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2023 International Seminar on Application for Technology of Information and Communication, iSemantic 2023

作者： Naufal, Muhammad Rizky Sari, Christy Atika Rachmawanto, Eko Hari Handoko, Lekso Budi Isinkaye, Folasade Olubusola Al-Dayyeni, Wisam Subhi Talib University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia Ekiti State University Department of Computer Science Ekiti Nigeria Ada University School of Information Technologies and Engineering Baku Azerbaijan

ISBN: (纸本)9798350339215

Data Encryption Standard (DES) is a symmetric encryption algorithm that uses a single key to encrypt and decrypt information. In addition, the cipher text will be hidden inside an image using Stepic. DES Encryption use symmetric encryption to encrypt and decryption to decrypt. It will secure the symmetric encryption and maintain the speed of the encryption and decryption. The result of this study is the lowest error that we got as the Mean Square Error (MSE) is 0.00% and is inversely proportional with the Peak Signal to Noise Ratio (PSNR) and Avalanche with 79.36% and 34.91% in order that is not stable for result of Avalanche Effect (AVA). Inversely proportional to the length of the text that is hidden in the image, the longest text that is hidden, the more changes that we get in the image with the highest Unified Average Changing Intensity (UACI) and Number of Pixels Change Rate (NPCR) with the biggest image size with 43.47% for UACI and 99.87% for the NPCR. © 2023 IEEE.

关键词： Pixels

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Silicon-Based Charge Trapping Memory Devices for Next-Generation Flexible Electronics Application

IEEE Journal on Flexible Electronics

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IEEE Journal on Flexible Electronics 2023年第5期2卷 408-413页

作者： Das, Uttam Kumar Aslam, Nabeel Hussain, Muhammad Mustafa El-Atab, Nazek Program of ECE Computer Electrical Mathematical Science and Engineering Division Thuwal23955 Saudi Arabia KAUST Core Labs Thuwal23955 Saudi Arabia Purdue University Elmore Family School of ECE West LafayetteIN47907 United States

Silicon-based charge trapping memory (CTM) devices currently dominate the nonvolatile memory (NVM) technology due to their excellent reliability, scalability, and maturity of the manufacturing process;however, they are rigid, which limits their potential in futuristic applications, such as wearables and flexible displays, among many others;moreover, the majority of previously reported studies on flexible NVM have been limited to either nonsilicon-based CTM or to emerging NVM technologies, such as ferroelectric random access memory and memristors, among others, which still need to overcome different challenges, including, but not limited to, reliability issues and complementary metal-oxide-semiconductor (CMOS) compatibility. In this article, a flexible silicon-based CTM device is developed using a volumetric reduction process. A MOS memory structure with a 7-nm thin Si3N4 layer embedded between 5-nm tunneling (SiO2) and 9-nm blocking oxides (Al2O3) is first fabricated. Next, a backside sequential etching process transforms the rigid die into an ultrathin (20μm) flexible Si die for future application in flexible electronics. The fabricated two-terminal device exhibits a 2.32 V memory window in both rigid and bent states, as observed using capacitance-voltage measurements. A three-terminal version of the device was also developed, where the source and drain terminals were activated using an in situ doped plasma-enhanced CVD (PECVD) process. The flexible encapsulated chip was tested using current-voltage measurements, and the performance was compared at different mechanical bending conditions. The electrical characterization confirms that the flexible devices show similar endurance (104 cycles) and retention (105s) performances to their rigid counterparts. © 2022 IEEE.

关键词： Aluminum oxide

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Development of Machine Learning Models to Predict Strip Breakage During the Aluminium Cold Rolling Process

Development of Machine Learning Models to Predict Strip Brea...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Tiago Ramos Abreu Alexandre Magno Andrade Maciel Graduate Program in Computer Engineering (PPGEC) University of Pernambuco (UPE) Recife Brazil

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

The aluminium processing industry relies on cold rolling as a crucial method for producing materials essential to everyday life. As a consequence of thickness reduction: Strip Breakage, which is one of the main degraders in the aluminum rolling process, arises. In more recent related studies, data were mainly chosen by experts, which can sometimes hide crucial causal factors. Therefore, this work develops Machine Learning models to predict strip breakage, by investigating the relationship between features and the breakage event, using attribute selection techniques to reduce the dimensionality of the problem, comparing classification methods based on trees, such as Decision Trees (DT), Random Forest (RF) and Extra Trees (ET). This work uses the following methodology: first, the models were evaluated for the complete set of data with default initial parameters, then a new evaluation of the models was carried out with the optimized parameters still with high data dimensions, and finally, an evaluation was carried out of the models with the best-selected attributes. The model that performed best was the DT with 21 attributes, with a recall or TPR (True Positive Rate) of 0.863 and an AUC (Compute Area Under of ROC Curve) of 0.926. The models also indicated that there is no unique cause that characterizes the breaks in the aluminium cold mill, but several others, such as the effect of the rolling mill, coil history domain, oil mill and lamination cylinders.

关键词： Industries Radio frequency Performance evaluation Strips Computational modeling Oils Aluminum Predictive models Data models Random forests

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The Effect of Cache Decision Policies on QoE in Multiple Video and Audio Streaming over ICN/CCN

The Effect of Cache Decision Policies on QoE in Multiple Vid...

