bluuebunny/crossref_metadata_2025 huggingface dataset:
Fractional Dimension Parameters Modelling and Optimization Based on Pulverized Coal Image
Authors: Wang Zheng  , Wang Mei
Published: February 2025

Because of the complex environment in coal mines, it is extremely hard to process pulverized coal images with large sum of noise. Fractional dimension characterization and model in bounded variation space are presented to optimize pulverized coal image. This paper puts on fractional calculus theory in bounded variation space and discusses the characterization model to enhance image optimization stability. Applying the regional characteristics of the pulverized coal image, the fractional dimension characteristic parameter u and regularized parameter λ of each image pixels are modified by adaptive algorithm. To evaluate image optimization effect, Numeric experimentations show that the PSNR (peak signal-to-noise ratio) and ERI (edge-preserving index). The two quantitative indicators have better performance considerably with the improved algorithm than the traditional algorithm. Because of the sound smoothing effect in the “non-texture region” and the excellent texture retention capacity in the “texture region”, fractional dimension characterization in bounded variation space optimization algorithm is effective and expeditious image filtering approach. The advanced algorithm is employed to observe pulverized coal in underground and succeeds in achieving satisfactory outcomes.
Algorithm Design of GNSS/INS Integrated Navigation for Vehicle Location in Cities
Authors: Wang Han  , Wang Maosong  , Wen Kun
Published: February 2025

With the development of modern urban intelligent transportation system, the requirement of accuracy and reliability of autonomous navigation becomes higher and higher. GNSS/INS is the most widely used method of integrated navigation at present, but in cities, satellite signals tend to be blocked by tall buildings, resulting in fewer than four visible satellite. This paper presents loosely-coupled and tightly-coupled GNSS/INS integration models using EKF and UKF algorithm respectively. The system simulation platform is built, and the dilution of precision (DOP) is adopted to help the satellite selection which ensures the effectiveness of integrated navigation. The experimental results show that when the satellite signal is more than four, both the integration models have high navigation accuracy. When the satellite signal is less than four, using the tightly-coupled model instead of the invalid loosely-coupled model with the observable satellite information can ensure the navigation precision and improve the anti-interference ability of the system.
Online Road Boundary Detection for Sparse 3D Laser
Authors: Sun Pengpeng  , Zhao Xiangmo  , Sun Ya  , Min Haigen
Published: February 2025

The ability to extract road boundary in the outside scene is key for autonomous vehicle navigation. This paper proposed a novel road boundary detection method for autonomous vehicle based on spatial knowledge and consistency of road boundary exploiting a 3D LiDAR. More specifically, a novel method was first used to separate the ground points so as to remove obstacles and speed up the processing of road boundary points selection. Secondly, we extract boundary candidate points from individual scan lines based on spatial knowledge, and a two-pass filter was used to eliminate fake boundary points based on consistency of road boundary. Finally, polynomial fitting and boundary update strategies were exploited to produce smoother transition and prevent line-jumping. A challenging realistic traffic scene dataset was collected to evaluate this proposed method and the experimental results demonstrate that the proposed method can detect road boundary with strong robustness at real time for both static and dynamic scenes. The proposed method has been successfully applied to our autonomous vehicle.
Application and Structure Design of Polyvinylidene Fluoride Membranes in Road Energy Collection
Authors: Xiao Jian  , Zhang Yufei  , Zou Xiang  , Li Pengfei  , Gen Hongyang  , Huang Linlin
Published: February 2025

With the promotion of green energy, road piezoelectric system is causing more and more people's attention. In this paper, the finite element simulation of polyvinylidene fluoride (PVDF) composites is studied. Four different types of protective measures are designed and tested on asphalt pavements. The piezoelectric output of the piezoelectric sensor is evaluated. The road piezoelectric performance of each protection measure is studied and analyzed. The experimental results show that the PVDF polymer film with length of 20 mm, width of 20 mm and thickness of 190 μm could meet the requirements of asphalt pavement power generation system. The epoxy resin encapsulation structure has better piezoelectric performance.
Research on the Construction of Network Security Attack and Defense Range System in Power Monitoring System
Authors: Wei Mingxin
Published: February 2025

To face the changes of network security situation in industrial control field of power industry and the security needs of important information system and meet the requirements for special network security tools, we carry out the top design work of network attack and defense simulation range in power industry and build a network security test simulation platform which include the power monitoring system, an important information system which similar to the real production environment. In this paper, we list recent developments concerning the construction of network security attack and defense range system in power monitoring system at home and abroad. According to the overall scheme of power monitoring system for security. We found a highly simulated range environment containing all of these parts–sending, changing, matching, usage, scheduling, information, design the network security attack and defense platform architecture and ensure the safe, reliable and stable operation of the power system effectively.
The U.S. National Action Plan to Improve Health Literacy: A Model for Positive Organizational Change
Authors: Baur Cynthia  , Harris Linda  , Squire Elizabeth
Published: February 2025

