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Computer Technologies (ICCTech), International Conference on

作者： Andi Sama Meyliana Yaya Heryadi Taufik Roni Sahroni Computer Science Department Binus Graduate Program - Computer Science Bina Nusantara University Jakarta Indonesia Information System Department School of Information System Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program-Doctor of Computer Science Jakarta Jakarta Indonesia Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350395419

ISBN: (纸本)9798350395426

IT/OT convergence in the form of a Cyber-Physical system (CPS) presents an opportunity to apply recent information Technology (IT) advancements to Operational Technology (OT). The IT/OT convergence introduces cyber security threats for OT. The OT communication protocols, for example, have limited or no security capabilities for securing data exchange beyond basic authentication. The RNG (Random Number Generator) function is crucial in PLC for producing the encryption keys or the initial seed for security algorithms. The software-based PRNG (Pseudo RNG) is the most common approach for RNG in OT, instead of hardware-based RNG. This study provides a systematic literature review of the most recent evidence in digital transformation to secure data exchange in smart factories, within OT, or across OT and IT settings. It does this by looking at the PRNG on PLC and identifying the most recent trends and best practices. The findings include up-to-date data on author countries' distribution, published journals, research trends, industries, and industry types. The findings also address whether data flow is encrypted or shared in plaintext to ensure secure data transfer between IT and legacy OT environments. This paper concludes that while there is known RNG implementation in the actual embedded system in ICS, there is no evidence in the literature for using RNG in ICS networks for PLC implementation to secure data transfer with encryption.

关键词： Industries systematics Market research Data transfer Control systems Generators Encryption

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Wearable Technology Application for Banjar Language Translator to Support Ease of Communication: Prototyping and Sustainability Opportunities

Wearable Technology Application for Banjar Language Translat...

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2022 International Conference on Data and Software engineering, ICoDSE 2022

作者： Syahidi, Aulia Akhrian Arai, Kohei Smart City Information System Applied Undergraduate Program Politeknik Negeri Banjarmasin Banjarmasin City Indonesia Graduate School of Science and Engineering Saga University Computing Division Honjo-machi Saga Japan

ISBN: (数字)9798350397055

ISBN: (纸本)9798350397055

Language differences are one of the obstacles to communication. Especially if you use certain regional languages such as Banjar Language. Banjar Language is the mother tongue used by the Banjar tribe in South Kalimantan Province, Indonesia. South Kalimantan is known as an area that has promising tourism potential and is the main gateway of the new nation's capital city. This causes many tourists to visit (overtourism). Tourists will face obstacles when communicating with local residents of Banjar. The purpose of this research is to produce a prototype of a tool in the form of a wearable technology-based translator application, using speech recognition with Python programming, then investigate the usability and sustainability opportunities of the prototype that has been made. A total of 200 respondents have been involved consisting of domestic tourists and local residents of Banjar, these respondents were involved in exploring needs and when evaluating usability. The results show that the prototype that has been made provides usability and is feasible to proceed to the implementation stage, as a means to help tourists from the archipelago and local residents of Banjar to communicate and also transact. © 2022 IEEE.

关键词： Sustainable development

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Image Reconstruction for Still Image Capture Using Wireless CMOS Imaging Device

Image Reconstruction for Still Image Capture Using Wireless ...

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Microscopy Histopathology and Analytics, Microscopy 2024 - Part of Optica Biophotonics Congress: Biomedical Optics

作者： Treepetchkul, Thanaree Siwadamrongpong, Ronnakorn Tan, Renzo Roel P. Takehara, Hironari Sunaga, Yoshinori Haruta, Makito Tashiro, Hiroyuki Sasagawa, Kiyotaka Ohta, Jun Division of Materials Science Graduate School of Science and Technology Nara Institute of Science and Technology 8916-5 Takayama Nara Ikoma630-0192 Japan Division of Information Science Graduate School of Science and Technology Nara Institute of Science and Technology 8916-5 Takayama Nara Ikoma630-0192 Japan Department of Opto-Electronic System Engineering Faculty of Science and Technology Chitose Institute of Science and Technology 758-65 Bibi Hokkaido Chitose366-8655 Japan Department of Health Science Faculty of Medical Sciences Kyushu University 3-1-1 Maidashi Hikashi-ku Fukuoka812-8582 Japan

We introduce a wireless system for lensless imaging devices. By reconstructing the low-resolution image acquired by dividing the image into sub-pixel arrays, a high-resolution still image was acquired on a low-transfe... 详细信息

关键词： CMOS integrated circuits

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Design of 900 MHz-band one-sided directional slot antenna by Bayesian optimization

Design of 900 MHz-band one-sided directional slot antenna by...

