bluuebunny/crossref_metadata_2025 huggingface dataset:
Ontology-Based Customization of a Scheduling System for Discrete Manufacturing
Authors: Sanko Jelena  , Haav Hele-Mai  , Kotkas Vahur
Published: February 2025

Customization is a very important feature of any manufacturing scheduling system. In many cases large commercial manufacturing scheduling systems are not easily and efficiently customizable to meet requirements of small and medium size enterprises. Therefore, this paper proposes an ontology-based architectural solution for the customization of manufacturing scheduling systems. According to the approach, the input to the scheduling system is a customized manufacturing scheduling ontology that is an extension of the manufacturing scheduling ontology provided in this paper. The customized manufacturing scheduling ontology performs as a knowledge base and data access point for the manufacturing scheduling system and enables it to be easily adapted to different products and their manufacturing processes.
Fatty Acid β-Oxidation Defects
Authors: Harding Cary O.
Published: February 2025

Inherited fatty acid oxidation disorders (FAOD) are among the most common inborn errors of metabolism. The spectrum of clinical phenotypes associated with FAOD is wide, correlates to the severity of the specific enzyme deficiency, and includes cardiomyopathy, fasting or illness-induced hypoketotic hypoglycemia, or recurrent rhabdomyolysis, generally triggered by exercise or febrile illness. Diagnosis is accomplished through specialized biochemical analysis followed by either measurement of specific enzyme activity or more commonly molecular analysis of disease-associated genes. Newborn screening detects the majority of but not all infants with FAOD and frequently allows treatment initiation prior to symptom onset. Avoidance of extreme fasting prevents hypoglycemia and is life saving for at risk infants. Restriction of dietary fat intake and replacement with medium chain triglyceride (MCT) oil to provide a usable energy substrate may also be included in the treatment of individuals with defects in long chain fatty acid oxidation. Long term outcomes for many FAOD are generally satisfactory once a diagnosis has occurred and steps to avoid episodes of metabolic decompensation have been taken. However, chronic complications of peripheral neuropathy or pigmentary retinopathy associated with vision loss may occur in specific disorders of long chain FAOD despite dietary therapy.
A Globally-Integrated Environmental Analysis and Visualization System with Multi-Spectral & Semantic Computing in “Multi-Dimensional World Map”
Authors: Kiyoki Yasushi  , Chen Xing  , Sasaki Shiori  , Koopipat Chawan
Published: February 2025

In the design of multimedia data mining systems, one of the most important issues is how to search and analyze media data, according to contexts. We have introduced a semantic associative search method based on our “Mathematical Model of Meaning (MMM) [1, 2, 3]”. This model is applied to compute semantic correlations between keywords, images, music and documents dynamically in a context-dependent way.
A Multispectral Imaging and Semantic Computing System for Agricultural Monitoring and Analysis
Authors: Wijitdechakul Jinmika  , Kiyoki Yasushi  , Sasaki Shiori  , Koopipat Chawan
Published: February 2025

Multispectral image becomes widely used for environmental analysis to detect an object or phenomena that human eyes cannot capture. One of the main type of images acquired by remote sensing such as satellite or aircraft for earth observation. This paper presents a multispectral analysis for aerial images that captured by dual cameras (visible and infrared camera), which are mounted on an unmanned autonomous vehicle (UAV) or Drone. In our experiments, four spectral bands (three visible and one infrared band) were imaged, processed and analyzed to detect agricultural area and measure the health of vegetation. To interpret environmental phenomena and realize an environmental analysis, this study applies semantic analysis by creating a multispectral semantic image space, combined with three numerical indicators (the normalized difference vegetation index (NDVI), the normalized difference water index (NDWI) and the soil adjusted vegetation index (SAVI)) that can be used to analyze plant health, photosynthetic activity and detect environmental object to determine an agricultural area. This paper also proposed the concept of multi-spectrum semantic-image space for agricultural monitoring by defining the correlation meaning from multi-dimensional parameters which related to agricultural analysis to realize and explain agriculture conditions. This paper presents the experimental study on a rice field, a cornfield, a salt farm and a coconut farm in Thailand.
The Influence of Cultural Factors on Crowdsource Product Designing
Authors: Al-Sohibani May  , Dahanayake Ajantha
Published: February 2025

The services and products are provided to the community through crowdsourcing platforms where crowds are of different backgrounds, nationalities, languages, religions, and education levels. These differences affect the results of services and products that are developed using crowdsource platforms. This study presents the way of integration of cultural factors into the design features of crowdsource product designing. The research presents the activities of crowdsource product designing, and the cultural factors to derive the theoretical foundation for formulating the cultural factors for crowdsource product designing. Also, the study derives methods that are used for integrating the cultural factors into crowdsourcing product design platforms. Also, it illustrates the design of the user interface of crowdsourcing product design platforms taking cultural factors into consideration. The research is validated by prototyping and conducting test cases. Finally, it presents a discussion of the research results and explains the effect of cultural factors on crowdsource product designing. Thus confirms the necessity of designing platform activities integrating the cultural factors in order to satisfy the crowdsource product design users' needs.
Logic of Inferable Knowledge
Authors: Duží Marie  , Menšík Marek
Published: February 2025

