bluuebunny/crossref_metadata_2025 huggingface dataset:
A Bidirectional Deep Manifold Model for Image Representation
Authors: Yang Shangming  , Liu Yongguo  , Li Qiaoqing
Published: February 2025

Deep learning model has been extensively applied to the area of data classification and clustering in recently years because of its high similarity to human neurons in computational performance. In this paper, we propose a new deep model, multi-layer manifold based nonnegative matrix factorization with partial neural connections for image representation. In this model, a bidirectional multi-layer NMF decomposition for both basis and encoding vectors are conducted to capture structures in high dimensional data space. The connections of neurons in the learning are constrained in a neighborhood so that the similarities of elements in the same cluster can be learned. Test results on two different image datasets confirm that the proposed method can learn very good performance for image clustering tasks.
A Fast and Robust Grid-Based Clustering Method for Dataset with Arbitrary Shapes
Authors: Wang Lei  , Lu Yonggang  , Yan Huanqian
Published: February 2025

Clustering analysis is a significant unsupervised machine learning method and plays a more and more important part in multifarious fields. Although many types of clustering methods have been developed for the past few years, most conventional clustering methods can only work with round-shaped clusters and may be affected by the parameter settings and initialization. What's more, the effectiveness of clustering process would be limited by its time and space complexity when the size of the dataset becomes extremely large. In this paper a new and fast grid-based clustering algorithm is proposed which can stably deal with large datasets. In this method, the grid size is automatically determined, and then the local densities at the grid nodes are estimated. Finally, the breadth-first search strategy is used to find the clusters with arbitrary shapes. The method can be successfully applied to various datasets which contain non-spherical clusters with different dimensionalities. Some synthetic datasets and real-world datasets are tested and experiment results show that the proposed method is more effective and more efficient than the conventional methods.
Noisy Image Restoration Using A Modified Artificial Bee Colony Algorithm
Authors: Yu Weiyu  , Yang Jie
Published: February 2025

This paper proposes a new approach for noisy image restoration using modified artificial bee colony algorithm (ABC algorithm). ABC algorithm combined with the constrained least squares filtering method is used to restore image. In the fuzzy identification, point spread function (PSF) is obtained using ABC algorithm. In the restoring part, the constrained least squares filtering method is used for image restoration. Iterative process is repeated to obtain the estimation of the noisy image. Proposed approach overcomes the problem of the traditional image restoring, which needs to know the PSF in advance. In addition, this method improves the performance of the traditional ABC algorithm by initializing the first group of bee colony. The pretreatment can reduce the randomness and improve the performance of ABC algorithm. Experimental results showed that the proposed method is effective for image restoration.
Implementation of Simplified Optical Flow Field Algorithm Based on FPGA
Authors: Yi Qian
Published: February 2025

In view of the problem that embedded software cannot meet the real-time processing speed of digital image, the idea of hardware accelerator is proposed to realize the optical flow field target detection algorithm on Field Programmable Gate Array (FPGA). By parallel processing data and pipeline design, the processing speed of algorithm is greatly improved. The modular hardware design method is adopted to ensure the portability and scalability of the system. Finally, the algorithm is processed by verilog programming, and is simulated and verified on ZedBoard.
Improved Bee Colony Optimization for Traveling Salesman Problem
Authors: Zhang Liyi  , Li Hongbo  , Fei Teng  , Pan Xuhua
Published: February 2025

An improved artificial bee colony algorithm is proposed for traveling salesman problem, which is a classical NP- hard problem. By improved artificial bee colony algorithm we introduce swarm behavior of the artificial fish swarm algorithm and the crossover operator of the genetic algorithm, and enlightens the underdamping motion of physics which uses it to adaptively update for the visual range of the artificial fish swarm algorithm. Through the simulation of six classic traveling salesman problems in the TSPLIB standard library and comparison with other improved algorithms, we show that the improved artificial bee colony algorithm has a better performance and better results than the original artificial bee colony algorithm in solving the TSP problem.
Identity Authentication Scheme for Information Non-Repudiation in Blockchain: An Overview
Authors: Xu Yifan  , Zhu Jun  , Fang Weidong  , Zhao Yufeng  , Huang Lei
Published: February 2025

Since its inception, the security of the blockchain technology has drawn all kinds of attention. Although there are some researches on the security of blockchain, there is no specific security study on non-repudiation of this field. In this paper, we introduce the identity authentication ensuring non-repudiation in the blockchain, security and performance of different authentications in blockchain are analyzed too. Then this paper provides a comprehensive introduction to the identity authentication, reviews some special authentication schemes and enhancement solutions of identity authentication proposed by different researchers, and finally suggests some future helpful directions and references toward this field.
The Improvement and Application of Collaborative Filtering Algorithm Based on Item
Authors: Xin Sui  , Fan Yu  , Zheng Tong  , Zeng Yan  , Li Longsheng  , Liu Dan
Published: February 2025