This chapter presents the U.S. National Action Plan to Improve Health Literacy and its unique contribution to public health and health care in the U.S. The chapter details what the National Action Plan is, how it evolved, and how it has influenced priorities for health literacy improvement work. Examples of how the National Action Plan fills policy and research gaps in health care and public health are included. The first part of the chapter lays the foundation for the development of the National Action Plan, and the second part discusses how it can stimulate positive organizational change to help create health literate organizations and move the nation towards a health literate society.
Patient Activation and Health Literacy: What's the Difference? How Do Each Contribute to Health Outcomes
Authors: Hibbard Judith
Published: February 2025

In this paper we define health literacy and patient activation, discuss how each construct is measured, and review the evidence linking each construct to outcomes.
Health Informatics and Technology for Integrated Elderly Care in the Context of Hong Kong: A Case Study
Authors: Chau Cheuk Wing  , Leung Eman
Published: February 2025

The aging population creates tremendous pressure to healthcare. To resolve, scholars recognized the solution to this challenge is integrated care. To facilitate integrated care, health information technologies (HIT) is a critical enabler. This paper will first review how technology enhanced integrated care, and review on the existing literatures in system effective use and the three key external factors that enable HIT implementation. Applying Burton-Jones and Volkoff's contextualized theories of effective use of HIT to understand the role of health informatics and technology in the unique context of Hong Kong, we have conducted a case study research to identify the levers for improving HK integration of care through HIT.
Clinical Supervision of Interns: Understanding the View of Interns and the Potential of ICT to Deliver Supervision for Safer Patient Care
Authors: Yee Kwang Chien  , Madden Angela  , Nash Rosie  , Connolly Michael
Published: February 2025

Clinical communication and clinical supervision of junior healthcare professionals are identified as the two most common preventable factors to reduce medical errors. While multiple strategies have been implemented to improve clinical communication, clinical supervision has not attracted as much attention. This is in part due to the lack of understanding of clinical supervision. Furthermore, there is a lack of exploration of information communication technology (ICT) in assisting the delivery of clinical supervision from the perspective of users (i.e. junior clinicians). This paper presents a study to understand clinical supervision from the perspective of medical and pharmacy interns. The important elements of good clinical supervisors and good clinical supervision have been presented in this paper based on our study. More importantly, our results suggest a distinction between good supervisors and good supervisions. Both these factors impact on patient safety. Through discussion of user requirements of good supervision by users (interns), this paper then explores and presents a conceptual framework to assist in the discussion and design of ICT by healthcare organisations to improve clinical supervision of interns and therefore improve patient safety.
Access Visits Using Video Communication
Authors: Mazumdar Suvodeep  , Ciravegna Fabio  , Ireson Neil  , Read Jennifer  , Simpson Emma  , Cudd Peter
Published: February 2025

An online video communication system is presented that enables Occupational Therapists (OTs) assess patient homes for assistive technology needs before acute care discharge to ensure appropriate independence and recovery conditions. Explorations under multiple conditions revealed perspectives from OTs and volunteer facilitators. Preliminary key findings and insights are reported.
Stepping Stones for People with Cognitive Disabilities and Low Digital Literacy
Authors: Lee Steve
Published: February 2025

The open source components presented have been designed for use by developers creating applications for people with cognitive disabilities or low digital literacy. They provide easy access to common online activities and include configurable levels of complexity to address varying preferences.
An Introduction to the Development of Transfer Assistive Robots in Japan
Authors: Kajitani Isamu  , Wakita Yujin
Published: February 2025

This paper briefly introduces the development of transfer assistive robots in terms of development support. In addition, some products that have been developed are reviewed. Our study reveals there are two development styles with completely opposite directions, namely: complex to simple; and simple to complex.
IntelliTable: Inclusively-Designed Furniture with Robotic Capabilities
Authors: Prescott Tony J.  , Conran Sebastian  , Mitchinson Ben  , Cudd Peter
Published: February 2025

IntelliTable is a new proof-of-principle assistive technology system with robotic capabilities in the form of an elegant universal cantilever table able to move around by itself, or under user control. We describe the design and current capabilities of the table and the human-centered design methodology used in its development and initial evaluation. The IntelliTable study has delivered robotic platform programmed by a smartphone that can navigate around a typical home or care environment, avoiding obstacles, and positioning itself at the user's command. It can also be configured to navigate itself to pre-ordained places positions within an environment using ceiling tracking, responsive optical guidance and object-based sonar navigation.
Modular Gesture Interface for People with Severe Motor Dysfunction: Foot Recognition
Authors: Yoda Ikushi  , Ito Kazuyuki  , Nakayama Tsuyoshi
Published: February 2025

We have collected various gestures from persons with motor dysfunction who cannot use normal interface switches to develop contactless, non-constraining, and inexpensive gesture interfaces for operating PCs by utilizing a commercially available image range sensor. We describe the collection and classification of the gestures and the foot gesture recognition module.
A Community-Level Perspective on Digitally and Socially Including Disabled People
Authors: French Tom  , Richardson James
Published: February 2025

