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Design of Cluster-Computing Architecture to Improve Training Speed of the Neuroevolution Algorithm 9th

Design of Cluster-Computing Architecture to Improve Training...

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9th International Congress on Information and Communication Technology (ICICT)

作者： Omelianenko, Iaroslav Inst Software Syst Kiev Ukraine

ISBN: (纸本)9789819735556;9789819735563

In this paper, we review the key features and major drawbacks of the NeuroEvolution of Augmenting Topologies (NEAT) algorithm, such as slow training speed that limits its area of application. The main reason for the performance issues of the NEAT algorithm is the huge number of calculations required at the end of each epoch to estimate the fitness of each organism in the population. We propose a software system architecture that can be implemented to solve NEAT performance problems based on Ray cluster-computing framework. Finally, we demonstrate how fitness estimation computations can be distributed across stateless distributed workers deployed either on-premise or in the cloud using Ray framework.

关键词： Genetic algorithms NeuroEvolution of Augmenting Topologies Ray framework Distributed computing Cluster computing Cloud computing

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Performance Evaluation and Comparative Analysis of Machine Learning Techniques to Predict the Chronic Kidney Disease

Performance Evaluation and Comparative Analysis of Machine L...

引用

International Conference on Artificial Intelligence: Theory and Applications (AITA)

作者： Malik, Majid Bashir Ali, Mohd Bashir, Sadiya Ganie, Shahid Mohammad Baba Ghulam Shah Badshah Univ Dept Comp Sci Rajouri 185234 India Woxsen Univ AI Res Ctr Sch Business Hyderabad 502345 India

ISBN: (纸本)9789819984787;9789819984794

Chronic kidney disease is one of the most fatal diseases affecting people worldwide. As a result, it is critical to forecast and identify this illness as early as possible, enabling medical professionals and patients to take the necessary and appropriate steps. In this paper, we propose a framework using machine learning techniques including logistic regression (LR), naive Bayes (NB), support vector machine (SVM), and decision tree (DT) for better prediction of chronic kidney disease. A publicly available dataset containing 25 parameters and 400 records of patients was employed. We conducted a thorough exploratory data analysis to improve the quality assessment of dataset. The DT method outperformed the other three algorithms by achieving the highest training and testing accuracy rate as 100% and 99.16%, respectively. To validate the model, other performance evaluation metrics were calculated. The model has provided a better predicted outcome when compared to similar research studies. Our proposed model can be used in the healthcare industry for better decision making regarding chronic kidney disease.

关键词： Chronic kidney disease Exploratory data analysis Machine learning Decision tree Support vector machine Naive Bayes Logistic regression

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Audio Streaming and Multimedia Communication with Bluetooth Low Energy 20th

Audio Streaming and Multimedia Communication with Bluetooth ...

引用

20th International Workshop on Combinatorial Image Analysis (IWCIA)

作者： Aslantas, Recep Toptas, Faruk Gumuskaynak, Enes Celik, Tunahan Balki, Fatih Ozen, Yunus Sarp, Salih Hisar Saglik Res Ctr Istanbul Turkiye Yalova Univ Fac Engn Dept Comp Engn Yalova Turkiye Virginia Commonwealth Univ Richmond VA 23284 USA

ISBN: (纸本)9783031665936;9783031665943

The primary objective of this study is to develop a real-time audio transmission and multimedia messaging platform that can operate between mobile devices, utilizing smartphones or devices equipped with Bluetooth Low Energy (BLE) connectivity, all without necessitating internet access. In pursuit of this goal, the study delved into the examination of the BLE application programming interfaces designed for smartphones, with the aim of establishing a well-suited architecture for real-time audio transmission. The study also meticulously scrutinized the challenges encountered during the audio data transmission process and implemented potential solutions to address them. As part of the investigation, the study involved a comparison of various codec alternatives designed to compress audio data, with the Opus codec emerging as the preferred choice. Ultimately, the study successfully achieved real-time audio transmission between mobile devices via BLE and meticulously recorded and analyzed the obtained results.

关键词： Bluetooth BLE audio voice communication

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Criteria Prioritization for Data Maturity Assessment Problem Using Continuous Intuitionistic Fuzzy Analytic Hierarchy Process 1

引用

International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Demir, Zeynep Burcu Kizilkan Oztaysi, Basar Istanbul Tech Univ Dept Ind Engn Istanbul Turkiye

ISBN: (数字)9783031700187

ISBN: (纸本)9783031700170;9783031700187

With recent developments in data processing and analysis, the concept of data maturity has gained substantial significance. Data maturity is the refinement of an organization's ability to harness, interpret, and influence data effectively for decision-making. The data maturity of an organization provides a meaningful insight into the company's capabilities for data practices over time. A mature data environment can be determined by an organization's standing in data management, data processing, data infrastructure, data security, and the allocation of human resources in a data-driven environment. The presence of these matters at various levels exposes a need for improvement to enhance the organization's ability to derive meaningful outputs. Organizations with a mature data environment adapt better to market changes, identify emerging trends, and capitalize on new opportunities. By employing frameworks, organizations can systematically assess their data maturity levels and identify areas for improvement. This study determines the criteria of data maturity assessment model and develops a hierarchical framework to analyze some organizations from different sectors using Continuous Intuitionistic Fuzzy Sets (CINFUS).

