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2nd International Conference on ICT for Rural Development, IC-ICTRuDev 2021

作者： Santoso, Imam Setyo Ferdinansyah, Alex Sensuse, Dana Indra Suryono, Ryan Randy Kautsarina Hidayanto, Achmad Nizar Universitas Indonesia Faculty of Computer Science Depok Indonesia Universitas Indonesia Faculty of Computer Science Depok Indonesia Universitas Indonesia Faculty of Computer Science Depok Indonesia Universitas Teknokrat Indonesia Faculty of Engineering and Computer Science Bandar Lampung Indonesia Universitas Indonesia Faculty of Computer Science Depok Indonesia Universitas Indonesia Faculty of Computer Science Depok Indonesia

ISBN: (纸本)9781665433754

The majority of mobile mental health (mMHealth) that has been offered have used the gamification feature. However, gamification of mMHealth has practical difficulties, particularly in developing countries. On the other hand, it's crucial when choosing game elements since the improper ones might have a detrimental impact on individuals with mental illnesses. The use of gamification that has been adopted by the majority of mMHealth is also a challenge, because almost some people at a young age who experience anxiety disorders and depression as well as social dysfunction, do not want to use mMHealth as a mental health self-management. This study recommends using gamification to promote patient engagement in the usage of the mMHealth application based on functionality and acceptable qualities for persons with mental illnesses. SUS has been used as a system-wide test to evaluate the usability of the apps against the proposed solution with an average score of 82.5. Overall, the SUS score on the mMHealth solution illustrates the patient's subjective assessment that the proposed solution is effective, efficient and satisfying for patients, especially patient with mental illness. © 2021 IEEE

关键词： Developing countries

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Robust Adaptive Backstepping Control Design for MIMO Electrically Driven Robot Manipulators Using RBF Neural Network With Disturbance 26

Robust Adaptive Backstepping Control Design for MIMO Electri...

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26th International computer science and engineering Conference, ICSEC 2022

作者： Jamil, Muhammad Usman Ahmad, Irfan Buatoom, Uraiwan Assumption University Department of Electrical and Computer Engineering Samut Prakan Thailand Faculty of Science and Arts Chanthaburi Thailand

ISBN: (纸本)9781665491983

In this paper, a robust adaptive (RA) radial basis function (RBF) neural network (NN) based backstepping control design is proposed for multi-input multi-output (MIMO) electrically driven robot manipulators (EDRM) with completely unmodeled dynamics, unknown nonlinearities, disturbance, and virtual control inputs. The proposed research methodology guarantees the controller's resilience even in the presence of parameter changes. The main idea of the backstepping control design is to reduce the error to zero via the use of parameter adjustment rules and a virtual control technique. The recursive backstepping design method treats specific system signals as virtual inputs to smaller subsystems. This novel control strategy guarantees the boundedness of the trajectory tracking error and also weight updates of NN. The key advantage of our control strategy is that it eliminates the requirement for regression matrices, the linear in parameter (LIP) assumption, and an offline learning phase. The results of proposed robust adaptive control methodology with unknown disturbance are compared with conventional proportional-derivative (PD) control scheme, i.e., without backstepping. © 2022 IEEE.

关键词： Backstepping

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Toward Parallelization Technique for Stream-based Lossless Data Compression

Toward Parallelization Technique for Stream-based Lossless D...

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2023 IEEE International Conference on Big Data, BigData 2023

作者： Kato, Taiki Yamagiwa, Shinichi Wada, Koichi Master's Program in Computer Science Degree Program in Systems and Information Engineering University of Tsukuba Ibalaki Tsukuba Japan University of Tsukuba Faculty of Engineering Information and Systems Ibalaki Tsukuba Japan

ISBN: (纸本)9798350324457

IoT edge platform has become popular in various distributed environments. The edge devices need to communicate BigData among them or with the cloud servers by collaborating with AI technologies for finding events from the applications. Those devices exchange data streams from such as distributed sensors and remote image/video devices. We focus on an acceleration technique for the communication performance using a stream-based lossless data compression technology. This paper proposes a parallelization technique for the compression process in a software environment running on a multicore processor. The technique invokes concurrent compression processes assigned to multiple threads with splitting a data stream to chunks. The paper exposes three scheduling methods for assigning the chunks to the threads: in-order, hybrid and out-of-order. As an original data order of chunks must be obtained in decompression side, the proposed technique introduces packeting mechanisms in each chunk by adding headers to support the scheduling methods. Through experimental performance evaluations, we discuss the packeting overhead focusing on compression ratio and speedup by the parallelization with three scheduling methods. © 2023 IEEE.

关键词： Data Stream IoT Lossless Data Compression Multi-Threading Parallelization

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Games for Scrum Team Collaboration in the Global Software Development Environment: A Literature Review 7

Games for Scrum Team Collaboration in the Global Software De...

