bluuebunny/crossref_metadata_2025 huggingface dataset:
A Clause Tableau Calculus for MinSAT
Authors: Li Chu Min  , Manyà Felip  , Soler Joan Ramon
Published: February 2025

We define a clause tableau calculus for MinSAT, and prove its soundness and completeness. The calculus allows one to compute the maximum number of clauses that can be falsified in a multiset of clauses by applying, finitely many times, tableaux-like inference rules. We also describe how the calculus can be extended to solve weighted MinSAT and weighted partial MinSAT.
Word Embeddings for Latvian Natural Language Processing Tools
Authors: Znotiņš Artūrs
Published: February 2025

Word embeddings or distributed representations of words in a low dimensional vector space have been shown to capture both syntactic and semantic word relationships. Recently, multiple methods have been proposed to learn good word vector representations from very large text corpora effectively. Such word representations have been used to improve performance in a variety of natural language processing tasks. This work compares multiple methods to learn word embeddings for Latvian language and applies them to part of speech tagging, named entity recognition and dependency parsing tasks achieving state-of-the-art results for Latvian without resorting to any hand crafted and language specific features or resources such as gazetteers.
Towards Hybrid Neural Machine Translation for English-Latvian
Authors: Pinnis Mārcis
Published: February 2025

This paper investigates a hybrid method for translation from English into Latvian by chaining an NMT system with an SMT system in order to cover out-of-vocabulary word translation. Different from other works, the primary translation is handled by the NMT system, and the SMT system acts as a secondary system. Automatic evaluation results have shown that the hybrid method allows improving NMT translation quality by up to three BLEU points.
Robots and Moral Obligations
Authors: Smakman Matthijs
Published: February 2025

Using Roger Crisp's [1] arguments for well-being as the ultimate source of moral reasoning, this paper argues that there are no ultimate, non-derivative reasons to program robots with moral concepts such as moral obligation, morally wrong or morally right. Although these moral concepts should not be used to program robots, they are not to be abandoned by humans since there are still reasons to keep using them, namely: as an assessment of the agent, to take a stand or to motivate and reinforce behaviour. Because robots are completely rational agents they do not need these additional motivations, they can suffice with a concept of what promotes well-being. How a robot knows which action promotes well-being to the greatest degree is still up for debate, but a combination of top-down and bottom-up approaches seem to be the best way.
Moral Patients: What Drives the Perceptions of Moral Actions Towards Humans and Robots?
Authors: Küster Dennis  , Świderska Aleksandra
Published: February 2025

Robots will eventually become capable of engaging in norm-regulated interactions with humans. But do people perceive them as equivalent moral entities? We will present two psychological studies (one completed, one ongoing) on the perception of robots as moral patients. Our data suggest that robots are afforded a certain degree of moral consideration in the face of malevolent as well as benevolent actions, yet systematic differences to humans still remain. We will attempt to explain these empirical findings as a function of the level of human likeness of appearance and behaviors of robots, using visual vignettes.
A Generic Scale for Assessment of Attitudes Towards Social Robots: The ASOR-5
Authors: Damholdt Malene Flensborg  , Olesen Martin Hammershøj  , Nørskov Marco  , Hakli Raul  , Larsen Stefan  , Vestergaard Christina  , Seibt Johanna
Published: February 2025

The research field into social robotics is expanding and with it the need for consistent methods for assessing attitudinal stance towards social robots. In this paper we describe the development and planned validation of the Attitudes towards social robots scale (ASOR-5): a generic questionnaire developed by an interdisciplinary taskforce.
Bringing the Notion of Everyday Life Back to the Center of Social Robotics and HRI
Authors: Hannibal Glenda
Published: February 2025

Notions such as agency, interaction, gender, sociality, animacy, emotions, and empathy have all been favored in critical explorations of social robotics. In this paper I aim to show that, since the notion of everyday life is motivating the entire field of social robotics and HRI, it is necessary to empirically reconstruct how roboticist within these fields interpret and (re)construct this specific notion. The notion of everyday life with its current meanings and some initial reflections about how such notion gets its content, as well as how this concern differs from the one found in laboratory studies, will be discussed. After these theoretical reflections, very general suggestions will be given about how to empirically study the notion of everyday life when taking into account the ways in which it is being used among the social robotics and HRI engineers themselves.
Assessment of Computer-Assisted Screening Technology for Diabetic Retinopathy Screening in India – Preliminary Results and Recommendations from a Pilot Study
Authors: John Sheila  , Ram Keerthi  , Sivaprakasam Mohanasankar  , Raman Rajiv
Published: February 2025