关键词： data maturity analytic hierarchy process fuzzy sets continuous intuitionistic fuzzy sets

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From Technology Adaptation to Technology Adoption: An Insight into Public Islamic School Administrative Management 1

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9th International Congress on Information and Communication Technology (ICICT)

作者： Huda, Miftachul Rohim, Moh Abdul Bin Hehsan, Aminudin Qodriah, Sari Laelatul Junaidi, Juhazren Haron, Zulkiflee Yusof, Farahwahida Mohd Abu Hussin, Mohd Fauzi Abas, Hafiza Univ Pendidikan Sultan Idris Fac Human Sci Tanjong Malim 35900 Malaysia Univ Teknol Malaysia UTM Ctr Res Fiqh Sci & Technol CFiRST Ibnu Sina Inst Sci & Ind Res ISI ISIR Skudai 81310 Malaysia Univ Muhammadiyah Cirebon Cirebon 45153 Jawa Barat Indonesia

ISBN: (数字)9789819733057

ISBN: (纸本)9789819733040;9789819733057

The current trends of technology advancement offered with such features have given a substantive support to the human development including social life interaction, business, and education sectors. It is especially in the government sector that technology development is currently being the trending topic since the gradual shift paradigm comes to adapt such distinctive structures in order to reach beneficial value. Thus, this paper aims to investigate the technology adaptation followed by its adoption in giving a critical insight into helping to run the administrative management of public school. The literature analysis was made by reviewing the current works related to the technology adaption and its adoption in contributing to the public school administrative management. The finding of this study found that the significant features of advanced technology enhancement provide a sustainable contribution in playing the role on helping to systematize the administration procedure and process in a good flow and proper way in line with the original objective of organization. Thus, this study is supposed to contribute in giving the particular insight on developing the framework on looking at the clear point about the technology adaption and adoption on public school administrative management.

关键词： Technology adaptation Technology adoption Information and communication technology (ICT) Administrative management Public school institution

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Performance Evaluation of Whale and Harris Hawks Optimization Algorithms with Intrusion Prevention systems 6th

Performance Evaluation of Whale and Harris Hawks Optimizatio...

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6th International Conference on Soft Computing and Data Mining (SCDM)

作者： Abualhaj, Mosleh M. Abu-Shareha, Ahmad Adel Al-Allawee, Ali Munther, Alhamza Anbar, Mohammed Al Ahliyya Amman Univ Dept Networks & Cybersecur Amman 19328 Jordan Al Ahliyya Amman Univ Dept Data Sci & Artificial Intelligence Amman 19328 Jordan Univ Haute Alsace IRIMAS Lab F-68000 Colmar France Univ Technol & Appl Sci Sur 411 Muscat Oman Univ Sains Malaysia Natl Adv Ctr IPv6 Gelugor 11700 Penang Malaysia

ISBN: (纸本)9783031669644;9783031669651

Intrusion Prevention systems (IPS) protect computer networks from hostile activities. This study investigates the effectiveness of two optimization algorithms, Hawks Optimization (HHO) and Whale Optimization Algorithm (WOA), in selecting features to improve the performance of Intrusion Prevention systems (IPS). The NSL-KDD dataset is employed as a standard to assess the influence of specific features on classification accuracy. The study uses the K-nearest neighbors (KNN) classification algorithm to assess the efficacy of feature selection techniques. The implementation is carried out using Python, using its flexible libraries and frameworks. Comparative investigation shows that when combining the chosen features, KNN achieves better outcomes than using the whole dataset of features. The results demonstrate that the combination of KNN with WOA provides a remarkable accuracy rate of 97.42%, highlighting the effectiveness of WOA in improving IPS performance. On the other hand, the combination of KNN and HHO demonstrates an impressive accuracy rate of 96.87%.

关键词： WOA HHO KNN IPS NSL-KDD

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Computer Vision for Analyzing Children's Lived Experiences

Computer Vision for Analyzing Children's Lived Experiences

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Intelligent systems Conference (IntelliSys)

作者： Zahra, Anam Martin, Pierre-Etienne Bohn, Manuel Haun, Daniel Max Planck Inst Evolutionary Anthropol CCP Dept D-04103 Leipzig Germany

ISBN: (纸本)9783031477232;9783031477249

Children's social and physical environment plays a significant role in their cognitive development. Therefore, children's lived experiences are important to developmental psychologists. The traditional way of studying everyday experiences has become a bottleneck because it relies on short recordings and manual coding. Designing a non-invasive child-friendly recording setup and automating the coding process can potentially improve the research standards by allowing researchers to study longer and more diverse aspects of experience. We leverage modern computer vision tools and techniques to address this problem. We present a simple and non-invasive video recording setup and collect egocentric data from children. We test the state-of-the-art object detectors and observe that egocentric videos from children are a challenging problem, indicated by the low mean Average Precision of state-of-the-art. The performance of these object detectors can be improved through fine-tuning. Once accurate object detection has been achieved, other questions, such as human-object interaction and scene understanding, can be answered. Developing an automatic processing pipeline may provide an important tool for developmental psychologists to study variation in everyday experience.

