ensure the quality of this kind ...
The issue of validity threats in empirical software engineering research is important. However, some authors overlook this, focusing on validating their work through application of fundamental testing...
Open Educational Resources (OERs) are freely accessible materials for teaching, learning, and research that have been made available such that they can be freely used, modified, and shared. Prompted b...
One goal of software testing may be the identification or generation of a series of test cases that can detect a fault with as few test executions as possible. Motivated by insights from research into...
Computer science (CS) subjects have been rapidly growing in popularity, and demand for CS education and training has put increasing pressure on teaching resources in higher education (HE) and elsewher...
Several qualitative spatial logics used in reasoning about geospatial data have a sound and complete axiomatisation over metric spaces. It has been open whether the same axiomatisation is also sound a...
Medical text classification assigns medical related text into different categories such as topics or disease types. Machine learning based techniques have been widely used to perform such tasks despit...
Abstract China’s approach to developing a world-class science system includes a vigorous set of programmes to attract back Chinese researchers who have overseas training and work experience. No analys...
Smart pervasive sensor networks are becoming an important part of our daily lives. Low-power, high-availability and high-throughput 5G mobile networks provide the necessary communication means for hig...
While many computer science (CS) curricula are increasingly addressing a demand for more communicative and ethical graduates, reports of CS student difficulties with nontechnical subjects, such as Pro...
Purpose Many transport and logistics companies nowadays use raw vehicle GPS data for travel time prediction. However, they face difficult challenges in terms of the costs of information storage, as we...
In this paper, a Mixed-Shift Vehicle Routing Problem is proposed based on a real-life container transportation problem. In a long planning horizon of multiple shifts, transport tasks are completed sat...
With the growing popularity of machine translation services, it has become increasingly important to be able to assess their quality. However, the test oracle problem makes it difficult to conduct aut...
This is the original dataset, where white spaces are used to separate words of all languages. This is however not the best method of analyzing some Asian languages. Please refer to the following new v...
Test case prioritization (TCP) plays an important role in identifying, characterizing, diagnosing, and correcting faults quickly. The TCP has been widely used to order test cases of different types, i...
Combinatorial Interaction Testing (CIT) aims at constructing an effective test suite, such as a Covering Array (CA), that can detect faults that are caused by the interaction of parameters. In this pa...
Patient X: A 67-year-old Caucasian man slips on a patch of ice. He has abrasions to his hands and has sustained significant damage to his hip. At the emergency room, he informs clinicians he takes ato...
The Huff model is a well used mathematical abstraction for predicting shopping centre patronage. It considers two factors: shopping centre attractiveness, and customers' travel costs. Here, taxi traje...
We present an interactive decision support system for assisting city infrastructure inter-asset management. It combines real-time site specific data retrieval, a knowledge base co-created with domain ...
The historical determinants of modern economic development have been widely studied since the seminal work of Engerman and Sokoloff (1997, 2002) and Acemoglu et al. (2001, 2002). The literature is lar...
Extant research finds that exchange rate pegs do little to reduce firms’ exposure to exchange rate risk in emerging markets. We study whether exchange rate risk exposures under a pegged/controlled flo...
Purpose The purpose of the paper is to identify the multiple types of data that can be collected and analyzed by practitioners across the cold chain, the ICT infrastructure required to enable data cap...
University of Nottingham Ningbo China (UNNC) was the first Sino-foreign higher education institution (SmEI) to be established in Mainland China, and has been host to a number of student-staff project ...
Open educational resources (OERs) are teaching, learning, and research resources that have been made available such that they can be used, shared, and modified freely. Motivated by recent OER developm...
We report on a novel use of metamorphic relations (MRs) in machine learning: instead of conducting metamorphic testing, we use MRs for the augmentation of the machine learning algorithms themselves. I...
Open Educational Resources (OERs) represent an opportunity to enhance quality access to education. However, OER adoption has not yet made as substantial an impact as might have been expected. This cas...
Presents the introductory welcome message from the conference proceedings. May include the conference officers' congratulations to all involved with the conference event and publication of the proceed...
Modern information technology paradigms, such as online services and off-the-shelf products, often involve a wide variety of users with different or even conflicting objectives. Every software output ...
Metamorphic testing is an approach to both test case generation and test result verification. A central element is a set of metamorphic relations, which are necessary properties of the target function...
In recent years, metamorphic testing has been successfully and systematically adopted within Adobe Systems to improve the cost effectiveness of its software process. In this industry experience report...
What if we could know that a program is buggy, even if we could not tell whether or not its observed output is correct? Metamorphic testing provides this ability. This article explains the basics of t...
Abstract test cases are derived by modeling the system under test, and have been widely applied in practice, such as for software product line testing and combinatorial testing. Abstract test case pri...
Test‐case prioritisation (TCP) attempts to schedule the order of test‐case execution such that faults can be detected as quickly as possible. TCP has been widely applied in many testing scenarios such...
Taxi trajectory data (GPS data collected for 15,000 taxis at intervals of 30 seconds across three million journeys over eight days) is used to generate a spatio-temporal prediction of shopping behavio...