Intensional epistemic logics are not apt for handling properly the specification of communication and reasoning of resource-bounded agents in a multi-agent system. They oscillate between two unrealistic extremes: either the explicit knowledge of an ‘idiot’ agent, deprived of any inferential capabilities, or the implicit knowledge of an agent who is a logical/mathematical genius. The goal of this paper is to introduce the notion of inferable knowledge of a rational yet resource-bounded agent. The stock of inferable knowledge of such an agent a is the closure of a chain-of-knowledge sequence validly derivable from a's existing stock of explicit knowledge via one or more rules of inference that a masters. We are using Pavel Tichý's Transparent Intensional Logic as our framework. This logic models knowing as a relation-in-intension between an agent and a construction (a hyperintensional mode of presentation of a possible-world proposition) rather than a set of possible worlds or a piece of syntax. We motivate the restriction of the epistemic closure principle to inferable knowledge, present the theoretical framework, define the concept of inferable knowledge, and explain the technicalities of the so restricted closure principle.
Detecting Topic Evolutions in Bibliographic Databases Exploiting Citations
Authors: Ito Hiroyoshi  , Amagasa Toshiyuki  , Kitagawa Hiroyuki
Published: February 2025

This paper proposes a scheme of detecting topic evolutions in bibliographic databases. There have been a lot of scientific bibliographies, such as DBLP, CiteSeerX, MEDLINE/PubMed, ADS, arXiv, etc., and hence it has been extremely important to extract useful information from these databases. It should be noticed that, in such databases, citations play crucial role to represent relationships among different publications. To make the best use of citation information as well as textual features for extracting topic evolutions in a bibliographic database, we propose a scheme based on non-negative matrix factorization (NMF). More precisely, we first partition the set of publications in a database according to their publication years, and apply NMF to extract clusters of publications. Notice that we take into account citation information to perform NMF for better clustering. Having obtained sets of publications for each time span, we associate similar clusters in consecutive time spans according to their similarity. Thus we can obtain time evolution of topics and clusters of publications. In the experiments we demonstrate the proposed scheme can successfully extract topic evolutions in real bibliographic databases, CiteSeerX and arXiv.
Fuzzy Rule-Based Stock Ranking Using Price Momentum and Market Capitalization
Authors: Peachavanish Ratchata
Published: February 2025

Stock market investing is an inherently risky and imprecise activity, requiring complex decision making under uncertainty. This paper proposes a method that applies fuzzy rule-based inference to rank stocks based on price momentum and market capitalization. Experiments performed on Thai stock market data showed that high-momentum stocks significantly outperformed the market index benchmark, and that stocks of companies with small market capitalization performed better than larger ones. Fuzzy rule-based inference was applied to combine both the momentum factor and the market capitalization factor, with different sets of rules for different prevailing market conditions. The result produced a higher investment return than using either momentum or market capitalization alone.
Yield Rate Prediction of a Dynamic Random Access Memory Manufacturing Process Using Artificial Neural Network
Authors: Chang Chun-Wei  , Lin Shin-Yeu
Published: February 2025

To provide a reference for the fault detection of a dynamic random access memory (DRAM) manufacturing process, we propose a yield-rate predictor using an artificial neural network (ANN). The inputs to the ANN are the machining parameters in each step of the manufacturing process for a DRAM wafer, and the output is the yield rate of the corresponding wafer. In this study, a three-layer feed-forward back propagation ANN is used and trained by input-output pairs of data collected from real manufacturing process. We have tested the proposed ANN for five cases, and each case has different size of training data set. The test results show that the average of the absolute prediction errors in all five cases are very small, and as the size of the training data set increases, the prediction accuracy increases and the associated standard deviation decreases.
A Decision Tree Model for Meta-Investment Strategy of Stock Based on Sector Rotating
Authors: He Li-Min  , Chen Shao-Dong  , Zhang Zhen-Hua  , Hu Yong  , Jiang Hong-Yi
Published: February 2025

This study firstly proposes Meta-Investment Strategy, derived from the concept of Meta-Search in network and Meta-Cognition in psychology. We compare enormous web information to all A shares in China, process of searching information to stock selection and search engines to equity funds. Based on the sector rotation theory and decision tree model, through the construction of indicator system and the statistical model, some stock selection rules according to funds information can be extracted. After classifying the period from 2016.02 to 2016.04 as recovery, we selected finance industry. By importing 12 stock indicators of all the component stocks in finance industry as input variables and whether it is heavily held by stocks funds as target variable, a decision tree model is constructed. Finally, by entering data of the last quarter in 2015, the predictive classification results are obtained. Result shows that Meta-Investment Strategy outperformed CSI300 and CSI300 of Finance Sector (000914) and obtained significant excess return from 2016.02.01 to 2016.04.30.
A Fuzzy Control Based Parallel Filling Valley Equalization Circuit
Authors: Ran Feng  , Hu Ke-Wei  , Zhao Jing-Wei  , Ji Yuan
Published: February 2025

