bluuebunny/crossref_metadata_2025 huggingface dataset:
Determinants of Clinical Information Logistics: Tracing Socio-Organisational Factors and Country Differences from the Perspective of Clinical Directors
Authors: Esdar Moritz  , Liebe Jan-David  , Babitsch Birgit  , Hübner Ursula
Published: February 2025

The establishment of successful clinical information logistics (CIL) within the care processes is one of the main objectives of strategic health IT management in hospitals. While technical realisations in terms of useful, usable and interoperable IT solutions are essential precursors of CIL, there is limited empirical research on what socio-organisational factors underlie an innovation-friendly culture and how they can affect successful information provision. We applied factor analysis on survey data from 403 clinical directors from Germany, Austria and Switzerland and used the dimensions identified to explain the level of CIL with ordered logistic regression analysis. The intensity of collaboration and exchange with the IT department as well as the degree of executive IT leadership showed to be strongly associated with better CIL while personal views and attitudes of clinical directors were not. Analysing country differences revealed the degree of the exchange with the IT department to be significantly lower in German hospitals. This points at a potential strategic lever for German hospital executives to focus on.
Ontology-Guided Markerless Navigation and Situational Awareness for Endoscopic Surgery
Authors: Tahar Kais  , Uciteli Alexandr  , Röppischer Philip  , Herre Heinrich  , Siemoleit Sebastian
Published: February 2025

Optical navigation systems help surgeons find their way through the complex anatomy of a patient. However, such systems are accident-sensitive, time-consuming and difficult to use because of their complicated technical requirements such as the setting of optical markers and their intraoperative registration. The BIOPASS project, therefore, provides an innovative localisation system for markerless navigation in endoscopic surgery to support medical decision making. This system comprises several machine learning classifiers to recognise anatomical structures visible in the endoscopic images. To verify the data provided by these classifiers and to alert medical staff about surgical risk situations, we developed a new ontology-based software called OntoSun. Our software improves the precision and the sustainable traceability of the classifiers' results and also provides warning messages that increase situational awareness during surgical interventions.
Deep Learning Employed in the Recognition of the Vector that Spreads Dengue, Chikungunya and Zika Viruses
Authors: Arista-Jalife Antonio  , Sanchez Alejandra  , Nakano Mariko  , Tünnermann Henrik  , Perez-Meana Hector  , Shouno Hayaru
Published: February 2025

In this paper, a novel Deep Neural Network topology is presented with the objective of recognizing the Aedes aegypti and Aedes albopictus mosquito in their larvarian stage, which are the vectors that cause Dengue, Chikungunya, Zika and Yellow Fever outbreaks. This solution allows to determine if a sample image is a larva of the Aedes aegypti or Aedes albopictus mosquito with an accuracy of 91.28%, a true positive rate of 94.18% and a true negative rate of 88.37%. This Deep Neural Network topology allows the implementation of fast and accurate preventive measures in under-developed countries and isolated areas where a trained specialist might not be available.
Multidisciplinary Approach to Myocardial Regeneration: In Vitro and In Silico Studies of Stem Cells Behaviour
Authors: Marconi Silvia  , Ledda Mario  , Bersani Alberto M.  , Giorgio Ivan  , Lisi Antonella  , Bersani Enrico  , Andreucci Daniele  , Genuini Igino  , Pisanelli Domenico M.  , De Lazzari Claudio
Published: February 2025

Stem cell therapy is a regenerative medicine technique consisting in introducing new cells into a damaged tissue in order to restore it. In this paper we present our multidisciplinary approach about the possible use of the Human Mesenchymal Stem Cells in treating heart failure. A multidisciplinary team composed by biologists, mathematicians, cardiologists and bioengineers was selected in order to investigate the feasibility of repairing the necrotic tissue damaged by myocardial infarction by means of Mesenchymal Stem Cells and to implement a new software simulator able to reproduce cells implantation, migration and proliferation. In the first step, biologists and cardiologists studied the Human Mesenchymal Stem Cells and measured selected parameters. Stem cells were isolated and cultured in order to study their growth and characterization. In the second step, mathematicians and bioengineers developed a new numerical model based on the studies and the data measured during in vitro experiments. The first version of the software simulator named MiStTher is able to give a first qualitative description of the stem cell therapy in some simplified schemes.
A Two-Tier Hybrid Parameterization Framework for Effective Data Classification
Authors: Mohamad Masurah  , Selamat Ali
Published: February 2025