This article reports an undergraduate software engineering project in which, over a period of 2 years, four student teams from different cohorts developed a note-taking app for four academic clients a...
The UN's Sustainable Development Goals present a challenge for biotechnology to develop new environmentally‐friendly and sustainable products and production processes.\n\n
In Systems Engineering (SE), development of complex systems involves a collaboration of expertise from different domains. Heterogeneous artifacts are generated using different modeling tools. Capturin...
Test case prioritization (TCP) attempts to order test cases such that those which are more important, according to some criterion or measurement, are executed earlier. TCP has been applied in many tes...
Abstract test case prioritization (ATCP) aims at ordering abstract test case in order to increase the speed at which faults are detected, potentially increasing the fault detection rate. This paper em...
Despite promising reforms, autonomy is unclear
Correctly detecting cycle slips is essential for the application of the GPS carrier phase observations in precise positioning. However it is still a challenge to detect small cycle slips caused by ion...
The process of component security testing can produce massive amounts of monitor logs. Current approaches to detect implicit security exceptions (those which cannot be identified by visual inspection ...
Inspired by recent Open Educational Resource (OER) development successes in a Sino-foreign Higher Education Institution in China, we were motivated to explore the possibility of creating a new OER to ...
Open educational resources (OERs) are essentially resources made freely available to the public for the purpose of enabling education. This paper examines the experiences of a collaborative team of in...
Purpose This paper presents an initial development of a personal data attitude (PDA) measurement instrument based on established psychometric principles. The aim of the research was to develop a relia...
Open Educational Resources (OERs) are teaching learning, and research resources that have been made available such that they can be used, shared, and modified freely. They have already had a significa...
The Service Network Design Problem (SNDP) is generally considered as a fundamental problem in transportation logistics and involves the determination of an efficient transportation network and corresp...
The behaviour of a system under test can be influenced by several factors, such as system configurations, user inputs, and so on. It has also been observed that many failures are caused by only a smal...
Metamorphic Testing (MT) is a testing technique that exploits the relationships among the inputs and outputs of multiple executions of the program under test, so- called Metamorphic Relations (MRs). M...
As the promise of Virtual and Augmented Reality (VR and AR) becomes more realistic, an interesting aspect of our enhanced living environment includes the availability ? indeed the potential ubiquity ?...
This paper summarises some of the best practices learned from an extended software engineering project completed through a collaboration of multidisciplinary faculty and several teams of computer scie...
In this paper, a dynamic truck dispatching problem of a marine container terminal is described and discussed. In this problem, a few containers, encoded as work instructions, need to be transferred be...
Through a three-year revision involving various stakeholders, China has enacted a new Environmental Protection Law ( EPL ). The new law seeks to harmonize economic and social development with environm...
The service network design problem (SNDP) is a fundamental problem in consolidated freight transportation. It involves the determination of an efficient transportation network and the scheduling detai...
Fault Localization Prioritization (FLP) aims to order the execution sequence of test cases so that faulty statements in a faulty program can be localized faster. FLP is an important part of the automa...
In freight transportation, less-than-truckload carriers often need to assign each vehicle a cyclic route so that drivers can come back home after a certain period of time. However, the Node-Arc model ...
Random testing (RT) has been identified as one of the most popular testing techniques, due to its simplicity and ease of automation. Adaptive random testing (ART) has been proposed as an enhancement t...
Twelve GPS Block IIF satellites, out of the current constellation, can transmit on three-frequency signals (L1, L2, L5). Taking advantages of these signals, Three-Carrier Ambiguity Resolution (TCAR) i...
The Vehicle Routing Problem with Time Windows (VRPTW) consists of constructing least cost routes from a depot to a set of geographically scattered service points and back to the depot, satisfying serv...
Test case prioritization (TCP) attempts to improve fault detection effectiveness by scheduling important test cases earlier, where important is determined by some criteria and strategy. Adaptive rando...
Because the human aspect of cybersecurity remains less well understood, the problem of security design with unfriendly user interfaces persists. A major challenge to addressing the human component of ...
The current trend of ubiquitous device use whereby computing is becoming increasingly context-aware and personal, has created a growing concern for the protection of personal privacy. Privacy is an es...
Travel time prediction is important for freight transportation companies. Accurate travel time prediction can help these companies make better planning and task scheduling. For several reasons, most c...
This study examines the evolution of institutional logics and private firm financing practices in Ningbo, a commercial seaport city in China where the private sector has prospered for centuries, durin...
Testing is a major approach for the detection of software defects, including vulnerabilities in security features. This article introduces metamorphic testing (MT), a relatively new testing method, an...
Software testing, as part of the software quality assurance processes in software engineering (SE), is seldom cited as the most engaging part of a software engineer's training. In spite of its importa...
The use of web services has been growing significantly, with increasingly large numbers of applications being implemented through the web. A difficulty associated with this development is the quality ...
While China’s economy has been subject to a wide range of economic reforms since 1978, its capital account is still restricted. The issue of capital account convertibility is widely debated both in Ch...
This paper examines teachers' views on Technology Enhanced Learning (TEL) and Open Educational Resources (OERs) in Vocational and Professional Educational and Training (VPET) in Hong Kong. A number of...
