JUCS - Journal of Universal Computer Science最新文献

An Embedded Neural Network Approach for Reinforcing Deep Learning: Advancing Hand Gesture Recognition 强化深度学习的嵌入式神经网络方法：推进手势识别

JUCS - Journal of Universal Computer Science Pub Date : 2024-07-28 DOI: 10.3897/jucs.110291

Anwar Mira, Olaf Hellwich

{"title":"An Embedded Neural Network Approach for Reinforcing Deep Learning: Advancing Hand Gesture Recognition","authors":"Anwar Mira, Olaf Hellwich","doi":"10.3897/jucs.110291","DOIUrl":"https://doi.org/10.3897/jucs.110291","url":null,"abstract":"Deep neural networks (DNNs) can face limitations during training for recognition, motivating this study to improve recognition capabilities by optimizing deep learning features for hand gesture image recognition. We propose a novel approach that enhances features from well-trained DNNs using an improved radial basis function (RBF) neural network, targeting recognition within individual gesture categories. We achieve this by clustering images with a self-organizing map (SOM) network to identify optimal centers for RBF training. Our enhanced SOM, employing the Hassanat distance metric, outperforms the traditional K-Means method across a comparative analysis of various distance functions and the expanded number of cluster centers, accurately identifying hand gestures in images. Our training pipeline learns from hand gesture videos and static images, addressing the growing need for machines to interact with gestures. Despite challenges posed by gesture videos, such as sensitivity to hand pose sequences within a single gesture category and overlapping hand poses due to the high similarities and repetitions, our pipeline achieved significant enhancement without requiring time-related training data. We also improve the recognition of static hand pose images within the same category. Our work advances DNNs by integrating deep learning features and incorporating SOM for RBF training.","PeriodicalId":124602,"journal":{"name":"JUCS - Journal of Universal Computer Science","volume":"1 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141797001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A New Performance Metric to Evaluate Filter Feature Selection Methods in Text Classification 评估文本分类中过滤器特征选择方法的新性能指标

JUCS - Journal of Universal Computer Science Pub Date : 2024-07-28 DOI: 10.3897/jucs.111675

Rasim Çekik, Mahmut Kaya

{"title":"A New Performance Metric to Evaluate Filter Feature Selection Methods in Text Classification","authors":"Rasim Çekik, Mahmut Kaya","doi":"10.3897/jucs.111675","DOIUrl":"https://doi.org/10.3897/jucs.111675","url":null,"abstract":"High dimensionality and sparsity are the primary issues in text classification. Using feature selection approaches, the most effective way to solve the problem is to select a subset of features. The most common and effective methods used for this process are filter techniques. Various performance metrics such as Micro-F1, Macro-F1, and Accuracy are used to evaluate the performance of filter methods used for feature selection on datasets Such methods work depending on a classification algorithm. However, when selecting features in filter techniques, the information on the individual features is evaluated without considering the relationship between the features. In such an approach, the actual performance of the filter technique used in feature selection may not be determined. In such a case, it causes the existing methods to be insufficient in testing the validity of the proposed method. For this purpose, this study suggests a novel performance metric called Selection Error (SE) to determine the actual performance evaluation of filter techniques. The Selection Error metric allows us to analyze the information value of the selected features more accurately than existing methods without relying on a classifier. The feature selection performance of the filtering approaches was performed on six different datasets with both The Selection Error and traditional performance metrics. When the results are examined, it is seen that there is a strong relationship between the proposed performance metric and the classification performance metric results. The Selection Error aims to significantly contribute to the literature by demonstrating the success of filtering feature selection methods, regardless of classifier performance. ","PeriodicalId":124602,"journal":{"name":"JUCS - Journal of Universal Computer Science","volume":"3 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141797124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Empirical Study on the Correctness and Effort to Integrate Feature Models 关于整合特征模型的正确性和工作量的实证研究

JUCS - Journal of Universal Computer Science Pub Date : 2024-07-28 DOI: 10.3897/jucs.94073