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7th International Conference on Informatics and Computing, ICIC 2022

作者： Hidayati, Anita Ismail, Iklima Ermis Yuly, Ade Rahma Edison, Henry Politeknik Negeri Jakarta Department of Computer and Informatics Engineering Depok Indonesia Universitas Dian Nuswantoro Faculty of Computer Science Semarang Indonesia Blekinge Institute of Technology Department of Software Engineering Sweden

ISBN: (纸本)9798350345711

Software development companies commonly use Global Software Development (GSD) in their industry. A competent Scrum team supports the success of the GSD project. This research aims to identify the game components in the form of types, elements, and technologies that contribute to building experience for the Scrum team in a GSD environment. We used a Systematic Literature Review (SLR) with the Kitchenham and snowball method. From the 12 papers, we concluded that none of the games specifically focused on the competence of the Scrum team at GSD. The SLR results also identify ten game elements and technologies as a reference for game development to meet the challenges in GSD. The conclusion is that there are still great opportunities to develop a game that can improve the competence of the GSD Scrum team. Game development should refer to elements and identified technologies. © 2022 IEEE.

关键词： Software design

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Artificial Intelligence for Monitoring and Evaluation of Cardiopulmonary Resuscitation

SSRN

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SSRN 2024年

作者： Momeny, Mohammad Marhamati, Mahmoud Esfarayen Faculty of Medical Science Esfarayen Iran Department of Computer Engineering Faculty of Engineering Yazd University Yazd Iran

CPR, cardiopulmonary resuscitation, is a life-saving technique that is given typically to someone who is in cardiac arrest. During the education process of CPR, the rescuer's performance is educated and evaluated by human tutors. Our aim is to use artificial intelligence for education and evaluation of rescuers during CPR. Among the criteria for proper CPR administration, the correct and incorrect position of a rescuer is more common and is tracked by human tutors/supervisors. The present study focuses on the detection of the correct and incorrect positions of rescuers for chest compression using deep transfer learning. To deal with the challenge of detecting the correctness of the rescuer’s position, we built a dataset of 76 sequences of the 30-second recorded video of CPR administration with both correct and incorrect positions. We applied the learning to augment strategy to generate new images for data augmentation in order to improve generalizability of deep networks. The proposed method uses a Bayesian optimizer to determine the optimal value of Gaussian and speckle noise parameters for generating new noisy variants of the original image. We trained six state-of-the-art deep networks, such as DarkNet19, EfficientNetB0, GoogleNet, MobileNet-v2, ShuffleNet, and NASNet-Mobile, with the best data augmentation policies to overcome the overfitting problem. Validation of the proposed method in detecting rescuers’ correct position demonstrated the best sensitivity (98.3%), specificity (95.4%), precision (95.5%), recall (98.3%), and F-measure (96.9%) for the pre-trained NASNet-Mobile network when incorporated with both learning-to-augment and conventional data augmentation strategies. © 2024, The Authors. All rights reserved.

关键词： Resuscitation

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Inflated 3D ConvNet for detection of sign language 4

Inflated 3D ConvNet for detection of sign language

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4th International Conference on Signal Processing and Machine Learning, CONF-SPML 2024

作者： Chandana, D. Tushara, M. Sri, A. Ramya Sakhamuri, Sridevi Abualigah, Laith Department of Electronics and Computer Engineering Koneru Lakshmaiah Education Foundation AP Vaddeswaram522502 India Computer Science Department Prince Hussein Bin Abdullah Faculty for Information Technology Al al-Bayt University Mafraq25113 Jordan MEU Research Unit Middle East University Amman Jordan

ISBN: (纸本)9781510674721

Every human has their own kind of disabilities, we all try to live and overcome them in our life. We educate ourselves to overcome them, we invent technology to achieve our goals. Sign Language is a communication path for deaf-mute people through hand gestures and actions. Sign Language helps people who can’t speak sign language to interact with the people who can speak sign language, this deep learning paper aims to help build a communication bridge for this reason. We used Amazon Rekognition service which uses Deep CNN algorithm for the detection of static images of the signs. As most of the signs are for words they are in the form of videos. We used the I3D algorithm for the classification of videos of the signs of words. The PyTorch framework provides support for CuDNN (NVIDIA CUDA Deep Neural Network) which provides fast GPU implementations for the deep neural networks. The Experimental results has shown that the models used has displayed good results in detecting the words. © 2024 SPIE.

关键词： Deep neural networks

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Analyzing Standardized Inverse Time-Current Curve Types of Overcurrent Relays for Efficient Overcurrent Protection in Distribution Networks

Analyzing Standardized Inverse Time-Current Curve Types of O...

