bluuebunny/crossref_metadata_2025 huggingface dataset:
A Study on the Construction of an Intelligent Prediction Model for Corporate Tax Risk
Authors: Chen Zhen
Published: November 2024

In order to solve the constraints on flexibility and scalability of traditional rule-based assessment methods in the comprehensive processing of massive, multi-dimensional and heterogeneous tax-related data for tax risk analysis of large enterprises, an intelligent prediction model for enterprise tax risk is proposed. Aiming at the typical scenarios of tax risk of related transactions of large enterprises, the characterization extraction method of tax data features is defined, and the tax risk analysis and prediction model based on artificial neural network multilayer perceptron is constructed. In order to evaluate the performance of the proposed model, a test dataset is constructed using real tax data and expert labeled data, and experiments are conducted under different positive and negative sample ratios and sample capacity sizes, and compared with several widely used machine learning models. The experimental results show that the model in this paper achieves better performance than the comparative models in both positive and negative sample balanced and unbalanced cases. Among them, when the ratio of positive and negative samples is 5:5, all the models achieve the optimal results relative to the data imbalance, while the model in this paper outperforms all the comparative models, and achieves the best precision rate, recall rate, F1 value and AUC value. Conclusion: The proposed method has good performance in terms of accuracy and effectiveness. With the continuous improvement of data labeling in tax authorities, the method of artificial neural network for tax risk assessment has a broad prospect in business use.
Deep Learning-Based Video Content Understanding and Analysis
Authors: Jing Xuehong , Jing Yang
Published: November 2024

This research proposes a video content understanding method based on deep learning to effectively understand video content. First, use ResNet to extract global features and Places365-CNNs migration learning to extract deep scene features. Then, scene vectors are generated by multi-layer perceptron and used as the input of LSTM network to encode and decode video images and description statements. Finally, by pre training on the MSCOCO dataset, accurate description statements are generated for video key frames. The experimental results show that with the increase of data volume, the performance of the model is significantly improved, especially in CIDER-D evaluation, which is superior to other models. The conclusion shows that the proposed model shows high accuracy and performance improvement in describing video content.
An Attention Mechanism-Based Algorithm for Recognizing High-Resistance Ground Faults in Distribution Networks
Authors: Chen Kun
Published: November 2024

In order to solve the problem that when the high resistance grounding fault occurs in the distribution network, the resistance at the fault point is large, the sudden changes of voltage and current are not obvious, and the conventional protection is difficult to act accurately, an algorithm based on attention mechanism is proposed to identify the high resistance grounding fault in the distribution network. This paper constructs a time-frequency matrix by HHT band-pass filtering of three- phase voltage and zero sequence voltage of the bus, calculates the standard deviation of each frequency band as the eigenvector, and finally uses KNN combined with attention mechanism to identify faults. The experimental results show that the recognition accuracy of the algorithm can reach more than 95% through adaptability analysis under different simulation conditions. Conclusion: The algorithm can identify high resistance faults with high accuracy.
Sustain Power: Energy Harvest for Smart Wearable Device
Authors: Wang Chenrui , Li Xia , Xu Jiang
Published: November 2024

The study aims to investigate the direction of product design from the perspective of user behavior by analyzing user behavior data, in order to guide product design and achieve design outcomes that align with user needs. Additionally, we conducted a comprehensive analysis of energy consumption patterns for smart wearable devices across various usage scenarios. Drawing upon the principles of user experience design, we proposed a multifunctional power supply solution and completed hardware design, encompassing evaluation of product appearance, structure, and extended battery life. This project offers profound insights into scientifically designing energy supply for wearable devices and holds significant reference value.
A Study of a Secure and Transparent Governance Framework for Blockchain in Digital Government
Authors: Yuan Chao , Liu Zhiyong , Aoqi  , Bayaer
Published: November 2024

This study proposes a secure and transparent governance framework for blockchain in digital government, aiming to solve the problems of data quality, open timeliness, sharing awareness, interactive feedback, technical standards and data regulatory security in the existing digital government practice. It provides new perspectives and solutions through in-depth analysis of the intrinsic logical connection between blockchain technology and digital government governance. Through the analysis of a city’s “directory blockchain” scenario, the results show the feasibility and effectiveness of the framework, proving the accessibility of open and shared governance of on-chain data. It is concluded that the framework can realize the open sharing and governance of government data and promote the development of digital government.
Characterizing Changes in Performance in Taekwondo Competitions from a Data Analysis Perspective
Authors: Jin Zhongxuan
Published: November 2024

This paper analyzes video recordings of 60 taekwondo athletes from a specific Olympic Games to summarize global trends in technique and tactics. Results show that scoring first in the initial round increases win probability, while recovery from an initial deficit through active attack improves chances. Regional differences in tactical use are evident, with Europeans utilizing first-round scoring tactics most (47.36%) and achieving a high win rate (60.52%), contrasting with Africans (9.09% tactic use, 9.09%-win rate). This study provides valuable insights for taekwondo athletes to develop effective competition strategies.
A Study on Intelligent Scheduling and Optimization of Electric Vehicle Charging Facilities
Authors: Qu Xinying , Qu Dongzhe , Liu Guangyu
Published: November 2024

