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1st International Conference on Smart Technology, Applied Informatics, and engineering, APICS 2022

作者： Ardhi, Ovide Decroly Wisnu Soeprobowati, Tri Retnaningsih Adi, Kusworo Prakasa, Esa Rachman, Arief School of Postgraduate Studies Universitas Diponegoro Doctoral of Information System Program Semarang Indonesia Vocational School Universitas Sebelas Maret Department of Informatics Engineering Surakarta Indonesia Universitas Diponegoro Faculty of Science of Mathematics Department of Biology Semarang Indonesia Universitas Diponegoro Faculty of Science of Mathematics Department of Physics Semarang Indonesia Bandung Indonesia Jakarta Indonesia

ISBN: (数字)9781665489850

ISBN: (纸本)9781665489850

This study investigates trends in deep learning research on microscopic images to identify and classify plankton. We performed a bibliometric analysis using VOSviewer to display the visualizations. The first step is to extract the relevant journals from the Scopus database. Extraction from relevant journals found 42 articles, including 21 journals and 21 conferences. We analyzed publication trends and analyzes of co-authorship, co-occurrence, and citations. In addition, it examines the collaborative relationship between authors by country, the emergence of co-author keywords, and the citation of journal sources. We found that the researchers performed plankton classification tasks that achieved high accuracy (>90%). The plankton identification method uses a deep learning architecture based on the Convolutional Neural Network. Among the architectures are AlexNet, GoogleNet, InceptionV3, VGGNet (16.19), ResNet (50.101), DenseNet, NasNet, MobileNetV2, ResidualNet, Shufflenet, EfficienNet, and CapsNet. Some researchers combine CNN with SparseConvNets, LMP, SVM, MorphoCluster, and Quantification Algorithm (CC, AC, PCC, PAC, Hdy). Some methods also implement transfer learning, fine-tuning, and advanced features. In addition to the CNN approach, End-to-End Object Detection with transformers is one of the new approaches in the future to identify plankton. © 2022 IEEE.

关键词： Deep learning

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Monitoring System for Elderly Health Care Using Smart Band, Raspberry Pi, and Node-Red 2

Monitoring System for Elderly Health Care Using Smart Band, ...

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2nd International Conference on Electronic and Electrical engineering and Intelligent System, ICE3IS 2022

作者： Ardiyanto, Yudhi Adi, Kusworo Kurnianingsih Putra, Karisma Trinanda Utomo, Pradityo System School of Postgraduate Studies Universitas Diponegoro Doctoral Program of Information Semarang Indonesia Universitas Muhammadiyah Yogyakarta Faculty of Engineering Department of Electrical Engineering Yogyakarta Indonesia Universitas Diponegoro Faculty of Science and Mathematics Department of Physics Semarang Indonesia Politeknik Negeri Semarang Faculty of Engineering Department of Electrical Engineering Semarang Indonesia Universitas Merdeka Madiun Faculty of Engineering Department of Informatics Management Madiun Indonesia

ISBN: (纸本)9781665465410

The decline in physical, cognitive, and sensory functions for most elderly people leads to the development of several health issues such as memory loss, a tendency to fall, dizziness, and reduced ability to care for oneself independently. These can be mitigated using devices designed to monitor vital signs and human activity such as a smart band. However, the application of a smart band is characterized by a disadvantage which involves storing user data in the vendor's cloud and only one device can access the client applications. Therefore, nurses, doctors, and family members cannot simultaneously analyze data and receive alerts when abnormal conditions occur in elderly patients. This study aims to develop a system capable of monitoring the health conditions of multiple elderly individuals and sending alerts during abnormal conditions based on the heart rate value read by the smart band sensor. The process involved installing a database on the Raspberry Pi to store data while a monitoring system was built on the Node-RED platform to display elderly health data and made it accessible locally. The detection of an abnormal heart rate condition in the elderly patient leads the system to send notifications via telegram to multiple receivers registered in the system using their telegram identity. © 2022 IEEE.

关键词： Heart

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A Proposal of GA Using Symbiotic Evolutionary Viruses and its Virus Evaluation Techniques

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Journal of Advanced Computational Intelligence and Intelligent Informatics 2004年第4期8卷 421-425页

作者： Sakakura, Yoshiaki Taniguchi, Noriyuki Hoshino, Yukinobu Kamei, Katsuari Frontier Doctoral Program in Science and Engineering Ritsumeikan University Japan Graduate School of Science and Engineering Ritsumeikan University Japan Human and Computer Intelligence College Information Science and Engineering Ritsumeikan University 1-1-1 Noji-higashi Kusatsu Shiga525-8577 Japan

In this paper, we propose a Genetic Algorithm (GA) using symbiotic evolutionary viruses based on both the building block hypothesis and the virus theory of evolution. The proposed GA aims to control the destruction of building blocks by discovery, maintenance, and propagation of building blocks based on virus operation. We prepare a group of individuals and a group of viruses. The group of individuals searches for solutions and the group of viruses searches for building blocks. These searches are done based on the symbiotic relation of both groups. Also, our GA has two types of virus evaluation technique. In one type, each virus is evaluated by the difference of the fitness of an individual before and after virus infection. In the other type, all viruses are evaluated by the difference of the fitness of an individual before and after infection of all viruses. We applied the proposed GA to a minimum value search problem using a test function with some local minima far from the optimum. Finally, we also discuss the search behavior in the proposed GA based on each virus evaluation technique. © Fuji Technology Press Ltd. Creative Commons CC BY-ND: This is an Open Access article distributed under the terms of the Creative Commons Attribution-NoDerivatives 4.0 International License (http://***/licenses/by-nd/4.0/).