A presentation of findings from the evaluation of the Future Digital Inclusion programme funded by the UK Government Department of Education. Data show the effectiveness of embedding digital inclusion support within wider social inclusion services at the local level, mediated by institutions and organisations which have established pathways to engage socially excluded people, including disabled people.
Co-Creation Learning Procedures: Comparing Interactive Language Lessons for Deaf and Hearing Students
Authors: Hosono Naotsune  , Inoue Hiromitsu  , Tomita Yutaka
Published: February 2025

This paper discusses co-creation learning procedures of second language lessons for deaf students, and sign language lessons by a deaf lecturer. The analyses focus on the learning procedure and resulting assessment, considering the disability. Through questionnaires ICT-based co-creative learning technologies are effective and efficient and promote spontaneous learning motivation goals.
Evaluation of Orientation Performance of Attention Patterns for Blind Person
Authors: Fujisawa Shoichiro  , Ishibashi Tatsuki  , Sato Katsuya  , Ito Sin-Ichi  , Sueda Osamu
Published: February 2025

Tactile walking surface indicators (TWSIs) are installed on footpath to support independent travel for the blind. There are two types of TWSIs, attention patterns and guiding patterns. The attention pattern is usually installed at the crosswalk entrances. The direction of the crossing can be acquired by the row of the projection of the attention pattern through the soles of the shoes. In addition, truncated domes or cones of the attention pattern were arranged in a square grid, parallel or diagonal at 45 degrees to the principal direction of travel. However, the international standard organization (ISO) allows a wide-ranging size. In this research, the direction indicating performance was compared at the same intervals for the five diameters specified by the international standard. As a result of the experiment, the diagonal array does not indicate the direction of travel, but the projection row does indicate the direction of travel in the parallel array. When the attention pattern is installed at a crosswalk entrance, a parallel array should be installed in the direction of the crossing.
Data Based Feature Identification of Polymorphic Functional Marker from Transcriptome Comparison
Authors: Yang Cin-Han  , Pai Tun-Wen  , Chen Ronshan  , Chou Hsin-Yiu
Published: February 2025

Next Generation Sequencing technology has become an efficient approach for analyzing functional genomics and facilitates discovery of molecular biomarkers for various biological applications. This study is aim to discover all simple sequence repeat (SSR) biomarker candidates and associated genetic functions from two different tilapia strains. The two transcriptome datasets, Nile Tilapia and Mozambique Tilapia, were retrieved from the public SRA database for transcriptome assembly and functional biomarker discovery. We adopted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases for gene function annotations. A total of 116,781 SSRs and 126,324 SSRs were identified from these two tilapia strains, and there were 31,950 SSR variations could be detected within annotated genes. To illustrate effective and efficient performance of our proposed system, we used the keywords of “skeletal system development” as an example for discovering associated SSR markers. There are three genes annotated with function of skeletal system development, and which possess 5 different SSRs within the gene sequences. Under such a particular functional constraint, a gene cluster can be automatically defined and all linked polymorphic SSRs could be identified between the two different species. These identify linked SSR markers are important for further analysis on genetic regulation, genetic disease detection, gene therapy, or cultivation of various agricultural products.
An Overview of Myocardial Infarction Registries and Results from the Hungarian Myocardial Infarction Registry
Authors: Piros Péter  , Fleiner Rita  , Ferenci Tamás  , Andréka Péter  , Fujita Hamido  , Ofner Péter  , Kovács Levente  , Jánosi András
Published: February 2025

Nowadays, several databases store information about patients and diseases, but only a few exists that focus directly on myocardial events and treatments. This paper is divided into two parts. In the first part, we list and summarize the ongoing European myocardial projects (Myocardial Ischaemia National Audit Project (MINAP) in England, Swedish Web-system for Enhancement and Development of Evidence-based care in Heart disease Evaluated According to Recommended Therapies (SWEDEHEART) in Sweden, National Registry of Acute Myocardial Infarction in Switzerland (AMIS Plus) in Switzerland). Where possible, we discuss the validity and accuracy of the stored data. In the second part, we introduce the history and legal environment of the Hungarian Myocardial Infarction Registry (HUMIR), and some research results that were achieved with the help of the information in the Hungarian registry.
Safety Verification Method for Priority-Based Real-Time Software
Authors: Narisawa Fumio  , Ueda Yoshikazu
Published: February 2025

The number of functions and the sizes of electronic controls and software systems in automobiles are increasing, as ADASAdvanced Driver Assistance Systems
Estimation of Rice Area from Satellite Data Using Neural Networks
Authors: Omatu Sigeru
Published: February 2025

