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International Conference of Advanced informatics: Concept, Theory and Application (ICAICTA)

作者： Akeyla Pradia Naufal Dessi Puji Lestari Ayu Purwarianti Kurniawati Azizah Dipta Tanaya Sakriani Sakti School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia Faculty of Computer Science University of Indonesia Depok Indonesia Graduate School of Information Science Nara Institute of Science and Technology Nara Japan

ISBN: (数字)9798331520311

ISBN: (纸本)9798331520328

Developing natural speech recognition and speech synthesis systems requires speech data that authentically represents real emotions. However, this type of data is often challenging to obtain. Machine speech chain offers a solution to this challenge by using unpaired data to continue training models initially trained with paired data. Given the relative abundance of unpaired data compared to paired data, machine speech chain can be instrumental in recognizing emotions in speech where training data is limited. This study investigates the application of machine speech chain in speech emotion recognition and speech recognition of emotional speech. Our findings indicate that a model trained with 50% paired neutral emotion speech data and 22% paired non-neutral emotional speech data shows a reduction in Character Error Rate (CER) from 37.55% to 34.52% when further trained with unpaired neutral emotion speech data. The CER further decreases to 33.75% when additionally trained with combined unpaired speech data. The accuracy of recognizing non-neutral emotions ranged from 2.18% to 53.51 %, though the F1 score fluctuated, increasing by up to 20.6% and decreasing by up to 23.4%. These results suggest that the model demonstrates a bias towards the majority class, as reflected by the values of the two metrics.

关键词： Training Emotion recognition Accuracy Error analysis Natural languages Training data Speech recognition Speech enhancement Data models Speech synthesis

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Towards Swarm Intelligence Ontology for Formal Description of Metaheuristics Algorithms 4

Towards Swarm Intelligence Ontology for Formal Description o...

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4th International Conference on Computing, Networking, Telecommunications and engineering sciences Applications, CoNTESA 2023

作者： Tulicic, Domagoj Horvat, Marko Lovrencic, Sandra University of Applied Science in Information Technology Department of Computer System and Networks Zagreb Croatia University of Zagreb Faculty of Electrical Engineering and Computing Department of Applied Computing Zagreb Croatia University of Zagreb Faculty of Organization and Informatics Foundations of Information Sciences Department of Theoretical and Applied Varaždin Croatia

ISBN: (纸本)9798350382754

Swarm intelligence is a class of nature-inspired metaheuristic algorithms, that is specifically derived from biological systems in nature with an emphasis on their social interactions. These algorithms have been primarily developed to solve complex combinatorial optimization problems and are extremely popular among researchers in metaheuristic algorithms. This is evident from the numerous published scientific papers describing algorithms inspired by biological systems, ranging from insects such as ants and bees to the largest animals on the planet like whales. All these algorithms share some common concepts and relationships that can be explicitly identified, named, and formalized. These shared concepts and relationships can be organized and represented through the construction of an ontology. The goal of this paper is to present a formal ontology that standardizes vocabulary, as well as a set of rules enabling precise communication and reasoning about these algorithms. Ultimately, this will improve our understanding, analysis, research processes, and utilization of these computational approaches. © 2023 IEEE.

关键词： Swarm intelligence

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Performance Improvement of 3D-CNN for Blink Types Classification by Data Augmentation

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, Information and Systems 2024年第4期144卷 328-329页

作者： Sato, Hironobu Abe, Kiyohiko Matsuno, Shogo Ohyama, Minoru College of Science and Engineering Kanto Gakuin University 1-50-1 Mutsuura-higashi Kanazawa-ku Kanagawa Yokohama236-8501 Japan School of System Design and Technology Tokyo Denki University 5 Senju Asahi-cho Adachi-ku Tokyo120-8551 Japan Faculty of Informatics Gunma University 4-2 Aramaki-machi Maebashi Gunma371-8510 Japan

When developing a blink input interface, conscious (voluntary) and natural (involuntary) blink types must be automatically classified. We previously proposed a method for blink type classification using a 3D convolutional neural network (3D CNN). This CNN model outputs a predicted probability that determines three classes: "voluntary blinking," "involuntary blinking," and "not blinking" from a periocular image sequence. Previously, we found that the bias of the eye position in the input image is a factor that reduces the classification accuracy. To address this problem, we employ data augmentation with a shifting 5 or 10 pixels in the horizontal and/or vertical directions. © 2024 The Institute of Electrical Engineers of Japan.