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Proceedings of the International Convention MIPRO

作者： Michele Rojnić Rene Prenc Marina Dubravac Zvonimir Šimić Faculty of Engineering University of Rijeka Croatia Faculty of Electrical Engineering Computer Science and Information Technology University of Osijek Croatia

ISBN: (数字)9798350382501

ISBN: (纸本)9798350382518

The selection of the appropriate curve type of overcurrent relay function is significant for achieving optimal coordination of overcurrent protection in distribution networks. In this study, we conducted a comprehensive analysis of the overcurrent relays performance regarding their different inverse time-current curve types. Additionally, different fault locations were taken into consideration. To investigate the impact of curve types on overcurrent relays coordination, we employed a uniform curve type for all overcurrent relays in two representative power systems. The results, encompassing three standardized IEC curve types, are presented, and analyzed to illustrate the efficacy of our proposed approach. Therefore, this study underscores the critical role that curve type selection has in determining the feasibility of attaining reasonably low overcurrent relay trip times.

关键词： Sensitivity Protective relaying Distribution networks Fault location Robustness Power system reliability Relays

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Profile face recognition based on elements by normalizing global and local features 8

Profile face recognition based on elements by normalizing gl...

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8th International Iranian Conference on Signal Processing and Intelligent Systems, ICSPIS 2022

作者： Khoshnevisan, Erfan Hassanpour, Hamid Alyannezhadi, Mohammad. M. Shahrood University of Technology Faculty of Computer Engineering Iran Unicerversity of Science and Technology of Mazandaran Department of Mathematics Iran

ISBN: (纸本)9781665476232

Despite recent advances in face recognition using deep learning, pose changes are still one of the challenging problems. In this paper, we presented a method to normalize the image in the feature space by capturing local consistency during training. we used facial elements such as eyes, lips, nose, and hairstyle in addition to its general state for recognition. For this purpose, all the elements were detected and localized by semantic segmentation and then normalized. Specifically, an Attention-based convolutional neural network is introduced to integrate local features with their long-range dependencies yielding better feature representations and hence generate representation that preserves identities better, especially for larger pose angles. We used the face/head segmentation dataset for training and the FERET dataset for testing, and the results were good for images with the most difficult angular conditions. The performance of this model on the +90° images of the FERET dataset for 980 samples was 49.6%compared to VGGFace which was only 2.6% accurate. © 2022 IEEE.

关键词： Face recognition

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An Example of Indoor Positioning Possibility Using WiFi Network and Mobile Phone 5

An Example of Indoor Positioning Possibility Using WiFi Netw...

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5th IEEE International Conference on Smart Systems and Technologies, SST 2022

作者： Grgić, Krešimir Balić, Luka Križanović, Višnja Žagar, Drago Josip Juraj Strossmayer University of Osijek Faculty of electrical engineering computer science and information technology Osijek Croatia

ISBN: (数字)9781665482158

ISBN: (纸本)9781665482158

In outdoor environment, navigation and localization services are usually provided by different global navigation satellite system (GNSS). However, indoor localization must rely on different solutions since there is no line of sight between the satellite and the receiver. WiFi networks are densely deployed in indoor environments and may also be used for indoor positioning. The paper presents and analyses the applied example of possible use of WiFi network for indoor localization. © 2022 IEEE.

关键词： Wireless local area networks (WLAN)

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Electricity Demand Prediction through Artificial Intelligence Methods

Electricity Demand Prediction through Artificial Intelligenc...

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2024 International Conference on Sustainable Computing and Integrated Communication in Changing Landscape of AI, ICSCAI 2024

作者： Kumar, Neeraj Mittal, Tanusha Al-Jawahry, Hassan M. Bansal, Saloni Deepak, A. Deepika, N.M. Kaushik, Rohit Department of Electrical Engineering Doon Institute of Engineering and Technology Uttarakhand Rishikesh India Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun India Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Department of Computer Engineering and Applications GLA University Mathura India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Tamilnadu Chennai India Institute of Aeronautical Engineering Dundigal Hyderabad India Faculty of Management SRM Institute of Science and Technology NCR Campus India

ISBN: (纸本)9798350355338

Recently accurate predictions of electricity demands have emerged from the Liberalization and commercialization of the energy area. The future energy or intelligent grid market. A better request-side management method and a shift of mindset are required for a more credible system scale estimate of up to one year. However, electricity is difficult to forecast as elements, including sociological and environmental activity and climatic influences, are affected. The two methodologies utilized to predict cargo, in general, are artificial intelligence and analytical procedures. All analytical methodologies are frequently used in regression literature: linear regression, Box-Jenkins’ methodology, and nonparametric methods. The analytical approaches function effectively in everyday settings regarding meteorological, sociological, and psychological problems but don’t give satisfying outcomes. Consequently, the period of time does not change on the basis of economic developments. Inference systems tactics are among the artificial intelligence systems. © 2024 IEEE.

关键词： Demand response

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