The classification process is a decision-making task. In order to obtain a good decision, the classification process needs to be conducted by following a standard framework or approach. The selection of a good parameterization method plays an important role in executing an effective parameterization process. The parameterization process will generate an optimized parameter reduction set that helps the classifier in generating a significant result. However, the size and characteristics of the dataset might also influence the generation of results in the classification process. The process of parameterization becomes more complex when the dataset is big and consists of uncertain and inconsistent data. Therefore, these problems need to be considered during the decision-making process. Many solutions have been provided recently by researchers, but most of the research works did not consider the highlighted issues as problems that should be solved together through the use of a single framework. In this paper, an alternative framework was proposed for decision-makers in conducting the decision-making process. The framework was demonstrated by the use of a two-tier hybrid parameterization phase that involving two main processes for identifying the most optimized parameter set for uncertain and inconsistent big datasets. The results showed that the proposed framework can be implemented to significantly increase the classification performance by returning an accuracy rate of more than 70% for all datasets.
Impact of Mutation Operators on the Ratio of Equivalent Mutants
Authors: Marsit Imen  , Omri Mohamed Nazih  , Loh Ji Meng  , Mili Ali
Published: February 2025

Software mutation is a widely used technique of software testing that consists in generating variants of a base program by applying standard modifications to its source code. One of the main obstacles in the use of software mutations is the existence of equivalent mutants, i.e. mutants whose behavior is indistinguishable from the base program, even though their source code is distinct. Despite several decades of research, the identification of equivalent mutants remains an open problem. Rather than attempting to identify individual mutants that are equivalent to the base, we argue that it is often sufficient to estimate the number of equivalent mutants; also, we argue that the number of equivalent mutants depends on two factors that must be considered in the estimation effort, namely the base program and the mutation operators that are used; in this paper, we explore the impact of mutation operators on the number of equivalent mutants.
Intelligent Educational Software in Discrete Mathematics and Graph Theory
Authors: Do Nhon V.  , Nguyen Hien D.  , Mai Thanh T.
Published: February 2025

Intelligent software has been very useful in education, especially those support studying knowledge. The knowledge of Discrete Mathematics and Graph Theory are essential in STEM education. There have been many computer programs that support students to study in the above knowledge domains such as Wolfram Alpha, Maple, etc. However, they do not satisfy students' requirements. This article will present knowledge representation methods, reasoning and querying techniques to design and to implement an intelligent software for effectively studying Discrete Mathematics and Graph Theory. The system consists of two subsystems for knowledge retrieval, visualization of methods or algorithms, and for solving problems. It can be easily used for studying the knowledge as well as for solving problems.
A Population-Based Incremental Learning Approach to Network Hardening
Authors: Paulsen Alexander  , Yazidi Anis  , Feng Boning  , Ou Xinming
Published: February 2025

Enterprise networks constantly face new security challenges. Obtaining complete network security is almost impossible, especially when usability requirements are taken into account. Previous research has provided ways to identify multi-stage attacks caused by network vulnerabilities and misconfigurations, but few have addressed ways to circumvent those multi-stage attacks, especially when usability requirements are taken into account. The latter problem is reckoned as Network Hardening problem [10] and is known to be an NP hard combinatorial problem. In this paper, we map the network hardening problem to a constrained optimization problem and resort to the theory of Population-Based Incremental Learning (PBIL) in order to solve it. We devise two approaches based on the PBIL, namely the Acceptance-Rejection approach, and the Penalty-based approach. Our aim is to tighten the security of the network by minimizing the number of privileges that an attacker can gain over network under some usability constraints measured in terms of the number of configurations in a network that can be activated or cannot be deactivated. The Acceptance-Rejection approach disqualifies configurations that violate the usability constraint while the Penalty-based approach relaxes the latter constraint by attempting to find a compromise between security and usability of the configuration. While the Acceptance-Rejection approach can be seen as a simple alternative to the state of the art MinCostSAT solution adopted in [10], the Penalty-based approach is, to the best of our knowledge, the first solution in the literature that tries to find such compromise. Experimental results show that the devised approaches are computationally efficient, scalable and reliable.
Markov Games for Persuasive Dialogue
Authors: Rach Niklas  , Minker Wolfgang  , Ultes Stefan
Published: February 2025

This work discusses the formulation of argumentative dialogue as Markov game. We show how formal systems for persuasive dialogues that adhere to a certain structure can be reformulated as Markov games and thus be addressed as Reinforcement Learning task in a multi-agent setting. We validate our approach on an implementation of a proof of principle scenario where we show that the optimal policy can be learned.
Preference in Abstract Argumentation
Authors: Kaci Souhila  , van der Torre Leendert  , Villata Serena
Published: February 2025