The collaborative filtering algorithm is mainly used to predict users' preferences and realize intelligent recommendation through data mining of users' behaviors. In the practical applications, with the increasing complexity of the contents and users, there are many problems, among which cold-start is the most prominent. In this paper, we proposed a recommendation model (BROCF) of collaborative filtering algorithm based on binary relative comparison sorting, which aims to improve the efficiency of the algorithm and the accuracy of the recommended results. The comparative experiment results showed that the improved algorithm in this paper had significant increase in forecast accuracy, the deviation of improved algorithm between the predictive results and the real value was the lowest comparing with other algorithms, which certified the feasibility and effectiveness of the algorithm.
Impact of Ferroelectric Layer Thickness on Negative Capacitance Mosfets
Authors: Lü Wei-Feng  , Dai Liang  , Lin Mi  , Zhang Hai-peng
Published: February 2025

In this study, the impact of ferroelectric layer thickness (Tfe) on negative capacitance metal-oxide-semiconductor-field-effect-transistor (NCFET) is investigated by the analytical model. Base on the analytical model, the performance parameters of NCFET are compared with those of baseline MOSFET. It is observed that the device characteristics of NCFET are significantly via the internal amplification. Meanwhile, they are also influenced by the Tfeinduced by the NC effect. In addition, for avoiding the hysteresis phenomenon in the integrated devices and circuits, reducing Tfeis required. Under the condition of Tfe< 30 nm, NCFEF shows the superior device performance compared with the baseline MOSFET.
Gene Prioritization Using a Deep Learning Approach
Authors: Liu Feng  , Xiong Yuting  , Wang Zezhen
Published: February 2025

The research of related genes is an extremely important issue in the study of human genes. Scientists could utilize related human genes to build huge, integrated gene regulatory network which enables scientists to discover the relationships between genes and diseases. In this research, we conduct the text mining through Natural Language Processing (NLP) by introducing a deep learning method. In order to obtain the association between genes based on the text information, we construct a parallel Convolutional Neural Network (CNN) with parallel convolutional layers and dynamic convolutional pooling layers to deduce the relationship – positive, negative, or nonexistent. Unlike other studies, we extract the positive and negative gene relationships, and apply the deep learning method to this field. For gene relationship recognition, the accuracy is 85.2%. The result of this algorithm turns out to be promising.
Toward the Generation of Smell Maps: Matching Electro-Chemical Sensor Information with Human Odor Perception
Authors: Gongora Andres  , Chaves David  , Jaenal Alberto  , Monroy Javier  , Gonzalez-Jimenez Javier
Published: February 2025

Smell maps are geo-localized representations of the odors present in an environment as perceived by humans. They provide a convenient mean to assess the smellscape of urban areas, determine regions with heavy impact on the population, and measure the reach of industrial emissions. However, their use is not widespread because they are laborious to generate and easily outdated, as they rely on in-place human annotations of the perceived smells. In this work we study the feasibility of automatizing the generation of smell maps by means of a wearable electronic nose (e-nose) as replacement for the human sense of smell; being our main objective the analysis of whether this technology can be employed to map the subjective information inherent in smells. We have collected to that end a dataset composed of more than 450 labeled samples of 10 different smells with a wearable e-nose, and performed a thorough comparison of several machine learning algorithms to evaluate their suitability for this task. As a second contribution, we present a smartphone application developed to record (in situ) e-nose measurements and GPS coordinates as well as the human perception of smells (using a form-based input method). Finally, we present an illustrative example with several automatically generated smell distribution maps and discuss their accuracy.
Towards Egocentric Person Re-Identification and Social Pattern Analysis
Authors: Talavera Estefania  , Cola Alexandre  , Petkov Nicolai  , Radeva Petia
Published: February 2025

Wearable cameras capture a first-person view of the daily activities of the camera wearer, offering a visual diary of the user behaviour. Detection of appearance of people the camera user interacts with for social interactions analysis is of high interest. Generally speaking, social events, life-style and health are highly correlated, but there is a lack of tools to monitor and analyse them. We consider that egocentric vision provides a tool to obtain information and understand users social interactions. We propose a model that enables us to evaluate and visualize social traits obtained by analysing social interactions appearance within egocentric photostreams. Given sets of egocentric images, we detect the appearance of faces within the days of the camera wearer, and rely on clustering algorithms to group their feature descriptors in order to re-identify persons. Recurrence of detected faces within photostreams allows us to shape an idea of the social pattern of behaviour of the user. We validated our model over several weeks recorded by different camera wearers. Our findings indicate that social profiles are potentially useful for social behaviour interpretation.
A User Model Ontology for Adaptive Systems in Cultural Tourism Domain
Authors: Pandolfo Laura  , Pulina Luca  , Grosso Enrico
Published: February 2025

There is an increasing interest in using adaptive technologies in cultural heritage field to personalize and enhance the user's visit experience. However, personalizing the cultural experience is a challenging task that requires a deep knowledge of those user's aspects that influence the visit, such as some physical, socio-cultural, and educational aspects. In other words, to be effective and to facilitate the learning process during the visit, personalized systems should consider differences between users. In this paper, we propose a user model ontology for cultural tourism applications with the aim at adapting their functionalities to the end-users' background and interests.
‘Bismarck 4.0’: A Cross-Disciplinary Thought Experiment on Cyber Pacifism
Authors: Funk Michael  , Reichl Peter  , Dieber Bernhard
Published: February 2025

