bluuebunny/crossref_metadata_2025 huggingface dataset:
Multicultural Adaptive Systems
Authors: Jaakkola Hannu  , Thalheim Bernhard
Published: February 2025

The paper develops an approach to information system adaptation supporting diversity and heterogeneity of users. The user perspective is handled from culture point of view. Cultures are layered and this structure can be used for starting with national cultures and deriving stereotypes. Culture is recognised as a multidimensional structure, in which national culture provides a basement for the behavioural variations of individuals in personal level. For information system development this layering covers three different perspectives: cultural stereotypes and user models, organisational models and technology models. We thus may develop a coherent information system perspective that supports adaptivity in multicultural information system applications.
eLogika – the system for teaching logic
Authors: Menšík Marek  , Duží Marie  , Gerlich Jakub
Published: February 2025

In this paper we introduce the Learning Management System (LMS) eLogika that has been developed in our department for teaching mathematical logic. There were many reasons that led us to the decision to develop such a system, including inter alia a great amount of students enrolled for the courses on logic. Yet the most important reason was a specific character of logic education. As a result, the eLogika system is a web application that provides didactic material for courses on mathematical logic. Its main goal is an automatic test generation and computer-aided test evaluation based on a large database of logic tasks. The system makes it possible to adjust the level of particular tests according to students' knowledge level. To this end we developed a feedback module that makes use of statistics and data mining methods. The system can generate a large number of training as well as exam test variants for each common thematic topic. At the same time it provides effective semi-automatic methods of test rating and evaluation. In the paper we describe particular modules of eLogika with the focus on the modules of data mining and statistics.
Development And Usage Of A Process Model Corpus
Authors: Walter Jürgen  , Thaler Tom  , Ardalani Peyman  , Fettke Peter  , Loos Peter
Published: February 2025

Process modeling plays an increasingly important role in organizational and software design. However, there is a lack of concrete examples of process models. An open and freely available corpus covering process models from different domains and application areas would offer a great potential for research and development. Typical applications of a model corpus are: (1) Creating a consistent and coherent understanding of business application systems in different domains and industries, (2) reusing the process models in other contexts, (3) creating a homogeneous data basis for different application and analysis scenarios. Against that background, this paper aims at developing a process model corpus, which may serve as a standardized data basis for the mentioned application scenarios. In order to realize that objective, the authors propose a procedure model serving as the basis for the process model corpus. This corpus contains reference models, models from practice and models from controlled environments and, in total, comprises 16 model collections with 2,290 process models.
Emotion Identification System for Musical Tunes based on Characteristics of Acoustic Signal Data
Authors: Endrjukaite Tatiana  , Kiyoki Yasushi
Published: February 2025

We design and implement a music-tune analysis system to realize automatic emotion identification and prediction based on acoustic signal data. To compute physical elements of music pieces we define three significant tunes parameters. These are: repeated parts or repetitions inside a tune, thumbnail of a music piece, and homogeneity pattern of a tune. They are significant, because they are related to how people perceive music pieces. By means of these three parameters we can express the essential features of emotional-aspects of each piece. Our system consists of music-tune features database and computational mechanism for comparison between different tunes. Based on Hevner's emotions adjectives groups we created a new way of emotion presentation on emotion's plane with two axes: activity and happiness. That makes it possible to determine perceived emotions of listening to a tune and calculate adjacent emotions on a plane. Finally, we performed a set of experiments on western classical and popular music pieces, which presented that our proposed approach reached 72% precision ratio and show a positive trend of system's efficiency when database size is increasing.
Activity Classification Using Mobile Phone based Motion Sensing and Distributed Computing
Authors: Artetxe Arkaitz  , Beristain Andoni  , Kabongo Luis
Published: February 2025

In this work we present a system that uses the accelerometer embedded in a mobile phone to perform activity recognition, with the purpose of continuously and pervasively monitoring the users' level of physical activity in their everyday life. Several classification algorithms are analysed and their performance measured, based for 6 different activities, namely walking, running, climbing stairs, descending stairs, sitting and standing. Feature selection has also been explored in order to minimize computational load, which is one of the main concerns given the restrictions of smartphones in terms of processor capabilities and specially battery life.
Method for Building a Medical Training Simulator with Bayesian Networks: SimDeCS
Authors: Flores Cecilia Dias  , Fonseca João Marcelo  , Bez Marta Rosecler  , Respício Ana  , Coelho Helder
Published: February 2025

Distance education has grown in importance with the advent of the internet. An adequate evaluation of students in this mode is still difficult. Distance tests or occasional on-site exams do not meet the needs of evaluation of the learning process for distance education. Bayesian networks are adequate for simulating several aspects of clinical reasoning. The possibility of integrating them in distance education student evaluation has not yet been explored much. The present work describes a Simulator based on probabilistic networks built to represent knowledge of clinical practice guidelines in Family and Community Medicine. The Bayesian Network, the basis of the simulator, was modeled to playable by the student, to give immediate feedback according to pedagogical strategies adapted to the student according to past performance, and to give a broad evaluation of performance at the end of the game. Simulators structured by Bayesian Networks may become alternatives in the evaluation of students of Medical Distance Education.
Two Innovative Healthcare Technologies at the Intersection of Serious Games, Alternative Realities, and Play Therapy
Authors: Brahnam Sheryl  , Brooks Anthony L.
Published: February 2025