This paper proposes an intelligent scheduling and optimization model to solve the congestion problem of electric vehicle charging stations. First, the queuing time of different charging options is analyzed, and a dynamic pricing model is proposed based on the queuing rate and time-of-use electricity price to affect the charging behavior of car owners. The model takes into account the charging cost and the total route travel time based on the origin and destination points, and uses the DEB-ABC algorithm to solve the problem with reducing the total cost as the optimization goal. The simulation verification results show that the model proposed in this article significantly reduces the average waiting time, charging cost and driving time, effectively improves the utilization rate of charging resources, and reduces grid load fluctuations.
A Method for Evaluating the Satisfaction of Public Services in Zhaoqing Based on the Modified IPA Analysis Method
Authors: Tang Wei , Cheng Zixin , Zhu Zhaoyang
Published: November 2024

The evaluation scale of cultural and tourism public services in Zhaoqing City consists of thirty-one evaluation indicators in seven categories. The modified IPA analysis method is used to explore the perceived needs of tourists further, determine the perceived and derived importance values of the evaluation indicators of cultural and tourism public services in Duanzhou District, Zhaoqing City, and analyze the differences in demand between the indicators in terms of perceived and derived importance. By constructing a quadrant distribution map, the indicators are categorized into advantageous areas, maintenance areas, opportunity areas, and key improvement areas. A total of 13 indicators were analyzed for the improvement of cultural and tourism public services in Duanzhou District, Zhaoqing City, focusing on three systems: convenient tourism transportation services, public infrastructure services, and public information services.
Research and Application of Machine Learning-Based Image Semantic Segmentation Techniques in Visual Communication
Authors: Liu Yajun
Published: November 2024

In order to improve the utilization of spatial-spectral features in hyperspectral image classification algorithms, this paper investigates an image semantic segmentation technique based on machine learning. The method consists of randomly sampling a window from the training image, using the comparison of the values of two pixels in the window to generate a feature vector, and using it to train a random forest classifier. In the testing stage, the category of each pixel is determined by voting on the leaf nodes of the random forest. The experimental results show that the average classification accuracy of the improved algorithm is improved from 0.3006 to 0.3295, and the global classification accuracy is improved from 0.4430 to 0. 4909. It is concluded that the proposed improved algorithm performs well in semantic image segmentation.
The Application of Virtual Reality and Augmented Reality in Mechatronics Education Reform
Authors: Hou Xue
Published: November 2024

In order to solve the problems of tedious operation and low learning efficiency of traditional virtual training system, the application of virtual reality and augmented reality in mechatronics teaching reform was proposed. This paper proposes an algorithm for creating scenarios and image recognition. First, quickly find the relationship between the application scenario and the training experiment. Second, apply rendering algorithms and lighting models to quickly and vividly load virtual devices; Finally, an interactive mode algorithm based on augmented reality technology is proposed to enhance the experience and operation of training experiments. The experimental results show that the whole system can complete the preparation of the test environment in only 1.2s∼1.8s. The control group needs 3.3s-5.2s to prepare. After the improvement, the overall running speed of the system has increased by about 2.75 times. Conclusion: The application of augmented reality technology makes the operation of virtual training system simpler and more convenient, and the learning efficiency has been greatly improved.
A Model Analysis of the Development of Ethnic Traditional Sports in Higher Vocational Colleges and Universities in Anhui Province Under the Perspective of Intelligence
Authors: Liu Zongsheng
Published: November 2024

In order to solve the problem of low efficiency and low accuracy of learning effect analysis of traditional system in traditional national sports teaching, the development model analysis of traditional national sports in higher vocational colleges in Anhui Province from the perspective of intelligence was proposed. In this paper, firstly, based on the teaching information management platform and the independent physical training monitoring system, students’ sports learning related information is collected; Then, normalization and missing value supplement processing were carried out, and Apriori algorithm was used to obtain association rules between college students’ sports learning information, and the Apriori algorithm was reduced by deletion and comparison strategies to reduce connection operations; Finally, the system designed in this paper is verified by experiments. The experimental results show that the data mining response time of the algorithm in this paper is significantly lower than that of the traditional Apriori algorithm. When the number of students reaches 80, the algorithm in this paper saves 21.5s. Conclusion: The system designed in this paper improves the operational efficiency of learning effect analysis.
Discovery and Confirmation of Diagnostic Serum Lipid Biomarkers for Alzheimer’s Disease Using Direct Infusion Mass Spectrometry
Authors: Anand Swati , Barnes Justin M. , Young Sydney A. , Garcia Diana M. , Tolley H. Dennis , Kauwe John S.K. , Graves Steven W.
Published: November 2024