Consider an argument A that is attacked by an argument B, while A is preferred to B. Existing approaches will either ignore the attack or reverse it. In this paper we introduce a new reduction of preference and attack to defeat, based on the idea that in such a case, instead of ignoring the attack, the preference is ignored. We compare this new reduction with the two existing ones using a principle-based approach, for the four Dung semantics. The principle-based or axiomatic approach is a methodology to choose an argumentation semantics for a particular application, and to guide the search for new argumentation semantics. For this analysis, we also introduce a fourth reduction, and a semantics for preference-based argumentation based on extension selection. Our classification of twenty alternatives for preference-based abstract argumentation semantics using six principles suggests that our new reduction has some advantages over the existing ones, in the sense that if the set of preferences increases, the sets of accepted arguments increase as well.
Abstraction in Argumentation: Necessary but Dangerous
Authors: Prakken Henry  , De Winter Michiel
Published: February 2025

While work on abstract argumentation frameworks has greatly advanced the study of argumentation in AI, its use is not without danger. One danger is that the direct modelling of examples in abstract frameworks instead of through a theory of the structure of arguments and the nature of attacks leads to ad-hoc modellings. Another danger is that it may be overlooked that abstract accounts of argumentation can implicitly make assumptions that are not shared by many of their instantiations. A variant of this is where assumptions valid for specific argumentation contexts are incorrectly generalised by abstracting away from the context. This paper gives examples of both dangers. A lesson drawn from this is that abstraction in AI research, although necessary for understanding the essentials of the object of study, can oversimplify in ways that are not easily noticed without an explicit account of the structure of arguments and the nature of attack.
Self-Reading Texts and Books
Authors: Mihkla Meelis  , Hein Indrek  , Kiissel Indrek
Published: February 2025

The rise of e-books, the cumulative digitisation of written library materials and the advancement of speech technology have reached a stage enabling library services and e-books to be read out loud to customers in synthetic speech and paper books (either published or still in print) to be delivered in the audio form. The user environment of the digital archive Digar of the Estonian National Library includes a special reading machine capable of producing an audio version of electronic texts in Estonian (books, magazines etc). The application of Elisa Raamat provides access to more than 2500 Estonian e-books, which can not only be read visually from the screen of a smartphone or tablet but also listened to. The speech server of the Institute of the Estonian Language offers, as a public service, the text-to-speech system Vox populi, inviting people to have an audio version synthesized from any text of interest, being prepared to convert any uploaded text (an article, paper, subtitle file, e-book etc.) into an audio file. The present study is focused not only on the description of the systems but also on various issues of text processing and pronunciation as well as on the reflection of text structure in synthetic speech. The quality of self-reading largely depends on how adequately the input abbreviations, numbers and other non-letter sequences are converted into words in correct morphological form and how closely the output pronunciation of foreign names matches that of the source language. In the article we will also discuss a special module for text pre-processing, which helps in the case of more complex text structures and character sequences (e.g. geographic coordinates, sports results, numeral inflection). In addition, book reading requires an as accurate as possible rendering of text structure. The study also analyses audio books to capture the essence of human prosodic phrasing as well as different pauses and the marking of reported speech when talking.
A Patient Agent to Manage Blockchains for Remote Patient Monitoring
Authors: Uddin Md Ashraf  , Stranieri Andrew  , Gondal Iqbal  , Balasubramanian Venki
Published: February 2025

Continuous monitoring of patient's physiological signs has the potential to augment traditional medical practice, particularly in developing countries that have a shortage of healthcare professionals. However, continuously streamed data presents additional security, storage and retrieval challenges and further inhibits initiatives to integrate data to form electronic health record systems. Blockchain technologies enable data to be stored securely and inexpensively without recourse to a trusted authority. Blockchain technologies also promise to provide architectures for electronic health records that do not require huge government expenditure that challenge developing nations. However, Blockchain deployment, particularly with streamed data challenges existing Blockchain algorithms that take too long to place data in a block, and have no mechanism to determine whether every data point in every stream should be stored in such a secure way. This article presents an architecture that involves a Patient Agent, coordinating the insertion of continuous data streams into Blockchains to form an electronic health record.
Habitual Personal Movement Patterns in a Structured Environment
Authors: Poultney Nathan  , Maeder Anthony
Published: February 2025

This paper presents an approach for describing personal movement patterns for typical daily activities undertaken by subjects within free living structured environments (e.g. home or office). Conventionally this requires specialized technology for personal movement monitoring involving measurement of location and motion, and results in the collection of large datasets in order to provide sufficient descriptive power. Here we advocate the preferential observation of sentinel activities based on the expectation of routine and repetitive personal movement episodes, which can be considered as ‘habits’. These identified habitual patterns provide a useful context for understanding the dominant characteristics of typical daily activities, enabling purposeful design of behaviour change interventions to improve healthy living. This approach has been applied here to office stepcount data from consumer wearables.
Vehicle Pose Estimation Using G-Net: Multi-Class Localization and Depth Estimation
Authors: García López Javier  , Agudo Antonio  , Moreno-Noguer Francesc
Published: February 2025