Using game technologies and digital media for improving physical and mental health and for the therapeutic benefit and well-being of a wide range of people is an area of study that is rapidly expanding. Much research in this emerging field is centered at the intersection of serious games, alternative realities, and play therapy. In this paper the authors describe their transdisciplinary work at this intersection: i) an integrative system of psychotherapy technologies called MyPsySpace currently being prototyped in Second Life with the aim of offering new and virtual translations of traditional expressive therapies (virtual sandplay, virtual drama therapy, digital expressive therapy, and virtual safe spaces) and ii) a mature body of research entitled SoundScapes that is exploring the use of interactive video games and abstract creative expression (making music, digital painting, and robotic device control) as a supplement to traditional physical rehabilitation intervention. Aside from introducing our work to a broader audience, our goal is to encourage peers to investigate ideas that reach across disciplines–to both risk and reap the benefits of combining technologies, theories, and methods stemming from multiple disciplines.
Specification of Extended Reflexive Ontologies in the context of CDSS
Authors: Sanchez Eider  , Toro Carlos  , Graña Manuel  , Sanín Cesar  , Szczerbicki Edward
Published: February 2025

Decision recommendations are a set of alternative options for clinical decisions (e.g. diagnosis, prognosis, treatment selection, follow-up and prevention) that are provided to decision makers by knowledge-based Clinical Decision Support Systems (k-CDSS) as aids. We propose to follow a reasoning over domain approach for the generation of decision recommendations, by gathering and inferring conclusions from production rules. In order to rationalize our approach we present a specification that will sustain the logic models supported in the Knowledge Bases we use for persistence. We introduce first the underlying knowledge model and then the necessary extensions that will convey towards the solution of the reported needs. The starting point of our approach is the work of Toro et al. [13] on Reflexive Ontologies (RO). We also propose an extension of RO, by including the handling and reasoning that production rules provide. Our approach speeds-up the recommendation generation process.
Social Robots and Social Interaction
Authors: Hakli Raul
Published: February 2025

I study the implications of the use of social robotics to our concepts of social interaction in everyday usage and in philosophical theories of social action. If people sometimes conceive their activities with robots as cases of social interaction even though they do not attribute to robots all the capacities that philosophers take to be necessary requirements for participating in social interaction, these requirements may need to be reconsidered. For instance, some analyses of social interaction require that the parties of interaction are jointly committed in the activity in question in ways that involve obligations. However, such normative concepts as commitments and obligations may not be attributable to robots, but people may still conceive themselves as being involved in social interaction with them. If this is the case, there is a tension between how social interaction is understood in everyday contexts and how it is analysed in philosophy. I study different ways to understand this tension in terms of alternative methodological orientations towards conceptual analysis of social interaction.
Social Robots as Mirrors of (Failed) Communion
Authors: Toivakainen Niklas
Published: February 2025

The initial point of this paper is that when we are engaged with the world, with human beings and morality in a technological or techno-scientific framework, we are projecting an interest of power — our interest to know how things are “work” — into our conceptual scheme. In contrast to a technological understanding, I suggest that human beings are characterised by a non-technological moral necessity. I characterise this moral necessity as an inherent responsiveness, an I-you relationship, whereas my claim is that a technological conception of morality takes as its ethical basis collective social identities.
A New Single Image Deblurring Algorithm Using Hyper Laplacian Priors
Authors: Chang Chia-Feng  , Wu Jiunn-Lin
Published: February 2025

Motion blur is an ill-posed problem which has been addressed for a long time in digital photographing. It usually happened under the circumstance that surrounding light is not enough. Several methods had been proposed for this problem. However, ringing is inevitable artifacts arising in the deconvolu-tion stage. To suppress undesirable artifacts, regularization based methods have been proposed using natural image priors to overcome the ill-posedness of de-convolution problem. These studies suggest that priors based on natural image statistics can regularize deblurring problems to yield better results.
A (n, n)-threshold Secret Sharing Scheme for Barcode Application
Authors: Lin Pei-Yu  , Chen Yi-Hui  , Chuang Jun-Chou
Published: February 2025

A secret sharing systembased upon two-dimensional QR barcode is proposed in this article. The proposed approach utilizes the QR characteristics to achieve secret sharing and can resist the print and scan operation. General browsers can read the original data from the marked QR tag via barcode reader. Only the authorized participants can cooperate to reveal the lossless secret. According to the experiments, the new secret sharing approach can satisfy the content readability and cheater detectability of the QR barcode.
Extended Cycles Embedding on Folded Hypercubes with Vertex-Fault-Tolerant
Authors: Kuo Che-Nan
Published: February 2025