关键词： Convolutional neural networks

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Experimentation of Integrating Roadmapping and Sci-Fi Prototyping Methods

Experimentation of Integrating Roadmapping and Sci-Fi Protot...

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2024 Portland International Conference on Management of engineering and technology, PICMET 2024

作者： Nishinaka, Miwa Shirahada, Kunio Kishita, Yusuke Miyamoto, Dohjin Osawa, Hirotaka Kiyokawa, Sachiko Takeda, Hideaki The Graduate School of Management Kagawa University Kagawa Takamatsu Japan Ishikawa Nomi Japan The University of Tokyo Department of Precision Engineering Tokyo Japan Communication in Science and Technology Education and Research Program Hokkaido University Sapporo Japan Keio University Faculty of Science and Technology Kanagawa Yokohama Japan Graduate School of Education The University of Tokyo Tokyo Japan National Institute of Informatics Tokyo Japan

ISBN: (纸本)9781890843458

In 2023, we proposed a hypothetical knowledge management framework that incorporates science fiction prototyping (SFP) into the traditional roadmapping (RM) method to make RM more innovative and create a future beyond what we can currently imagine. Our main objective is to create a new organizational knowledge co-creation method for generating innovative ideas by incorporating humanistic factors utilizing SFP into RM. In the current article, we present the exploratory study we conducted to examine the hypothetical framework. Experimental workshops were held in November 2023 to compare the integrated method, in which SFP is applied to RM, with the original RM method. We followed a crossover design in the workshops and analyzed the results qualitatively and quantitatively following the perspectives proposed in the hypothetical framework. The qualitative analysis revealed successful integration regarding diverse and broader perspectives. The quantitative analysis utilizing Wilcoxon signed rank tests showed that the scores of the integrated method were significantly higher than those of RM for variables evaluating the effectiveness of the integration, while not for variables related to participants' feelings and satisfaction with the workshops, and sustainability. These findings indicate that the integration was successful in terms of its effectiveness as a method, while participants' subjective feelings toward the workshops were not different in both methods. As for sustainability, which requires a long-term perspective, no apparent differences were observed in these short-term workshops. © 2024 PICMET.

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Development of Automotive-mobility Training in the TRIREME project

Development of Automotive-mobility Training in the TRIREME p...

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International Symposium for Design and technology of Electronics Packages (SIITME)

作者： Bálint Medgyes Csaba Farkas Marek Spanyik Stefano Danieli Elena Cantiani Jakub Stolfa Department of Electronics Technology Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Budapest Hungary Department of Computer Science Faculty of Electrical Engineering and Computer Science VSB - Technical University of Ostrava Ostrava Czechia Mylia – Adecco Formazione Milan Italy

ISBN: (数字)9798331539511

ISBN: (纸本)9798331539528

To achieve climate neutrality by 2050, the consistent transformation of the mobility sector is one of the most important pillars of the European Green deal. As a result of green and sustainable approaches, novel automotive concepts and massive digitalisation in the mobility ecosystem is undergoing a continuous development towards eco-friendly solutions and novel business models, and the changing landscape of automotive industry comes with a significant social impact as well. The overall horizontal collaboration on skills agenda in the Automotive-Mobility Ecosystem is assured throughout the Automotive Skills Alliance (ASA) [1], which is the Large-scale Pact for Skills Partnership. The latest strategic project of the partnership to support its activities is the Digital & Green Skills Towards Future of the Mobility Ecosystem (TRIREME) which promotes a collaboration between industry stakeholders and training providers including Vocational education Trainings (VETs), Higher Educations (HEs) and universities), moreover, also emphasizing the widespread public representation of different project segments and evaluating the social impacts and regional impact of the changes in the Automotive-Mobility Ecosystem. In parallel to the development of sectoral skills strategy, our department (Department of Electronics technology - ETT) is contributing to deliver specific training materials and courses within Work Package 4 (WP4), which is based on the gathered and processed intelligence from previous desk research, survey activity and participation in professional events. The methodology of course development relies on the concept of modularity, our professional competences in the field of Automotive-mobility, and the fulfillment of requirements to cover the needed skills, the competence and the occupational profile subsets.

关键词： Training Industries Surveys Ecosystems Green products Collaboration Tutorials Stakeholders Automotive engineering Meteorology

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Mining Intelligence Hierarchical Feature for Malware Detection 15th

Mining Intelligence Hierarchical Feature for Malware Detecti...