Background: Diabetic retinopathy (DR) is regarded as a major cause of preventable blindness, which can be detected and treated if the cases are identified by screening. Screening for DR is therefore being practiced in developed countries, and tele screening has been a prominent model of delivery of eye care for screening DR.
Executable Models of Event Driven Systems
Authors: Bicevskis Janis  , Bicevska Zane  , Karnitis Girts
Published: February 2025

The approach proposed in this paper is based on usage of Domain Specific Languages (DSL) and allows create executable information systems' models. It lets us apply principles of the Model Driven Development (MDD) to information systems development and use: bridges the gap between business and IT, take an exact specification of information system, up-to-date documentation etc. The practical experience proves the viability of the proposed approach.
A Goal-Oriented Approach to Dynamic Business Process Simulation
Authors: Vasilecas Olegas  , Savickas Titas  , Normantas Kestutis  , Vysockis Tadas  , Kalibatiene Diana
Published: February 2025

Nowadays, to stay competitive businesses must be able to quickly adapt to rapidly changing marketing environment and/or exploit new market opportunities. Simulation of business process allows to analyze various business scenarios under different circumstances, provides an understanding of the most important factors affecting the process, and helps in identifying critical parts of the process. However, traditional business process simulation approaches consider business process as a pre-defined sequence of activities, limiting possibilities to adapt a process model to changes occurring in the business environment. In this paper we present a goal-oriented approach to simulate dynamic business processes, where a complete set of process activities as well as their execution sequence are not known in advance. The paper highlights main principles of the dynamic business process simulation approach, presents a prototype tool implementing the approach, and provides an example, demonstrating the dynamic business process simulation.
Implementation of Self-Management
Authors: Bicevskis Janis  , Bicevska Zane  , Oditis Ivo
Published: February 2025

The paper is devoted to the topics of self-management and its implementation. Self-management features are intended to support the usage and maintenance processes in information systems life cycle. Four self-management types are analyzed in the paper. Run-time verification and environment testing can be implemented without any intervention in base business processes, while self-testing and business process incorporation in system require an instrumentation of the base business processes. The approach is applied in praxis and shows that the implementation of self-management features requires relatively modest resources.
Infiniviz – Virtual Machine Based High-Resolution Display Wall System
Authors: Bundulis Rudolfs  , Arnicans Guntis
Published: February 2025

The existing research in the field of large-scale high-resolution display wall systems has mainly been focused on specific needs and environments. In many cases, the solutions built for large-scale high-resolution visualization are only valid for a specific use case (e.g. distributed 3D rendering, presentation of HTML content, stereoscopic projection). However, such solutions can soon become outdated and be left unmaintained (as seen with several distributed OpenGL library implementations). This happens due to the appearance of new technologies that solve the existing tasks in a more effective manner. A possible solution is to prevent most limitations on the set of technologies that can be used when the software is running on a display wall system. One way of achieving this is to use virtualization. This chapter presents Infiniviz – a virtual machine based high-resolution display wall system. Infiniviz approaches the visualization task in a seamless manner. The main aim of Infiniviz is to be able running any common desktop operating system software on a large scale high-resolution display wall without any modifications. Infiniviz achieves this by running a headless virtual machine with the required operating system backed by a custom software stack that handles the actual visualization. The authors have performed performance evaluations, virtualization environment comparisons and comparisons among other display wall architectures. This work along with key conclusions has been summarized in this chapter.
Database to Ontology Mappings in RDB2OWL: Notation and Implementation
Authors: Būmans Guntars  , Čerāns Kārlis
Published: February 2025

We review the RDB2OWL language for relational database to RDF/OWL mapping specification, as it has evolved from the original notation, taking into account the experience from practical use cases. We describe the RDB2OWL mapping implementation via translation both into D2RQ and standard R2RML mapping notations.
Refactoring – Key to Success for Constantly Developed Projects
Authors: Põld Janari  , Kalja Ahto  , Robal Tarmo
Published: February 2025

Each day new applications are developed and extra features are added to the existing ones. This means establishment of new program code or introducing modifications to the existing code. To ease up new modifications, software design should be constantly improved to cope with the vast changes added. The quality of software architecture plays an important role, it determines the time to market new features, maintainability and extensibility of applications and readability of the source code. Sustaining overall quality of architecture requires refactoring phases for the design to cope with new changes, which also restores source code readability and extensibility. More experienced developers conduct code reviews in different phases of application development to pin point places that need improvements. Several code refactoring steps can be applied to source code, to recover maintainability and extensibility of it. Refactoring is playing an important role, not only in software development, but also in other fields. In this article the authors give an overview, what can be achieved by refactoring and point out some success stories. Several aspects of refactoring process are studied, and a refactoring strategy proposed.
The Performance of Allocation Method on Imbalanced Data
Authors: Karakatič Sašo  , Heričko Marjan  , Podgorelec Vili
Published: February 2025