An n-dimensional folded hypercube FQnis an attractive variance of an n-dimensional hypercube Qn, which is obtained by a standard hypercube with some extra edges established between its vertices. An n-dimensional folded hypercube (FQnfor short) for any odd n is known to be bipartite. In this paper, let f be a faulty vertex in FQn. It has been shown that (1) Every edge of FQn−{f} lies on a fault-free cycle of every even length l with 4≤l≤2n−2 where n≥3; (2) Every edge of FQn−{f} lies on a fault-free cycle of every odd length l with n+1≤l≤2n−1, where n≥2 is even. In terms of every edge lies on a fault-free cycle of every odd length in FQn−{f}, our result extend the result of Cheng et al. (2013) where odd cycle length up to 2n−3.
A Near-Duplicate Video Detection Method Based on Invariant Moments and Feature Point Matching
Authors: Chang Tang-You  , Guo Min-Yuan  , Tai Shen-Chuan  , Lin Guo-Shiang
Published: February 2025

In this paper, a two-level near-duplicate video detection method based on invariant moment was proposed. To reduce the computational complexity of near-duplicate video detection, a coarse-to-fine approach was adopted in the proposed method. The proposed method is composed of key-frame selection, invariant moment calculation, feature point extraction and matching, similarity measurement, and near-duplicate classifier. After key-frame selection, the proposed method coarsely finds the corresponding frame pairs based on invariant moments. For each chosen frame pair, SURF is used to find the corresponding point pairs between the query frame and the test one. After feature-level, spatial-level, and temporal-level similarity measurement, we can decide whether the query video clip and the test one are near-duplicate. The experimental results show that the proposed method can effectively detect near-duplicate videos. In addition, the proposed method has good performance against possible operations, re-scaling, and frame-rate change.
Fast Coding Unit Depth Decision Method for HEVC Encoders
Authors: Wang Chou-Chen  , Wang Hsiang-Chun  , Jhou Ming-Shum
Published: February 2025

The newest standard of video coding, the high efficiency video coding (HEVC) achieves significantly better coding efficiency than all existing video coding standards. HEVC adopts the quadtree-structured coding unit (CU) to improve the coding efficiency. Each CU node in quadtree will be traversed by depth first search process to find the best coding tree unit (CTU) partition. Although this quadtree search process can obtain the best CTU partition, it requires a very high computational complexity, especially the motion estimation (ME) process in interframe coding. To alleviate the encoder computation load in interframe coding, a fast CU depth range decision (FCUDRD) method is proposed by reducing the depth search range. Based on the depth information correlation between temporal-spatial adjacent CTUs and the current CTU, some depths can be adaptively excluded from the depth search process in advance. The best depth of current CTU is determined by an intersection between temporal predicted depth ranges by 9 Gaussian weightings from encoded blocks and spatial predicted depth ranges by 4 best weightings from encoded blocks, separately. Experimental results show that the FCUDRDcan achieve time improving ratio (TIR) about 55.73% for RA and 65.77%for LD on average, respectively, as compared to the HM8.1 with insignificant loss of image quality.
Green Computing: An SLA-based Energy-aware Methodology for Data Centers
Authors: Chang Yao-Chung  , Peng Sheng-Lung  , Liao Yi-Hsuan  , Chang Ruay-Shiung
Published: February 2025

Cloud computing enables a pay-as-you-go model of utility-oriented services. It also enables the hosting of common applications for consumer and business use. However, the energy consumption, operational costs, and carbon emissions of data centers are very high. Therefore, a Green Cloud Computing solution is needed not only to reduce the energy consumption and environmental impact of cloud computing, but also to minimize operational costs. Conventional Green Cloud computing solutions reduce the performance of Cloud data center hosts. They may also incur penalties for Service-Level-Agreement (SLA) violations. This study therefore proposes a new framework for improving the energy efficiency of data centers by using efficient virtual machine allocation and selection mechanisms to reduce power consumption. A DVFS (Dynamic Voltage and Frequency Scaling) technique is also used to shorten host wakeup time. The proposed framework addresses the growing importance of SLA by decreasing total operational costs.
A global optimized neuro-fuzzy system using artificial bee colony evolutionary algorithm
Authors: Liu Yu-Ting  , Lin Yang-Yin  , Hsieh Tsung-Yu  , Wu Shang-Lin  , Lin Chin-Teng
Published: February 2025