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15th International Conference on Intelligent Computing and Networking, IC-ICN 2024

作者： Davuluri, Sandeep Kumar Soni, Mukesh ALMahadin, Ghayth Rivera, Richard Upadhyay, Jinal Patel, Pavan Department of Information Technology University of the Cumberlands Williamsburg United States Dr. D. Y. Patil Vidyapeeth Dr. D. Y. Patil School of Science & Technology Tathawade Pune India Faculty of Information Technology Al Ahliyya Amman University Amman Jordan Department of Informatics and Computer Science Escuela Politécnica Nacional Quito Ecuador HasmukhGoswami College of Engineering Gujarat Vahelal India Ahmedabad Institute of Technology Gujarat Ahmedabad India

ISBN: (纸本)9789819786305

In recent years, a new strain of malware, known as mining malware, has emerged, resulting in significant losses for its victims due to its encryption techniques. This research proposes an innovative approach to detect mining malware by integrating hierarchical threat intelligence features, focusing on the static attributes of mining malware. From the perspective of mining malware threat intelligence, we train classifiers using distinct layers of features, including byte-level features, Portable Executable (PE) structure features, and mining operation execution features. By leveraging diverse malicious software attributes for detection preferences, we develop a comprehensive mining malware detector based on a hierarchical feature integration methodology. To evaluate our approach, we conducted experiments in both controlled lab settings and real-world datasets. The results indicate that our hierarchical feature-integrated mining malware detection method achieves an impressive accuracy rate of 97.01% on the simulated real-world dataset, demonstrating a substantial 6.13% accuracy improvement compared to the baseline mining malware detection method. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Adversarial machine learning

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Label Estimation of Data Using the Modified Fisher Criterion

Label Estimation of Data Using the Modified Fisher Criterion

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2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022

作者： Motoki, Ryuhei Jin'no, Kenya Tokyo City University Informatics Graduate School of Integrative Science and Engineering Tokyo Japan Tokyo City University Faculty of Information Technology Department of Intelligent System Tokyo Japan

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

In supervised learning, the amount of work required to assign labels to data becomes enormous as the input data increases. To reduce this work, we propose a method for label estimation using only a small amount of labeled data. The SVM separation hyperplane is moved by iterating label assignment and classification, and the results are evaluated using a new cluster evaluation criterion. This criterion is based on the Fisher criterion used for linearly separable data and applied to nonlinear data. Some semi-supervised learning methods, which are related to the proposed method, are also explained. We show that the proposed method is effective for linearly inseparable data through experiments. In addition, we compared the performance of the proposed method with some semi-supervised learning methods. The contributions of this study are the classification of data in situations where labeled data is scarce and the development of new criteria for evaluating non-linear classification results. © 2022 IEEE.

关键词： Support vector machines

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Image Recognition Imitating Saccadic Eye Movement in Grid Cell Net 13

Image Recognition Imitating Saccadic Eye Movement in Grid Ce...

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Joint 13th International Conference on Soft Computing and Intelligent Systems and 25th International Symposium on Advanced Intelligent Systems, SCIS and ISIS 2024

作者： Matsuda, Yuichi Niwa, Kazuma Aoki, Takeru Takadama, Keiki Sato, Hiroyuki Graduate School of Informatics and Engineering The University of Electro-Communications 1-5-1 Chofugaoka Chofu Tokyo182-8585 Japan Tokyo University of Science Faculty of Engineering 6-3-1 Niijuku Katsushika-ku Tokyo125-8585 Japan Graduate School of Information Science and Technology The University of Tokyo 6-2-3 Kashiwanoha Kashiwa-shi Chiba277-0882 Japan

ISBN: (纸本)9798350373332

This paper proposes an autonomous focal location transition method that imitates saccadic eye movement for image recognition. Grid Cell Net (GCN) is an image recognition algorithm inspired by the human neocortex. GCN focuses on a part of the target image at the same time and sequentially changes the focal location on the target image. At each time step, GCN receives feature data from the focal location of the target image and the focal location transition. GCN recognizes the image from these time series data. However, the conventional GCN randomly transitions the focal locations to recognize the target image and lacks a mechanism to autonomously determine the focal location transition. The proposed method introduces an autonomic focal location transition to enhance image recognition by incorporating a candidate class selection and a next focal location prediction. The candidate class selection finds a promising recognition class at each transition step, while the next focal location prediction finds the next focal location that effectively reduces the recog-nition class candidates. Experimental results using the MNIST dataset show that the proposed method not only autonomously transitions the focal location but also achieves higher recognition accuracy compared to the conventional GCN. © 2024 IEEE.