Alzheimer’s disease (AD) is a neurodegenerative disorder lacking early biochemical diagnosis and treatment. Lipids have been implicated in neurodegenerative disorders including AD. A shotgun lipidomic approach was undertaken to determine if lipid biomarkers exist that can discriminate AD cases from controls. The discovery study involved sera from 29 different stage AD cases and 32 controls. Lipid extraction was performed using organic solvent and the samples were directly infused into a time-of-flight mass spectrometer. Differences between AD cases and controls were detected with 87 statistically significant lipid candidate markers found. These potential lipid markers were reevaluated in a second confirmatory study involving 27 cases and 30 controls. Of the 87 candidates from the first study, 35 continued to be statistically significant in the second confirmatory set. Tandem MS studies were performed and almost all confirmed markers were characterized and classified. Using a Bayesian lasso probit regression model on the confirmed markers, a multi-marker set with AUC = 0.886 was developed comparing all stages of AD with controls. Additionally, using confirmed biomarkers, multi-marker sets with AUCs >0.90 were developed for each specific AD Clinical Dementia Rating versus controls, including the earliest stage of AD. More conservative and likely more realistic statistical analyses still found multi-marker sets that appeared useful in diagnosing AD. Finally, using ordinal modeling a set of markers was developed that staged AD accurately 70% of the time, p = 0.0079. These results suggest that these serum lipidomic biomarkers may help diagnose and perhaps even stage AD.
Comparison of 12/10 switched reluctance motors with star and polygon connections
Authors: Niguchi Noboru , Hirata Katsuhiro , Suzuki Hironori , Okamoto Junka , Takemura Nozomu
Published: November 2024

We propose a 6-phase 12/10 switched reluctance motor (SRM) with a polygon connection. The transformation between star and polygon connections is not equivalent to that between star and delta connections of a conventional 3-phase motor. In this paper, the transformation between star and polygon connections is theoretically described. In addition, the current condition that maximizes torque is described. Finally, the torque of both connections is compared in terms of the AC-DC current ratio.
APPLICATION OF THE INDEPENDENCE AXIOM ON THE DESIGN OF	OBJECT-ORIENTED SOFTWARE USING THE AXIOMATIC DESIGN THEORY
Authors: Pimentel Andrey Ricardo , Stadzisz Paulo Cézar
Published: November 2024

Current software design methodologies and techniques enhance software quality features. However, it is difficult to evaluate if a software design solution is good enough without a theoretical foundation. The use of Axiomatic Design, together with a traditional software development methodology, can improve decision-making during the design process. This work presents an approach for object-oriented software design that intends to maintain the quality of the design solution along the development process. The goal of this approach is to facilitate the use of the Axiomatic Design together with Unified Modelling Language and object-oriented software development methodologies such as Unified Process. This design approach relates object-oriented software design concepts such as use cases, collaborations, classes, operations, and objects with functional requirements, design parameters, and the zigzagging process. This work presents a functional decomposition hierarchy, based on software design concepts, which can be applied together with software design methodologies. This work also presents a case study to illustrate the application of a design approach, based on Axiomatic Design, on an object-oriented design of a real-time embedded software system. The case study evaluates alternative design solutions to illustrate the application of the Independence Axiom in order to maintain the quality of the design.
DIAGRAMMATIC EDUCATION FOR SOFTWARE ENGINEERING
Authors: Kawabata Ryo , Itoh Kiyoshi
Published: November 2024

In the education of software engineering, it is important to educate learners about diagrammatic representations for analyzing configurations or functions of a target system. In systems analysis two or more diagrammatic representation are described in appropriate order, which experts know as the effective analysis process. Education of the analysis process using diagrammatic representations is more important and essential rather than education of notations of diagrammatic representations. This paper proposes an intelligible analysis process which is suitable for education. Learners of systems analysis can acquire the process model effectively by using the process model, which includes Petri Net, STD, DFD, and IDEF0, in this order. It is easy to reuse components between the diagrammatic representations according to the analysis process.
ECONOMIZING ISP INTERCONNECTIONS AT INTERNET EXCHANGE POINTS
Authors: Altmann Jörn , Goel Deepak
Published: November 2024

The Internet service provider market is very competitive. Small and medium-size Internet service providers (ISPs) are competing for customers, while, at the same time, they are under price pressure from upstream providers. Therefore, these ISPs have to reduce their overall cost of interconnection. In order to address this issue, Internet exchange points (IXPs) have been built up in recent years, which allow small and medium-size ISPs to go into public or private peering with other ISPs. However, those ISPs do not have sufficient information to select the optimal set of ISPs, with which they should go into private peering agreements. In this paper, we describe an approach, which provides ISPs with the information about the most economical interconnections to other ISPs. This approach helps small and medium-size Internet service providers to reduce their interconnection costs for upstream connectivity and to improve network performance for their customers. To achieve that, our approach uses Internet topology information in close neighborhood of the ISP (which is determined by the set of ISPs connected to the IXP), measurement information about the number of bytes transmitted, and traffic pricing schemes. Based on real data, our analysis results demonstrate that our approach provides the necessary information to ISPs for locally optimizing their interconnection agreements (e.g. peering, sibling, transit agreements).
HEURISTICS AND QUALITATIVE RULES FOR THE PERFORMANCE DESIGN OF	COLLABORATIVE SYSTEMS
Authors: Gonsalves Tad , Itoh Kiyoshi
Published: November 2024