This paper presents results of classification on imbalanced data with ensemble allocation method. The result of the allocation method were compared to traditional techniques for dealing with imbalaced datasets – the sampling methods. The allocation method is a two level ensemble that combines unsupervised and supervised learning. In this research the first level of allocation the unsupervised anomaly detection is used as an allocator which is combined with several traditional classification method on second level of ensemble. The allocation method is tested on imbalanced datasets and the results are compared to two well used sampling methods – under-sampling of majority instances, and over-sampling with SMOTE which introduces new artificial instances of minority class to the dataset. Results of all of the methods were compared on overall accuracy and average F-score metrics. The results show that allocation method produces the best classification model, which is also supported by statistical analysis.
Chance Constrained Twin Support Vector Machine for Uncertain Pattern Classification
Authors: Yang Ben-Zhang  , Xiao Yi-Bin  , Huang Nan-Jing  , Cao Qi-Lin
Published: February 2025

In this paper, using chance constrained programming formulation, a new chance constrained twin support vector machine (CC-TWSVM) is proposed. This paper studies twin support vector machine classification when data points are uncertain with measurement statistically noise. With some properties known for the distribution, the CC-TWSVM model aims to ensure the small probability of error classification for the uncertain data. We also provide equivalent second-order cone programming (SOCP) model of the CC-TWSVM model by the properties of moment information of uncertain data. The dual problem of SOCP model is introduced and the optimal value of the CC-TWSVM model can be solved directly. In addition, we also show the performance of CC-TWSVM model in artificial data and real data by numerical experiments.
Deep Learning with Large Scale Dataset for Credit Card Data Analysis
Authors: Niimi Ayahiko
Published: February 2025

In this study, two major applications are introduced to develop advanced deep learning methods for credit card data analysis. Credit card information is contained in two data sets; credit approval dataset and card transaction dataset. The credit card dataset has two problems. One problem is using credit card approval dataset, it is necessary to combine multiple models, each referring to a different clustered group of users. The other problem is using card transaction dataset, since the actual unauthorized credit card use is very small, these imprecise solutions do not allow the appropriate detection of fraud. To solve these problems, we proposed deep learning algorithm to apply credit card dataset. The proposed methods are validated using benchmark experiments with other machine learnings. To evaluate our proposed method, we use two credit card datasets, credit approval dataset by UCI machine learning repository and credit transaction dataset constructed by random. The experiments confirm that deep learning exhibits comparable accuracy to the Gaussian kernel support vector machine (SVM). The proposed methods are also validated using large scale transaction dataset. Moreover, we apply our proposed method for the time-series benchmark dataset. Deep learning parameter adjustment is difficult. By optimizing the parameters, it is possible to increase the learning accuracy.
Soil Heavy Metal Pollution Research Based on Statistical Analysis and BP Network
Authors: Sun Wei-Wei  , Sheng Xing-Ping
Published: February 2025

Heavy metals in soil not only affect the growth of plants, also harm to people's health through the food chain, and may cause the problem such as air and water pollution, influence the ecological function of urban soil. Therefore, in order to improve the living environment and solve the pollution problem thoroughly, we must find out the cause of the heavy metal pollution. In this article, through pollution index evaluation, statistical analysis, BP network spatial interpolation to establish mathematical model. The soil heavy metal pollution degree, reason and pollution source location are obtained. It provides important basis for environmental protection and urban development.
Quantum Inspired Bee Colony Optimization Based Multiple Relay Selection Scheme
Authors: Lai Feng-Gang  , Li Yu-Tai  , Shang Zhi-Jie
Published: February 2025

Multiple relay selection schemes for cooperative relaying considering maximizing the end-to-end signal to noise ratio (SNR) and power efficiency are researched in this paper. In cooperative multiple relay networks, the relay nodes which is selected are very important to the system performance. How to choose the best cooperative relay node number and which relay nodes are selected are an optimization problems. The exhaustive search scheme can solve the relay selection problem but the complexity will increase exponentially with the size of network, that is, the number of relays in the network. Two novel quantum bee colony optimization (QBCO) based relay selection schemes which optimize the SNR and power efficiency are proposed in this paper respectively. Simulation results show that the QBCO-based scheme has a much better performance compared with other schemes in literature.
Recommending Entities for E-R Model by Ontology Reasoning Techniques
Authors: Xu Xiao-Xing  , Ouyang Dan-Tong  , Liu Jie  , Ye Yu-Xin
Published: February 2025