This paper proposes a novel Takagi–Sugeno–Kang-type (TSK-type) neuro-fuzzy system (NFS), which utilizes the artificial bee colony (ABC) evolutionary algorithm for parameter optimization. The ABC evolutionary algorithm was developed based on imitating foraging behavior of natural bees for numerical optimization problems, and it has been proved to outperform other metaheuristic approaches on different constrain optimization problems in previous studies. The proposed NFS in this paper adopts an adaptive clustering method to generate fuzzy rules for determining the system architecture, and the TSK-type reasoning is employed for the consequent part of each rule. Subsequently, all free parameters in the NFS designed, including the premise and the consequent parameters, will be optimized by ABC algorithm. This study compares the performance of ABC algorithm with that of Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE). The simulation results show that the performance of ABC algorithm is superior to that of the mentioned algorithms for solving dynamic system problems.
Code Smells Detection and Visualization of Software Systems
Authors: Lee Shin-Jie  , Lin Xavier  , Lo Li Hsiang  , Chen Yu-Cheng  , Lee Jonathan
Published: February 2025

Bad smells are symptoms in the source code that indicate possible deeper problems and may serve as drivers for code refactoring. Although efforts have been made on measuring code complexity in object-oriented systems, such as CK metrics, little emphasis has been put on analyzing code smells through a visualization manner. In this paper, we present a system for detecting and visualizing three kinds of code smells of software systems: Long Method, Large Class, and Long Parameter List. Thresholds for identifying the code smells are calculated based on statistics analysis on the source code of 50 open source projects. Code smells are visualized as graphs with colored nodes according to their different severity degrees.
A Leading Indicator of Post-Release Defect Density in Refactoring-based Software Maintenance – A Case Study
Authors: Cheng Yu Chin  , Jwo Jung-Sing  , Tsai Ching-Tsorng
Published: February 2025

We look to create a leading indicator to relate, between two consecutive releases of a software product, the changes in post-release defect density to the changes of the internal factors identified as interrelated to refactoring. In the case study that involves a maintenance phase to bring the post-release defect densities of two suites of tools down to within the organization's upper limit, the proposed leading indicator correctly generated the desired negative correlation with the trend of changes in post-release defect density.
Context-Aware RESTful Service Delivery Mechanism for Smartphones
Authors: Ma Shang-Pin  , Chen Ping-Chang  , Li Chi-Chia  , Lee Wen-Tin
Published: February 2025

How to provide continued and smooth access to web services from smartphones under unstable network or during network disconnections is an important issue to be solved. In the past decade, many methods for service caching are proposed, however, a significant concern is commonly overlooked in these methods: a variety of contexts, namely, how to maintain the availability of mobile services for smartphones under a variety of mobile network conditions, such as high-speed network, unstable network, and no network access. In this paper, we propose a context-aware RESTful service delivery (CARSD) approach to address the above issue. The CARSD approach is encapsulated as client-side libraries to be utilized by mobile applications to invoke backend RESTful services. CARSD can perform different actions for different network conditions, such as prefetching service responses and using cached service in high speed wireless network, only using cached service in unstable wireless network, and allowing the user to request cached service response from other users when no wireless network can be accessed. The implementation and experiments demonstrate that the proposed CARSD approach can effectively improve service availability and shorten service response time in various network conditions.
A Novel Light Weight Balance Monitoring Tool for Elderly Care
Authors: Chu William Cheng-Chung  , Chang Chih-Hung  , Hsu Tse-Chuan  , Kawsar Ferdaus A.  , Johnson Nadiyah  , Saxena Piyush  , Williams Drew  , Ahamed Sheikh Iqbal  , Tsao Chia-Yu
Published: February 2025

Novel balance detection systems are an important for various reasons. It is especially necessary for measuring imbalance for elderly people. Every year lot of older adults are injured caused by fall. A potential risk of falling can be identified from the measurement of balance of a person. Though injuries from fall can happen to persons of any age, it is it is particularly important for elderly people as they have a higher possibility of fall. Tools to measure imbalance are either very expensive or inaccurate. We have developed a system that can measure imbalance of a person and thus can detect risk of falling. It can be used by older adults to measure their balance and help care givers design appropriately for a particular elderly person.
A Novel Parallel Deduplication and Noise Reduction Method for Vertical Search Engine
Authors: Song Junjie  , Liu Jin  , Ni Ming  , Li Fei  , Wang Jian
Published: February 2025

This paper proposes a method noise reduction of topic specific web pages. The novel method is based on the frequency statistics and a method of deleting duplicate web pages through hash table and inverted index. According to the frequency statistics, those frequent occurrences of clauses will be considered to be noise and be deleted. Then the clauses and their urls will become the hash table's keys and values to search the duplicate web pages. We use four Map-Reduce tasks to ensure the method of web noise reduction and deleting duplicate web pages. The experiment result shows that the algorithm can remove duplicate web pages efficiently and accurately.
Forecasting the Impacts of Articles and Authors on the Social Forum during Emergencies
Authors: Wang Ming-Hung  , Lei Chin-Laung
Published: February 2025