Vinícius Bischoff, Kleinner Farias

{"title":"An Empirical Study on the Correctness and Effort to Integrate Feature Models","authors":"Vinícius Bischoff, Kleinner Farias","doi":"10.3897/jucs.94073","DOIUrl":"https://doi.org/10.3897/jucs.94073","url":null,"abstract":"Feature model integration is pivotal in software development, particularly in evolving software product lines through new feature accommodations. Despite its significance, the influence of developers’ experience on integration efforts and correctness still needs to be more adequately understood. This study conducted a controlled experiment with 25 participants (18 students and seven professionals) following well-known guidelines to run empirical studies. Each participant addressed ten experimental tasks, encompassing 250 integration scenarios, to explore two research questions. The effort and correctness rate in integrating feature models were quantified, revealing that students exerted higher effort (29.23%) and achieved a higher number of correct integrations (39.53%) than professionals. Notably, this superiority lacked statistical significance. Additionally, this article highlights practical implications and noteworthy challenges for the scientific community, providing valuable insights for software development practices. The findings lay a foundation for future studies, delving into software development tasks where students and professionals may achieve comparable results. Finally, this study marks an initial step towards an ambitious agenda, empirically advancing the feature model integration field.","PeriodicalId":124602,"journal":{"name":"JUCS - Journal of Universal Computer Science","volume":"6 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141796458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

LESCA: Scaffolding and its impact on the higher cognitive levels and emotions of the student LESCA：支架及其对学生较高认知水平和情感的影响

JUCS - Journal of Universal Computer Science Pub Date : 2024-07-28 DOI: 10.3897/jucs.110173

D. Alulema, Maximiliano Paredes-Velasco, Ricardo de Arriba Lasso

{"title":"LESCA: Scaffolding and its impact on the higher cognitive levels and emotions of the student","authors":"D. Alulema, Maximiliano Paredes-Velasco, Ricardo de Arriba Lasso","doi":"10.3897/jucs.110173","DOIUrl":"https://doi.org/10.3897/jucs.110173","url":null,"abstract":"Teaching technical content in science and engineering requires the development of high-level competencies such as analytical and critical thinking skills, and is perceived by students as a difficult subject to understand. One way to help students learn this type of content is through the use of scaffolding, which dynamically regulates and adjusts learning according to the student’s needs. Although the use of scaffolding has already been applied in different educational contexts, so far there are no studies analysing its impact on students’ emotions and perception. In this paper we propose the LESCA system, which performs adaptive content feedback through scaffolding. The main hypothesis of this article is that the use of this tool together with teacher scaffolding improves the acquisition of content at higher cognitive levels and improves the student’s emotional state during learning. An experience has been carried out with 36 students of Industrial Electronics and Robotics Associate Degree with a pre-post design, where one group of students did not use the tool and another one did. The findings indicate that knowledge acquisition at the higher levels of Bloom’s taxonomy improved after the use of technological scaffolding and that this acquisition improved significantly when incorporating teacher scaffolding. On the other hand, students who performed the tasks with the system experienced significantly less anxiety and despair than students who did not use it. In addition, it has been found that students perceive teacher scaffolding to be significantly more useful than technological scaffolding.","PeriodicalId":124602,"journal":{"name":"JUCS - Journal of Universal Computer Science","volume":"1 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141796719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Hybrid Study for Epileptic Seizure Detection Based on Deep Learning using EEG Data 基于深度学习的脑电图数据癫痫发作检测混合研究

JUCS - Journal of Universal Computer Science Pub Date : 2024-07-28 DOI: 10.3897/jucs.109933