Designing E-R model is still the key process for database design. This paper proposes a novel method to recommend entities for E-R model by OWL ontology. OWL ontology is open and shared knowledge which can be easily obtained for anybody from the internet. We adopt ontology reasoning techniques to capture domain concepts according to a set of predefined vocabularies. Some corresponding concepts in OWL ontology are pinpointed by a preprocessing module first. Then these concepts used as seeds are extended, deleted and modified by an operation module. We can acquire reasonable entities for E-R model through a series of processes. Based on experimental study the entities recommended by this method approach the expert level.
V-Sync: A Velocity-Based Time Synchronization for Multi-Hop Underwater Mobile Sensor Networks
Authors: Zhang Meng-Na  , Wang Hai-Yan  , Gao Jing-Jie  , Shen Xiao-Hong
Published: February 2025

Time synchronization plays an essential role in underwater wireless sensor networks (UWSNs). Many time synchronization methods have been proposed for terrestrial wireless sensor networks. However, none of them can be directly applied to UWSNs, because there are two fundamental challenges namely large propagation delays and node mobility. In this paper, we proposed a velocity-based time synchronization algorithm, called V-Sync. It's a novel method for multi-hop mobile UWSNs, which investigates the relationship between time-varying propagation delay and node mobility to eliminate the effect of node mobility and then corrects time deviation. In addition, it generates a stratified node model to make the multi-hop network time synchronized. Simulation results show that V-Sync achieves high precision and outperforms the existing time synchronization algorithms obviously.
Complex System in Scientific Knowledge
Authors: Xie Zong-Lin  , Xie Zheng  , Li Jian-Ping  , Duan Xiao-Jun
Published: February 2025

The research of complex systems is widespread in scientific fields, which mainly investigates how relationships among individual parts generate the collective behaviors of a system. This paper aims to analyze the effects of complex system in scientific knowledge by using the co-word occurrence analysis to the corpus of papers published in PNAS in the years 1999–2012. Surprisingly, the percentage of the papers containing ‘complex’ and ‘system’ contributing to the total accounts for 47%. The major topics of complex system, such as complex network, emergence, complexity, uncertainty also show growth trends. Some topic words in the social, biological, and physical sciences are selected by domain experts and are mapped into networks respectively based on their co-occurrence frequency. Finding is that ‘complex’ and ‘system’ are the core nodes in each network, which shows the importance of complex system in every research field.
State Assessment of Oil-Paper Insulation Based on Fuzzy Rough Sets
Authors: He De-Hua  , Cai Jin-Ding  , Xie Song  , Zeng Qing-Mei
Published: February 2025

Return voltage method (RVM) is a good method to study aging state of transformer insulation, but it is difficult to accurately assess the insulation aging state by a single characteristic quantity. In this paper, the fuzzy rough sets theory combined with RVM is proposed to assess the oil paper insulation state of transformer and construct the assessment system of oil paper insulation of transformer based on a lot of test data. First, the evaluation index of oil-paper insulation status of transformer is established by return voltage characteristic parameters. Then, fuzzy c-means clustering algorithm is used to obtain the membership function of the transformer test data along with fuzzy partition of characteristics .Moreover, the fuzzy attributes of assessment table of oil paper insulation statue is simplified according to the distinct matrix,and it extracts the evaluation rule of oil paper insulation condition. Finally, the examples in this paper demonstrate that the assessment system is effective and feasible, which provides a new idea for the assessment of transformer oil-paper insulation state. The research has practical value in application of engineering
Describing Legal Policies as Story Tropes in Normative Systems
Authors: Thompson Matthew  , Padget Julian  , Satoh Ken
Published: February 2025

TropICAL is a Domain Specific Language (DSL) for the description of abstract legal policies. Taking inspiration from narrative tropes, our DSL enables the creation of component “policies” that may be reused between case descriptions. These components are compiled to social institutions, which are realised in Answer Set Programming (ASP) code. In this way, the actions of defendant and plaintiff take the shape of a story which must conform to the rules in the ASP description. We propose the use of our DSL in a tool designed for lawyers to generate arguments for the argumentation process.
Interface Usability Across and Within EHR Vendors and Medical Settings: The Often Unexamined Need for Interface Similarities
Authors: Koppel Ross  , Kuziemsky Craig
Published: February 2025

Usability of health information technology (HIT), if considered at all, is usually focused on individual providers, settings and vendors. However, in light of transformative models of healthcare delivery such as collaborative care delivery that crosses providers and settings, we need to think of usability as a collective and constantly emerging process. To address this new reality we develop a matrix of usability that spans several dimensions and contexts, incorporating differing vendors, user, settings, disciplines, and display configurations. The matrix, while conceptual, extends existing work by providing the means for discussion of usability issues and needs beyond one setting and one user type.
Integration of Health Information Systems Using HL7: A Case Study
Authors: Kuo Jessica Wan-Yi  , Kuo Alex Mu-Hsing
Published: February 2025