The domain expert's heuristics in the performance design and improvement of collaborative systems are systematized as Qualitative rules. A knowledge base system built by using the Qualitative rules diagnoses the bottlenecks in the system operation and suggests improvements or tuning. However, the bottlenecks cannot be completely resolved due to the constraints imposed on the system resources. In such a case, our strategy is to resolve the local bottlenecks, while maintaining the global stability of the system. To enforce this strategy, we demarcate the system model into local, upstream and downstream sections, and set up the Qualitative improvement rules for each of these sections. A performance improvement task is then guided by a set of local, forward propagation, backward propagation and global rules. Local rules correspond to a local improvement. When the local rules fail to yield satisfactory results, the backward propagation rules are called upon to indicate the improvements to be made in the upstream of the network so as to resolve the problematic local bottleneck. The forward propagation rules estimate the effects on the downstream of the network due to the resolution of the chosen bottleneck. Finally, the advisability of resolving a local bottleneck, while keeping the global adverse effects to a minimum, is given by the global rules.
THE BOEING 777: NO CHAINSAW MASSACRES, PLEASE!
Authors: Jørgensen Niels
Published: November 2024

Iterative life cycle models have become popular in software engineering, e.g. in agile development. In contrast, the waterfall model appears to prevail in manufacturing engineering disciplines. This includes aircraft engineering and Boeing's project for developing its most recent passenger aircraft, the 777. The paper walks through the phases of the 777's development and compares this process to iterative development. The comparison suggests two observations: Firstly, the over-all waterfall approach in the 777 project appears to be well-motivated by the physical, manufactured nature of aircraft components such as wings, in addition to safety concerns. Secondly, several iterative elements in the development of the 777 can also be identified. A major source of these is digitalization of development, in particular the use of CAD tools for a process called digital preassembly.
A DYNAMIC RELATIONSHIP FRAMEWORK FOR INNOVATION: IMPLICATIONS FOR	THE BRAZILIAN AEROSPACE STRATEGY OPERATIONS
Authors: Bueno Cristiane Gattaz , Neto João Amato , Catharino Mauro , Techima Katuchi , Sampaio Renato C.
Published: November 2024

The present paper aims at identifying some critical factors related to current relationship structure frameworks that better organizes the strategy operations of the Brazilian aerospace industry to be the best qualifying candidate for innovation operation with a high level of efficiency and effectiveness. The objective of this study, based on the case study research methodology, is to analyze the inter-organizational relationship structure framework of the Brazilian Aerospace Agency (BAA) strategy operation case. As a result, the improvement of the innovation relationship governance structure and its transaction costs reduction are the main implications when applying the identified critical factors.
PEDAGOGICAL ENRICHMENT OF INFORMATION OBJECTS
Authors: Heyer Susanne
Published: November 2024

This paper presents a distinction between content parts (information objects) and educational parts of learning objects. A plea is made for the separation of content and educational context references to maintain the content's high potential for reusability. Since content alone does not constitute a didactical situation, however, after its separation content needs to be enriched with educational elements such as learning objectives and learning activities. This paper proposes ways of rejoining content with educational elements in a repository using an educational objectives taxonomy. The taxonomy could be further implemented to collect data on the different pedagogical purposes an information object was used for. Pedagogical repurposing, however, is not just understood as a reuse within different subject matter but also as a reuse for different pedagogical goals, such as the promotion of higher cognitive processes in learning.
ON THE NATURE OF FORMAL SYSTEM DECOMPOSITION PRINCIPLES AND THEIR	POTENTIAL APPLICATIONS TO THE BASIS OF CARCINOGENESIS
Authors: Tuncer Tolga , Tuncer Yalcin , Tanik Murat M.
Published: November 2024

The notion of complex systems and system decomposition principles are briefly reviewed. From the perspective of formal decomposition of systems and as an application of entropic principles, an attempt is made to open up a new avenue of investigation for carcinogenesis.
REFINING METHOD OF BUSINESS PROCESS MODEL – SCENARIO ORIENTED	APPROACH FOR CROSS ORGANIZATIONAL BUSINESS PROCESS
Authors: Kumagai Satoshi , Tomita Yoshitaka
Published: November 2024