It is well-known that a neural network is useful to classify several patterns. In order to estimate the rice area we apply a network of learning vector quantization (LVQ) to remote sensing data including Synthetic Aperture Radar (SAR) and optical sensors for estimation of a rice area. The satellite data were observed before and after planting rice. Three RADARSAT and one SPOT/HRV data are used in Higashi-Hiroshima City, Japan. RADARSAT image has only one band data and it is dificult to extract a rice area. However, SAR back-scattering intensity in a rice area decreases from April to May and increases from May to June. Thus, three RADARSAT images from April to June are used to know the changes of rice growth. The LVQ classification is applied to RADARSAT and SPOT data in order to evaluate rice area. It is shown that the true production rate of rice area can be estimated from RADASAT data using LVQ by approximately 60% compared with SPOT data. It will be shown that the proposed method is much better compared with SAR image classification by the maximum likelihood (MLH) method.
Workflow Based Query Management System for Astronomical Data Repository
Authors: Shrestha Shashank  , Chu Wanming  , Wu Yilang  , Cortez Ruth  , Vazhenin Alexander  , Shu Absalom  , Bhalla Subhash
Published: February 2025

Astronomy is a data-intensive science. The large amount of data available in the astronomical domain needs query languages to gain valuable astronomical information. The paper has two goals. First, it presents the challenges for domain-specific query language for managing astronomical data. Second, it proposes a solution of managing such large amount of data through incorporating a multi-stage query language with Workflow Management technique. The paper demonstrates a web based query management system able to handle user queries in single or multi-stage.
Construction of Intelligent Tutoring System Based on Semantic Web
Authors: Dai Kai-yu  , Lu Jian  , Lu Sheng-qi  , Zhao Yi-ming
Published: February 2025

The depth integration of Internet + Education and the introduction of intelligent technologies, are reconstructing the education system. In this paper, we construct a knowledge graph of discipline field by using web ontology technology, and propose a two-layer architecture model that relationally maps the knowledge unit of specialized courses to the knowledge elements of discipline field through learning goal. The Marzano educational instructional framework is introduced as the description standards of the goals, resources, evaluation of learning and learner's knowledge state, etc. The corresponding generation rule of learning goals ranking strategy is given, and therefore the recommended learning roadmap can be automatically deduced from the knowledge graph. The combination of knowledge space theory and Vygotsky's “Zone of Proximal Development” offers an intelligent tutoring algorithm, which has well solved intelligent tutoring problem based on learning goal and graph in online education.
Affect Aware Ambient Intelligence: Current and Future Directions
Authors: Karyotis Charalampos  , Doctor Faiyaz  , Iqbal Rahat  , James Anne
Published: February 2025

The promise of a reality where intelligent technologies and unobtrusive networks of interconnected electronic devices support individuals in their daily tasks and activities is delivered by the vision of Ambient Intelligence. In order for this vision to be realized modern technology should posse an understanding of a core aspect of human nature, namely emotion. Affective Computing is a multidisciplinary scientific field which has emerged in order to deliver applications which are able to recognize their user's emotion, produce affect sensitive outputs in order to aid them and respond in a human like manner, resulting in a higher level of human machine interaction. This chapter provides a review of current research aiming to offer an insight into affective computing by exploring all key aspects relating to the development of an effective human centered system and by identifying open questions and future research directions for this scientific area.
Persuadee Modelling in Computational Argumentation in Marketing
Authors: Dellunde Pilar  , Mantilla Marco  , Sabater-Mir Jordi
Published: February 2025

This article is a position paper on strategic argumentation in multi-agent systems. We study argumentation persuasive dialogues between two agents, one persuader and one persuadee. We analyze a real case study in the field of marketing, not studied before in the automated argumentation literature.
Target Detection and Tracking for Grasping Sea Floor Objects During Underwater Intervention Operations
Authors: Company-Corcoles Joan P.  , Ortiz Alberto  , Negre-Carrasco Pep Lluis
Published: February 2025

Recent advances in technology have allowed robotic platforms to implement some tasks currently accomplished by humans. Of particular relevance is the fact that this technology is allowing to perform tasks in hazardous environments. Underwater environments fall into this category, specially when carried out at high depth areas, naturally risky for divers. An important capability, lately affordable by autonomous underwater robots, is to grasp objects from the sea floor. To accomplish this task, the target has to be found into the scene and its pose estimated to guide the robot manipulator. In this work, we present an object detection and pose estimation pipeline which guides the target grasping during an intervention operation. The proposed algorithm is based on two stages: detection and tracking. The detection process takes care of detecting the object pose for the first time, or when it is lost by the second stage. On the other hand, the tracking process, less computationally demanding, is responsible for correcting some small odometry inaccuracies or for adjusting the current pose to align better with the object. To conclude, we report on the results of a number of experiments, carried out by an underwater robot operating in various environments, a water tank and in the sea, and using a stereo camera as the input sensor.
Using Community Detection Techniques to Discover Non-Explicit Relationships in Neurorehabilitation Treatments
Authors: Sanchez-Pinsach David  , Arcos Josep Lluis  , Laxe Sara  , Bernabeu Montserrat  , Tormos Josep Maria
Published: February 2025