Abdulkadir Buldu, Kaplan Kaplan, Melih Kuncan

{"title":"A Hybrid Study for Epileptic Seizure Detection Based on Deep Learning using EEG Data","authors":"Abdulkadir Buldu, Kaplan Kaplan, Melih Kuncan","doi":"10.3897/jucs.109933","DOIUrl":"https://doi.org/10.3897/jucs.109933","url":null,"abstract":"Epilepsy, a neurological disease characterized by recurrent seizures, can be diagnosed using Electroencephalogram (EEG) signals. Traditional diagnostic methods often face limitations, leading to delays and potential misdiagnoses. In response, researchers have been developing low-cost assistive systems to enhance diagnostic accuracy and reduce life-threatening risks for epilepsy patients. In this study, a hybrid approach is proposed to diagnose epilepsy disease. To validate the success of the proposed algorithm, Hauz Khas and Bonn data sets were used. AlexNet, GoogleNet, VGG19, ResNet50, and ResNet101 classifiers were employed in this study along with the Continuous Wavelet Transform (CWT) and Short Time Fourier Transform (STFT). To increase the generalization capability, 10-fold cross-validation method was used in the classification process. Firstly, the preictal and ictal moments in the Hauz Khas dataset was classified with 99.5% success rate by CWT method and Resnet101. Similarly, 99.8% accuracy was achieved in the binary classification of the Bonn dataset using the CWT method with Resnet101. Finally, for the classification with the AB-CD-E group, 99.33% classification success rate was achieved by using the CWT method with the Resnet-101 model. These findings underscore the potential of the proposed assistive system to significantly improve the diagnosis and management of epilepsy, demonstrating high accuracy and reliability across different datasets and classification techniques. ","PeriodicalId":124602,"journal":{"name":"JUCS - Journal of Universal Computer Science","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141796797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

JUCS - Journal of Universal Computer Science Pub Date : 2024-04-28 DOI: 10.3897/jucs.103011

Shahrzad Riahi, R. Khosravi, F. Ghassemi

{"title":"Knowledge-Related Policy Analysis in an Inference-Enabled Actor Model","authors":"Shahrzad Riahi, R. Khosravi, F. Ghassemi","doi":"10.3897/jucs.103011","DOIUrl":"https://doi.org/10.3897/jucs.103011","url":null,"abstract":"People provide their information to distributed systems to receive the desired services. This information may be disclosed to the agents of the system as part of messages transmitted among them. As the agents of the system are smart, they can infer new information from their obtained information, that they may not be authorized to know. So preserving privacy in such systems is an important and yet challenging issue. We study the problem of analyzing the disclosure of private information in distributed asynchronous systems. Our approach to prevent private information disclosure is to require the system to follow knowledge-related policies defined for the system at design time. To achieve this, we construct a model of the system and assume the policies as the system properties and check whether these properties are satisfied in the system or not. In order to construct a model of the system, we extend the actor model, which is a well known reference model for distributed asynchronous systems, by enriching actors by the knowledge base and inference capability. As our knowledge-related policies should not be violated in any state of the system, we propose an efficient invariant model checking algorithm to verify the satisfaction of the policies in our actor model.","PeriodicalId":124602,"journal":{"name":"JUCS - Journal of Universal Computer Science","volume":"52 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140652139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mapping and Integrating Security and Risk Standards: a Systematic Literature Review 绘制和整合安全与风险标准：系统文献综述

JUCS - Journal of Universal Computer Science Pub Date : 2024-04-28 DOI: 10.3897/jucs.111677

André Fernandes, João Cruz, Miguel Mira da Silva, Rúben Pereira

{"title":"Mapping and Integrating Security and Risk Standards: a Systematic Literature Review","authors":"André Fernandes, João Cruz, Miguel Mira da Silva, Rúben Pereira","doi":"10.3897/jucs.111677","DOIUrl":"https://doi.org/10.3897/jucs.111677","url":null,"abstract":"Organizations are under increasing pressure to comply with various rules, standards, and policies in today’s regulatory environment. Compliance controls are put in place to avoid legal or regulatory violations, which could lead to severe penalties, loss of reputation, and financial damages. However, these controls may have similar scopes and objectives, resulting in duplicated work and unnecessary costs for the organizations. To address this issue, researchers carry out the mapping and integration of these standards to avoid duplication, streamline compliance efforts, and identify best practices. Our work aims to improve the State-of-the-Art by exploring the main benefits and problems resulting from these processes, as well as identifying methods or artifacts that can be reused in the future. We focus on the fields of Risk, Security, and Business Continuity, as these are critical areas where compliance is crucial for organizations. Through our research, we have found that current methods of generating mapping artifacts are not only cumbersome to execute but also ineffective, as they output a single artifact without the reasoning behind it.","PeriodicalId":124602,"journal":{"name":"JUCS - Journal of Universal Computer Science","volume":"54 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140652032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