关键词： Time series

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Synthesis, Characterisation, and Corrosion Inhibition Performance of a β-Cyclodextrin/Melamine Supramolecular Complex on St20 Steel in Acidic Media

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Journal of Bio- and Tribo-Corrosion 2024年第4期10卷 1-22页

作者： Berdimurodov, Elyor Eliboev, Ilyos Dagdag, Omar Lal, Basant Berisha, Avni Rajabov, Yusufboy Mamatov, Jaykhun Wan Nik, W.B. Kholikov, Abduvali Akbarov, Khamdam Chemical & amp Materials Engineering New Uzbekistan University 54 Mustaqillik Ave. Tashkent100007 Uzbekistan Faculty of Chemistry National University of Uzbekistan Tashkent100034 Uzbekistan Uzbek-Finnish Pedagogical Institute Spitamen Street 166-Home Samarqand Uzbekistan Department of Mechanical Engineering Gachon University Seongnam13120 Korea Republic of Department of Chemistry Institute of Applied Science and Humanities GLA University Mathura281406 India Department of Chemistry Faculty of Natural and Mathematics Science University of Prishtina Prishtina10000 Albania Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Kuala Nerus21030 Malaysia Physics and Chemistry "Tashkent Institute of Irrigation and Agricultural Mechanization Engineers" National Research University Tashkent100000 Uzbekistan Natural Science University of Tashkent for Applied Sciences Str. Gavhar 1 Tashkent100149 Uzbekistan Physics and Chemistry Western Caspian University BakuAZ-1001 Azerbaijan

Corrosion poses major challenges in various industrial sectors such as oil and gas, chemicals, and infrastructure. Traditional corrosion inhibitors have limitations in terms of toxicity and environmental compatibility. Supramolecular complexes are promising as green corrosion inhibitors, as the interaction between host and guest molecules can be tailored for different application needs. This study investigates a β-cyclodextrin (β-CD)/melamine (ME) supramolecular complex. The synthesis of the complex is confirmed by Raman spectroscopy, 1H NMR, and FT-IR methods. A range of characterisation techniques are used to analyse the complex’s structure. Gravimetric and electrochemical tests, including potentiodynamic polarisation and electrochemical impedance spectroscopy, evaluate its corrosion inhibition performance on steel in 0.5 M HCl solution at varying concentrations (25–100 mg/L) and temperatures (303 to 333 K). Computational modelling, including Density Functional Theory, Monte Carlo, and Molecular Dynamics simulations, provides atomic-scale insights into the mechanisms of inhibition. The synthesis, characterisation, and corrosion prevention performance of a novel supramolecular complex, β-cyclodextrin/melamine (β-CD/ME), on St20 steel, in acidic conditions, were the subjects of an inventive investigation that was described in this publication. The complex’s structural alterations, physical interactions, and structure were effectively disclosed, using Raman spectroscopy, 1H NMR, and FT-IR. The β-CD/ME complex’s ability to prevent corrosion in hostile solutions exceeded 92–94%, resulting in the formation of a thin protective film on the metal surface and acting as a mixed-type inhibitor. A novel mix of theoretical and experimental methods is used in this work to comprehend the underlying mechanisms, including the influence of structural factors on corrosion prevention effectiveness and the adsorption energies of the complex on the metal surface. Electrochemical tests

关键词： Molecular dynamics

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RCDs Tripping in the Range from DC to AC 50 kHz for Slowly Rising Residual Current

RCDs Tripping in the Range from DC to AC 50 kHz for Slowly R...

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International Conference on Digital Technologies (DT)

作者： Hanan Tariq Stanislaw Czapp Vitaly Levashenko Faculty of Electrical and Control Engineering Gdansk University of Technology Gdansk Poland Faculty of Management Science and Informatics University of Zilina Zilina Slovakia

The wide use of power electronic converters means that in many low-voltage systems earth fault currents containing components from DC to AC of various frequencies have to be taken into account. Due to the tendency to increase the modulation frequency in converters, components of higher frequencies may be in the order of several tens of kilohertz. Therefore, it is very important to verify the behavior of devices for protection against electric shock in the presence of earth currents with frequencies other than the nominal frequency of the network, as well as for a DC component. The paper presents the results of tests of residual current devices (RCDs), with slowly rising earth/residual current at selected frequencies within the range 1 Hz - 50 kHz, and at pure DC. Tests have shown that RCDs may not respond to certain frequencies and pure DC, which carries a risk of electric shock.

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