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Electronics Packaging Technology Conference (EPTC)

作者： Mao Shinchi Kumar Goodwill Haruichi Kanaya Graduate School of Information Science and Electrical Engineering Kyushu University Laboratory of Material Cycle IoT System Kyushu University Fukuoka Japan

In this paper, we proposed to design the one-sided directional slot antenna for 900 MHz band application by Bayesian optimization, one of the machine learning-based optimization methods, to reduce the simulation time by electromagnetic field analysis. Bayesian optimization, an efficient black-box function optimization technique, is applied to the antenna design to reduce the design time and simplify the design. We confirm the effectiveness of this method by fabricating and experimenting with the designed antenna.

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IoT for Water Quality Categorization 5

IoT for Water Quality Categorization

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5th International Conference on Cybernetics and Intelligent systems, ICORIS 2023

作者： Sastrohartono, Hermantoro Krisdiarto, Andreas Wahyu Uktoro, Arief Ika Rahutomo, Reza Suparyanto, Teddy Pardamean, Bens Institute of Agriculture Stiper Faculty of Agricultural Technology Agricultural Engineering Department Yogyakarta Indonesia Bina Nusantara University School of Information Systems Information System Department Jakarta11480 Indonesia Bina Nusantara University Bioinformatics & Data Science Research Center Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Master of Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350369489

In agricultural water research, the adoption of Internet of Things (IoT) technology has emerged as a pivotal approach for large-scale data collection. Water availability in the context of water quality is very important, both for domestic and industrial purposes. For domestic purposes, drinking water and bathing water are separated. Meanwhile, for the palm oil industry, boiler filler is differentiated from additional process water (dilution water). Water quality parameters can be assessed from turbidity and Total Dissolve Solid (TDS). Measurements using measuring instruments separately and repeatedly require significant energy, time, and costs. This research was conducted with the primary objective of presenting a novel method for categorizing water quality with the approach of IoT sensor technology. The research methodology entailed the utilization of an integrated IoT water sensors system in conjunction with manual water categorization. The methods consist of (1) system design, (2) design and installation of sensor and IoT-based microcontrollers, and (3) accuracy and precision testing compared with laboratory measurements. The precision of the integrated IoT water sensors was assessed through a dedicated sensor precision test, resulting in an accuracy rate of 94.4% for the turbidity sensor and 97.5% for the TDS sensor. Notably, this approach successfully discriminated drinking water with valid categorization, while other water types, including groundwater, water with tea, and water with coffee, yielded null categorization results. © 2023 IEEE.

关键词： Internet of things

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An attention mechanism extension of automatic HTML generation from web page design images

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, information and systems 2020年第12期140卷 1393-1401页

作者： Chinen, Hiroki Ohki, Hidehiro Gyohten, Keiji Takami, Toshiya Computer Science and Intelligent System Course Graduate School of Engineering Oita University 700 Dannoharu Oita870-1192 Japan

The purpose of this study is to improve the accuracy of automatic HTML generation from web page design images. pix2code is the state of art in this field. It is consist of design image learning part by CNN and HTML learning part by LSTM. We propose three improvements of adding a word embedding layer, applying VGG16 fine tuning to CNN, replacing LSTM to Bidirectional LSTM or GRU, and introducing attention mechanism. In the experiment, we employed a conventional data set which was used in pix2code and evaluated by a standard natural language generation metric called BLEU. As the results, the one of proposed models that contained the word embedding layer and the attention mechanism scored the accuracy of 99%. It overcomes the result of state of art scored 88%. © 2020 The Institute of Electrical Engineers of Japan.

关键词： HTML

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On a Piecewise Linear Function Approximation for Quantum Computation

On a Piecewise Linear Function Approximation for Quantum Com...

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IEEE Asia-Pacific Conference on Circuits and systems

作者： Hideaki Okazaki Dept. of Informatics Faculty of Informatics Computer Science Course (or Field) Graduate school of Electrical and Information Engineering Shonan Institute of Technology Fujisawa Kanagawa Japan

In quantum computing, although correspondences between quantum circuits and polynomials have been explored, a correspondence between a quantum circuit and a low-degree polynomial, even a linear function has not fully clarified. In this paper, a quantum circuit approximating a linear function for building piecewise linear functions, is proposed. First, for qubit operations, a dimensionless form in $[0,1]$ of a linear function is provided. Secondly, a theorem of a parameterized quantum circuit approximating linear functions are provided. Thirdly, by using Yao: an open source Julia package, the quantum circuit simulation results to approximate the linear functions are presented. Finally, the principal results are summarized.