In this paper we present a new network architecture, called G-Net, for 3D pose estimation on RGB images which is trained in a weakly supervised manner. We introduce a two step pipeline based on region-based Convolutional neural networks (CNNs) for feature localization, bounding box refinement based on non-maximum-suppression and depth estimation. The G-Net is able to estimate the depth from single monocular images with a self-tuned loss function. The combination of this predicted depth and the presented two-step localization allows the extraction of the 3D pose of the object. We show in experiments that our method achieves good results compared to other state-of-the-art approaches which are trained in a fully supervised manner.
Mild Abstraction in Spatial Problem Solving
Authors: Freksa Christian
Published: February 2025

Everyday spatial problems such as tying shoelaces, untangling cables, locating objects, opening doors, matching shapes, finding routes, solving puzzles, … are embedded in 3-dimensional physical space and their solutions need to be manifested in physical space. Such problems can be solved either directly in space by means of perception and manipulation or they can be transformed into abstract representations in order to be solved by reasoning or computation and subsequently transformed back into physical space. In my contribution I will compare the two approaches and I will discuss how they can be combined. I will introduce the notion of mild abstraction as a way of combining the best features of both worlds, present a variety of forms of mild abstraction, demonstrate their uses for spatial problem solving, and propose that mild abstraction can be exploited for non-spatial domains, as well.
A Concept for Improving Cross-Sector Care by a Mobile Patient Navigator App
Authors: Denecke Kerstin  , Kyburz Philip  , Gfeller Sascha  , Deng Yihan  , Bürkle Thomas
Published: February 2025

Hip and knee joint prosthetic implants are common surgical interventions in Switzerland, as well as in other countries. Different care providers are involved in the care process which constitutes a potential risk of inefficiency and communication deficits. A patient can get lost on his cross-sectoral clinical pathway, miss appointments or underestimate the relevance of certain control visits or examinations. To address this, we introduce a concept for a mobile application that guides patients along the cross-sectoral clinical pathway. The information on appointments is consistently retrieved from information systems at the care provider's side. This facilitates the coordination of activities and appointments not only for the patient, but also for the care providers. The aim is to promote the patients' autonomy, to support their management of appointments, to increase the understanding for their clinical condition and to improve their adherence to the prescribed measures – all of which lead to an improved outcome. Another aim is to increase patient satisfaction in terms of adequate information and quality of treatment. The advantages and disadvantages of the concept will be discussed. goes here.
Terminology Coverage from Semantic Annotated Health Documents
Authors: Ndangang Marie  , Grosjean Julien  , Lelong Romain  , Dahamna Badisse  , Kergourlay Ivan  , Griffon Nicolas  , Darmoni Stéfan J.
Published: February 2025

Background: Unstructured health documents (e.g. discharge summaries) represent an important and unavoidable source of information.
Ontologies in Big Health Data Analytics: Application to Routine Clinical Data
Authors: Liyanage Harshana  , Williams John  , Byford Rachel  , Stergioulas Lampros  , de Lusignan Simon
Published: February 2025

Ontologies are an important big-data analytics tool. Historically code lists were created by domain experts and mapped between different coding systems. Ontologies allow us to develop better representations of clinical concepts, data and facilitate better data extracts from routine clinical data. It also makes the process of case identification and key outcome measures transparent. We describe a process we have operationalised in our research. We use ontologies to resolve the semantics of complex health care data. The use of the method is demonstrated through a pregnancy case identification method. Pregnancy data are recorded in different coding systems and stored in different general practice systems; and pregnancy has its own complexities in that not all pregnancies proceed to term, they have different lengths and involve multiple providers of health care.
Using Design Thinking to Develop New Methods of Inclusive Exhibition Making
Authors: Hesseldahl Katrine  , McGinley Chris  , Monk Georgia
Published: February 2025

Museums and galleries are now making significant developments in the area of inclusion and awareness of disability rights. There have been noticeable advances in the design of cultural, physical and digital spaces, which provide wider access to a museum's physical and intellectual resources, for individuals of diverse ages and abilities. However, responses have varied in consistency, efficacy, and legacy. This year-long design research project, in partnership with the Wellcome Collection and the Helen Hamlyn Centre for Design, Royal College of Art, develops a working set of tools that can be used by museums to improve accessibility in a more permanent and reiterative manner, with a view towards gathering and sharing relevant data, and design responses, within a broad network of museums and cultural institutions. This paper outlines recent approaches by relevant experts in the field and outlines a new approach to incorporating inclusive design within the process of exhibition creation. It uses co-design methods to provide a set of principled guidelines that respond to all relevant stakeholders. These guidelines are predicated on the understanding that establishing empathetic links between exhibition-makers and exhibition audience members is essential, resulting in a positive collaboration, combining the skills of museum professionals with the lived experience of people with disabilities. A central goal of the research is to explore how design issues surrounding access can be framed as an essential and positive component of the design process, and, more importantly, an opportunity for innovation, not simply an obligatory requirement. This paper comprises the observations of a current research project of a 12 month project, commencing in September 2017 and concluding in September 2018.
Tools to Upgrade Facilities for All: How to Improve Business Dealing with Tourism
Authors: Chiarelli Barbara  , Garofolo Ilaria  , Novak Valentina
Published: February 2025