Aiming at the problem of high cost and slow equalization speed in traditional circuit, a parallel filling valley equalization circuit based on fuzzy control is proposed in this paper. A fuzzy controller suitable for the circuit is designed. The average voltage, voltage range and the balance electric quantity of the battery pack are modeled by fuzzy model. The fuzzy reasoning and defuzzification is produced to optimize the circuit control logic, which can be adapted to the nonlinearity of the battery pack and the uncertainty of the battery parameters. The simulation and experiment results show that, in the process of charging and discharging, the fuzzy control based parallel filling valley equalization circuit has the advantage of fast and efficient equalization which can improve the use efficiency of the battery pack.
Novel DBN Structure Learning Method Based on Maximal Information Coefficient
Authors: Li Guo-Liang  , Xing Li-Ning  , Chen Ying-Wu
Published: February 2025

Dynamic Bayesian Network (DBN) is a mainstream approach to modeling various biological networks including the gene regulatory network (GRN). For such DBN models that consist only of inter-timeslice arcs, most current methods for learning it employ either a score and search approach or Markov chain Monte Carlo (MCMC) simulation, both of which ignore the structural constraints of DBN models. These structural constraints were first applied to translate the structure learning problem into discovering associations among variables, and then a new method was presented to obtain inter-timeslice arcs. This method was based on maximal information coefficient (MIC). Experiment results showed that the proposed MIC-based method outperformed MI-based, MCMC, and K2 algorithm methods on the quality of learned structure.
A Speed up Method for Collaborative Filtering with Autoencoders
Authors: Tang Wen-Zhe  , Wang Yi-Lei  , Wu Ying-Jie  , Wang Xiao-Dong
Published: February 2025

Collaborative Filtering (CF) is a widely used technique in Recommender System. With recent development in deep learning, Neural network based CF has gained great attention in recent years, especially auto-encoders. However, the main disadvantage of autoencoder based CF is the problem of the large sparse target. In this paper, we propose a training strategy to tackle this issue, We run experiments on two popular real world datasets MovieLens 1M and MovieLens 10M. Experiments show orders of magnitude speed up while Attaining similar accuracy compare to existing autoencoder based CF method.
Safety Risk Early-Warning for Metro Construction Based on Factor Analysis and BP_Adaboost Network
Authors: Wang Hong-De  , Ma Bai-Le  , Zhang Yan-Chao
Published: February 2025

In order to improve the level of safety risk early warning management of metro construction, firstly, built early warning indicators from four aspects of the human, machinery, environment, and management. Then quantized the early warning indicators by combining 12 metro construction projects and using the Dlephi method. Thirdly, based on factor analysis method, optimized the 30 early warning indicators to reduce to 7 indicators. Finally, obtained index factors as the input of the neural network, established BP_Adaboost network warning model and made the subway construction safety risk early warning. The results show that the input data optimization technique based on factor analysis method to BP_Adaboost input factor to optimize neural network early warning model, raised the speed of the warning, but also improved the precision of the subway construction safety risk early warning.
The Study of an Improved Intelligent Student Advising System
Authors: Li Xiaosong
Published: February 2025

This paper describes an improved intelligent student advising system. Comparing it to the initial system, the improvements include: the initial system was integrated with WEKA, both K-means algorithm and Cobweb algorithm were implemented for training and testing data sets, and course and pathway recommendations were also implemented. The recommendations given by the improved system were based on the K-means algorithm only, and the results were meaningful. However, the quality of the recommendations could be improved. For that purpose, Cobweb algorithm was also experimented. The results showed that it is hard to identify proper parameters for Cobweb algorithm to produce meaningful clusters. Furthermore, the results of the experiments suggested that Cobweb algorithm is less efficient than K-means algorithm for this system. The results of the experiments also suggested that Cobweb algorithm is more reliable than K-means algorithm for this system. Future research should focus on improving the efficiency of Cobweb algorithm.
The Improved Projection Pursuit Evaluation Model Based on Depso Algorithm
Authors: Zhu Bin  , Jin Wei-Dong
Published: February 2025

In this paper, a new projection pursuit model based on differential evolution & particle swarm optimization (DEPSOPP) is proposed. Firstly, a hybrid differential evolution particle swarm optimization algorithm (DEPSO) is proposed through the combination of the improved particle swarm optimization algorithm with variable weights (VWPSO) and differential evolution algorithm (DE). Secondly, the optimization of the projection direction is the key of the projection pursuit algorithm. The hybrid DEPSO algorithm would be applied in the optimization of the projection direction. Finally, the experiment results of test functions show that the new hybrid DEPSO algorithm has the excellent convergence, accuracy and robustness. This indicates that the DEPSOPP evaluation model is a better feature assessment model.
A New Integrating SAW-TOPSIS Based on Interval Type-2 Fuzzy Sets for Decision Making
Authors: Abdullah Lazim  , Kamal C.W. Rabiatul Adawiyah C.W.
Published: February 2025