This essay summarizes the claims on IT security that have been presented and discussed during the workshop “YuMi in Action! Ethics and Engineering as Transdisciplinary Robotics Performance”. As a sort of “Ems Telegram” in the era of digital transformation, this essay aims to be a cross-disciplinary thought provocation on IT security and what Bismarck, Prussian's 19th-century militarism and industrial quality ‘Made in Germany’ may teach us in this respect, such as values of technical functionality like accuracy, precision, standardization, resilience, accessibility, simplicity, autarchy, and reliability. What we definitely not want to take over are ideologies which have contributed to the horrible 20th-century world wars, war crime, antisemitism or racism in any fashion. Joining the perspectives of a philosopher of technology, a computer scientist and a robotics researcher, our goal is to work towards a (maybe utopian) world where IT security as a problem disappears. To this end, we propose the concept of ‘Bismarck 4.0’ as an alternative draft in times of cyber warfare and social robots that overrun our firewalls like herds of next generation Trojan horses. Basic elements of this approach include strategic de-networkification as well as a clear emphasis on strengthening IT autarchy and resilience. The resulting position of newly gained strength will allow to increase network- and user-centric quality (including security) as well as, eventually, to go for a sustainable openness and neutrality by design. In this away, we arguably introduce some historical experimental evidence into a current debate that, ironically, refers to almost identical problem settings.
Why Do/Should We Build Robots?—Summary of a Plenary Discussion Session
Authors: Funk Michael  , Seibt Johanna  , Coeckelbergh Mark
Published: February 2025

This article is a summary of a joint discussion session that was held impromptu at the RP 2018 conference. The session addressed the two main questions: “Why do we build robots, why should we build robots?” along a series of queries, which were directly posed to, and discussed by, the conference plenum (the audience of a large lecture hall with about 150–200 participants). The session produced concrete answers, but also many further questions, pointers, and useful trajectories. In this summary we try to collect the highlights of this spontaneous yet well-focused event. We reconstruct nine answers to the question of why we do build robots, and nine answers to the question of why we should or should not build robots. In addition, we report on more general and fundamental observations concerning special normative tasks arising with social robotics. We conclude with some reflections on the idea and format of this impromptu session, as a tool for future conferences.
A Process Calculus for Design and Modeling of Retro-Synthesis
Authors: Broholm Gabriel  , Hammeken Maliina B.S.  , Hansen Marcus Skov  , Juhl Alexander  , Larsen Marc Storm  , Nilsson Jørgen Fischer  , Pethick Thomas M.  , Sørensen Magnus Gether
Published: February 2025

We describe a logical calculus for process synthesis applying reaction rules for consuming, transforming and producing products at costs. Unlike common logical calculi, which deal with propositions supported by truth semantics, the process synthesis calculus deals with products (in a concrete or abstract sense) and their costs, and creation of products by the composing of appropriate reaction assemblies from a database of reactions or transactions. As such the calculus may be understood as a resource logic akin to linear logics. The calculus appeals to means-end backwards reasoning using a derivative of definite clause logic. Although rather general in scope, as an interesting case in this paper the calculus is applied to chemical retro-synthesis – in particular with the notoriously difficult Solvay cluster designs.
Relationship Between Vegetation Indices and SPAD Values of Waxy Corn Using an Unmanned Aerial Vehicle
Authors: Jermthaisong Panath  , Kingpaiboon Sununtha  , Chawakitchareon Petchporn  , Kiyoki Yasushi
Published: February 2025

The amount of chlorophyll in a plant can indicate leaf N concentration, as chlorophyll is a major component of nitrogen. Identifying chlorophyll levels in plants, therefore, leads to appropriate nitrogen fertilizer recommendations for the plants and to their fertilization at the proper time, optimizing efficiency of agricultural production and helping to preserve the environment by reducing excess use of nitrogen fertilizer. Measuring leaf N concentration in a high accuracy laboratory is expensive and time consuming, whereas a SPAD chlorophyll handheld meter can be carried conveniently in the field and can assess rapidly. However, the handheld meter's capacity is limited, especially in large areas, where samples must be taken to represent an area. The use of vegetation indices calculated from UAV imagery and correlated with SPAD values enables better estimations of N leaf concentrations over large areas. The result showed that relationship between NDVI and SPAD value (chlorophyll contents) of waxy corn (Zea mays L. var. ceratina) at V6 and R1 stage in R2were 0.594 and 0.632, respectively. The results of this study are beneficial for knowing the amount of chlorophyll in plants, which can result in accurate nitrogen fertilizer requirements and better administration of management zones in precision agriculture.
K-Means Clustering for Controversial Issues Merging in Chinese Legal Texts
Authors: Tian Xin  , Fang Yin  , Weng Yang  , Luo Yawen  , Cheng Huifang  , Wang Zhu
Published: February 2025

In the fact of growing number of cases, Chinese courts have gradually formed a trial mode to improve the efficiency of trials by conducting trials around the controversial issues. However, identifying the controversy issue in specific cases is not only affected by the uncertainty of facts and laws, but also by the discretion of the judges and extra-case factors, and cannot be expressed as a standard format, which lead to the controversial issues based case retrieval a challenge problem. In this paper, we propose a controversial issues merging algorithm based on K-means clustering for Chinese legal texts. The proposed algorithm can determine the number of clusters of the given cause of action automatically and merge the controversial issues semantically, which makes the case information retrieval more accurate and effective.
Passenger Traffic Volume Prediction with LSTM Neural Network
Authors: Wang Xu  , Yang Linjian  , An Yisheng  , Huo Yunxiao
Published: February 2025