Providing quality services to any traveller requires constant efforts to ensure that tourist destinations, products, and services are accessible to all people, regardless of their health condition, physical limitations, gender, origin, age. This entails a collaborative process among all the interested parties: administrators, tourist agencies, tour operators, and end users, who expressing their points of view can objectively contribute to reach shared and effective solutions. A single visit destination can involve many factors, including access to information: the project A Region for All, promoted by Promoturismo FVG in collaboration with CRAD FVG and the University of Trieste, focused on this issue. Promoturismo FVG is a semi-public destination management organization. Its mission is to develop the regional tourism system collaborating with all the active subjects to improve the promotion and to optimize the resources by concentrating the efforts. The organization pursues its objectives by planning and organizing the offer through specific tourism products. In 2016 a mapping process has been started to investigate the usability of the relevant services to tourists / visitors with special needs along the itinerary of eight tourist centers of the Friuli Venezia Giulia region. To date, more than 200 facilities (bars, restaurants, pharmacies, cash machines…) have been detected. The paper will present the development of the work conducted by TrIAL – Trieste Inclusion & Accessibility Lab at Department of Engineering and Architecture within the University of Trieste for the management of the mapping process. On the strength of the mapping experience developed during the previous project LabAc (Laboratory of Accessibility) for the Province of Trieste and the project Trieste for All for the Municipality of Trieste (from 2013 to 2016), the research group has adopted and set a series of digital tools, has identified specific indicators and has focused on an efficient return of data to Promoturismo FVG. The overall project is still ongoing: collected data have not yet been published by the organization. Overall monitoring and evaluation activities are still lacking and will be part of a future phase of research.
Emulating Perceptual Experience of Color Vision Deficiency with Virtual Reality
Authors: Szczurowski Krzysztof  , Smith Matt
Published: February 2025

One of the major goals of Universal Design is to create experiences that are inclusive to all users, including those affected by Color Vision Deficiency. Color Vision Deficiency might have a significant impact on a users' perception of the content or the environment. There is a range of tools already available, that can be used to either aid or automate the process of readability testing for digital interfaces and content in respect to Color Vision Deficiency. Two different approaches to addressing this issue can be found. A brief review of such methodologies is provided in this paper. The first approach (user-end) attempts to solve the problem by altering mediation between the user and the content. The second (design-end) allows the designer to view an image, or color scheme altered to recreate the perceptual experience of a user affected by Color Vision Deficiency and asses the design from the perspective of a color-blind user. With an implemented proof-of-concept we investigate the potential use of Virtual Reality Head-Mounted Displays to employ similar methodology, to allow designers or interior decorators to experience physical environments (i.e.: classroom, library or a cafeteria) from the perspective of a color-blind person. Such tools might increase the designers' empathy towards color-blind users but also allow them to identify visual components, such as infographics or advertisement, in a physical environment that are poorly visible to color-blind users. Such tools could be developed by taking advantage of a modern Head-Mounted Displays six degrees of freedom tracking, a 360 camera and color processing filters applied during post-processing at run-time, allowing a designer to easily switch between different types of colorblindness emulation.
Ireland's Higher Education Teachers Have a National Professional Development Framework, Now What?
Authors: Donnelly Roisin  , Maguire Terry
Published: February 2025

Momentum has been building for professional development (PD) for all staff who teach in Irish higher education – they now have the national Professional Development Framework (PDF) to support them in planning and engaging with authentic, inclusive, scholarly, learner-centred and collaborative PD across their career. In mid-2016, the PD Framework was published by the National Forum for the Enhancement of Teaching and Learning. In 2017, the PDF was piloted with 215 individuals from 22 professional identity groups from across the sector, working with the framework to reflect on their professional practice and set goals for their future professional development.
Designing and Building the Visual Pathway as Public Art: Some Pros and Cons of Design-Build Pedagogy for Higher Education
Authors: Cranz Galen
Published: February 2025