Most of the integrated methods of multi-attributes decision making (MADM) used type-1 fuzzy sets to represent uncertainties. Recent theory has suggested that interval type-2 fuzzy sets (IT2 FS) could be used to enhance representation of uncertainties in decision making problems. Differently from the typical integrated MADM methods which directly used type-1 fuzzy sets, this paper proposes an integrating simple additive weighting – technique for order preference similar to ideal solution (SAW-TOPSIS) based on IT2 FS to enhance judgment. The SAW with IT2 FS is used to determine the weight for each criterion, while TOPSIS method with IT2 FS is used to obtain the final ranking for the attributes. A numerical example is used to illustrate the proposed method. The numerical results show that the proposed integrating method is feasible in solving MADM problems under complicated fuzzy environments. In essence, the integrating SAW-TOPSIS is equipped with IT2 FS in contrast to type-1 fuzzy sets for solving MADM problems. The proposed method would make a great impact and significance for the practical implementation. Finally, this paper provides some recommendations for future research directions.
Generalized Hybrid Carrier Modulation System Based M-WFRFT with Partial FFT Demodulation over Doubly Selective Channels
Authors: Li Yong  , Song Zhi-Qun  , Sha Xue-Jun
Published: February 2025

To mitigate the inter-symbol interference (ISI) and inter-carrier interference (ICI) over doubly selective (DS) channel, we, in this paper proposed a novel communication system, generalized hybrid carrier modulation (GHCM) system with the partial fast Fourier transform (FFT) demodulation. The GHCM system, which is based on the multi-Weighted type fractional Fourier transform (M-WFRFT), merges together the components of single carrier modulation (SCM) system and orthogonal frequency division multiplexing (OFDM) system. And GHCM system with partial FFT demodulation is expected to perform better than SCM and OFDM systems with the same demodulation and channel equalization over DS channels. In this paper, we first derive the structure of GHCM with partial FFT demodulation after the basic knowledge. According to the numerical simulation, it can be demonstrated that the GHCM with partial FFT performs better than SC and OFDM systems. Furthermore, GHCM can be the development of hybrid carrier modulation (HCM) system.
Two-Wavelength Transport of Intensity Equation for Phase Unwrapping
Authors: Zhang Cheng  , Cheng Hong  , Shen Chuan  , Zhang Fen  , Bao Wen-Xia  , Wei Sui  , Han Chao  , Fang Jie  , Xia Yun
Published: February 2025

A novel method based on two-wavelength transport of intensity equation (TW-TIE) is proposed for phase unwrapping under large-step discontinuities condition. With a wrapped phase obtained by interferometry setup, two different wavelength illuminations are used to obtain two different intensity images, then TW-TIE is applied to phase unwrapping. Numerical experiments are presented to demonstrate the feasibility and effectiveness of our proposed method.
Towards a Global Importance Indicator for Court Decisions
Authors: van Opijnen Marc
Published: February 2025

Tagging court decisions as to their importance is indispensable for the accessibility of voluminous case law repositories, but such an attribute has been implemented in only a few databases yet. In this paper some of these are briefly discussed and a lowest common denominator is proposed. This could be especially useful in federated search solutions like the ECLI Search Engine.
A Pattern for the Representation of Legal Relations in a Legal Core Ontology
Authors: Griffo Cristine  , Almeida João Paulo A.  , Guizzardi Giancarlo
Published: February 2025

This paper extends UFO-L, a Legal Core Ontology (LCO) based on Robert Alexy's Theory of Constitutional Rights and grounded on the Unified Foundational Ontology (UFO). We present the first pattern of UFO-L's patterns catalogue and its application. The general idea is to use these ontological patterns to support the modeling of legal concepts in conceptual models of the legal domain. Moreover, our approach has the specific purpose of emphasizing the use of a relational perspective rather than a normative perspective of the Law.
Semanticification in Connected Health
Authors: Goossen-Baremans Anneke  , Collins Sarah  , Park Hyeoun-Ae
Published: February 2025

The purpose of the implementation of nursing terminologies is to capture and process meaningful health data wherein facts about patients and nursing care can be recorded and inferences for nursing care, patient outcomes and associations with all care delivered by the interprofessional team can be made. This paper describes the clinical information landscape, implementation of semantic content, and competencies required for nurses. Health data can be outlined in a high level clinical information ecosystem where nursing terminologies can be represented for implementation. This ecosystem consists of both the structural and dynamic aspects of the support of care.
Integrating Health Information Technology Safety into Nursing Informatics Competencies
Authors: Borycki Elizabeth M.  , Cummings Elizabeth  , Kushniruk Andre W.  , Saranto Kaija
Published: February 2025