Interoperability is a prerequisite for health information systems (HIS) that will reduce waste of unnecessary costs, errors, delays, and futile repetition. Many previous studies had proposed different approaches in the attempt to solve interoperability challenges. In this paper, we report our experiences in using Health Level 7 (HL7) standard and adopting the Common Gateway Model for exchanging heath data. The benefits and challenges of using standards for data interoperability are also described.
Developing a Manually Annotated Corpus of Clinical Letters for Breast Cancer Patients on Routine Follow-Up
Authors: Pitson Graham  , Banks Patricia  , Cavedon Lawrence  , Verspoor Karin
Published: February 2025

This paper introduces the annotation schema and annotation process for a corpus of clinical letters describing the disease course and treatment of oestrogen receptor positive breast cancer patients, after completion of primary surgery and radiotherapy treatment. Concepts related to therapy, clinical signs, and recurrence, as well as relationships linking these, are identified and annotated in 200 letters. This corpus will provide the basis for development of natural language processing tools for automatic extraction of key clinical factors from such letters.
Medical and Healthcare Curriculum Exploratory Analysis
Authors: Komenda Martin  , Karolyi Matěj  , Pokorná Andrea  , Vaitsis Christos
Published: February 2025

In the recent years, medical and healthcare higher education institutions compile their curricula in different ways in order to cover all necessary topics and sections that the students will need to go through to success in their future clinical practice. A medical and healthcare curriculum consists of many descriptive parameters, which define statements of what, when, and how students will learn in the course of their studies. For the purpose of understanding a complicated medical and healthcare curriculum structure, we have developed a web-oriented platform for curriculum management covering in detail formal metadata specifications in accordance with the approved pedagogical background, namely outcome-based approach. Our platform provides a rich database that can be used for innovative detailed educational data analysis. In this contribution we would like to present how we used a proven process model as a way of increasing accuracy in solving individual analytical tasks with the available data. Moreover, we introduce an innovative approach on how to explore a dataset in accordance with the selected methodology. The achieved results from the selected analytical issues are presented here in clear visual interpretations in an attempt to visually describe the entire medical and healthcare curriculum.
Connecting the Links: Narratives, Simulations and Serious Games in Prehospital Training
Authors: Heldal Ilona  , Backlund Per  , Johannesson Mikael  , Lebram Mikael  , Lundberg Lars
Published: February 2025

Due to rapid and substantial changes in the health sector, collaboration and supporting technologies get more into focus. Changes in education and training are also required. Simulations and serious games (SSG) are often advocated as promising technologies supporting training of many and in the same manner, or increasing the skills necessary to deal with new, dangerous, complex or unexpected situations. The aim of this paper is to illustrate and discuss resources needed for planning and performing collaborative contextual training scenarios. Based on a practical study involving prehospital nurses and different simulator technologies the often-recurring activity chains in prehospital training were trained. This paper exemplifies the benefit of using narratives and SSGs for contextual training contributing to higher user experiences. The benefits of using simulation technologies aligned by processes can be easier defined by narratives from practitioners. While processes help to define more efficient and effective training, narratives and SSGs are beneficial to design scenarios with clues for higher user experiences. By discussing illustrative examples, the paper contributes to better understanding of how to plan simulation-technology rich training scenarios.
Bridging the Semantic Gap Between Diagnostic Histopathology and Image Analysis
Authors: Traore Lamine  , Kergosien Yannick  , Racoceanu Daniel
Published: February 2025

With the wider acceptance of Whole Slide Images (WSI) in histopathology domain, automatic image analysis algorithms represent a very promising solution to support pathologist's laborious tasks during the diagnosis process, to create a quantification-based second opinion and to enhance inter-observer agreement. In this context, reference vocabularies and formalization of the associated knowledge are especially needed to annotate histopathology images with labels complying with semantic standards. In this work, we elaborate a sustainable triptych able to bridge the gap between pathologists and image analysis scientists. The proposed paradigm is structured along three components: i) extracting a relevant semantic repository from the College of American Pathologists (CAP) organ-specific Cancer Checklists and associated Protocols (CC&P); ii) identifying imaging formalized knowledge issued from effective histopathology imaging methods highlighted by recent Digital Pathology (DP) contests and iii) proposing a formal representation of the imaging concepts and functionalities issued from major biomedical imaging software (MATLAB, ITK, ImageJ). Since the first step i) has been the object of a recent publication of our team, this study focuses on the steps ii) and iii). Our hypothesis is that the management of available semantic resources concerning the histopathology imaging tasks associated with effective methods highlighted by the recent DP challenges will facilitate the integration of WSI in clinical routine and support new generation of DP protocols.
Acquisition of Expert/Non-Expert Vocabulary from Reformulations
Authors: Antoine Edwige  , Grabar Natalia
Published: February 2025