The Sunflower movement is one of the most influential protests in Taiwan in recent years. Without any sign in advance, the protesters entered and occupied the building of the Legislative Yuan (the parliament) of Taiwan on March 18, 2014. However, there were few reporters at the scene, and information was in chaos at that time. In order to find an efficient approach to filter and disseminate information under this kind of urgent situations, we study the user behaviors on the largest bulletin board system in Taiwan. From our results, we provide effective methodologies to quantify and predict the impact of each article on the social forum and propose approaches to identify opinion leaders during emergencies.
A Novel SVM Based Multi-Facet Ranking Method for Topic Specific Web Pages
Authors: Cao Yanjun  , Liu Jin  , Zhang Jingtai  , Li Fei  , Zhong Bei
Published: February 2025

With the rapid development of network technology, Internet has become an important tool to publish, exchange and acquire information. Many fields such as news, advertising, consuming, finance, education, E-commerce are involved. However, the huge, dynamic, heterogeneous and semi-structured data structure environment makes general search engine hard to avoid “topic drift”, which needs users to choose the topic they are interested in. So, a topic specific search engine, which is more explicit in classification, having more data related to the topic and updates more timely is needed. To compensate for the general search engine's weakness processing domain information, this paper proposes a novel ranking algorithm based on machine learning for topic specific web pages, describes an experimental search engine based on this algorithm, and presents the experiment results.
Development of Graphical Editor for Supervisory Control and Data Acquisition System in Agriculture Greenhouse
Authors: Tsai Wen-Hao  , Liu W.C.  , Lee K.R.  , Su W.T.  , Chen P.Y.  , Kuo Y.H.
Published: February 2025

This paper based on facilitating information system integrators to develop supervisory control and data acquisition (SCADA) system customized in agriculture greenhouse, developed a “Graphical Editor for Supervisory Control And Data Acquisition System in Agriculture Greenhouse” for the establishment of agriculture greenhouse SCADA system. The system provides (1)Open System: the PLC can be the product of any brand, so that the user can no longer spend the extra money to replace hardware to get a customized SCADA system, if the user already has a SCADA system. It can effectively reduce the cost of the system replacement, and can also enhance the quality of agriculture planting. (2)Graphical Editor: SCADA Development Environment provides a convenient and user-friendly graphical user interface that makes information system integrators engineers to immediately establish a customized SCADA system via simply drag the icons. Furthermore, basic settings for the system, such as database connection, device control rule setting, permission setting, alarm setting and other functions, can be easily configured by user through the graphical editor. The main feature of SCADA Development Environment is that provide engineers setting communication between each peripheral device (sensor) and gateway without writing any code, and finally the whole project will automatically generate an executable file which can running on the specified gateway. This system greatly reduces the burden of information system integrator engineer; even the young farmers have relevant knowledge may also establish their SCADA system by themselves.
Landscape Recommendation System Using Public Preference Mining and Social Influence Analysis
Authors: Tsai Wen-Hao  , Lin Yan-Ting  , Lee Kuan-Rung  , Kuo Yau-Hwang  , Lu Bing-Huei
Published: February 2025

A novel landscape recommendation system which employs public preference and social influence to classify user preference orientation is proposed in this paper. Unlike traditional content-based or collaborative filtering recommendation approaches, we collected large scale information from heterogeneous data sources to construct the public preference model for user's feature-based preference orientation classification. Moreover, the social relation graph of target user is constructed to analyze social influence of preference between users in it. Then, the social influence of preference is calculated by social influence and interest similarity between users. The purpose of this paper is that using public preference to infer user preference and further adjusting user preference through social influence of preference from neighbors. The proposed method deals with the cold-start issue in recommendation system. There two main advantages of the proposed method are social relationship can be easily obtained from online social network and any type of recommendation system can be applied in the proposed method. In our experiment, Facebook, the most famous social media, is the platform selected for social relationship analysis. The experimental result shows our approach not only innovation but also practicable.
A Trustworthy Assurance-as-a-Service Architecture
Authors: Ramkumar Mahalingam  , Mohanty Somya
Published: February 2025

Increasing complexity and inter-dependency of information systems (IS), and the lack of transparency regarding system components and policies, have rendered traditional security mechanisms (applied at different OSI levels) inadequate to provide convincing confidentiality-integrity-availability (CIA) assurances regarding any IS. We present an architecture for a generic, trustworthy assurance-as-a-service IS, which can actively monitor the integrity of any IS, and provide convincing system-specific CIA assurances to users of the IS. More importantly no component of the monitored IS itself is trusted in order to provide assurances regarding the monitored IS.
Regulatory Framework for Information Security in Taiwan's New Personal Information Protection Act of 2012
Authors: Liao Wei-min
Published: February 2025

The New Personal Information Protection Act of 2012 of Taiwan (the PIPA) went into effect on October 1st, 2012. After almost 2 years it is still open to many questions and comments concerning the incorporation of information security in it. However, the regulatory framework for information security in the PIPA is in many aspects very promising for a solid development. This article purports to give a sketch of the legal basis, to make an introduction to the newest development, and to call for a rapider pace for the dialogue between jurists and information security engineers.
A High Capacity Reversible Multiple-Image Hiding Scheme
Authors: Lee Chin-Feng  , Chen Jui-Yu  , Chen Si-Ting
Published: February 2025