Nursing informatics competencies are constantly changing in response to advances in the health information technology (HIT) industry and research emerging from the fields of nursing and health informatics. In this paper we build off the work of Staggers and colleagues in defining nursing informatics competencies at five levels: the beginning nurse, the experienced nurse, the nursing informatics specialist, the nursing informatics innovator and the nursing informatics researcher in the area of HIT safety. The work represents a significant contribution to the literature in the area of nursing informatics competency development as it extends nursing informatics competencies to include those focused on the area of technology-induced errors and HIT safety.
An Ethnographically Informed Participatory Design of Primary Healthcare Information Technology in a Developing Country Setting
Authors: Shidende Nima Herman  , Igira Faraja Teddy  , Mörtberg Christina Margaret
Published: February 2025

Ethnography, with its emphasis on understanding activities where they occur, and its use of qualitative data gathering techniques rich in description, has a long tradition in Participatory Design (PD). Yet there are limited methodological insights in its application in developing countries. This paper proposes an ethnographically informed PD approach, which can be applied when designing Primary Healthcare Information Technology (PHIT). We use findings from a larger multidisciplinary project, Health Information Systems Project (HISP) to elaborate how ethnography can be used to facilitate participation of health practitioners in developing countries settings as well as indicating the importance of ethnographic approach to participatory Health Information Technology (HIT) designers. Furthermore, the paper discusses the pros and cons of using an ethnographic approach in designing HIT.
Nursing Students' Perceived Learning from a Digital Health Assignment as Part of the Nursing Care for the Childbearing Family Course
Authors: Theron Maggie  , Redmond Anne  , Borycki Elizabeth M.
Published: February 2025

To increase the competency of undergraduate nursing students to find and evaluate online health information, a Digital Health Assignment was created for second year nursing students. Facebook was used as the assignment platform. Students chose and appraised social media postings regarding topics of interest for expecting families. Students utilized an adapted Trust in Online Health Information scale to appraise the social media postings, including the quality of information. At completion of the assignment, student evaluation surveys revealed the knowledge gained through the learning activity. Implications for nursing education are suggested.
A Digital Framework to Support Providers and Patients in Diabetes Related Behavior Modification
Authors: Abidi Samina  , Vallis Michael  , Piccinini-Vallis Helena  , Imran Syed Ali  , Abidi Syed Sibte Raza
Published: February 2025

We present Diabetes Web-Centric Information and Support Environment (D-WISE) that features: (a) Decision support tool to assist family physicians to administer Behavior Modification (BM) strategies to patients; and (b) Patient BM application that offers BM strategies and motivational interventions to engage patients. We take a knowledge management approach, using semantic web technologies, to model the social cognition theory constructs, Canadian diabetes guidelines and BM protocols used locally, in terms of a BM ontology that drives the BM decision support to physicians and BM strategy adherence monitoring and messaging to patients. We present the qualitative analysis of D-WISE usability by both physicians and patients
Development and Validation of a Multivariable Prediction Model for the Occurrence of Delirium in Hospitalized Gerontopsychiatry and Internal Medicine Patients
Authors: Kramer Diether  , Veeranki Sai  , Hayn Dieter  , Quehenberger Franz  , Leodolter Werner  , Jagsch Christian  , Schreier Günter
Published: February 2025

Delirium is an acute confusion condition, which is common in elderly and often misdiagnosed in hospitalized patients. Early identification and prevention of delirium could reduce morbidity and mortality rates in those affected and reduce hospitalization costs. We have developed and validated a multivariate prediction model that predicts delirium and gives an early warning to physicians. A large set of patient electronic medical records have been used in developing the models. Classical learning algorithms have been used to develop the models and compared the results. Excellent results were obtained with the feature set and parameter settings attaining accuracy of 84%.
Bluetooth Low Energy Peripheral Android Health App for Educational and Interoperability Testing Purposes
Authors: Frohner Matthias  , Urbauer Philipp  , Sauermann Stefan
Published: February 2025

Based on recent telemonitoring activities in Austria for enabling integrated health care, the communication interfaces between personal health devices (e.g. blood pressure monitor) and personal health gateway devices (e.g. smartphone, routing received information to wide area networks) play an important role. In order to ease testing of the Bluetooth Low Energy interface functionality of the personal health gateway devices, a personal health device simulator was developed. Based on specifications from the Bluetooth SIG a XML software test configuration file structure is defined that declares the specific features of the personal health devices simulated. Using this configuration file, different scenarios are defined, e.g. send a single measurement result from a blood pressure reading or sending multiple (historic) weight scale readings. The simulator is intended to be used for educational purposes in lectures, where the number of physical personal health devices can be reduced and learning can be improved. It could be shown that this simulator assists the development process of mHealth applications by reducing the time needed for development and testing.
Ad hoc Participation in Professional Tele-Collaboration Platforms
Authors: Staemmler Martin  , Rimmler Barbara  , Münch Heiko  , Engelmann Uwe  , Sturm Johannes
Published: February 2025