Passenger traffic volume as the basic data of traffic science management, has extremely high feedback ability and research value. The timely and accurate prediction of passenger traffic volume plays an important role in intelligent traffic management and control. With the rapid increase of traffic data volume in today society, along with highly nonlinear and random traffic systems, the prediction of passenger traffic volume is still a problem. This paper uses the long-term and short-term memory (LSTM) neural network, combined with actual passenger traffic data, through experiments and comparison with other representative forecast models validates that the proposed LSTM network can achieve a better performance, simultaneously analyzed the effects of various input settings on the LSTM forecast performance. In the passenger environment with large quantity and periodic regularity, the calculation time is saved and the prediction precision is improved, and the calculation speed of the same scale prediction problem is greatly improved. It can effectively provide the reference of traffic scheduling and planning during peak hours for the main transport stations with large passenger traffic.
The Research on Charge and Discharge Characteristics with Single Li-NiCoMn Lithium-Ion Battery
Authors: Chen Sujuan  , Zhao Zhendong  , Gu Xinyan
Published: February 2025

The open-circuit voltage (OCV) of batteries is a crucial characteristic parameter which reflects many aspects of a battery's performance, such as capacity, state of charge (SOC) and state of health (SOH). In order to improve and better the applicability of Li-NiCoMn lithium-ion batteries in electric vehicles, a series of charge and discharge experiments were carried out in constant current mode. The battery capability of Li-NiCoMn lithium-ion batteries had been obtained from the experiment results with multiple different type models. Based on the analysis on the charge and discharge curves, the battery capacity as well as SOC can be deduced according to the corresponding OCV. The results of charge and discharge tests indicate that Li-NiCoMn lithium-ion batteries have heavy load charge and discharge performance.
Non-Nested Generalisation (NNGE) Algorithm for Efficient and Early Detection of Diabetes
Authors: Gbenga Dada Emmanuel  , Hemanth D. Jude  , Chiroma Haruna  , Abdulhamid Shafi'i Muhammad  , Taiwo Adewale Johnson
Published: February 2025

Diabetes is a disease that is gaining popularity on daily basis in recent times globally and among different age groups. Diabetes causes damage to nerves, blood vessels, kidney, and retina. Machine learning techniques have proved to be very effective in detecting diabetes. In this study, we applied the Non-Nested Generalisation exemplar classifiers on Pima Indians diabetes dataset to effectively and efficiently classify whether patients are having diabetes or not. Our proposed algorithm proved to be highly effective and efficient with a resultant classification accuracy of 100%, very low false positive rate (0.00) and very high true positive rate of 1.00. All experiments are conducted on WEKA data mining and machine learning simulation environment.
Vehicle Estimation Using Floating Car Trajectory Data at Signalized Intersection
Authors: Yan Xiaoxiao  , Yuan Xianghong
Published: February 2025

With the rapid development of GPS and communication technology, floating car data (FCD), which is also called probe vehicle, become the essential composition of traffic information. In this paper, we propose the model based on the speed-density relationship, to estimate the vehicles between the floating cars at signalized intersection, and then we can obtain the traffic volume at intersection and other evaluation index such as queue length, which is crucial to signal optimization and control. The model is tested using SUMO simulation data. We use the error of traffic volume at intersection as the evaluation index to estimate trajectory data with penetration rates of 20% to 50%. The results indicate that the proposed model is very sensitive to penetration rates, the success rate increases with the growth of penetration rates.
Dependency of Color Ratings on Interface Types
Authors: Zariņa Līga  , Šķilters Jurgis  , Luguzis Artis  , Bāliņa Signe  , Apse Linda
Published: February 2025

It has been demonstrated in a number of studies that color preferences, emotions and associations are interlinked in various ways (e.g., [1, 2, 3, 4, 5]). To a lesser extent it is also known that color preferences are task-dependent. In our study we apply rating tasks in an in-group quasi-experimental setting (150 participants) to test dependence of color ratings on different types of e-services (or interface types) in Latvia. According to our results, color ratings are highly dependent on the type of the e-service but to a different degree. There are colors that are highly variable across the interface types (e.g., red, yellow or purple); there are colors that are rated relatively positive (green, blue) and relatively negative (black, pink) in all types of interface but to a different degree. Finally, we might generalize our findings to underline the task-dependency of color ratings and color categorization in general.
ICT-Based Interventions for Women Experiencing Intimate Partner Violence: Research Needs in Usability and Mental Health
Authors: El Morr Christo  , Layal Manpreet
Published: February 2025

The aim of this systematic review is to summarize studies in different settings that used Information and Communication Technologies (ICT) to address intimate partner violence (IPV). We've conducted a systematic review using PRISMA guidelines using the following databases: PubMed, CINAHL, PsycINFO, and Web of Science. Inclusion criteria were ICT-based interventions addressing IPV, focused on women. 21 studies were identified in which ICT was found to be a suitable low-cost option for screening and disclosure of IPV, as well as for preventing IPV. More research is needed to use ICT for prevention and treatment of IPV, taking consideration new ICT environments such as virtual communities.
Using a Markov Chain Model to Analyze the Relationship Between Avoidable Days and Critical Care Capacity
Authors: Hudson Darren  , Singh Gurmeet
Published: February 2025