This paper proposed a high capacity two-phased method of reversible data hiding on dual steganographic images. The first phase calculates the difference values between adjacent grayscale pixels to generate a histogram and utilizes the histogram modification to embed data. The method of the first phase can embed 13~195 KB confident data for a 512×512 grayscale image while keeping a high PSNR of 52 dB for all nature images. The second phase generates two stego-images using the differences in blocks based on a four-quadrant magic matrix. The nature images of the second-phase method can carry a large amount of data (1.16~1.24 bit per pixel) while possessing a good visual quality (the PSNR of the stego-image versus the cover image is around 44.2 dB for all images). The proposed method compares the performance with the existing methods and is better than many of the existing algorithms.
Information Technologies to Improve Public Health: A Systematic Review
Authors: Manhas Melissa  , Kuo Mu-Hsing
Published: February 2025

This systematic review examines a total of eighteen studies on the use of health information technologies to improve public health. Health information technologies are tools that allow for the management of health information in computerized systems. Health information technology, including electronic health records, computers/emails, social media, and cellphones/text messaging are becoming widespread and readily accessible to populations around the globe. In this review, the use of these technologies and interventions are discussed and evaluated for their potential to improve public health. This review found some good-quality evidence on the use of electronic health records and little good-quality evidence on the use of email, social media, cell phones and text messaging to improve healthcare, illustrating the need for further study in these areas.
Modelling System Level Health Information Exchange: An Ontological Approach
Authors: McMurray J.  , Zhu L.  , McKillop I.  , Chen H.
Published: February 2025

Investment of resources to purposively improve the movement of information between health system providers is currently made with imperfect information. No inventories of system-level digital information flows currently exist, nor do measures of inter-organizational electronic information. exchange (HIE). Using Protégé 4, an open-source OWL Web ontology language editor and knowledge-based framework we formalized a model that decomposes inter-organizational electronic health information flow into derivative concepts such as diversity, breadth, volume, structure, standardization and connectivity. Self-reported data from a regional health system is used to measure HIE; the ontology identifies providers with low and high HIE, useful for planners, and using a related database is used to monitor data quality.
Closed circuit video for organizational learning in emergency unit
Authors: Parv Liisa  , Nøhr Christian
Published: February 2025

The ER is a highly erratic and error-prone environment where continuous organizational learning is an important part of providing good quality medical care. The article aims to evaluate how closed circuit video system is used in the ER department based on qualitative interviews with staff members. The results show that the system is used to improve work processes and treatment decisions as well as aid in professional training. Often video recordings provide the most objective information about a critical situation. The staff considers the system to protect and help professionals in their work and the security measures to be sufficient to protect patients.
Research on applying digital technology and infusing innovative teaching to courses of business administration education
Authors: Wu Ming-Hsiung  , Sun Jan-Pine  , Hung Ju-Yao  , Lee Bo-Jian  , Chan Tsun-Lu  , Shih Pei-Chun  , Ge Ting-Ting  , Yuan Yu-Hsi  , Lin Kuei-Miao  , Chen Chun-Han  , Wu Chi-Ming
Published: February 2025

The purpose of this study is to compile the teaching materials for education on college of commerce and management, and develop the corresponding digital learning achievement test and creativity test as evaluation mechanism. It aims to apply digital technology and the creative pedagogy to the curriculum of college of commerce and management at technology universities, in order to stimulate students' learning interests, learning initiatives, and critical thinking skills. This project is a three-year research plan and currently only the first year of the project was permitted and under engagement. This study compiled the digital-media teaching materials in the field of business administration, corresponding with the requirements of two courses “Innovative Technology Management” and “Cultural and Creative Industries Management”. The innovative pedagogy is applied to the two courses to achieve the main goal of developing student's problem-solving knowledge and abilities. The participants will be the junior students in the college of commerce and management at China University of Science and Technology. The two courses require students to download and preview the digital teaching materials from the WebDrive in advance of each class. There are activities of group discussion and achievement evaluation during each class to facilitate enhancing students' learning interests and learning effectiveness. Both group discussion and achievement evaluation are conducted once every three weeks and there are total six group discussions and six assessments in the 16-topic/week session. For course “Innovative Technology Management”, the digital teaching materials cover topics of creativity theories and practices, commercial innovation models and innovative technology management. And course “Cultural and Creative Industries Management” developed teaching materials of 16 units, and also held a “project planning contest for local cultural roots” for the junior students to cultivate their creativity, integration and implementation capabilities.
New IPA Discrimination Index for Cloud Virtualization Survey Platform
Authors: Wang Chiung-Hsia  , Hsu Hsueh-Fang  , Mai Yi-Ting  , Liu Hsiang-Chuan
Published: February 2025