Technical medical terms are complicated to be correctly understood by non-experts. Vocabulary, associating technical terms with layman expressions, can help in increasing the readability of technical texts and their understanding. The purpose of our work is to build this kind of vocabulary. We propose to exploit the notion of reformulation following two methods: extraction of abbreviations and of reformulations with specific markers. The segments associated thanks to these methods are aligned with medical terminologies. Our results allow to cover over 9,000 medical terms and show precision of extractions between 0.24 and 0.98. The results and analyzed and compared with the existing work.
On the Prototyping of an ICT-Enhanced Toilet System for Assisting Older Persons Living Independently and Safely at Home
Authors: Panek Paul  , Fazekas Gabor  , Lüftenegger Theresa  , Mayer Peter  , Pilissy Tamas  , Raffaelli Matteo  , Rist Atilla  , Rosenthal Ramona  , Savanovic Arso  , Sobjak Anna  , Sonntag Franziska  , Toth Andras  , Unger Birgit
Published: February 2025

Standard toilets often do not meet the needs of a significant number of older persons and persons with disabilities. The EU funded iToilet project aims at design and development of a new type of ICT enhanced modular toilet system which shall be able to support autonomy, dignity and safety of older persons living at home. Methodologically the project started with gathering user requirements by means of questionnaires, interviews and focus group discussion involving a total of 74 persons, thereof 41 subjects with movement disorders (primary users), 21 caregivers (secondary users) and 12 healthcare managers (tertiary users). Most important wishes were bilateral removable handrails, height and tilt adjustment, emergency detection, simplicity. In parallel to the ongoing technical development participatory design activities have been carried out at user test sites in order to continuously involve users into the design process and to allow quick feedback with regards to early prototype parts. The project currently is working on the finalization of the first prototype ready to enter the lab trial stage in spring 2017. The experiences will be used for redesigning a prototype 2 which is planned to be tested in real life settings early 2018.
A View on Dealing with Privacy and Computer Malware Concerns
Authors: Longpré Luc
Published: February 2025

Computer security and privacy concerns have become a priority for our nation. A traditional approach is to develop strong and intelligent virus and intrusion detection programs. Although this approach is important, we believe this approach will never really put these concerns to rest. A more promising approach for running security and privacy sensitive programs is to be able to run them with guaranteed confidentiality and integrity in spite of a computing environment containing malware. We start with the difficulty of defining privacy and a review of some existing definitions. We continue with different approaches to run programs securely in an insecure environment. This includes white listing and process isolation techniques.
Impact of Network Coding Buffers on the Video Transmission Performance
Authors: Lopez-Fuentes Francisco de Asís  , Cabrera-Medina Cesar
Published: February 2025

Network coding is a promising technique in the field of Information Theory that has shown improved performance of communication networks. These benefits have been mainly oriented to energy savings or increase throughput. This paper evaluates the impact of network coding in buffer usage during the process of video transmission. In this evaluation, the video packets are encoded in the source while network coding is implemented in the intermediate nodes before forwarding the encoded packets to the end nodes. The received packets are decoded in the end nodes in order to recover the original video signal. The video sequences are compressed under the H.264/MPEG-4 AVC standard, and the experiments are simulated in network simulator (NS-2). The results show that network coding provides savings in the use of buffers in video transmission, which allows decreasing the delay, increasing throughput, and improving the video quality.
Generics Pricing: The Greek Paradox
Authors: Karafyllis Ioannis  , Variti Lamprini
Published: February 2025

This paper explains and develops a methodological framework to help evaluate the performance of generic pharmaceutical policies and the correct evaluation of generics sales. Until today erroneous recording of generics does not help proper pricing and their penetration in the Greek market. This classifies Greece on the outliners in every study or comparison that is referred on papers or studies.
User Perceptions of the Implementation of an Electronic Medication Management System in a Paediatric Setting
Authors: Hardie Rae-Anne  , Baysari Melissa T.  , Lake Rebecca  , Richardson Lauren  , McCullagh Cheryl  , Westbrook Johanna I.
Published: February 2025

The roll-out of a hospital-wide electronic medication management system (eMMS) is a challenging task, requiring planning, coordination, communication and change management. This research aimed to explore the views of doctors and nurses about the strategy used to implement an eMM system in a paediatric hospital. Semi-structured interviews were performed during the first week of the implementation on each ward, and were then followed up three and six weeks post implementation. In total, 90 users (60 nurses and 30 doctors) were asked about their impressions of the implementation, as well as their perceptions of training and IT support. Qualitative thematic analysis was performed by three researchers. Most users perceived the implementation of the eMM to be positive overall. Although perceptions of the implementation process remained largely consistent across the six weeks, users identified several areas where improvements were needed, especially early in implementation, including resources, planning, roll-out strategy and training. These findings are useful for future implementations of eMM systems in paediatric hospitals.
dSPACE Based HIL Simulation Platform for Missile Control System
Authors: Chen Yun  , Ma Qinghua  , Wang Gen  , Miao Haochun
Published: February 2025