UP-Home: A Self-Adaptive Solution for Smart Home Security UP-Home：智能家居安全的自适应解决方案

JUCS - Journal of Universal Computer Science Pub Date : 2024-04-28 DOI: 10.3897/jucs.107050

Josival Silva, Nelson Rosa, Fernando Aires

{"title":"UP-Home: A Self-Adaptive Solution for Smart Home Security","authors":"Josival Silva, Nelson Rosa, Fernando Aires","doi":"10.3897/jucs.107050","DOIUrl":"https://doi.org/10.3897/jucs.107050","url":null,"abstract":"Smart home devices are vulnerable to attacks that put their users’ security at risk. Vulnerabilities are discovered very frequently and can expose these devices through unsecured services. Meanwhile, the lack of standardisation in upgrade methods makes smart homes a potentially vulnerable environment. Furthermore, many manufacturers release their products and then abandon them, refusing to support security updates. As a result, security updates are needed to deal with the emergence of new attacks. There are several proposals to promote security in smart homes. However, there are rare solutions where changes for security purposes occur with little or no human intervention. This paper presents UP-Home, a self-adaptive solution that manages the security of smart homes. UP-Home aims to ensure that smart home devices meet the security requirements set by industry standards. The solution can continually identify and mitigate smart home security vulnerabilities. With autonomous computing techniques, UP-Home seeks to ensure the self-protection of devices and, consequently, the entire smart home. With the UP-Home evalu-ation, it was possible to notice significant improvements in the security of the smart home without any human intervention.","PeriodicalId":124602,"journal":{"name":"JUCS - Journal of Universal Computer Science","volume":"52 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140652138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Reactive Traffic Congestion Control by Using a Hierarchical Graph 利用层次图进行反应式交通拥堵控制

JUCS - Journal of Universal Computer Science Pub Date : 2024-04-28 DOI: 10.3897/jucs.111879

Sahar Idwan, J. Zubairi, Syed Ali Haider, W. Etaiwi

引用次数: 0

Multi-Class Microscopic Image Analysis of Protozoan Parasites Using Convolutional Neural Network 利用卷积神经网络对原生动物寄生虫进行多级显微图像分析

JUCS - Journal of Universal Computer Science Pub Date : 2024-04-28 DOI: 10.3897/jucs.112639

S. Elayaraja, Sunil Yeruva, V. Stejskal, Satish Nandipati

{"title":"Multi-Class Microscopic Image Analysis of Protozoan Parasites Using Convolutional Neural Network","authors":"S. Elayaraja, Sunil Yeruva, V. Stejskal, Satish Nandipati","doi":"10.3897/jucs.112639","DOIUrl":"https://doi.org/10.3897/jucs.112639","url":null,"abstract":"Protozoan parasites cause a wide range of devastating diseases in various kinds of organisms, including humans. It may be lethal if untreated promptly. To detect specific disease-causingorganisms parasites, a wide range of immunological and molecular technologies are now widely available. However, all of this depends on the worker's expertise and are time-consuming, error-prone, and expensive. With the development of technology, compared to traditional biological techniques, convolutional neural networks have reached excellent achievements in image classification, cutting costs while attaining an overall higher accuracy and eliminating human error. Many models include numerous convolutional layers and offer an accuracy between 90 and 95 percent. In this study, 4740 microscopic images of protozoan parasites from six classes with a balanced dataset and an 80–20% split were classified using three convolutional layers with stochastic gradient descent as an optimizer. A 5-fold cross-validation approach is used to evaluate the proposed method. We also examine and evaluate with deep learning models namely VGG16, ResNet50, and InceptionV3. The performance evaluation of the proposed model shows an accuracy of 94% with a precision range (of 0.83-0.99) and a recall range (of 0.76-1.00), respectively. The retrained model was able to recognize and classify all 6 different parasites. Except for class Leishmania, where 24% of images are incorrectly classified as Plasmodium and Trichomonas, the model demonstrates that most cases are correctly identified.","PeriodicalId":124602,"journal":{"name":"JUCS - Journal of Universal Computer Science","volume":"52 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140652140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0