关键词： Genetic algorithms

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Integrating Noise Classification and Speech Enhancement Model for Hearing Aids 21

Integrating Noise Classification and Speech Enhancement Mode...

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21st International System-on-Chip Design Conference, ISOCC 2024

作者： Hung, Ying-Hsiu Chang, Yen-Ching Lai, Shin-Chi Juang, Wen-Ho Sheu, Ming-Hwa Lee, Jeng-Dao National Yunlin University of Science and Technology Dept. Electronics Engineering Douliu Taiwan National Formosa University Doctoral Degree Program in Smart Industry Technology Research and Development Huwei Taiwan National Formosa University Dept. Automation Engineering Smart Machinery and Intelligent Manufacturing Research Center Huwei Taiwan National Formosa University Dept. Computer Science and Information Engineering Huwei Taiwan National Formosa University Dept. Automation Engineering Huwei Taiwan

ISBN: (纸本)9798350377088

As the global population ages, the number of elderly people needing hearing aids is increasing. This paper proposed an architecture designed to enhance speech based on noise conditions. After noise types are identified by a Convolutional Neural Network (CNN) noise classification model, these noise conditions are combined with the noisy speech and input into a conditional Generative Adversarial Network (cGAN) for speech enhancement. The CNN noise classification model achieves an average recognition accuracy of nearly 92%, with a Kappa value as high as 0.88. The cGAN speech enhancement achieves lower error values in the Mel-Cepstral Distortion (MCD) measure. Although some parts of the human voice may be filtered out, the results demonstrate the potential development of the proposed algorithm. © 2024 IEEE.

关键词： Generative adversarial networks

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Probabilistic and grouping methods for morphological root identification for Afaan Oromo

Probabilistic and grouping methods for morphological root id...

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International Conference on Confluence The Next Generation information Technology Summit (Confluence)

作者： Getachew Mamo Wegari Massimo Melucci Solomon Teferra IT Doctoral Program Addis Ababa University Addis Ababa Ethiopia Department of Information Engineering University of Padua Padua Italy Department of Information Science Addis Ababa University Addis Ababa Ethiopia

ISBN: (纸本)9781467382045

Morphological models are used in many natural language processing tasks including machine translation and speech recognition. We investigated probabilistic and grouping methods to develop a morphological root identification model for Afaan Oromo. In this paper, we have experimentally shown that the proposed methods can improve the morphological root identification performance of some state-of-the-art methods.

关键词： Probabilistic logic Natural language processing Testing Speech recognition information retrieval Writing Europe

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Suffix sequences based morphological segmentation for Afaan Oromo

Suffix sequences based morphological segmentation for Afaan ...

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AFRICON Conference

This paper reports on a morphological segmentation model for Afaan Oromo based on suffix sequences approach. Understanding and identifying the suffix sequences of a language allow us to detect morpheme boundaries of many words of Afaan Oromo. Morphological segmentation models can be used in many Natural Language Processing applications such as machine translation, speech recognition, information retrieval and part-of-speech tagging. A divisive hierarchical clustering and frequency distribution were used to build a tree of candidate stems from which segmented suffix sequences can be modeled. The proposed morphological segmentation model was evaluated with test word-lists. The accuracy obtained by our morphological segmentation model is encouraging.

关键词： Computational modeling Training Natural language processing Algorithm design and analysis Clustering algorithms Pragmatics

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Digital Dictionary Using Binary Search Algorithm 1

Digital Dictionary Using Binary Search Algorithm

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1st International Conference on Computer science and Applied Mathematic, ICCSAM 2018

作者： Fitrian, Riski Muhamad Taufik, Insan Ramadhan, Muhammad Sabir Mulyani, Neni Hutahaean, Jeperson Sitio, Arjon Samuel Sihotang, Hengki Tamando Teknik Informatika STMIK Pelita Nusantara Medan Sumatera Utara Indonesia Doctoral Program Vocational Technology Education Postgraduate Engineering Faculty Padang State University Padang West Sumatera Indonesia Sistem Informasi STMIK Royal Kisaran Sumatera Utara Indonesia Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia

Digital Dictionary of Computer and Network engineering can be used in the learning process of computer and nerwork enginering students. Dictionaries are generally book-shaped is hard to carry because of their thick and heavy, now can be accessed anywhere by development of web technology. Digital dictionaries can be accessed through computers, laptops dan cellphones, this is make student easily in learning process. The digital dictionary can not only be used by students of computer and network engineering, but can also by general public, as long as you have an internet connection, anyone can be use this digital dictionaries. The main process in this digital dictionary is the search process. Binary search algorithm used in the search process of binary search algoritm. Binary search algoritm search is applied to word search in this digital dictionary, because this algoritm is intended for sequintal data. program language that will be used to build this digital dictionary is PHP and MySQL. © Published under licence by IOP Publishing Ltd.