The interaction between patients and professionals in complex clinical domains, as in the case of Neurorehabilitation, is always a complex process where crucial decision making in a short period of time is required, and where every decision has a serious impact on the patient. In this situation, deciding which are the most appropriate interventions is not an easy task because these patients simultaneously present several impairments, multiple diagnoses, and required complex interdisciplinary approaches. In this context, a methodology and a tool based on ICF have been developed to explore the relationships between patient impairments and therapeutic goals. The proposed approach, based on graph analysis, was used to analyze a set of 1960 patients that suffered an Acquired Brain Injury. Results achieved show that the proposed methodology is able to find non-explicit relationships. This study constitute a first step to the goal of designing a clinical decision support tool for neurorehabilitation.
Classification of Breast Cancer Molecular Subtypes from Their Micro-Texture in Mammograms Using a VGGNet-Based Convolutional Neural Network
Authors: Singh Vivek Kumar  , Romani Santiago  , Torrents-Barrena Jordina  , Akram Farhan  , Pandey Nidhi  , Sarker Md. Mostafa Kamal  , Saleh Adel  , Arenas Meritxell  , Arquez Miguel  , Puig Domenec
Published: February 2025

Breast cancer can be detected at early stages by radiologists from periodic screening mammography. However, just by viewing the mammogram they cannot discern the subtype of the cancer (Luminal A, Luminal B, Her-2+ and Basal-like), which is a crucial information for the oncologist to decide the appropriate therapy. Consequently, a painful biopsy must be carried out for determining the tumor subtype from cytological and histological analysis of the extracted tissue. In this paper, we aim to design a computer aided diagnosis (CAD) system able to classify the four tumor subtypes just from the image pixels of digital mammography. The proposed strategy is to use a VGGNet-based deep learning convolutional neural network (CNN) that can be trained to learn the underlying micro-texture pattern of image pixels, expected to be characteristic of each subtype. We have collected 716 image samples of 100x100 pixels wide, manually extracted from real tumor image areas that had been labeled in the digital mammography by a radiologist, jointly with the corresponding oncologist diagnose based on histological indicators. Using this ground truth, we have been able to train and test the proposed CNN, which can achieve an accuracy rate of 78% when discerning only Luminal A and Luminal B subtypes. In turn, it yields an accuracy rate of 67% when all four tumor subtypes are considered.
Implementation of Task-Tracking Software for Clinical IT Management
Authors: Purohit Anne-Maria  , Brutscheck Clemens  , Prokosch Hans-Ulrich  , Ganslandt Thomas  , Schneider Martin
Published: February 2025

Often in clinical IT departments, many different methods and IT systems are used for task-tracking and project organization. Based on managers' personal preferences and knowledge about project management methods, tools differ from team to team and even from employee to employee. This causes communication problems, especially when tasks need to be done in cooperation with different teams. Monitoring tasks and resources becomes impossible: there are no defined deliverables, which prevents reliable deadlines. Because of these problems, we implemented task-tracking software which is now in use across all seven teams at the University Hospital Erlangen. Over a period of seven months, a working group defined types of tasks (project, routine task, etc.), workflows, and views to monitor the tasks of the 7 divisions, 20 teams and 340 different IT services. The software has been in use since December 2016.
Evaluation of the IT Infrastructure of the RESIST Study with the Evidence-Based CIPROS Checklist
Authors: Lindoerfer Doris  , Mansmann Ulrich
Published: February 2025

Efficient and powerful information systems are substantial to perform medical research projects successfully. Especially, translational medicine poses specific challenges to the corresponding IT infrastructure. The RESIST study is a translational research project in oncology where xenografts inform about patients second-line treatment. DBFORM, an in-house developed system, was used as EDC system. It was enhanced with project specific features. We demonstrate how the CIPROS checklist has the potential to optimize the related requirements engineering process. The CIPROS checklist consists of 72 items, organized within 12 Aspects/Topics and was developed to assess such patient registry software systems. In this paper we use the CIPROS checklist (1) to elucidate the projects requirements and (2) to assess systems features. The application of the CIPROS checklist to fix the RESIST project requirements and system features was successful. The interplay between (1) and (2) helped to accelerate the requirements engineering process and to set up a system suitable to perform the translational research project successful.
A Decentralized IT Architecture for Locating and Negotiating Access to Biobank Samples
Authors: Proynova Rumyana  , Alexandre Diogo  , Lablans Martin  , Van Enckevort David  , Mate Sebastian  , Eklund Niina  , Silander Kaisa  , Hummel Michael  , Holub Petr  , Ückert Frank
Published: February 2025