Combinatorial interaction testing is a well-studied testing strategy that aims at constructing an effective interaction test suite (ITS) of a specific generation strength to identify interaction fault...
Portfolio optimization is one of the most important problems in the finance field. The traditional mean-variance model has its drawbacks since it fails to take the market uncertainty into account. In ...
Unified Modeling Language (UML) activity diagrams are widely used to model concurrent interaction among multiple objects. In this paper, we propose a transformation-based approach to generating scenar...
The flipped classroom phenomenon has generated a lot of enthusiasm in teaching circles, but not all teachers have embraced this new paradigm. This paper discusses some of the challenges for Hong Kong ...
This paper investigates the profitability of several types of zero-cost price momentum and contrarian \nstrategies in the Chinese stock market for the 1994–2013 period. Several distinct features of Ch...
Good Laboratory Practice has been a part of non-clinical research for over 40 years. Optimization Research, despite having many papers discussing standards being published over the same period of time...
Teaching in higher education can be rewarding, but also stressful. Different teaching approaches and paradigms may mean that teachers are constantly trying to improve the learning experience for their...
Software Testing is an approach to ensuring the quality of software systems. Testing of safety-critical systems often requires conformance to certain code coverage criteria, including for example, in ...
The increasing globalization of business has heightened the opportunities and pressures to engage in cross-border mergers and acquisitions (hereafter, CBM&As) involving transitional economies, which h...
In late 2014 collaborative research was undertaken between colleagues in the departments of Computer Science, International Communications, the Centre for English language Education (CELE), and the La...
In spite of its importance to software quality, software testing is often considered the "poor man" of software engineering processes, left to the end of many projects, and frequently omitted altogeth...
Fault Localization Prioritization (FLP) aims at reordering existing test cases so that the location of detected faulty components can be identified earlier, using certain fault localization techniques...
Portfolio optimization is an important problem based on the modern portfolio theory (MPT) in the finance field. The idea is to maximize the portfolio expected return as well as minimizing portfolio ri...
This study investigates the impact of Chinese banks’ derivative activities on their exposure to exchange rate and interest rate changes. The standard Jorion 1990. “The Exchange-Rate Exposure of U.S. M...
In this paper, a full life cycle resource consumption model for automotive seats has been proposed based on the vehicle material-energy-pollution assessment model, and an assessment on energy consumpt...
Swarm intelligence suffers the premature convergence, which happens partially due to the solutions getting clustered together, and not diverging again. The brain storm optimization (BSO), which is a y...
Typical driving behaviors such as car-following and lane-changing can be described based on common concepts. But these behaviors could be different from driver to driver, from nation to nation due to ...
Combinatorial interaction testing has been well studied in recent years, and has been widely applied in practice. It generally aims at generating an effective test suite (an interaction test suite) in...
Abstract The convergence and divergence are two common phenomena in swarm intelligence. To obtain good search results, the algorithm should have a balance on convergence and divergence. The premature ...
The growing popularity and application of Web services have led to increased attention regarding the vulnerability of software based on these services. Vulnerability testing examines the trustworthine...
This paper describes a taxi scheduling system, which aims to improve the overall efficiency of the system, both from the perspective of the drivers and the customers. This is of particular relevance t...
Network coding is an emerging telecommunication technique, where any intermediate node is allowed to recombine incoming data if necessary. This technique helps to increase the throughput, however, ver...
The latest advances in clouding computing, big data and internet of things (IoT) have greatly transformed the operations and management of enterprise supply chains and logistics. They pro-vide a great...
In this paper, a real world short-haul commodity routing problem is presented. This problem shares several similarities with vehicle routing problem with time windows (VRPTW) and the service network d...
This paper explores the empirical question of whether Chinese stock and property markets are integrated or segmented. We find that, at the national level, investment returns in property and the A-shar...
In software testing, something which can verify the correctness of test case execution results is called an oracle. The oracle problem occurs when either an oracle does not exist, or exists but is too...
Combinatorial interaction testing is a well-recognized testing method, and has been widely applied in practice, often with the assumption that all test cases in a combinatorial test suite have the sam...
Recent changes in the assessment and management of risks has had the effect that greater importance has been placed on relationships between individuals and within groups to inform decision making. In...
Cost-benefit analysis has long been used in decision making about public health and security. Frequently, risk and uncertainty are involved, and benefit and cost are not evenly shared by all stakehold...
Nurse rostering is an important search problem with many constraints. In the literature, a number of approaches have been investigated including penalty function methods to tackle these constraints wi...
Service network design is a core problem for logistic transportation planning. It involves determination of the most cost-effective transportation network, package flow distribution as well as balance...
Search spaces sampled by the process of Genetic Programming often consist of programs which can represent a function in many different ways. Thus, when the space is examined it is highly likely that d...
We revisit the roots of Genetic Programming (i.e. Natural Evolution), and conclude that the mechanisms of the process of evolution (i.e. selection, inheritance and variation) are highly suited to the ...
Asignificant amount of work has investigated inventory control problems associated with fresh produce. Much of this work has considered deteriorating inventory control with many models having been pro...