关键词： Students

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Initial Study of Oil Palm Crop Condition Detection Through Drone Imagery: A YOLO Approach

Initial Study of Oil Palm Crop Condition Detection Through D...

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International Conference on Informatics, Multimedia, Cyber and information System (ICIMCIS)

作者： Winata Nugraha Ermatita Deris Stiawan Faculty of Computer Science Doctoral Program Faculty of Engineering Universitas Sriwijaya Palembang Indonesia Department of Information System Universitas Sriwijaya Palembang Indonesia Faculty of Computer Science Universitas Sriwijaya Palembang Indonesia

ISBN: (数字)9798331533243

ISBN: (纸本)9798331533250

Oil palm plantations in Indonesia still have many challenges, especially in terms of monitoring and mapping technology. One of the important aspects in the monitoring stage of oil palm plantations is monitoring the productivity of oil palm plants. To identify the oil palm plants, many previous studies have utilized image analysis to solve the problem. The problem is that poor image conditions can affect the architecture model to be built.[1] So in this research we do tune mapping on the image to produce a quality image. Each image data that has been improved will be feature extracted using ResNet and VGG to produce the best model. Furthermore, the classification model development process is carried out using CNN architecture as the model architecture. We also provide innovation by using object detection technology. Which uses artificial neural networks. Here we train the model using aerial video datasets of oil palm plants obtained from drones. Furthermore, to evaluate the performance of the above technique, it is proposed to use the mapping model, precision and accuracy evaluation obtained in the test phase[2]

关键词： YOLO Productivity Technological innovation Oils Multimedia systems Plantations Feature extraction Informatics Monitoring Drones

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An Improvement Data Hiding Scheme Based on Formula Fully Exploiting Modification Directions and Pixel Value Differencing Method

An Improvement Data Hiding Scheme Based on Formula Fully Exp...

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Asia Joint Conference on information Security (Asia JCIS)

作者： Wen-Chung Kuo Jyun-Jia Li Chun-Cheng Wang Lih-Chyau Wuu Yu-Chih Huang Department of Computer Science and Information Engineering National Yunlin University of Science & Technology Taiwan R.O.C. Graduate School of Engineering Science and Technology Doctoral Program National Yunlin University of Science & Technology Taiwan R.O.C.

ISBN: (纸本)9781509022861

Recently, a modified data hiding scheme based on pixel value differencing and improving exploiting modification directions is proposed by Shen and Huang. There are two major contributions in this scheme. One is to enhance the embedding rate and good embedding capacity and the other is an optimization problem used to solve the overflow/ underflow problem. In fact, they propose the similar brute force method to solve overflow/underflow problem in their proposed scheme. To overcome the overflow/underflow problem exactly, we will propose the close form to solve this problem in this paper. Then, an improvement data hiding scheme based on FFEMD (Formula Fully Exploiting Modification Directions) and pixel value differencing method is proposed. According to our analysis, it is not only to keep the advantages of Shen-Huang scheme but also to use the close form to solve the overflow/ underflow problem.

关键词： Integrated circuits Cryptography Partitioning algorithms Streaming media Electronic mail Distortion

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Attentiveness Assessment in Learning Based on Fuzzy Logic Analysis

Attentiveness Assessment in Learning Based on Fuzzy Logic An...

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International Conference on Intelligent Systems Design and Applications (ISDA)

作者： Kuo-An Hwang Chia-Hao Yang Department of Computer Science and Information Engineering & Graduate Institute of Networking and CommunicationEngineering ChaoYang University of Technology Taiwan Graduate Institute of Informatics Doctoral program ChaoYang University of Technology Taiwan

Learner attention affects learning efficiency. However, in many classes, teachers cannot assess the degree of attention of every student. When a teacher is capable of addressing inattentive students immediately, he can avoid situations in which students are inattentive. Many studies have analyzed student attentiveness by the applying of image detection technologies. If this mechanism can be applied to in-class learning, it will help teachers keep students attentive, and reduce teacher load during class. This study mainly applies fuzzy logic analysis of student facial images when participating in class. Applying fuzzy logic can prevent erroneous judgments associated with a single term, and help teachers deal with student attentiveness.

关键词： Fuzzy logic Face detection Image analysis Image color analysis Education Eyes Design engineering Chaotic communication Image processing Face recognition

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