Using scenario is an effective way to acquire knowledge about business process. Scenario describes business process in users' perspective using their vocabulary. In cross organizational business process, scenario description is often fragmentary because each expert in the business process tends to be focused within his/her organizational scope. Each expert might be less knowledgeable about cross organizational aspects of business process. His/her description sometimes assumes ambiguous order of events in the scope. Clear terminology describing collaboration is missing. System analyst needs to supplement the description to obtain a business process model for consensus building beyond the scope. This paper presents a method for refining cross-organizational business process model through the use of complementary relationship in diagrammatic representations of scenario. It allows analyst to grasp the entire view of the business process through interactions with experts. Level of refinement is measured and evaluated.
DYNAMIC ARCHITECTURES FOR SOA-BASED APPLICATIONS
Authors: Tsai W. T. , Paul Raymond A. , Fan Chun , Wei Xiao
Published: November 2024

The architecture of SOA-based applications is different from traditional software architecture where the architecture is mainly static. The architecture of an SOA-based application is dynamic, i.e., the application may be composed at runtime using existing services. Thus SOA has provided a new direction for software architecture study, where the architecture is determined at runtime and the architecture can be dynamically changed at runtime to meet the new software requirements. This paper proposes an architecture classification scheme for SOA-based applications. Using this classification, several wellknown SOA-based applications are reviewed including the architectures proposed and adopted by major computer companies and standard organizations. The architecture classification provides a unified way to evaluate a variety of architectures for SOA-based applications.
OASAM - AN OPEN AND ADAPTIVE SOFTWARE ARCHITECTURE MODEL FOR	SERVICE-ORIENTED APPLICATIONS IN DYNAMIC NETWORK ENVIRONMENTS
Authors: Li Gang , Holtkamp Bernhard , Wang Jing , Han Yanbo
Published: November 2024

The dynamic characteristics of business processes and network computing environments bring new challenges to distributed applications. As an approach to solve the adaptation problem of serviceoriented applications, caused by changes of service resources and user requirements in such dynamic network computing environments, we present an open and adaptive software architecture model in this paper. We also discuss the deployment of the model in a real project. An analysis and evaluation of the model's capability to improve software adaptability shows that the model can improve service-oriented applications regarding change awareness, continuous evolution and selforganization.
Collaboration Across Disciplines to Integrate Clinical Expertise into Medical Software Development: The Approach of the Dedalus Medical Office
Authors: Rausch Dennis , Dahlweid Michael , Kozinova Irina , Wraith Clementine , Hochheim Ingrid , Marin Lise , Johnson Jane , McClelland Tracy , Gout Laurent , Kumar Gaurav , Yasini Mobin
Published: November 2024

Medical informatics is a multidisciplinary field combining clinical and technical expertise. Addressing the challenge of aligning software design with clinicians’ real-world needs, Dedalus established the Medical Office, a dedicated department designed to integrate clinical expertise directly into the software development process, in 2022. This paper details the approach and impact of the Medical Office. An international team of 15 healthcare professionals with experience in medical informatics was assembled. The team employed a multifaceted approach, incorporating global communication sessions and a ticketing system to track and analyze service requests. Over two years, 398 tickets were received, categorized into nine areas: clinical content curation, medical terminologies, clinical safety, clinical evaluation, design support, clinical UX, research & publication, real-world medical cases, and pre-sales support. The average duration of ticket resolution decreased over time, attributed to process fine-tuning and the formation of a relevant expert group. A preliminary satisfaction survey indicated positive feedback from technical teams. The collaborative model improved software design, usability, and clinical safety, demonstrating the value of clinician involvement. While preliminary results are promising, ongoing evaluation and adaptation are essential. The study emphasizes the importance of interdisciplinary collaboration in medical informatics and the benefits of clinician involvement in healthcare technology development. Future studies should explore this model’s long-term impacts and scalability in other organizations and healthcare systems.
Mobile Health Technologies and Their Features Affecting Medication Adherence Among Cancer Patients: A Scoping Review
Authors: Rahman Alsaify Abdel , Islam Supti Tourjana , Alzubaidi Mahmood , Househ Mowafa
Published: November 2024

This scoping review explores mobile health (mHealth) technologies and their features affecting medication adherence in cancer patients. Among 11 selected studies, predominantly from the USA, mHealth tools, particularly smartphone apps, were examined for their features in managing cancer patient’s medication adherence. The studies highlighted the importance of adherence in continuous cancer therapy, with mHealth tools offering reminders and interactive features, that aim to enhance patient engagement. However, the review identified research gaps, emphasizing the need for broader investigations into diverse mHealth tools beyond apps, including electronic capsules and smart pill dispensers. Additionally, it underscored the absence of information on costs, user input, integration with electronic health records, and data management. While acknowledging potential positive impacts on adherence, the review calls for more comprehensive research to substantiate these findings in clinical oncology.
Utilizing Open Source Clinical Information Systems in European Countries: Potential and Barriers
Authors: Magdub Fatma-Zahra , Nagarasa Sakirnth , Frick Florian , Sariyar Murat
Published: November 2024