dSPACE based hardware-in-the-loop (HIL) missile control system simulation platform with the key benefits of powerful operational capability and convenient hardware interface is provided. The system structure design and development steps were analyzed. In the platform, the compiled simulation model, established in the MATLAB/Simulink, runs on the real-time hardware platform, and the actuator as the real physical part. This platform realized the HIL design and simulation, and the simulation process is similar to the real environment. Experimental results showed that the dSPACE based real-time simulation system is an excellent platform for missile control system design which enhanced the efficiency and reliability.
Heath Care Management Using Knowledge Management and Information Technology
Authors: Karamat Jawad  , Tong Shurong  , Waheed Abdul  , Mahmood Kashif
Published: February 2025

The health care industry is a vital part of any country and its economy. The health care industry seek increasingly to improve quality by improving clinical outcomes, patient experiences and a business case that support movement toward ‘patient-centered care’. The health care industry by becoming knowledge based community. This can be done by creating communication between many hospitals, clinics, pharmacies, and customers. The sharing of knowledge should be increased, the reduction of administrative costs and improvement in the quality of care. The health care will be able to do this by using knowledge management (KM) and information technology (IT). This research study seeks to come up with a framework that investigates the different dimensions of knowledge management and IT and how it will help in improving health care. In order to come up with a framework the three elements of KM which are knowledge acquisition, knowledge application and knowledge dissemination and use of IT to make it efficient. If properly used IT can accelerate knowledge-sharing capabilities in both time and space dimensions. Locality, timing, and relevancy factors determine the expediency and the strength of IT's role in KM initiatives.
Mice Liver Cirrhosis Microscopic Image Analysis Using Gray Level Co-Occurrence Matrix and Support Vector Machines
Authors: Wang Yu  , Cao Luying  , Dey Nilanjan  , Ashour Amira S.  , Shi Fuqian
Published: February 2025

Liver cirrhosis is a commonly chronic disease that often requires checking liver pathological microscopic images. To reduce the intensity of the work of doctors, pre-classification work needs to be issued and in this paper, related liver microscopic image classification analysis was proposed. Firstly, the extraction methods of mice liver images were taken using different features for different image features, and secondly, image features were obtained to form the original data-set; finally, the image classification experiments were conducted using gray level co-occurrence matrix (GLCM) and a developed support vector machine (SVM). The best classification model derived from the established characteristics is that GLCM performed the highest accuracy of classification; the training model using 11 features was accurately that only trained by 8 GLCMs. The experimental results preliminarily verified the feasibility of the method used in the experiment of classifying liver microscopic images of mice, and laid the foundation for further construction of computer aided diagnosis system.
An Approach to Identify Travel Hotspots at Night Based on Mobile Phone Data
Authors: Dai Guanchen  , Li Linchao  , Zhang Jian  , Zhang Xiaoli  , Lei Yi  , Yang Zhongyue  , Peng Qiuying
Published: February 2025

To improve the urban transport planning and safety management, an approach is proposed to identify travel hotspots based on mobile phone data. The workflow including data processing, movement state recognition, computing of travel density, identification of travel hotpots and visualization is described. A case study is presented to test the proposed approach. Moreover, the spatial distribution change of travel hotspots by time internal is analyzed. The location differences of travel hotspots on weekdays and weekends are also identified accurately with thematic map. The result shows that the hotspot identification can locate spatial clustering of trip activities effectively. It indicates that this approach is a valuable supplementary way to make up for the deficiency of traditional field surveys. It can provide some significant information for unban transport management and planning.
Studies on Gravimeter Leveling Algorithm Based on Mixed Sensitivity Robust Control Theory
Authors: Wang Hai-miao  , Qin Yong-yuan  , Qiao Xiang-wei  , Zhang Zhao-fei
Published: February 2025

For providing a good condition of measuring, the gravimeter gyro-stabled platform plays an important part in the gravimeter system. By adopting the pure-inertial and the all-digital controlling technology of real-time leveling, the gravimeter gyro-stabled platform will be directed primarily towards isolating the angular motion of the carrier, and keeping the sensitive axis of the gravimeter parallel with the plumb line all the time. In the sea condition, the gravimeter gyro-stabled platform has a low precision in the disturbing of low frequency of sea waves, this paper introduces a leveling algorithm based on Mixed Sensitivity. By adopting a reasonable leveling bandwidth, performance bound function, controller weighting function and bounded uncertainty function, we achieve an optimal control to the leveling loop via the algorithm.
The Tracker with Online Training Based on the TLD Algorithm
Authors: Qi Yongfeng  , Zhang Peng
Published: February 2025