In recent years, Cloud services are more popular for many network services. Cloud computing utilizes computing resources via a high bandwidth network to facilitate the execution of complicated multi-tasks that require large-scale computing. In this paper, we propose a novel Cloud multiple-function survey system. The survey system will allow users to either choose one option with one category or spread their super multiple options with multiple categories for each question with results in a multi-level scale. To analyze survey performance, our proposed new Importance-Performance Analysis (IPA) model discrimination index will reflect a more accurate quantity than the IPA model proposed by Hollenhorst (1992). Further, the index is implemented to compare and distinguish the effects of different types of survey events. Adopting the new IPA discrimination index to compare the homogeneous survey results will demonstrate t our scheme has better information for performance comparisons.
A Framework for Multi-Label Learning Using Label Ranking and Correlation
Authors: Shaukat Malik Irfan  , Usman Muhammad
Published: February 2025

Multi-relational data mining is a rapidly growing area used for mining relational databases. While traditional data mining approaches search patterns in a single data table, relational data mining techniques look for patterns which exist in multiple tables. Multi-label learning (classification) comes under multi-relational data mining technique. In multi-label learning, each instance is linked with multiple labels and the aim is to predict the suitable label set for the unseen instance. In this paper, we reviewed the recent approaches for multi-relational data mining with a specific focus on multi-label classification. Furthermore, we critically evaluate the prevalent techniques for the prediction of class labels. Moreover, we propose a conceptual model for multi-label learning using label ranking and label correlation simultaneously. The proposed model works concurrently in two modules. In the first module, Label Ranking is used to enhance the classifier process by ranking the classes on the basis of priority and in the second module; degree of correlation of data labels among training classes has been utilized to enhance the overall process of multi-label learning.
Optimal Care Mother-Baby and Outcomes through Community-wide Data Sharing, Interoperability and Connectivity
Authors: Shaha Steven H.  , Gilbert-Bradley Diane
Published: February 2025

The power of interoperable systems with data/information integration, central to achieving the goals of Telehealth, is illustrated through mutually beneficial sharing between Labor & Delivery (L&D) and Obstetrics (OBs) Clinics. Data shared between L&D and OB brought improved practice patterns and outcomes, and increased satisfaction at both. Staffing and skillsets were significantly improved by knowing complications arriving and anticipated volumes. OBs increased clinic efficiencies and improved patient-direct care time with improved clinical and cost outcomes.
Meeting the Semantic Challenge of the Globally Unique Identification of Medicinal Products - The openMedicine Approach
Authors: Stroetmann Karl A.
Published: February 2025

To better enable cross-border healthcare delivery, particularly the exchange of ePrescriptions, this global undertaking advances the unique identification of medicinal products (MPs) and patient safety in cross-border settings. Major stakeholders harmonise their respective efforts to deliver
How to use concept mapping to identify barriers and facilitators of an electronic quality improvement intervention
Authors: van Engen-Verheul Mariëtte  , Peek Niels  , Vromen Tom  , Jaspers Monique  , De Keizer Nicolette
Published: February 2025

Systematic quality improvement (QI) interventions are increasingly used to change complex health care systems. Results of randomized clinical trials can provide quantitative evidence whether QI interventions were effective but they do not teach us why and how QI was (not) achieved. Qualitative research methods can answer these questions but typically involve only a small group of respondents against high resources. Concept mapping methodology overcomes these drawbacks by integrating results from qualitative group sessions with multivariate statistical analysis to represent ideas of diverse stakeholders visually on maps in an efficient way. This paper aims to describe how to use concept mapping to qualitatively gain insight into barriers and facilitators of an electronic QI intervention and presents experiences with the method from an ongoing case study to evaluate a QI system in the field of cardiac rehabilitation in the Netherlands.
Mapping Russian Laboratory Terms to LOINC
Authors: Kopanitsa Georgy
Published: February 2025

The paper presents the results of semiautomatic mapping of Russian laboratory terms to LOINC. Two clinics (A and B) and a laboratory service participated in the project. We were able to map 86% (Clinic A) and 87% (Clinic B) of laboratory terms. The required effort was reasonable and the price of mapping and maintenance was considered as relatively low. We established LOINC as a canonical coding method for a laboratory data exchange. This provided semantic interoperability for the data exchange process.
Feasibility of Post-Acute Hip Fracture Telerehabilitation in Older Adults
Authors: Bedra McKenzie  , Finkelstein Joseph
Published: February 2025

Recent studies demonstrated potential of home-based telerehabilitation in older adults and individuals with mobility impairment. However limited evidence exists on feasibility of home-based telerehabilitation in older adults after hip fracture. The aims of this study were: (1) to assess impact of home-based telerehabilitation of community dwelling older adults in post-acute phase of recovery after hip fracture on mobility, psycho-behavioral factors, quality of life, and satisfaction with care; (2) to estimate acceptance of the telerehabilitation system and adherence to the exercise program. We found statistically significant improvements in exercise self-efficacy, mobility, quality of life, and patient satisfaction after 30-day hip fracture telerehabilitation. Home telerehabilitation may be a viable model for post-acute hip fracture recovery and it is warranted for further evaluation in clinical trials.
Incidence Rate of Canonical vs. Derived Medical Terminology in Natural Language
Authors: Topac Vasile  , Jurcau Daniel-Alexandru  , Stoicu-Tivadar Vasile
Published: February 2025