Tele-collaboration between medical professionals is well established for specialties like radiology, cardiology or pathology. Typically these applications do not allow for ad hoc participation of non-registered users like patients and / or medical professionals. This paper describes an approach for extending these tele-applications to non-registered users and providing ad hoc participation with means for providing and accessing data. A light weight, web-based approach is used to assure acceptance and ease of use while maintaining and complying to the required regulations regarding authentication, authorization and protection of personal data. The approach has been implemented and is in use with a nationwide tele-collaboration network in Germany.
HifoCap: An Android App for Wearable Health Devices
Authors: Cheon Yoonsik  , Romero Rodrigo  , Garcia Javier
Published: February 2025

Android is becoming a platform for mobile health-care devices and apps. However, there are many challenges in developing soft real-time, health-care apps for non-dedicated mobile devices like smartphones and tablets. In this paper, we share our experiences in developing the HifoCap app, a mobile app for receiving electroencephalogram (EEG) wave samples from a wearable device, visualizing the received EEG samples, and transmitting them to a cloud storage server. The app is network and data-intensive. We describe the challenges we faced while developing the HifoCap app—e.g., ensuring the soft real-time requirement in the presence of uncertainty on the Android platform—along with our solutions to them. We measure both the time and space efficiency of our app and evaluate the effectiveness of our solutions quantitatively. We believe our solutions to be applicable to other soft real-time apps targeted for non-dedicated Android devices.
Registration and Visualization System Geo-Referenced in Health – SirGeoS
Authors: Olivera Guerrero Francisco Javier  , Soto Sumuano Jesús Leonardo  , Tlacuilo Parra José Alberto  , Garibaldi Covarrubias Roberto  , Romo Rubio Hugo  , Abundis Gutierrez Emmanuel
Published: February 2025

This application offers a computerized solution to the registration and geo-referenced visualization of patients, neoplasms and associated environmental contamination. The statistical information generated allows physicians and hospitals to evaluate in a timely manner the behavior of the disease and its association with the pollutants, also by means of algorithms to obtain clusters that allow the delimitation of high risk areas. In general, the application allows the study of pediatric patients with different neoplasms and different contaminants. The particular case presented here is the study and analysis of the electromagnetic contamination associated with leukemia in the infant population of the metropolitan area of Guadalajara, the application allows the registration of the general information of the patient as well as the measurements of electric and magnetic field in High and low frequency. The results shows the geographical distribution of patients, radiation values received, hospitals, schools, high voltage lines, telecommunication antennas and high risk areas for contamination using maps, graphs and data tables. As a conclusion, we now have a real-time tool that facilitates the creation of prevention policies to combat the impact of radiation as one of the possible causes in the development of leukemia in the child population considered as an additional element of health risk public.
Towards a Quantitative Approach for Web Usability Using Eye Tracking Data
Authors: Luna-Maldonado Mario  , Ortiz-Bustillos Ramón  , López-Orozco Francisco  , Florencia-Juárez Rogelio
Published: February 2025

This paper presents a relatively new approach to show how a web usability classical paradigm can be benefit from quantitative data of a non-classical approach. In a pilot stage, we used experimental eye tracking data acquired from 11 participants faced to a three simple tasks on a web page.
Evaluation and Comparison of Metrics for XML Schema Languages
Authors: Falola Oluwadamilare  , Misra Sanjay  , Adewumi Adewole  , Damasevičius Robertast
Published: February 2025

The importance of XML (eXtensible Markup Language) can't be understated; their usefulness may range from data sharing to data transport in software systems. Schema languages describe the structure of an XML document and the common schemas languages are Document Definition Type (DTD), W3C XML Schema and RelaxNG. Applications depend heavily on XML documents to be free of error and this makes it imperative to determine the quality of such schema document. Schema metrics is used to achieve this, and several of them have been proposed in recent years. In this paper we present the existing schema metrics and to make comparative studies on all schema metrics, figuring out the features, advantages and limitations of each metrics.
Pharmacovigilance Mobile Tool Design in the Field of Arhroplasty
Authors: Åserød Hanne  , Babic Ankica
Published: February 2025

Pharmacovigilance is an important part of the patient safety and it has a great appeal to physicians. It is concerned with the safety of medical devices and treatments in the light of understanding the risks and dangers based on the already reported safety issues. Internet resources such as the Manufacturer And User Facility Device Experience (MAUDE) web-site are often retrieved due to the lack of internal, local safety databases. The research looked at how Human Computer Interaction could improve user experience. We have designed data entry for safety reporting and pharmacovigilance based on the web-bases system called WebBISS (Web-based implant search system). The expectation is not only to improve usability, but also to stimulate physicians to enter their safety data and become also contributors, and not only users of information. The expert evaluation has been generally positive and encouraged stronger help and error reporting functions. The high fidelity design has given a good impression of the future mobile solution.
Smart Telecare Technology in Health and Social Primary Care Management for Personalized Approach in Greece
Authors: Alexandri Danae  , Tsirintani Maria
Published: February 2025