Hospital capacity strain is ubiquitous, and a significant stressor in critical care. Avoidable days (AD) are frequently used as a metric of capacity. Using a Markov chain model, we studied the relationship between AD and surgical cancellations in a cardiovascular ICU. The model varied the probability of discharging a patient to study this effect over a pool of 108 simulated patients with length of stay data reflecting the actual population. The model behaved as expected with decreasing AD with increasing probability of patient discharge. However, there was no effect on the surgical cancellation rate. We conclude that there is no relationship between AD and critical care capacity as measured by surgical cancellation rate.
Factors Affecting Adherence with Telerehabilitation in Patients with Multiple Sclerosis
Authors: Jeong In Cheol  , Liu Jiazhen  , Finkelstein Joseph
Published: February 2025

The goal of this study was to identify predictors of telerehabilitation adherence in patients with multiple sclerosis (MS). An adherence prediction model was based on baseline patient characteristics. Such a model may be useful for identifying patients who require higher levels of engagements in the early stages of home telerehabilitation programs. The resulting set of predictive features included education, patient satisfaction with the program, and psychological domain of the MS Impact Scale. Resulting prediction of high and low adherence had overall 80.0% accuracy, 81.8% sensitivity, and 77.8% specificity. We concluded that the baseline patient information may be instrumental in personalizing levels of support and training necessary for active patient participation in telerehabilitation.
A Preliminary Conceptual Framework in Knowledge Translation and Health Information Technology for Transparency in Policy-Making (The KhITT Framework)
Authors: Mallidou Anastasia
Published: February 2025

A preliminary conceptual framework on knowledge translation and health information technology is proposed for transparency in policy-making process. Three domains and ten recommendations/dimensions are briefly described.
Development of an Interprofessional Educational Electronic Health Record
Authors: Rees Glynda  , Morrison Janet  , Ahuja Kamal  , Anthony Joseph  , Blanes Nina  , Borycki Elizabeth M.  , Bower Lisa  , Isaak Cheryl  , Kruger Robert  , Kushniruk Andre  , Min Jason  , Moore Carmen  , Visosky Patricia  , Currie Leanne
Published: February 2025

This paper identifies issues relating to academic health record systems and outlines a project currently underway to develop an open source educational clinical information system to better support interprofessional health education.
Usability Analysis of Contending Electronic Health Record Systems
Authors: Tyllinen Mari  , Kaipio Johanna  , Lääveri Tinja
Published: February 2025

In this paper, we report measured usability of two leading EHR systems during procurement. A total of 18 users participated in paired-usability testing of three scenarios: ordering and managing medications by an outpatient physician, medicine administration by an inpatient nurse and scheduling of appointments by nursing staff. Data for audio, screen capture, satisfaction rating, task success and errors made was collected during testing. We found a clear difference between the systems for percentage of successfully completed tasks, two different satisfaction measures and perceived learnability when looking at the results over all scenarios. We conclude that usability should be evaluated during procurement and the difference in usability between systems could be revealed even with fewer measures than were used in our study.
Assessing the Alignment of Objectives, Instructional Activities, and Assessments in a Biomedical Informatics Curriculum
Authors: Williams Tremaine Brueon  , Kenney Bonita Elaine  , Littleton Daniel Kenneth  , Nahm Zozus Meredith
Published: February 2025

The objective of this research was to assess the alignment of course learning objectives, instructional activities, and course assessments in a Biomedical Informatics curriculum. Each syllabi in the curriculum was reviewed and scored according to a validated rubric. Disagreements among reviewers adjudicated by consensus. Only low and moderate levels of alignment were identified. The results indicated the needs and goals of courses could be more effectively met with faculty investment in syllabi redesign and clarification to achieve course objectives. Root causes included word choice in learning objective statement as well as lack of consideration of instructional scaffolding by the course developer.
On Ontological Categories
Authors: Garbacz Pawel
Published: February 2025

The paper aims to characterise the proper subject matter of ontology by drawing the boundary line between ontological and non-ontological categories. The account of ontological categories I sketch here defines them as equivalence classes of a certain family of equivalence relations that are determined by ontological relations. As a result, the demarcation problem for ontological categories turns out to be dependent on the demarcation problem for ontological relations.
Automated Verification of Structured Questionnaires Using HL7
Authors: Lackerbauer Anna M.  , Krauss Oliver  , Helm Emmanuel
Published: February 2025

Informed consent of patients to research studies is a cornerstone to modern healthcare, which has lead to considerable administrative effort. The purpose of this paper is to show how forms and questionnaires and their respective answers can be captured in a standardized, structured way, in order to enable automated verification. The use of the HL7 FHIR resources Questionnaire and QuestionnaireResponse is discussed with respect to the different implementation options of Extensions, POST Interceptors, FHIR Operations, and CDS Hooks. These four approaches are described and it is determined whether they produce standard-compliant results and how they can be integrated with other solutions. Since all approaches yield advantages and disadvantages, the choice amongst any option must be based on the actual use case.
The Vehicle as a Diagnostic Space: Efficient Placement of Accelerometers for Respiration Monitoring During Driving
Authors: Wang Ju  , Warnecke Joana M.  , Deserno Thomas M.
Published: February 2025