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GAN-Based Semantic-Aware Translation for Day-to-Night Images

GAN-Based Semantic-Aware Translation for Day-to-Night Images

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2022 IEEE International Conference on Consumer Electronics, ICCE 2022

作者： Shiotsuka, Daiki Lee, Jinho Endo, Yuki Javanmardi, Ehsan Takahashi, Kunio Nakao, Kenta Kamijo, Shunsuke Emerging Design and Informatics Course Graduate School of Interdisciplinary Information Studies University of Tokyo Tokyo Japan Graduate School of Information Science and Technology University of Tokyo Department of Information and Communication Engineering Tokyo Japan University of Tokyo Tokyo Japan Mitsubishi Heavy Industries Machinery Systems Ltd. Hyogo Japan Mitsubishi Heavy Industries Ltd. Hyogo Japan

ISBN: (纸本)9781665441544

Perception in autonomous driving has achieved robustness and high accuracy through deep learning. CNN-based methods require a large amount of data collection and annotation. However, most of the current datasets are built on daytime scenes, and there are few datasets for adverse conditions such as night-time. Recently, data augmentation by image-to-image translation using Generative Adversarial Networks (GANs) has attracted attention. GANs based image-to-image translation performs well for various image translation tasks. On the other hand, semantic information may be lost in problems with the significant domain gap, such as day and night. In this paper, we propose a semantic-aware image translation. This framework preserves semantic consistency by transfer learning a semantic segmentation network to GANs. Experimental results show that the proposed method achieved to generate natural night images compared to previous studies. © 2022 IEEE.

关键词： Generative adversarial networks

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A Unified Tensor-Based Joint AUD and ISAC Parameter Estimation With Large-Scale User Access

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IEEE Transactions on Cognitive Communications and Networking 2025年

作者： Yang, Tiancheng He, Dongxuan Hou, Huazhou Wang, Hua Yin, Hao Huang, Yongming Wang, Zhaocheng Quek, Tony Q.S. Beijing Institute of Technology School of Information and Electronics Beijing100081 China Purple Mountain Laboratories Nanjing211111 China Institute of China Electronic System Engineering Beijing100141 China Southeast University School of Information Science and Engineering Nanjing210096 China Tsinghua University Beijing National Research Center for Information Science and Technology Department of Electronic Engineering Beijing100084 China Tsinghua Shenzhen International Graduate School Shenzhen518055 China Singapore University of Technology and Design Singapore487372 Singapore

The integration of active user detection (AUD) and integrated sensing and communication (ISAC) enables the realization of communication and sensing functionalities over one hardware platform within the realm of ultra-massive machine-type communications (umMTC). However, the coupling of communication and sensing signals at the receiver poses challenges in accurately acquiring the respective parameters for both functionalities. In this paper, a unified tensor-based joint communication and sensing parameter estimation algorithm is proposed. First, leveraging CANDECOMP/PARAFAC decomposition (CPD), the channel model is converted into a unified tensor-based form, facilitating effective processing of the received signals. Subsequently, a two-stage CPD-based unified communication and sensing parameter estimation algorithm is developed. In the first stage, the factor matrix is estimated by utilizing the matrix subspace-based method and the Vandermonde property of the matrix. In the second stage, equivalent path parameters are extracted based on the estimated factor matrices. Furthermore, to solve the coupling problem of equivalent path parameters, a joint alternating iterative pilot-channel estimation (JAI-PCE) algorithm is proposed, effectively decoupling and accurately estimating the parameters. Simulation results verify the effectiveness of our proposed algorithm in terms of AUD, channel estimation, and radar sensing. © 2015 IEEE.

关键词： Channel estimation

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Trends, Opportunities, and Challenges in Detecting Depressive Disorders Through Mobile Devices: A Review 2

Trends, Opportunities, and Challenges in Detecting Depressiv...

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2nd International Conference on Computer system, information Technology, and Electrical engineering, COSITE 2023

作者： Elwirehardja, Gregorius Natanael Isnan, Mahmud Perbangsa, Anzaludin Samsinga Muchtar, Kahlil Pardamean, Bens Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Mahmud Isnan Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Information System Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Department of Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh23111 Indonesia Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9798350343069

Depressive Disorders (DD) is one of the most prevalent mental disorders in the world that may lead to suicide cases. To prevent the latter, ubiquitous early detection systems may be effective. Recent studies have since researched the development of such systems by exploiting several forms of data, including video, audio, Ecological Momentary Assessments (EMA), and passive sensing data using sensors embedded in mobile devices. To summarize the trends, opportunities, and existing challenges in this field, this study reviewed 15 papers to answer four research questions. EMA was the most popular data to be used in this task, but other approaches, such as using video, audio, and typing behaviors, may be considered due to the subjectivity of EMA. These data were typically recorded using smartphones and analyzed using Machine Learning (ML). However, most of the developed systems had yet to be implemented. Overall, it was concluded that further studies may need to explore usages of more objective data in multimodal approaches as well as consider using Mobile Cloud Computing (MCC) to deploy these systems to provide more effective and efficient diagnoses. Future studies must also take into account the existing challenges of the data and infrastructures, such as the weaknesses of several data types, limitations of mobile devices, as well as the challenges of diagnosis approaches. © 2023 IEEE.

关键词： Machine learning

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