The paper studies the smart telecare utility in health & social care fields for the satisfactory increase of external and internal user through personalized approach and the capability proof of continuing management improvement through quality indicators. Primary survey studies of aged people's satisfaction through smart telecare in Greece – maybe in good health or patients or socially isolated – interviewing four types involved – aged, caregivers, health or social care providers and smart technology providers or producers. The sample seems positive to smart telecare for prevention, protection, safety and security. To sum up, they believe there are organizational problems in Greece due to lack of information.
Professional Values Among Female Nursing Students in Saudi Arabia
Authors: Allari Rabia S.  , Ismaile Samantha  , Househ Mowafa
Published: February 2025

Professional values are essential to nursing practice because they guide standards for working, provide a structure for evaluating behavior, and influence decisions making. The purpose of this study is to explore the perception of Saudi female nursing students on professional values and to assess the correlation between their perception of professional values in relation to their year of academic studies. We used a cross-sectional descriptive study where a survey was administered to 150 Saudi female nurses living in Riyadh. Results show that Saudi female nurses have a high perception of professional values relating to confidentiality, privacy, moral and legal rights, health and safety, and the work environment. Whereas Saudi nursing students have a low perception for participating in professional nursing activities, utilizing research in practice, peer review, public policy, and engaging in on-going self-evaluation. There was positive correlation between different professional values and academic years. The highest correlations were for the items related to caring and trust more than activism because nursing students at higher academic levels viewed the relationship with patients as more important than advancing health care systems through public policy, research, and professional organizations. In conclusion, nursing program administrators should put emphasis on improving the development of professional values through a role modeling approach to promote activism and professional values through the arrangement of meetings, exchange forums, and conferences with other nurses, managers, policy makers, innovators, and researchers within the nursing field.
Characteristics of the Highest Users of Emergency Services in Veterans Affairs Hospitals: Homeless and Non-Homeless
Authors: Gundlapalli Adi V.  , Jones Audrey L.  , Redd Andrew  , Suo Ying  , Pettey Warren B.P.  , Mohanty April  , Brignone Emily  , Gawron Lori  , Vanneman Megan  , Samore Matthew H.  , Fargo Jamison D.
Published: February 2025

Efforts are underway to understand recent increases in emergency department (ED) use and to offer case management to those patients identified as high utilizers. Homeless Veterans are thought to use EDs for non-emergent conditions. This study identifies the highest users of ED services in the Department of Veterans Affairs and provides descriptive analyses of these Veterans, the diagnoses for which they were seen in the ED, and differences based on their homeless status. Homeless Veterans were more likely than non-homeless Veterans to have >10 visits in the 2014 calendar year (12% vs. <1%). Homeless versus non-homeless Veterans with >10 visits were more often male, 10 ED visits were often treated for chest and abdominal pain, and back problems, whereas homeless Veterans were frequently treated for mental health/substance use. Tailored case management approaches may be needed to better link homeless Veterans with high ED use to appropriate outpatient care.
Research on Frequencies Change Rules of Single-Damaged Simply Supported Beam
Authors: Hu Zhaoguang
Published: February 2025

Based on Euler-Bernoulli beam and structure dynamics theory and by means of numerical experimentation, taking a single-damaged simply supported beam as the research object, this paper obtains the frequencies of the beam under the conditions of different damage positions and damage degrees. With the concept of damage factor, rate of change of frequency(RCF), mean value of RCF(MRCF), amplitude of RCF(ARCF), and the ratio of RCF(RRCF), the paper researches frequency characteristics of a simply supported beam. The results show that the frequency and RCF sensitivities are related to damage degree and damage position, and that the RRCF sensitivities are relate to damage position only. The influence of damage degree on the frequency is greater than that of damage position, and that the RCF value variation of the beam is not a monotonic function with the increase of modal order when the damage position and damage degree are constant. The frequency and RCF of the beam at different damage position are oscillation curves, and the oscillation times and amplitude value of RCF curve varies with the change of modal order.
A Method of Constructing Scenario Information Model Based on Power Operation Scene
Authors: Hou Zhansheng  , Peng Lin  , Han Haiyun  , Xu Min  , Wang Gang  , Wang He  , Zhou Qiang
Published: February 2025

This paper deals with a method and system of scenario information model based on electric power scene. The construction method includes the following steps: (1) Collecting scene information, (2) Scenario information classification, (3) Information model construction, (4) The formation of power operations situational awareness system and scene applications. Based on the scenario information model of electric power operation scene, this paper describes the entity from the six dimensions of human, auxiliary equipment, environment, time, task and service, and finds out the relationship between entity, instance and entity, and constructs information model, To achieve the power of the task of service discovery, interpretation, query and unified scheduling, to provide the necessary services.
Research on Location Planning of Urban Rail Transit Emergency Facility Considering Vulnerability Node
Authors: Zhu Lei  , Zhang Ning
Published: February 2025