In-vehicle monitoring of bio-signals in real time is still an unsolved problem. To support continuous respiration monitoring, this work intends to reveal where such sensors can be deployed and how their signals are affected by noise during autonomous driving. A Shimmer3 IMU module was attached to the passenger seatbelt of a test vehicle for respiration monitoring. Four positions at the seatbelt (Shoulder, Chest, Side-Waist and Waist) were tested under four conditions (Engine Off, Engine On, and Drive on Flat and Uneven Road). The data capture protocol ensures the same respiration rate in all conditions. Three testers were measured with two repetitions each yielding a total of 96 records of 60 s lengths. All signals were low-pass filtered. Then, the fast Fourier transform was applied. We evaluated the highest peak in the frequency domain. If the highest peak in the range of 0.1 – 0.4 Hz was identified at the same position, the condition is counted as true. Surprisingly, side-waist position yields 67% on the uneven road while chest and waist (both in the middle of the subject) are unsuitable. In conclusion, monitoring respiration on the seatbelt is possible with accelerometers while driving, if the right sensor position is chosen. In future, smart textiles will be used to integrate unobtrusive and inexpensive biomonitoring in the vehicle.
Portal of Medical Data Models: Status 2018
Authors: Riepenhausen Sarah  , Varghese Julian  , Neuhaus Philipp  , Storck Michael  , Meidt Alexandra  , Hegselmann Stefan  , Dugas Martin
Published: February 2025

The Portal of Medical Data Models is an open-access platform for medical forms and data models. Annotation with UMLS codes enables semantic interoperability and secondary use of data. The number of forms and users are growing. The site has been updated and two analyzing tools have been added.
Empowering Diabetes Patients with Interventions Based on Behaviour Change Techniques
Authors: Jung Oliver  , Glachs Dietmar  , Strohmeier Felix  , Mulrenin Robert  , Huisman Sasja  , Smith Ian  , van Keulen Hilde  , Sont Jacob  , Ploessnig Manuela
Published: February 2025

The number of people with diabetes is increasing in every European country and like all chronic diseases it cannot be cured. However, patient empowerment is an acknowledged strategy for improving the patients' health situation. This paper describes the Action Plan Engine developed as a tool for diabetes patients in the POWER2DM project. The Action Plan Engine offers a guided workflow based on treatment goals and activities. A periodic review evaluates how successful a patient has fulfilled these goals and activities. Part of the evaluation is detailed feedback, in particular about 170 interventions based on Behaviour Change Techniques in order to change a patient's lifestyle behaviour towards a healthier, diabetes-appropriate lifestyle. Additionally, the Action Plan Engine offers decision trees for coping with barriers regarding glucose monitoring, exercise, carbohydrate, insulin and stress.
Improving the Prediction of Emergency Department Crowding: A Time Series Analysis Including Road Traffic Flow
Authors: Rauch Jens  , Hübner Ursula  , Denter Mathias  , Babitsch Birgit
Published: February 2025

Background: Crowding in emergency departments (ED) has a negative impact on quality of care and can be averted by allocating additional resources based on predictive crowding models. However, there is a lack in effective external overall predictors, particularly those representing public activity.
Using Neural Networks for Diagnosing in Dermatology
Authors: Bobrova Margarita  , Taranik Maksim  , Kopanitsa Georgy
Published: February 2025

The paper deals with neural networks for decision support in diagnosing in dermatology. There were several iterations during development. We classified six diseases using ANN: (1) Psoriasis, (2) Seborrheic dermatitis, (3) Lichen planus, (4) Pityriasis rosea, (5) Cronic dermatitis, (6) Pityriasis rubra pilaris. At first, we used all 35 attributes to conclude skin disease diagnosis with the accuracy of 96.9%. Then, we reduced the set of analyzed attributes by Pearson correlation approach to eight attributes and increased the accuracy to 98.64%. Data collection time was reduced. Thereby, the speed of the diagnosing process was increased and, as a result, it was possible to form a treatment plan more effectively. The tools used for neural network development were the Python language, Keras library and PyCharm platform.
Risk Classifications Interfere with Preference-Sensitive Decision Support
Authors: Kaltoft Mette Kjer  , Dowie Jack
Published: February 2025

Many guidelines for prevention and treatment still locate persons in risk classes (e.g. low, moderate, high) on the basis of thresholds placed on a continuous metric for a single criterion (e.g. risk of developing x). These ‘traffic light’ signals can lead to inferior decisions through their mono-criterial focus and lack of preference-sensitivity to the multiple criteria relevant to the person. It is arguably unethical to communicate to someone that they are at low, moderate, or high risk of x solely on the basis of the unpublished and often unknown preferences of the group that has set the classification thresholds. Any prior classification and labelling will interfere with the individual's balanced processing of information on the performance of all treatment options on their multiple relevant criteria - including treatment side effects and burdens as well as main benefit - and jeopardise meeting the requirements for fully informed and preference-based consent to any subsequent action. Personalised decision support tools based on Multi-Criteria Decision Analysis can help fulfil these objectives, with apomediative (at home) e-decision support especially appealing because of its empowering and resource-saving potential. The individual's absolute risk score is required in these tools since any threshold-based risk classification will interfere with the coherence of the analysis across the multiple criteria.
Carried Weight Affects Walking Speed Monitoring with the IngVaL System
Authors: Hellstrom Per Anders Rickard  , Folke Mia
Published: February 2025