GNU Health, an open-source clinical information system, offers a comprehensive solution for managing health records, hospital information, and laboratory data. Despite its robust functionality and cost-effective nature, GNU Health remains underutilized in the European healthcare context. This paper explores the potential benefits of implementing GNU Health in European healthcare systems, emphasizing its capacity for customization, integration, and scalability. We also examine the barriers to its widespread adoption, including regulatory challenges, interoperability issues, and resistance to change from established proprietary systems. Through one case study and expert interviews, we provide insights into why these obstacles can hardly be overcome.
Using Deep Learning to Suggest Treatment for Proximal Humerus Fractures
Authors: Azarpira Mohammadreza , Belhadj Ihssen , Khodja Mohammed
Published: November 2024

Proximal humeral fractures are among the most common fractures seen in emergency departments. Accurately diagnosing and selecting the most appropriate treatment for these fractures can be challenging, and consultation with a senior orthopedic surgeon can be time-consuming for both the patient and the emergency unit. We developed a machine learning model for predicting the type of treatment based on injury radiographic images. The model distinguishes between nonoperative and operative treatment options, achieving an accuracy of 86% and an interobserver reliability (kappa) of 0.722 for test-dataset, which is more than the interobserver agreement between shoulder surgeons. This model has the potential to serve as a therapeutic decision support system for the practitioners in the emergency departments to expedite treatment decisions and to reduce patients’ waiting time.
Survival Stacking Ensemble Model for Lung Cancer Risk Prediction
Authors: Alonso Eduardo , Calle Xabier , Gurrutxaga Ibai , Beristain Andoni
Published: November 2024

The most well-established risk factor for lung cancer (LC) is smoking, responsible for approximately 85% of cases. The Lung Cancer Risk Assessment Tool (LCRAT) is a key advancement in this field, which predicts individual risk based on factors like smoking habits, demographic details, personal and family medical history, and environmental exposures. This paper proposes a model with fewer features that improves state of the art performance, using a simplified stacking ensemble, making it more accessible and easier to implement in routine healthcare practice. The data used in this work were derived from two cohorts in the United States: The National Lung Screening Trial (NLST) and the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. Both our model and LCRAT achieve an AUC of 0.799 and 0.782 on test respectively. In terms of percentage of positives, in the 50% of the population, both detect 0.766 and 0.754 of the cases. The ensemble of different survival models enhances robustness by mitigating the weakness of individual models and directly impacts the efficiency of the model, increasing the efficiency and generalizability.
Prognostic Value of Ceramide Dynamics in Patients with Acute Coronary Syndrome
Authors: Usova Elena , Yakovlev Alexey , Kopanitsa Georgy , Metsker Oleg , Alieva Madina , Makarova Tatiana , Malishevskii Lev , Murashko Ekaterina , Kessenikh Elizaveta , Trusov Sergey , Alieva Asiiat , Konradi Alexandra
Published: November 2024

A dynamic study of ceramide concentrations and their association with recurrent event risk could enhance our understanding of cardiovascular complications. To assess the prognostic value of ceramide concentrations (Cer(d18:1/16:0), Cer(d18:1/18:0), Cer(d18:1/24:1), Cer(d18:1/24:0)) and their dynamics in combination with standard clinical and laboratory parameters and therapeutic interventions in ACS patients. Among 110 ACS patients, triple blood sampling was performed for targeted lipidomic analysis using high-performance liquid chromatography-tandem mass spectrometry. All ceramide concentrations peaked at admission and decreased by the 3rd day of hospitalization and at the 3-month follow-up. The difference between Cer(d18:1/18:0) concentration 3 months after hospital discharge and its baseline value on admission was strongly associated with recurrent events, independent of prior statin treatment. The association of the Cer(d18:1/18:0) change from 3rd day of hospitalization and its baseline concentration on admission with prognosis varied depending on the glycemic profile.
PROSurvival: A Technical Case Report on Creating and Publishing a Dataset for Federated Learning on Survival Prediction of Prostate Cancer Patients
Authors: Xu Tingyan , Wolters Timo , Lotz Johannes , Bisson Tom , Kiehl Tim-Rasmus , Flinner Nadine , Zerbe Norman , Eichelberg Marco
Published: November 2024

The PROSurvival project aims to improve the prediction of recurrence-free survival in prostate cancer by applying federated machine learning to whole slide images combined with selected clinical data. Both the image and clinical data will be aggregated into an anonymized dataset compliant with the General Data Protection Regulation and published under the principles of findable, accessible, interoperable, and reusable data. The DICOM standard will be used for the image data. For the accompanying clinical data, a human-readable, compact and flexible standard is yet to be defined. From the set of existing standards, mostly extendable with varying degrees of modifications, we chose oBDS as a starting point and modified it to include missing data points and to remove mandatory items not applicable to our dataset. Clinical and survival data from clinic-specific spreadsheets were converted into this modified standard, ensuring on-site data privacy during processing. For publication of the dataset, both image and clinical data are anonymized using established methods. The key challenges arose during the clinical data anonymization and in identifying research repositories meeting all of our requirements. Each clinic had to coordinate the publication with their responsible data protection officers, requiring different approval processes due to the individual states’ differing interpretations of the legal regulations. The newly established German Health Data Utilization Act is expected to simplify future data sharing in a responsible and powerful way.
Measurement of Explanations Generated by XAI Methods Using Features
Authors: Pesecan Cătălin-Mihai , Stoicu-Tivadar Lăcrămioara
Published: November 2024