A reasonable location planning of emergency facility is an important work in the emergency management of urban rail transit. Based on the complex network theory, we propose a reliable emergency facility location model that aiming to improve the coverage level for the nodes with high vulnerability. This is mainly due to that the nodes with the different vulnerabilities in the network have different requirements for coverage level. We research on the node vulnerability of urban rail transit using complex network theory, and identifies the key nodes in the network before location planning. The vulnerable nodes in the network will be given higher weight to improve their coverage level in the location model, so that the equilibrium and efficiency of emergency are enhanced. To efficiently solve the model, we develop a heuristic based on Lagrangian relaxation. Finally, the model and heuristic are applied to the emergency facility location in urban rail transit (URT) network in Nanjing, China. The proposed method is effective and robust, and contributes greatly to the performance of emergency facility location planning in emergency management of URT.
The Droplets Constant Culturing Analyzer Based on Microfluidic Chip Control
Authors: Qiao Xinyong  , Cai Qiang  , Huang Cancan  , Wang Zhenhua
Published: February 2025

The droplets constant culturing analyzer based on microfluidic chip control is a device that cut the bacterial fluid into 800 microns long columnar droplets in parallel to culture, in order to realize real-time monitor and control paraments like pH and specific chemical factors of each parallel segments. The instrument can perform micro-droplet segmentation, fresh medium droplet generation, electric fusion of new micro-drops function, realizing the cell culture and passage operation of micro-droplet, thus realizing the function of microbial amplification and mutation adaptation evolution of microorganisms.
Development of an Aircraft Turnaround Time Estimation Model Based on Discrete Time Simulation
Authors: Wang Haiqiang  , Wang Min  , Wu Yang
Published: February 2025

According to the actual operation data, the operation cost of a typical medium range single aisle commercial transport aircraft will increase 30 dollars if it stays on ground for one more minute, leading to 1 million dollars increase in its life cycle cost. For the purpose of decreasing cost, airlines require the airplanes can turnaround within a short time period. Boarding and deplaning time accounts for more than half of the total turnaround time, however the current estimation method uses empirical data and cannot evaluate the effects from the aircraft design parameters. An aircraft turnaround time estimation model is developed based on the discrete time simulation, which deems boarding and deplaning as a dynamic process. The interaction between one passenger and other passengers, and the interaction between passengers and cabin are taken into account. The model has been compared with the boarding and deplaning data suggested by aircraft manufacturers. A twin aisle airplane is studied and the sensitivity of cabin design parameters is investigated. The results show that the model is suitable for aircraft designers to determine aircraft design parameters to meet the constraint regarding to aircraft turnaround time.
ZLCC: Vehicle Detection and Fine-Grained Classification Based on Deep Network Responses and Hierarchical Learning
Authors: Joya Chen  , Li Shunxi
Published: February 2025

Vehicle detection and recognition is the research focus in Intelligent Transportation System (ITS) with many challenges. Based on the success of Convolutional neural networks (CNN) in object detection and image classification, we propose a ZLCC to locate vehicle and classify its maker & model & shape. Our framework focuses on two new perspectives: (i) how to generate a small number of high quality region proposals, (ii) how to improve vehicle classification accuracy rate by hierarchical learning policy. We use deep network's responses to generate aware-map in detection, and train network with multiple candidates softmax regression. We demonstrate the success of ZLCC on Stanford Cars for using the deep VGG16 architecture.
The Systematic Design of Road Traffic Signal Recognition Based on the Integration of ZigBee with Active FRID
Authors: Liang Ziyi  , Xu Ping
Published: February 2025

In order to improve the safety of motorists and to realize driving automation and unmanned, a road traffic signal recognition system based on the integration of ZigBee network and FRID is designed. Firstly, the devices of Radio Frequency Identification (RFID) is installed on the original road signs, traffic lights and road markings. It can transmit traffic signals, which are consistent with the original encoded information. At the same time, the device is the terminal node of ZigBee network. Then, routers and coordinator nodes are installed in the necessary place. At last, the network of road condition information is formed in the way of ad-hoc network. When the cars equipped with traffic signal recognition system are driving in this network, they can receive encoded information of traffic signal and converts the received traffic signal encoded information into a voice signal, or converts it into a vehicle control signal to control the vehicle. The system has some good points, with a high recognition rate, long recognition distance, real-time, secure, reliable, easy to implement and so on.
Energy Management Strategy for a Hybrid Vehicular Power System Based on Haar Wavelet Transform
Authors: Li Bo  , Bei Shaoyi  , Zhao Jingbo  , Zhou Ting  , Ni Zhang  , Liu Qing
Published: February 2025

Hybrid vehicular power system is a complicated and nonlinear system, and its energy management strategy is one key factor for vehicle performance. The hybrid powertrain consisting of engine, Ni-MH battery and ultra-capacitor is designed, and the energy management strategy for a hybrid vehicular power system is proposed by Haar wavelet which makes vehicle power demand into high frequency and low frequency parts, then distributed among engine, Ni-MH battery and ultra-capacitor by genetic algorithm with the aim of reducing fuel consumption, therefore, improves the system performance and lengthens the service life of components. System modeling and simulation are conducted in Matlab, and the results show that this method of power distribution can meet the design requirements, and have better fuel economy compared to fuzzy control strategy.