Earlier work has shown that the IngVaL pedobarography system can estimate walking speed during indoor walking using only three forefoot sensors. The aim of this study was to examine if monitoring of walking speed using data from these three forefoot sensors is affected of the weight a person carries, if the person performs a walk in a set speed on the treadmill. Shoe insoles with force sensing resistors were connected to an electronic unit for signal conditioning and sampling and then the data was sent via Bluetooth to a tablet. Fifteen test persons walked five times each carrying five different weights on the treadmill at 1 m/s. The force-time integrals for the sum of the three forefoot sensors were calculated. This study shows that the force-time integrals for the three forefoot sensors shows a linear relationship with the carried weight as long as the person is not fatigued.
Research of fatigue strength of welded joints of rails
Authors: Lesin A. V. , Karlina A. I. , Deryugin F. F , Byankin V. E. , Gorshkov A. A.
Published: February 2025

In order to confirm the efficiency of various versions of the modernized design of the rail quench cooling system sprayer, a study of the structure of the hardened layer, structural and fatigue strength of welded rail joints after various heat treatment methods was conducted. In order to confirm the results of hardness measurements on rails of three batches (I, II, III) and the results of static tests of batches II and III, templates were cut out and metallographic examination was carried out. Analysis of the presented microstructures in the rail head shows that the microstructure in the head is quenched sorbite. The microstructure in the rail neck is pearlite partially with a globular form of cementite, in the rail foot it is represented by sorbite-like pearlite, which is associated with cooling the foot in air. In this case, a pearlite microstructure is formed on the feet of the foot. The microstructure study on samples II and III was carried out at a distance of 5–10 mm from the welded joint after induction heat treatment. The microstructure in the rail head II in the central zone is represented by a sorbitic structure with a ferrite network, in the rail neck – by sorbitol of mixed morphology (lamellar and granular), in the base zone in the middle and feathers – by a structure of sorbitic pearlite, mixed morphology (lamellar and granular). The microstructure along the axis of the rail head III is represented by a sorbitic structure, in the neck – by a mixed morphology of sorbite (mixed and granular, the rail foot in the middle is troostite and troostosorbite. The microstructure of the foot feather consists of troostosorbite. The results of testing welded joints under three-point bending of rail samples are presented. As a result of the analysis, it was found that the indicators for the destructive load and deflection are higher when using a two-way compressed air supply system in the cooling sprayer. When testing samples, the load was applied to the head (in the stretch zone of the foot), the characteristics of fatigue tests were determined. The number of cycles cumulatively increased by 669 thousand with two-sided hardening, and destructive stresses by 9.5%.
Membangun Tim Guru yang Solid dan Profesional untuk Menciptakan Lingkungan Belajar yang Optimal
Authors: Faisal Romdonih  , Kamsidik  , Ruknan
Published: February 2025

Program Pengabdian kepada Masyarakat (PKM) ini dilaksanakan dengan tujuan untuk membangun tim pengajar yang solid dan profesional di TK Islam Al-Kamal, Kedaung-Pamulang. Dalam rangka menciptakan lingkungan belajar yang optimal, PKM ini memfokuskan pada peningkatan keterampilan guru dalam berkolaborasi, komunikasi efektif, serta profesionalisme pengajaran. Pelatihan dilakukan secara daring selama lima hariberturut-turut, dimulai dengan studi awal untuk memahami kondisi dan tantangan di lapangan, dilanjutkan dengan survei preferensi untuk mengetahui kebutuhan pengembangan diri guru. Sesi pelatihan mencakup materi tentang kerja tim, penggunaan teknologi dalam pembelajaran, metode inklusif, serta manajemen kelas dan dinamika siswa. Pendekatan interaktif seperti diskusi kelompok dan studi kasus digunakan untuk memperkuat penerapan praktis konsep-konsep tersebut dalam situasi nyata. Evaluasi dilakukan melalui sesi tanya jawab dan umpan balik peserta. Hasil kegiatan ini menunjukkan bahwa program PKM berhasil mencapai tujuan yang diharapkan, yaitu terciptanya tim guru yang lebih solid, terampil, dan mampu menciptakan suasana belajar yang positif serta mendukung perkembangan siswa. PKM ini diharapkan dapat memberikan dampak berkelanjutan dalam peningkatan mutu pendidikan di TK Islam Al-Kamal
Penerapan program konseling kelompok dalam perencanaan masa hadapan anak-anak Panti Asuhan Permata Camar di Kuantan, Pahang
Authors: Ula Nazratul , Novita Nelda , Khairunisa Khairunisa , Indra Syaiful , Jarnawi Jarnawi
Published: February 2025

Penelitian ini bertujuan untuk membantu klien dalam menyelesaikan permasalahanya dan memberikan pemahaman melalui dinamika kelompok yang membahas mengenai perencanaan masa depan anak dengan latar belakang keluarga dan kecerdasan yang berbeda-beda. Metode yang digunakan adalah melakukan sosialisasi serta diskusi manfaat pelayanan bimbingan dan konseling, dan penerapan layanan konseling kelompok. Hasil pengabdian ini adalah terwujudnya perubahan pemikiran anak-anak panti dalam menentukan pilihan masa depan yang tepat tanpa memikirkan latar belakang keluarganya. Serta menciptakan tekat dan strategi pemilihan pendidikan yang linier dengan keinginan dan kemampuanya.
Peningkatan Kesehatan Mental Pelajar Melalui Sosialisasi Kesehatan Mental Berbasis Islam
Authors: Kurnia Agus , Eka Apriani Lestari  , Fadhlina Shahira  , Resti Julia Agustiandini  , Winda Miranti  , Zerlinda Ariesta Pratiwi
Published: February 2025