One transformation among many in higher education is the turn toward experiential, hands-on learning including the design-build movement in architectural education. This paper on design practice reports on the pros and cons of experience with a design-build project in architectural education. “The Visionary” was inspired by the idea of creating the first ever walk-through human eye. The installation was designed, fabricated, and installed at the School of Optometry on the UC Berkeley campus by architecture undergraduates in the context of a design-build studio course with Professors Cranz and Duffy in the Department of Architecture in 2018. Student evaluations and staff-evaluations provide the basis for pedagogical lessons for other design-build projects in the future.
Should Colour Vision Deficiency Be a Recognized Special Education Need (SEN)?
Authors: Kvitle Anne Kristin
Published: February 2025

A colour vision deficiency (CVD) is a condition that affects about one in 12 of the male population, and one in 200 of the females. On average, there is at least one student in every classroom affected by a reduced colour vision. In schools and in teaching, colours are used as a tool to identify, group, highlight, warn and explain. For a colour vision deficient student, the colours used to code the information may be a source of confusion instead of a tool to decode. This paper provides an overview of the possible academic and social-emotional challenges for CVD students and propose strategies and actions to raise awareness and enable colour universal design.
An Augmentation of Fuzziness to Randomness in Project Evaluation
Authors: Kouatli Issam  , Abdallah Skander Ben
Published: February 2025

Net present value is the traditional approach to evaluate the financial viability of projects including large ones. Unfortunately, the NPV may mislead decision makers for two reasons. First, it does not take into consideration managerial flexibility which is the ability of decision-makers to react to upcoming information related to some uncertain events in a way that may change the project design and planning. Randomness based on standard deviation is usually utilized to accommodate such flexibility. Second, the NPV calculation relies on some fuzzy variables that are subject to imprecision or ambiguity such as the characteristics of the project cash flow and investment cost. The variability of these errors can also be represented in the volatility of the model. In such scenario, volatility would be randomness as well as fuzziness based. Researchers in the field propose to use project Investment and Project cost as fuzzy variables. We argue in this paper that both of these factors can be embedded in the randomness-based volatility factor. This paper investigates the use of the volatility factor as fuzzy parameter in a Real options approach to evaluate projects. Hence, the overall ambiguity would be represented in a combination of randomness as well as fuzziness to achieve acceptable evaluations.
Quantifying Cup-to-Disk Ratio Analogy Through k-Means for Glaucoma Screening
Authors: Shiny Priyadarshini J.  , Gladis D.
Published: February 2025

The Ocular cup-to-disc ratio is one of the habitual screening procedures done prior to the endorsement of glaucoma disorders. Glaucoma is one of the most dominant eye malfunctions which leads to perpetual vision loss hence retinal segmentation plays a censorious role in diagnosis of optic disc and cup. This paper highlights a very simple and straight forward approach to suspect glaucoma through k-means and a meticulous study has been made for CDR estimation. The Optic disc and cup are segmented as clusters and its CDR is calculated through mathematical quantifications. The results are tabulated and scrutinized which clearly shows the percentage and risk factor of glaucoma. The screened results can be further extended for clinical suites.
Entity Identification Framework of Chinese Public Database Based on Social Network Community Partitioning and Text Clustering
Authors: Zhang Zhenhua  , Liu Huimin  , Lin Xiaolong  , Yuan Shenguo  , Zhang Jing
Published: February 2025

Due to the characteristics of the data in public databases, it is difficult to clean the redundant data. It is an ideal solution to make full use of the features of original data to perform technical data cleaning. The entity identification technology is one of the effective solutions. Based on the key technologies of entity identification, combining the characteristics of the Chinese text data of Chinese public databases and the network relationships existing in the data, an entity identification framework based on text clustering and social network community division was proposed for the challenges with the same representation of different entities. The framework has been experimented on China's library database. Experimental results show the validity and accuracy of the framework.
Applications of Fuzzy Logic in Food Product Quality Control: A Review
Authors: Annapoorani G.  , Lathaselvi G.
Published: February 2025

Systems that are adjustable, time based and non-linear categories are credibly handled by applying fuzzy logic. Many authors had emphasized the role of fuzzy logic in food quality control for varying applications in the food industry domain. When considering the reasoning process, the support offered by fuzzy logic is remarkable, particularly in language based terminologies, related to operators and experts. In such cases, the system gets modeled using fuzzy logic by considering the values of linguistic variables and the vague relationships found amidst them. Uncertain and complex bioprocesses can be studied and their states can be assessed and forecast about their future can be done with the help of smart computer programs that play the role of software sensors. Imprecise and unfinished information can be accurately constructed with the help of fuzzy logic systems. Also process models can be precisely built by integrating the human expert knowledge into such models. This paper presents a survey enlisting the growth, advancement and current state of the art in applications of fuzzy logic in food product quality control. Remarkable expansions and inclinations to be made in future in this domain have also been emphasized.
The Fuzzy Mean-Absolute Deviation Portfolio Model with Inflation
Authors: Wang Qiang  , Li Ting  , Sun Shaun Zheng
Published: February 2025