There is a need among researchers for the easy discoverability of biobank samples. Currently, there is no uniform way for finding samples and negotiate access. Instead, researchers have to communicate with each biobank separately. We present the architecture for the BBMRI-CS IT platform, whose goal is to facilitate sample location and access. We chose a decentral approach, which allows for strong data protection and provides the high flexibility needed in the highly heterogeneous landscape of European biobanks. This is the first implementation of a decentral search in the biobank field. With the addition of a Negotiator component, it also allows for easy communication and a follow-through of the lengthy approval process for accessing samples.
Vibration Waveform Classification and Fault Diagnosis of Railway Train Based on Fractal Dimension and Nearest Neighbor Clustering
Authors: He Youquan  , Chen Xingjie  , Wang Yulin  , Long Xun  , Cai Juan
Published: February 2025

In this paper, we propose an approach for fault diagnosis of railway train based on a combination of fractal theory and k-mean clustering technique. First, the fractal dimensions of the waveforms were calculated to analysis the singular characteristics of the waveforms. Second, the k-mean clustering was used to cluster the singular characteristics in order to determine the running state and fault diagnosis. It can effectively monitor the running state and safety performance of the railway train, and provides technical support for the safe operation and maintenance of the railway train. The method has the advantages of strong real-time and high accuracy for fault classification, which has a certain reference value for analysis of uncertainty and irregular waveform.
Detect Exam Cheating Pattern by Data Mining
Authors: Chen Mason  , Chen Charles
Published: February 2025

This aim of this project is to apply a series of pattern detection Data Mining algorithms to accurately identify cheating by one or more students during classroom test exams. JMP software was utilized to analyze correlation among exam scores for 75 students (sitting at 25 different tables due to space constraints) who took a multiple-choice assessment exam. During the exam, three students were seated per table, each given an exam with the same questions but arranged in different order to prevent cheating. Each of the three students, therefore, was given Versions “A,” “B,” and “C” of the exam, respectively, per table. Nonetheless, the possibility of cheating by students existed since they could still synchronize the question sequence prior to, and during the exam. To detect if a pattern could be identified on the answer keys between students not attributable to chance alone (and therefore attributed to cheating), multivariate statistics tools were used to determine whether there was any association pattern among the students from the same exam table. Hierarchical Clustering and Dendrogram Tree were used to identify the grouping affinity behavior related to exam cheating pattern. The clustering analysis would group students with similar answering patterns among the 75 students who took the exam. The cheating pattern could be identified among the first few groupings if students were seated at the same test table during the exam. Authors also used JMP Graph Builder and Graphical Heat Map to identify and recognize patterns in exam scores among students using visual analysis. To further improve the prediction confidence of these combined tools, the authors also selected the top 20% of questions considered the most difficult ones (as identified by the instructor), in order to increase the detection signal-noise ratio. The probability of picking the same wrong answers on the difficult questions are even more unlikely by chance alone as compared to picking the right answers for the easy questions. It is statistically even more improbable that students would unintentionally select the same wrong answers on difficult questions, and therefore provides very evidence of cheating. Principle component analysis was also used to identify pairs of students who cheated, with separation of pairs based on the top two principle components. From the analysis presented using a unique set of Data mining tools, three tables were summarized in this paper and all supported evidence of cheating in the same student pairs. The predictive model approach using Data Mining tools was very powerful for analysis of the complex exam cheating patterns. This case study has been included in standard curriculum in graduate school course to discourage students cheating on exams. The approach herein can also be used to study patterns in students' multiple-choice answers across subject matter, and to help instructors design their future curriculums based on pattern recognition tools derived from these Data mining algorithms.
Constructing an Evaluating Model: Application of Dynamic Bayesian Network
Authors: Yan Peng  , Bo Wu
Published: February 2025

This paper studies the assessment model and the application of Dynamic Bayesian Networks (DBNs), which are based on budget management, and puts forward the assessment and prediction model of budget management based on Dynamic Bayesian Networks. A medium-sized industrial manufacturer was used as an example to describe the network model building, parameter learning, and reasoning process. A new Baum-Welch algorithm, based on genetic algorithm-based was implemented. Experiments show that the algorithm has a better global optimal search solution than the existing training algorithm. This model took the overall budget management as the research objective, modeling the budget management with DBNs theory and algorithm, in order to make up for a number of shortcomings which are caused by subjective human factors in the regular budget preparation and implementation.
Research on Semantic Similarity Algorithm of Chinese Words in a Specified Domain
Authors: Niu Qinzhou  , Zhao Xiang
Published: February 2025

The existing semantic similarity calculation method of Chinese words, basing on HowNet, cannot be used well for the similarity calculation of fuzzy concept in the specified significance and cannot accurately express the implicit semantic similarity which is vague and in the specified case. For this problem, on the basis of HowNet, combined with label semantic framework, a method based on mass semantic similarity is proposed. This paper presents an algorithm to calculate the semantic distance of Chinese words by using mass function, and proves that this method which is used to calculate the similarity of Chinese words in specified case can effectively improve the accuracy of word similarity calculation, and solve the problem of semantic similarity of Chinese words in specified domain.
Interpolation of Minimum-Phase HRIRs Using RBF Artificial Neural Network
Authors: Xu Ming  , Wang Zidao  , Gao Ying
Published: February 2025