TLD is a real-time long-term tracking system that decomposes the tasks into three components: tracking, learning and detection. The learning estimates detector's errors and updates it to avoid these errors in the future. However, Current implementation of TLD trains only the detector and the tracker stay fixed. As a result, the tracker makes always the same errors. In our paper, we develop a novel training method which combines naive Bayes classifier with the optical flow based on the TLD algorithm to train the tracker. The proposed algorithm mainly consists of two stages: one stage for training and a second stage for tracking. For the training stage, we sample some positive samples near the current target location and negative samples far away from the object center to update the classifier from the current frame. For the tracking stage, Optical flow tracker estimates the object's motion between consecutive frames under the assumption that the frame-to-frame motion is limited and the object is visible. And then we sample a set of image patches, using the classifier to each patch. We determine the target with the maximal classification score. With these definitions, we conduct extensive experiments and comparisons for the proposed method. The comparisons and experiments well demonstrate the effectiveness of our work.
A Preprocessing Algorithm Before Conflict Detection Based on Hybrid Surveillance
Authors: Wang Yu-bo  , Wang Hai-jun  , Jiao Wei-dong  , Zhou Bo  , Shen Xiao-yun
Published: February 2025

The probability of flight conflict is increased because of the increasing of flight flow and uncertainty of flight route. Considering the problem that redundant operation which caused by a large number of non-related targets. A preprocessing algorithm before conflict detection was proposed. Aircrafts within the surveillance scope of Automatic Dependent Surveillance-Broadcast (ADS-B) IN were divided into 26 different regions, and the correlation between targets was distinguished by special rule of each region. Then the correlated targets were further processed, but uncorrelated ones were blocked. So the calculation of conflict analysis for surveilling surrounding targets was decreased. Above all, the processing principle that security first should be followed, and rather false alarm but never leakage alarm. Finally, the necessity and validity of the proposed algorithm is examined by using Monte Carlo experiment. The simulation results show that not less than 30% of 30 random objects are blocked. The proposed algorithm is effective and accurate for detecting the correlation of them.
Innovative Approaches in Chronic Disease Management: Health Literacy Solutions and Opportunities for Research Validation
Authors: Villaire Michael  , Gonzalez Diana Peña  , Johnson Kirby L.
Published: February 2025

This chapter discusses the need for innovative health literacy solutions to combat extensive chronic disease prevalence and costs. The authors explore the intersection of chronic disease management and health literacy. They provide specific examples of successful health literacy interventions for managing several highly prevalent chronic diseases. This is followed by suggestions on pairing research and practice to support effective disease management programs. In addition, the authors discuss strategies for collection and dissemination of knowledge gained from collaborations between researchers and practitioners. They identify current challenges specific to disseminating information from the health literacy field and offer potential solutions. The chapter concludes with a brief look at future directions and organizational opportunities to integrate health literacy practices to address the need for effective chronic disease management.
Comparing Recent Reviews About Touchscreens for Dementia with Lessons Learnt from the Field
Authors: Schikhof Yvonne  , Goumans Marleen  , Joddrell Phil  , Astell Arlene
Published: February 2025

Conclusions were synthesised from recent reviews on (touchscreen)technologies and people with dementia and lessons learnt, using these devices in projects in the UK, the Netherlands and Canada. The combined findings provide a strong basis for defining new strategies for exploiting touchscreen technology for people with dementia.
Evaluation Method for an App Involving Kitchen Activities
Authors: Burzagli Laura  , Gaggioli Andrea
Published: February 2025

An app, developed for the national Italian project “Design for all”, is evaluated here. This app supports the user in most of his/her cooking activities. The evaluation process integrates different technologies, such as expert interview, cognitive walkthrough and focus group, to consider different aspects that include, but are not limited to, usability and accessibility.
Security Requirements Engineering (SRE) Framework for Cyber-Physical Systems (CPS): SRE for CPS
Authors: ur Rehman Shafiq  , Gruhn Volker
Published: February 2025

Security is an important feature of the software. Integrating security requirements right at the beginning not only ensure secure software but also save a lot of precious time and reduce the effort of rework of software development team. However, to build a secure system is not an easy task and it is extremely difficult to develop a secure system, especially in the case of cyber-physical systems (CPS). In this paper, we propose a security requirements engineering framework that provides ways to determine security requirements throughout the requirements engineering phase which consists of a number of activities to elicit and finalize the security requirements for CPS. Additionally, we determine the activities that need to be implemented in the security requirements engineering framework to address security requirements for CPS. We compare our proposed security requirements engineering framework with other existing software security frameworks. The result shows that not all software security frameworks perform all the basic and important activities in the development of secure software systems. This may also result in a development of an unsecure cyber-physical systems. Furthermore, this comparison survey helps us to identify the short-comings in SRE frameworks which has been rectified in our proposed security requirements engineering framework for CPS.