In financial markets, the presence of inflation may affect investments' real returns. In this paper, we extend the fuzzy portfolio models to take into account the effects of inflation within the framework of credibility theory. The above models were deduced under the assumptions that returns of assets and the inflation rates follow some special fuzzy distributions. In a numerical study, we analyze the optimal portfolios and efficient frontiers with different inflation rates. We conclude that the absolute deviation increases as inflation rate increases, as a result, investment risks will be underestimated if the effects of inflation were not considered in the models.
Personalized Two-Layer Regional Transportation Control Model for Big Events
Authors: Long Qiong  , Zhang Jinfan
Published: February 2025

This paper proposed a personalized two-layer regional transportation control model for urban transportation control issues during big events. Firstly,this paper analyzed basic regional transportation control principles faced during big events and built a two-layer regional transportation control model that was both a personalized transportation management model and control model, which could fully reflect personalized experiences of transportation controllers. Then, based on particle swarm algorithm,this paper proposed a model optimization solution based on compression particle swarm and finally ,generated a control vector of every area and intersection in each region. This paper used examples of organized big events in Changsha city to simulate and verify transportation control. The simulation results showed that during big events,regional transportation system worked well, which indicated that this model was able to effectively solve regional transportation problems during big events.
A Fast Spreading Code Compression Search Method for DS_CDMA System
Authors: Liang Zongwei  , Yang Junan  , Liu Hui  , Long Lang
Published: February 2025

In the highly dynamic environment, it is computationally-intensive and time-consuming for non-cooperative receivers to quickly search out the user's spreading codes and acquire code phase. A fast compression search method for spreading codes is proposed in this paper. To compress the frequency search dimension, this paper proposes a multi-phase carrier search algorithm based on the partial-related code acquisition algorithm of FFT, as it aims at the randomness of each user carrier phase. A compression code search algorithm based on the correlation of each spreading code in the same family is proposed to accelerate the search of spreading codes. A code phase compressor is adopted to compress code phase. As the simulations suggest, the proposed method can perform fast spreading code search and code acquisition for DS_CDMA system. Under the code length of 2047, the algorithm can search the spreading code search and capture the code phase of all users in the balanced code family within 100s. The actual data experiment also judged the effectiveness of the algorithm.
Comparison of Two Optical Image Encryption Techniques
Authors: Elshamy Ahmed M.  , Hussein Aziza I.  , Hamed Hesham F.A.  , Abdelghany M.A.  , Kelash Hamdy M.
Published: February 2025

It is necessary to identify the latest and newest techniques that proposed in order to fulfill the specific requirements and use it in the field of information security. There are some chaos techniques in image encryption and phase modulation encryption technique have been suggested. In the present paper the discrete Fourier transform was used to create phase modulation for a grayscale image. The image to encrypt is placed by one of chaos maps, Baker and Arnold cat maps, then combined with two random phase modulation based on the discrete Fourier transform. However, to decrypt the encrypted image required to have three keys, one for chaotic map and other two keys for removing phase modulation. The use of the discrete Fourier transform, phase modulation and chaos in image encryption add much more complexity to the decryption of the image for unauthorized person. The main contribution of this paper to compare between our two proposed in performance and efficiency. Numerical simulation results by Matlab have been executed to validate the two proposals. Furthermore, second proposal which implements by Arnold cat map and phase modulation achieved good test results in encryption quality metrics and noise immunity which is most optimal.
Natural Deduction System in the TIL-Script Language
Authors: Duží Marie  , Menšík Marek  , Pajr Miroslav  , Patschka Vojtěch
Published: February 2025

In this paper we deal with the extension of the functionalities of the TIL-Script language, namely the proof system based on natural deduction. The system processes a subset of the set of TIL-Script constructions that are typed to v-construct a truth-value. Since TIL-Script is a functional programming language based on a hyperintensional lambda calculus with procedural semantics, we also describe the way how to validly apply beta conversion and how to operate in a hyperintensional context where the very procedure is an object of predication.
Giving a Frame to the Concept Space
Authors: Locuratolo Elvira Immacolata
Published: February 2025

The concept space is large, unexplored and open. Concept structures to preserve and analyze database concepts are focused, and the properties of concepts completeness and classes/concepts completeness are introduced. Outside the space where structures preserving and analyzing database concepts are located, incompleteness holds. Exploiting these properties as reference points for the location of concepts and concept structures in the space, a frame is proposed. Not all the concept structures can be linked with the scientific domain of computer science. In the open concept space, both formal and informal concept structures are located. These can be complete, incomplete, not necessarily related to computer science. An example of the frame applicability is given.
Consideration of Likeness Preferences for Printed Images Based on Object Dependence of Edge Enhancement Effect
Authors: Hansuebsai Aran  , Kittiboongate Yolravee  , Im-Oep Nanyakorn  , Chareopsopa Krairop
Published: February 2025