Angka kejadian bunuh diri dan melukai diri (self harm) sendiri di kalangan pelajar di berbagai daerah di Indonesia merupakan permasalahan yang sangat serius yang perlu diatasi. Dalam hal ini, komunitas pelajar menjadi sasaran utama, karena banyak faktor dan penyebab yang mendorong terjadinya bunuh diri dan melukai diri sendiri (self harm) di kalangan pelajar. Pengabdian mahasiswa baru prodi ilmu komunikasi dalam mata kuliah Pendidikan Agama Islam (PAI) melakukan project “Islam dan SDGs” di SMP Negeri 15 Mataram, yang bertujuan memberikan pemahaman mengenai Islam dan Pengembangan Kesehatan Mental di Kalangan Pelajar. Kegiatan pengabdian ini dilakukan dalam bentuk sosialisasi kesehatan mental yang diintegrasikan dengan pendekatan Islami kepada siswa-siswi di kelas 7. Hasil pengabdian menunjukkan adanya perubahan pemahaman dan tingginya antusias para siswa dalam kegiatan ini. Hal ini terlihat dari peningkatan hasil pemahaman siswa yang diukur melalui kegiatan pre-test dan post-test siswa serta observasi yang dilakukan.  Kesimpulannya, pembelajaran berbasis project ini sangat membantu untuk meningkatkan kesehatan mental siswa sehingga mereka siap menghadapi tantangan psikis yang muncul di masa yang akan datang
Art Therapy: Penggunaan Media Seni Sebagai Upaya Mengatasi stress Warga Binaan
Authors: Suhara Grasi Cantika , Damai Syaputra Yogi , Furqonuddin Asep , Monalisa Monalisa
Published: February 2025

Inmates in prison environments are vulnerable to mental health problems and stress. Art therapy is a therapeutic method that uses art as a means to help individuals express and understand their emotions and thoughts. Based on previous literature reviews, art therapy was proven to reduce depressive symptoms in five participants. This service program aims to help inmates deal with stress and find out how art therapy can be an approach that can overcome stress in inmates and find out other benefits obtained from applying this method in a correctional environment. The program is implemented using psychotherapy methods with art therapy techniques. This activity involves counseling students, supervisory staff and residents of the class IIA correctional institution in Serang City in implementing the art therapy program. The art therapy activity was attended by 11 inmates with different types of cases and who had symptoms of stress at a moderate to severe level. As a result of this activity, students observed and conducted interviews and it was seen that the inmates who were previously gloomy and quiet were now able to smile and be open to telling stories. After holding the art therapy program, students saw changes in the behavior and facial expressions of the inmates. Art therapy has proven to be an effective method in dealing with stress in class IIA inmates in the city of Serang. Through the use of painting, therapy participants can channel their emotions and express feelings that are difficult for them to express verbally
Penyuluhan dan Edukasi Kesejahteraan Emosional Melalui Terapi SEFT Bagi Komunitas Wirit Desa Rimbang Sawang Aceh Tamiang
Authors: M. Ilyas Sabrida , Mua’zirin Mua’zirin , Nate Finte , Aulia Rahim Reynaldi , Lutfina Lutfina , Mayani Lubis Nazly
Published: February 2025

Kesejahteraan emosional ibu-ibu di Desa Rimbang Sawang menjadi perhatian utama dalam program pengabdian masyarakat ini, mengingat tantangan emosional yang mereka hadapi akibat kondisi sosial dan ekonomi yang sulit. Tujuan dari pengabdian ini adalah untuk meningkatkan kesejahteraan emosional melalui penerapan terapi Spiritual Emotional Freedom Technique (SEFT). Metode yang digunakan mencakup penyuluhan, praktik teknik SEFT, serta diskusi dan refleksi dengan 35 peserta ibu-ibu komunitas wirid berusia 28 hingga 60 tahun. Temuan penting dari hasil pengabdian menunjukkan penurunan signifikan dalam tingkat stres dan kecemasan peserta, dengan skor stres berkurang dari 7.2 menjadi 4.5 dan kecemasan dari 6.8 menjadi 4.3. Peningkatan juga terlihat dalam pemahaman dan keterampilan praktik SEFT, yang menunjukkan bahwa peserta memperoleh manfaat praktis dari pelatihan. Kesimpulannya, program ini berhasil mencapai tujuannya dengan memberikan dampak positif pada kesejahteraan emosional ibu-ibu wirid dan meningkatkan keterampilan mereka dalam menerapkan teknik SEFT. Hasil ini menegaskan efektivitas SEFT sebagai alat untuk mengelola stres dan memperbaiki kesejahteraan emosional dalam komunitas tersebut. Selanjutnya, disarankan untuk melanjutkan program ini dengan sesi lanjutan dan pembentukan kelompok dukungan untuk memastikan keberlanjutan manfaat yang diperoleh.