Now head-related transfer function (HRTF) databases we already have are not spatially continuous, it's necessary to reconstruct a high spatial resolution HRTF database to solve this problem. Based on the minimum-phase HRIRs (Head-related Impulse Responses), we analyze and compare the errors of three traditional methods include linear, cubic, and spline interpolation. Furthermore, we propose a method using RBF (radial basis function) artificial neural network to interpolate the minimum-phase HRIRs. The minimum-phase reconstructed empirical HRIRs are used to train and establish the neural network. By training RBF neural network, we can approximate HRIRs in any spatial positions. The experimental results show that this method retains the advantages of minimum phase HRIR. It has the minimum group delay, minimum filter length, less interpolation error and a good performance for estimation. The proposed method makes more convenient to obtain HRTFs at any required spatial positions in synthesizing virtual 3D sound.
Reliability Analysis of Wireless Sensor Networks Based on Fusion of Binary Decision Diagram and Fault Tree
Authors: Qiang Rong
Published: February 2025

In order to improve reliability of wireless sensor network, a new reliability analysis method of wireless sensor networks is proposed based on binary decision diagrams and fault tree in this paper. Firstly, fault tree model is built based on hierarchical clustering topology of wireless sensor networks, and then the network fault tree of topology structure is converted into binary decision diagrams structures. Finally, the simulation experiment is carried out to test the performance under different performance criterion such as node redundancy and different hops between nodes. The results show that the proposed method can provide useful message for the performance optimization of wireless sensor network and improve the reliability of wireless sensor network.
An Wireless Mobile Localization Algorithm for Underground Coal Mine
Authors: Gong Shangfu  , Xu Fengzhi  , Qiu Xingguo  , Luo Bibo
Published: February 2025

In order to know the position of moving target in real time, the problem of accurate mobile location is an important subject to be studied. The mobile deployment of communication nodes in wireless sensor network and the utilization of the location algorithm can effectively solve the problem of mobile target location in underground coal mine. After analyzing the characteristics and disadvantages of the traditional Monte Carlo localization algorithm (MCL), this paper improved some algorithms including sampling, filtering and other key links, then it presented an improved scheme that nodes to be located can actively request location. Simulation results show that the improved algorithm(MCLZ) has better performance than the MCL algorithm in some aspects such as real-time character of location, density and moving speed of node, and cost of location output.
A Non-Intrusive Decomposition Algorithm Based On Residential Load Signal Separation
Authors: Han Lu  , Qi Bing
Published: February 2025

Investigated here is a non-intrusive decomposition algorithm based on residential load signal separation, which established on non - intrusive load model by harmonic analysis of load steady - state current signal, and columned matrix equations by the harmonic component of a mixed signal and the harmonic component of a single signal. The equations are used as objective functions for load decomposition, and the least squares algorithm and the non-negative least squares algorithm are used to solve the global optimal solution of the objective function to get involved in the mixing of the various current signals and achieve the purpose of load de-composition. The simulation results demonstrate that the non-negative least squares algorithm is used to solve the equations with a higher load recognition accuracy than the least squares algorithm.
The Application of Internet of Things Technology in Power Transmission Line Condition Monitoring System
Authors: Ge Wei-chun  , Luo Huan-huan  , Zhou Gui-ping  , Meng Fan-bo  , Ma Yi-ling
Published: February 2025

The transmission line is the key equipment of power grid, which is the guarantee of stable operation of power grid. Integrating the Internet of things technology into the condition monitoring system of transmission line can improve the monitoring and operation management level of transmission lines. The paper primarily researches the key technologies of Internet of things and condition monitoring of transmission line, and analyzes the architecture of Internet of things. And then, constructs the structure of transmission line condition monitoring system based on Internet of things and researches the function and deployment principle of each layer network. The perception layer adopts a self designed monitoring device. At the network layer, the paper proposes a three-layer network structure of wireless sensor network, optical fiber composite overhead ground wire(OPGW), GPRS and Beidou navigation satellite to construct the network transmission layer of the condition monitoring system, which can meet the mutual inductance and the interconnection between the monitoring devices in the different transmission line environment, and reduce the configuration of terminal GPRS, Beidou navigation satellite and OPGW access point. Finally, the reliability and feasibility of the condition monitoring system integrated the technology of Internet of things are illustrated by practical cases, which provides a set of effective solutions for the safe and stable operation of transmission lines.
A Novel Quality Assessment Metric for Synthesized Virtual View in 3D Video
Authors: Zhang Yan
Published: February 2025