This study investigates the relationship between perceptual attributes on printed images and likeness preference as well as the influence of edge enhancement method. Printed images with varied edge enhancement filtering weights of four objects in everyday life were evaluated by observers in psychophysical experiment. By data analysis, it was found that three quality attributes such as image quality, detail expression and naturalness were sufficient to represent perceptual quality of images, by which they would probably influence in final decision of Like and Dislike of images. 5 stage-estimation indicated that there was a sensation limit based on these three attributes, depending on each object. The observers were able to some extent to differentiate the perceptual quality of printed images due to easy recognition of their clues. The relationship between the estimated data of three attributes and likeness preference was established. This finding could predict the likeness preferences of mixed objects in printed images for chosen edge enhancement filtering weight.
A Tool to Highlight Weaknesses and Strengthen Cases: CISpaces.org
Authors: Cerutti Federico  , Norman Timothy J.  , Toniolo Alice
Published: February 2025

We demonstrate CISpaces.org, a tool to support situational understanding in intelligence analysis that complements but not replaces human expertise, for the first time applied to a judicial context. The system combines argumentation-based reasoning and natural language generation to support the creation of analysis and summary reports, and to record the process of forming hypotheses from relationships among information.
Towards Explainable Semantic Text Matching
Authors: Landthaler Jörg  , Glaser Ingo  , Matthes Florian
Published: February 2025

The growing amount of textual data in the legal domain leads to a demand for better text analysis tools adapted to legal domain specific use cases. Semantic Text Matching (STM) is the general problem of linking text fragments of one or more document types. The STM problem is present in many legal document analysis tasks, such as argumentation mining. A common solution approach to the STM problem is to use text similarity measures to identify matching text fragments. In this paper, we recapitulate the STM problem and a use case in German tenancy law, where we match tenancy contract clauses and legal comment chapters. We propose an approach similar to local interpretable model-agnostic explanations (LIME) to better understand the behavior of text similarity measures like TFIDF and word embeddings. We call this approach eXplainable Semantic Text Matching (XSTM).
Legal Ontology for Modelling GDPR Concepts and Norms
Authors: Palmirani Monica  , Martoni Michele  , Rossi Arianna  , Bartolini Cesare  , Robaldo Livio
Published: February 2025

This paper introduces PrOnto, the privacy ontology that models the GDPR main conceptual cores: data types and documents, agents and roles, processing purposes, legal bases, processing operations, and deontic operations for modelling rights and duties. The explicit goal of PrOnto is to support legal reasoning and compliance checking by employing defeasible logic theory (i.e., the LegalRuleML standard and the SPINDle engine).
Dust Particle Recognition Using ROF Model and Feature Information
Authors: Wang Zheng
Published: February 2025

When explosive dust concentrations reach a certain value near an ignition source, it creates an explosion hazard. Therefore, we propose an explosive dust detection and characteristic analysis method using dust particle imagery. First, the Fourier transform domain of the fractional derivative is used to define the image filtering framework. The Rudin – Osher – Fatemi (ROF) model, in a bounded variation imagery function space, is selected to obtain prior noise knowledge with noise variance. Then, the imagery texture region and the nontexture region are divided according to the statistical information of the image local variance. A modified differential evolution particle swarm optimization algorithm is then used to identify the complex dust particles and to determine and update the fitting parameter optimal values, which can separate the overlapping particle intersection points. The model and algorithm are compared and analysed experimentally. The influence of the dust particle parameters is then obtained. We thus demonstrate that the noise suppression and staircase effect are better for the dust images, and that the overlapping particles are effectively separated. The research results indicate the correctness and feasibility of the proposed model, which provides the theoretical and experimental basis for the design of dust explosion concentration intervals.
Evaluation of the Correlation Between Ports and Rear Area Logistics Parks Based on Decision Tree Learning
Authors: Dong Yanze  , Liu Wei  , Li Shanshan
Published: February 2025

The cooperation between port and logistics parks is crucial for port to build the collection and distribution system. Using the Decision Tree Learning method, this work establishes evaluation model of correlation between ports and logistics parks in the rear area. Firstly, the correlation factors are analyzed, including the spatial correlation, the functional matching and the service object matching. Secondly, based on a number of industry regulation we generate a training dataset of 105 samples. Thirdly, the Decision Tree is built using the classic ID3 algorithm. All the process is implemented by MATLAB. Last but not least, we analyze the actual statistical data of Shenzhen port and its logistics parks based on the Decision Tree we build, and verify the validity of the evaluation model.