关键词： Egocentric computer vision Cognitive development Object detection

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Emotion Detection from Real-Life Situations Based on Journal Entries Using Machine Learning and Deep Learning Techniques

Emotion Detection from Real-Life Situations Based on Journal...

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Intelligent systems Conference (IntelliSys)

作者： Oyebode, Oladapo Ogubuike, Ruth Daniel, Darlington Orji, Rita Dalhousie Univ Fac Comp Sci Halifax NS B3H IW5 Canada

ISBN: (纸本)9783031477232;9783031477249

Emotion regulation is crucial for psychological well-being. Negative emotions such as anger, fear, and sadness have been shown to create unhealthy patterns of physiological functioning and reduce human resilience and quality of life. Positive emotions (e.g., happiness), however, improve physical and mental health. Therefore, our goal is to: (1) build emotion detection models trained on a dataset that captures people's real-life situations and experiences using machine learning (ML) and deep learning techniques, and then (2) design and develop an emotion-adaptive and persuasive mobile health (mHealth) application that delivers interventions for coping with challenging life events, promote positive emotions, and motivate behaviour change for improved mental health and well-being. Currentwork is focused on the first goal inwhich we trained and evaluated twenty-one classical ML, ensemble learning, and deep learning models to determine their capability in detecting five popular emotional states: anger, fear, disgust, happiness, and sadness from journal entries. The overall best performing model is MCBiLSTM (F1-score = 81.1%), a multichannel fusion model comprising three Convolutional Neural Network (CNN) channels and a Bidirectional Long Short-Term Memory (BiLSTM) recurrent neural network. Future work will integrate the model into our proposed mHealth application (second goal) to tailor therapeutic interventions based on individuals' current emotional state in real-time.

关键词： Emotion Detection Emotional States Journaling Journal Entries Diary Entries Machine Learning Deep Learning Natural Language Processing Mental Health Health Well-Being

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Machine Learning-Based Image Forgery Detection Using Light Gradient-Boosting Machine 4th

Machine Learning-Based Image Forgery Detection Using Light G...

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4th Congress on Intelligent systems (CIS)

作者： Ugale, Meena Midhunchakkaravarthy, J. Lincoln Univ Coll Petaling Jaya Selangor Malaysia

ISBN: (纸本)9789819990368;9789819990375

In recent days, due to the increasing development of digital automation, images have emerged as a significant way to interact as well as transfer messages in our community, and there was a high rise in the number of details transferred in the formation of virtual pictures in the day-to-day life especially with the disclosure of online medias such as Instagram, Twitter, and Facebook. Moreover, uploading pictures on social media and modifying those images with related software apps is considered a common method to do in current days. Even though, if every person does not perform with ominous meanings, but still, there is a noticeable rise in misconduct regarding the malignant image influence as well as updating. This research proposes an image/video forgery identification method by utilizing the light gradient boosting machine (Light-GBM) method to detect the fabrication in the visual data with an increased rate of accuracy. The performance, as well as comparative analysis, is estimated based on the performance metrics such as accuracy at 94.91%, sensitivity at 94.77%, and specificity at 93.26%, respectively, which is superior to the previous techniques.

关键词： Block-wise feature extraction Feature extraction Forgery detection Light gradient boosting machine Machine learning

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Software Testing in Ecuadorian University Education: A Debt to the Software Industry 12th

Software Testing in Ecuadorian University Education: A Debt ...

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12th World Conference on Information systems and Technologies (WorldCIST)

作者： Ceron, Belen Chicaiza, Alex Lamino, Johana Reyes Ch, Rolando P. Univ Politecn Madrid Campus Montegancedo Madrid Spain Univ Las Fuerzas Armadas ESPE Sangolqui 171103 Ecuador Univ Int La Rioja Madrid Spain

ISBN: (纸本)9783031602238;9783031602245

The software industry has evolved exponentially in the last 50 years, andwith it, software testing has become like a badge of software quality. However, during this evolution universities apparently have not kept pace with the changing and dynamic pace of the software industry. We have been motivated to carry out an exploratory study to analyze the current state of teaching software testing in careers related to Computer Science in Ecuadorian universities. We use a survey as an empirical strategy with a representative population of students in the country. The results are interesting and indicate possible problems in the teaching and culture of use of software testing. Consequently, this deficiency in the correct application of software testing by students is taken to the professional field and therefore to a high-growth industry. It is concluded that software testing in Ecuadorian university education still has deficiencies, making this a debt to be fulfilled by the software industry in Ecuador.

关键词： Software engineering software testing software development automated tools survey

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