An increasing number of explainability methods began to emerge as a response for the black-box methods used to make decisions that could not be easily explained. This created the need for a better evaluation for these methods. In this paper we propose a new method for evaluation based on features. The main advantage of applying the proposed method to CNNs explanations are: a fully automated way to measure the quality of an explanation and the fact that the score uses the same information as the CNN, in this way being able to offer a measure of the quality of explanation that can be obtained automatically, ensuring that the human bias will not be present in the measurement of the explanation.
Temporal relevance for representing learning over temporal knowledge graphs
Authors: Song Bowen , Amouzouvi Kossi , Xu Chengjin , Wang Maocai , Lehmann Jens , Vahdati Sahar
Published: November 2024

Representation learning for link prediction is one of the leading approaches to deal with incompleteness problem of real world knowledge graphs. Such methods are often called knowledge graph embedding models which represent entities and relationships in knowledge graphs in continuous vector spaces. By doing this, semantic relationships and patterns can be captured in the form of compact vectors. In temporal knowledge graphs, the connection of temporal and relational information is crucial for representing facts accurately. Relations provide the semantic context for facts, while timestamps indicate the temporal validity of facts. The importance of time is different for the semantics of different facts. Some relations in some temporal facts are time-insensitive, while others are highly time-dependent. However, existing embedding models often overlook the time sensitivity of different facts in temporal knowledge graphs. These models tend to focus on effectively representing connection between individual components of quadruples, consequently capturing only a fraction of the overall knowledge. Ignoring importance of temporal properties reduces the ability of temporal knowledge graph embedding models in accurately capturing these characteristics. To address these challenges, we propose a novel embedding model based on temporal relevance, which can effectively capture the time sensitivity of semantics and better represent facts. This model operates within a complex space with real and imaginary parts to effectively embed temporal knowledge graphs. Specifically, the real part of the final embedding of our proposed model captures semantic characteristic with temporal sensitivity by learning the relational information and temporal information through transformation and attention mechanism. Simultaneously, the imaginary part of the embeddings learns the connections between different elements in the fact without predefined weights. Our approach is evaluated through extensive experiments on the link prediction task, where it majorly outperforms state-of-the-art models. The proposed model also demonstrates remarkable effectiveness in capturing the complexities of temporal knowledge graphs.
Reporte Investigaciones Económicas Banrep - I-2024
Authors:   Centro de Apoyo a la Investigación Económica,   Subgerencia de Estudios Económicos
Published: November 2024

Este Informe de publicaciones presenta una síntesis periódica de las publicaciones y eventos relacionados con la actividad académica del Banco de la República. Este informe incluye la lista completa de los números de la revista ESPE (1), los documentos de trabajo (13) y los artículos indexados (17), publicados en el primer semestre del año 2024. De igual manera, se listan las entradas de blog publicadas (9) y los seminarios (26) desarrollados.
Studi Overhaul Aliran Beban PMT GI 150/70 kV Menggunakan Software ETAP pada Jaringan SUTT 70 kV
Authors: Siswanto Agus , Baehaqi Mudofar , Naufal Mansur
Published: November 2024

The power breaker (PMT) in the transmission system functions as a load breaker both under normal circumstances and when a disturbance occurs. In July 2021 it was discovered that there was an SF6 gas leak at (PMT) bay Arjawinangun 2 at Gi Sunyaragi. Under these conditions an overhaul was carried out which in the implementation found several sources of causes of leaks such as scale and corrosion at the joints and packing conditions that were no longer flexible. Before the implementation and after the implementation of the overhoul, tests were carried out including: contact resistance testing, insulation resistance testing and after a series of tests were carried out, then an analysis of the test results was carried out and a voltage drop simulation was carried out using the Etap 12.6 software from a series of activities, 5 simulation results were obtained and concluded that the system is still within safe limits (up 5%, down 10% from the nominal voltage). As well as other tests such as isolation resistance and contact resistance are still included in the specified standard category, so it is concluded that the PMT bay Arjawinangun 2 is in good condition and safe to operate.
MITIGASI RISIKO MANAJEMEN RANTAI PASOKAN ONCOM DI PABRIK ONCOM BU NANA CIBINONG, KABUPATEN BOGOR
Authors: Angelica Elizabeth Sinaga  , Alifa Ilmalana Al Ghifari  , Athahilda Salsabila Hidayat  , Hanni Rizky Osseani Setiawan  , Nayla Hasnah Khalisha  , Khoirul Aziz Husyairi
Published: November 2024