Medical terminology appears in the natural language in multiple forms: canonical, derived or inflected form. This research presents an analysis of the form in which medical terminology appears in Romanian and English language. The sources of medical language used for the study are web pages presenting medical information for patients and other lay users. The results show that, in English, medical terminology tends to appear more in canonical form while, in the case of Romanian, it is the opposite. This paper also presents the service that was created to perform this analysis. This tool is available for the general public, and it is designed to be easily extensible, allowing the addition of other languages.
Health Information Systems: evaluation and performance of a Help Desk
Authors: Pintos Leandro  , Stieben Adriana  , Garcia Gabriela  , Briatore Agustina  , Bertoia Agustina  , Benitez Sonia  , Giunta Diego  , Baum Analía  , Gonzalez Bernaldo de Quiros Fernán
Published: February 2025

A Help Desk (HD) is crucial in a computerized hospital.
GA-ANFIS Expert System Prototype for Prediction of Dermatological Diseases
Authors: Begic Fazlic Lejla  , Avdagic Korana  , Omanovic Samir
Published: February 2025

This paper presents novel GA-ANFIS expert system prototype for dermatological disease detection by using dermatological features and diagnoses collected in real conditions. Nine dermatological features are used as inputs to classifiers that are based on Adaptive Neuro-Fuzzy Inference Systems (ANFIS) for the first level of fuzzy model optimization. After that, they are used as inputs in Genetic Algorithm (GA) for the second level of fuzzy model optimization within GA-ANFIS system. GA-ANFIS system performs optimization in two steps. Modelling and validation of the novel GA-ANFIS system approach is performed in MATLAB environment by using validation set of data. Some conclusions concerning the impacts of features on the detection of dermatological diseases were obtained through analysis of the GA-ANFIS. We compared GA-ANFIS and ANFIS results. The results confirmed that the proposed GA-ANFIS model achieved accuracy rates which are higher than the ones we got by ANFIS model.
Development of a database and processing method for detecting hematotoxicity adverse drug events
Authors: Shimai Yoshie  , Takeda Toshihiro  , Manabe Shirou  , Teramoto Kei  , Mihara Naoki  , Matsumura Yasushi
Published: February 2025

Adverse events are detected by monitoring the patient's status, including blood test results. However, it is difficult to identify all adverse events based on recognition by individual doctors. We developed a system that can be used to detect hematotoxicity adverse events according to blood test results recorded in an electronic medical record system. The blood test results were graded based on Common Terminology Criteria for Adverse Events (CTCAE) and changes in the blood test results (Up, Down, Flat) were assessed according to the variation in the grade. The changes in the blood test and injection data were stored in a database. By comparing the date of injection and start and end dates of the change in the blood test results, adverse events related to a designated drug were detected. Using this method, we searched for the occurrence of serious adverse events (CTCAE Grades 3 or 4) concerning WBC, ALT and creatinine related to paclitaxel at Osaka University Hospital. The rate of occurrence of a decreased WBC count, increased ALT level and increased creatinine level was 36.0%, 0.6% and 0.4%, respectively. This method is useful for detecting and estimating the rate of occurrence of hematotoxicity adverse drug events.
A new tool for foetal phonocardiography simulation
Authors: Romano Maria  , Bifulco Paolo  , Iuppariello Luigi  , Clemente Fabrizio  , D'Addio Gianni  , Cesarelli Mario
Published: February 2025

Among diagnostic techniques for foetal monitoring, phonocardiography is gaining more and more interest for its low cost, passive nature and capability to detect some cardiac diseases. In spite of these characteristics, its use in clinical routine is still limited due to different troubles; for example, signals recorded through maternal abdomen show generally a quite low signal-to-noise ratio, so that detection and analysis of foetal heart sounds result very difficult. In this scenario, the availability of artificial phonocardiographic signals, simulated with conditions resembling different foetal conditions, week of gestation and noise amount, to name someone, can be a very useful tool to train medical staff. In this paper a software for phonocardiography simulation, updated to take account also of the split is presented. The software is completed with a user interface which allow to modify in a simple way simulation parameters. It is worth highlighting that this software can be useful also for testing performances of other analysis software and mathematical tools for recognising of valves components in the heart sounds.
A Method to Pinpoint Undiscovered Links in Genetic and Protein Networks
Authors: Ancusa Versavia  , Broasca Laura
Published: February 2025

Due to the still largely undiscovered gene interactions working with incomplete data is necessary. This paper presents a method to determine the information gap required to create a complete and workable depiction of a specific interaction network, starting from a database.