Three-dimensional (3D) video involves stereoscopic and multi-view provides the viewer with a depth perception. In order to reduce the transmission data, multi-view video plus depth which are the combination of texture image and associated depth map is applied. A limited number of views and corresponding depth maps are input to generate more intermediate virtual views for 3D display by view synthesis reference software. Due to the lack of ground truth, virtual view quality assessment is a difficult problem. This paper therefore proposes a novel reduced-reference quality assessment metric for synthesized virtual view by utilizing the edge similarity between undistorted and distorted synthesized view. Undistorted view edge is synthesized by uncompressed texture edge and depth map. Distorted edge is extracted from assessed virtual view. The results over multi-view video sets imply that the proposed metric can reflect virtual view quality and is highly consistent with full-reference metric.
Multiple Granulations of Fuzzy Soft Rough Sets
Authors: Liu Jianbo  , Liu Jing  , Wang Xiaomin  , Guo Chenxi  , Li Piyu  , Zhang Yanyan  , Zhao Pengyun
Published: February 2025

This study presents the concept of multi-granularity fuzzy soft rough sets (MGFSR-sets). A pair of multi-granularity fuzzy soft rough approximations is proposed. Basic properties of multi-granularity fuzzy soft rough approximations are presented and showed by some illustrative examples. In addition, new types of fuzzy soft sets such as jointly full fuzzy soft set, jointly intersection complete fuzzy soft set and jointly union complete fuzzy soft set are defined. Finally, some new multi-granularity fuzzy soft W-rough relations are given.
TSP Solver: An Integrated Framework for Solving Traveling Salesman Problems Consistent with TSPLIB
Authors: Avşar Bihter  , Esmaeili Aliabadi Danial  , Esmaeili Aliabadi Edris
Published: February 2025

The Traveling Salesman Problem (TSP) is the subject of study in operational research for more than 30 years. The TSP is considered as NP-complete; consequently, many heuristic and metaheuristic algorithms have been developed to cope with the intractable nature of the problem. Although the problem is well-studied, lack of integrated software that harnesses the new computers' computational power and provides an easy comparison between heuristic algorithms is sensible. TSP solver is the state-of-the-art software that provides a common framework to compare the performance of different algorithms over TSPLIB library. Academicians can focus on developing new methodologies without concerning the availability and correctness of reported algorithms in the literature. Practitioners may also benefit from provided transparency by our software solution and build their own customized packages to flourish their businesses. The proposed software can be a foundation for the future implementations in which users design their algorithm and results would be uploaded automatically on a public server together with the source code.
VaR and Tail Dependence Between the US and Asian Stock Exchange Indices—An EGARCH-Copula Approach
Authors: Ma Ji  , Liu Jiangxu  , Sriboonchitta Songsak
Published: February 2025

This paper uses the eGARCH-Copula model to examine the tail dependence and Value at Risk (VaR) of the log returns of the US and Asian exchange indices as pairs of portfolio in three periods: before, in and after finance crisis. The results indicated that the eGARCH-Copula model works well on measuring the tail dependence and VaR between the US and Asian stock market; and after finance crisis, the dependence structure changed including on tail dependence and VaR.
A Framework of the Urban Pulsation Analysis
Authors: Yao Xiaojing  , Chen Liujia  , Wang Xiaomeng  , Peng Ling  , Chi Tianhe  , Li Xiang  , Hu Yuan
Published: February 2025

The urban rapid development leads to a series of urban diseases. The developments of remote sensing and geographic information sciences generate varied of data and create great potentials for urban disease diagnosis. In this paper, a framework of the urban pulsation analysis is established to diagnose a specific urban disease. The urban pulsation analysis implements three tasks. They are optimizing an examinational index system for an urban disease, extracting spatio-temporal data sequences that corresponds to the index system, and spatio-temporal data mining with urban constraints. This paper describes the essential technologies of these tasks with perspectives of the further trend.
Application of Artificial Neural Network Method to Analyze User's Behavior Using Clickstream Data
Authors: Ho Hei-Fong  , Chen Chih-Chuan
Published: February 2025

The digital marketing has become more popular than ever. In order to realize the on-line behavior of the users and tackle the considerable web data generated by the users, the analysis of web browsing behavior has been drawn a lot of attention, which challenges researchers. Web usage mining (WUM) exploiting data mining, text mining, machine learning and statistic is a useful method to solve problems where the hidden knowledge can be extracted for better understanding various interests of web users. In this investigation, consumer browsing log data were collected at google analytics, and then unstructured browsing log was preprocessed into semi-structure text. For each session, all URLs were compacted as a sentence representing a consumer's browsing path, which was further performed by hierarchical neural network, and then renormalized by Hopfield neural network to obtain the stable weights between URLs. The final two visualizing graphs highlights two types of browsing patterns denoting the intent of two groups of consumers where the graph with more links reflects user as a visitor looking for interesting things and the plain graph reveals the user accessing website by using keywords at search engine as a consumer most likely taking action. The findings would make a significant contribution to the marketing strategy and understanding of the browsing behavior and intent of on-line users.