Manajemen risiko dalam rantai pasok produk pangan memainkan peran penting dalam menjaga kualitas dan kontinuitas produk, terutama pada produksi oncom. Penelitian ini bertujuan untuk mengidentifikasi risiko yang dihadapi dalam rantai pasok oncom serta mengusulkan strategi mitigasi yang efektif untuk mengatasi risiko tersebut. Metode yang digunakan dalam penelitian ini adalah pendekatan kualitatif dengan teknik purposive sampling, yang melibatkan partisipan kunci dari berbagai tahapan rantai pasok, mulai dari pemasok bahan baku hingga konsumen akhir. Hasil penelitian mengungkapkan bahwa risiko utama dalam rantai pasok oncom meliputi ketidakstabilan pasokan bahan baku, gangguan produksi, serta fluktuasi permintaan pasar. Untuk mengatasi risiko ini, strategi mitigasi yang diusulkan mencakup diversifikasi sumber bahan baku, peningkatan efisiensi proses produksi, serta penerapan teknologi informasi untuk memantau permintaan pasar secara real-time. Implementasi strategi ini diharapkan dapat menciptakan rantai pasok yang lebih stabil dan efisien, serta meningkatkan daya saing produk oncom di pasar.
Risk management in the food product supply chain plays an important role in maintaining product quality and continuity, especially in oncom production. This study aims to identify the risks faced in the oncom supply chain and propose effective mitigation strategies to overcome these risks. The method used in this study is a qualitative approach with a purposive sampling technique, involving key participants from various stages of the supply chain, from raw material suppliers to end consumers. The results of the study revealed that the main risks in the oncom supply chain include instability of raw material supply, production disruptions, and fluctuations in market demand. To overcome these risks, the proposed mitigation strategies include diversifying raw material sources, increasing production process efficiency, and implementing information technology to monitor market demand in real time. The implementation of this strategy is expected to create a more stable and efficient supply chain, as well as increase the competitiveness of oncom products in the market.
Does Increased Refugee Flows Lead to Rightward Political Shifts? An Empirical Analysis of European Cases Using Macro and Micro-Level Data
Authors:   United European Research Society, Kang Yoo-Duk
Published: November 2024

The study investigates the potential correlation between the rapid influx of refugees and the rise of far-right parties in European countries through domestic politicization. Two key questions are empirically addressed: first, whether increased refugee flows lead to a political shift to the right, and second, whether an individual's political orientation influences preferences for refugee policies. Specifically, the study aims to verify the prevailing notion that individuals with stronger right-wing inclinations tend to support restrictive refugee policies.
Analysis using country-level data suggests that while it is challenging to assert a direct causal link between increased refugee inflow and a rightward political shift, such a shift tends to occur when the refugee issue becomes a prominent topic of urgent debate. At the individual level, the study finds that individuals with stronger right-wing inclinations are indeed more likely to support restrictive refugee policies over inclusive ones. However, other variables such as education level, trust in government, and expectations regarding the role of government also influence policy preferences. Thus, the association between right-wing tendencies and support for restrictive refugee policies may be influenced by various contextual factors.
The implications for Korea underscore the importance of securing social conditions and policy response capabilities to effectively manage refugee acceptance. Without adequate measures, the influx of refugees could escalate into a political debate and exacerbate social conflict. By addressing these challenges, Korea can fulfill its role as a responsible member of the international community and successfully manage the refugee problem.
Anthocyanin content in fresh and long-term frozen black currant (Ribes nigrum L.) varieties bred by the Federal Horticultural Center for Breeding, Agrotechnology and Nursery
Authors: Guzeeva A. , Kapitova I. A. , Pavlov K. V. , Sazonov F. F. , Zakharychev V. V.
Published: November 2024

The article provides information on the species, composition and properties of anthocyanins, their functions in the plant and animal world, analyzed the directions and mechanism of the beneficial effect of anthocyanins on plants and the human body. The concept of the nature of chemical processes occurring with the participation of anthocyanins. The total content of anthocyanins in berry raw materials of various types of storage obtained from berries of 12 varieties of black currant of the Federal State Budgetary Scientific and Scientific Center of Horticulture was determined by pH differential spectrophotometry. Varieties with high and stable anthocyanin content have been identified for their further use in breeding. The effect of long-term freezing on the anthocyanin content was estimated. According to the results of two-year tests, the average anthocyanin content in fresh fruit was 1234.1 ± 86 ppm, in fruit stored at — 75 °C for 7 months was 1069 ± 74 ppm. The highest concentration of anthocyanins 1860 ± 130 ppm was found in fresh fruit of the Debryansk variety, the lowest 950 ± 95 ppm was in the Strelets variety. The varieties Debryansk, Favorite, Barmaley, and Myth were identified as the most valuable for use as a functional additive to food and for further use as sources of antioxidants. The effect of prolonged freezing of black currant berries made it possible to assess quantitative changes in the content of anthocyanins, as well as to identify varieties with a more stable content of product anthocyanins and draw conclusions about the storage conditions of black currant berries for more effective further use as antioxidant components.