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Communications and Networking (MeditCom), IEEE International Mediterranean Conference on

作者： Keisuke Kobayashi Toshiro Nunome Department of Engineering Computer Science Program Graduate School of Engineering Nagoya Institute of Technology Nagoya Japan

ISBN: (数字)9798350309485

ISBN: (纸本)9798350309492

This paper considers video and audio transmission in ICN (Information-Centric Networking)/ CCN (ContentCentric Networking), where each intermediate node can cache content. We have proposed LCD with Prob, combining traditional policies: LCD (Leave Copy Down) and probabilistic caching. This paper assumes a case where multiple video and audio streams exist simultaneously. We assess application-level QoS (Quality of Service) and QoE (Quality of Experience) of video and audio transmission utilizing LCD with Prob. We also add a mechanism for further QoE enhancement called “LCD with Prob deletion.” We assess application-level QoS using a computer simulation with a tree network and QoE by means of a subjective experiment. From the assessment result, we show the effectiveness of LCD with Prob deletion against existing policies.

关键词： Network topology Scalability Redundancy Quality of service Streaming media Probabilistic logic Liquid crystal displays

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Grade Classification of Chicken Eggs Through computer Vision 10

Grade Classification of Chicken Eggs Through Computer Vision

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10th International Conference on Computing and Pattern Recognition, ICCPR 2021

作者： Angelia, Hanna Leah Pacure Bolo, Julius Mizhar U. Eliot, Carl Jefferson I. Gelicania, Giovani Y. Computer Engineering Program University of Mindanao Philippines

ISBN: (纸本)9781450390439

This paper explored the use of Region-Convolutional Neural Network (CNN) algorithm. Classified through extracted region proposals from the picture a mere 2000 sections fed into CNN. This study aims to automate the classification of chicken eggs according to their grade (Grade A, B, C, Inedible). It highlights the application of image processing for which image classification technique is used to identify the attributes of the subject through images and overpassing challenges through viewpoints, image deformation, and lighting conditions. With a reading of 93.3% accuracy, this paper concludes that the image processing method used in identifying classifications has been a successful development in terms of image detection and recognition by computer vision for it recognize chicken eggs classification grading's based on the images being captured. Classifications of chicken eggs through computer vision have been achieved. © 2021 ACM.

关键词： Image classification

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Advanced technologies in InGaN micro-LED fabrication to mitigate the sidewall effect

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光：科学与应用（英文版） 2025年第2期14卷 307-332页

作者： Zhiyuan Liu Haicheng Cao Xiao Tang Tingang Liu Yi Lu Zixian Jiang Na Xiao Xiaohang Li Advanced Semiconductor Laboratory Electrical and Computer Engineering ProgramCEMSE DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia

The size of InGaN micro-LEDs is continuously decreasing to meet the demands of various emerging applications,especially in tiny micro-displays such as AR/***,the conventional pixel definition based on plasma etching significantly damages the mesa sidewalls,leading to a severe reduction in efficiency as the micro-LED size *** seriously impedes the development and application of *** this work,we comprehensively explain the origin of micro-LED sidewall effects and corresponding physical ***,we systematically review recent progress in micro-LED fabrication aiming at suppressing sidewall ***,we discuss advancements in micro-LED fabrication with"damage-free"techniques,which hold the potential to fundamentally address the issue of plasma damage in the micro-LED *** believe this review will deepen the understanding of micro-LED sidewall effects and provide a better insight into the latest associated fabrication technologies for high-efficient InGaN micro-LEDs.

关键词： technologies micro-led advanced ingan effect fabrication mitigate sidewall

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Analysis of Brain Excitability After Transcranial Direct Current Stimulation and Brain-computer Interface Based on Motor Imagery on a Post-stroke Patient 9th

Analysis of Brain Excitability After Transcranial Direct Cu...

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9th Latin American Congress on Biomedical engineering, CLAIB 2022 and 28th Brazilian Congress on Biomedical engineering, CBEB 2022

作者： Silva, Leticia Lima, Jéssica Schreider, Sheila Delisle-Rodriguez, Denis Krishnan, Sridhar Bastos-Filho, Teodiano Postgraduate Program in Electrical Engineering Universidade Federal do Espirito Santo Vitoria Brazil Postgraduate Program in Biotechnology Universidade Federal do Espirito Santo Vitoria Brazil Edmond and Lily Safra International Institute of Neurosciences Instituto Santos Dumont Macaiba Brazil Department of Electrical Computer and Biomedical Engineering Toronto Metropolitan University Toronto Canada

ISBN: (纸本)9783031494062

Stroke is a neurological syndrome that may cause severe cognitive and motor impairments for survival. Alternative rehabilitation techniques have been developed to recover lower-limb movements and gait of post-stroke patients, such as Motor Imagery (MI)-based Brain-computer Interfaces (BCIs), Virtual Reality (VR), and robotic devices. Transcranial Direct Current Stimulation (tDCS) is a non-invasive technique to stimulate the brain and modulate cortical excitability. This study aims to analyze the short-term effects of tDCS compared to sham stimulation before a lower-limb MI-BCI pedaling training (through a robotic monocycle) task in a patient with subacute stroke. We studied a post-stroke patient with 2 months of ischemic stroke and right hemiparesis who was submitted to the following tasks: active pedaling, sham tDCS and MI-BCI, and tDCS and MI-BCI. We evaluated the relative power around the foot area (Cz electrode), and a significant (p-value © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Brain computer interface

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Text-to-Speech User Interface for ChatGPT 4

Text-to-Speech User Interface for ChatGPT

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4th International Conference on Electronic and Electrical engineering and Intelligent System, ICE3IS 2024

作者： Suni, Alfa Faridh Utomo, Aryo Baskoro Fathoni, Khoiruddin Mahendra, Budiandra Yusuf Seinsiani, Izzati Gemi Hastawan, Ahmad Fashiha Universitas Negeri Semarang Computer Engineering Semarang Indonesia Universitas Negeri Semarang Electrical Engineering Semarang Indonesia Universitas Negeri Semarang Information Technology Education Semarang Indonesia Universitas Negeri Semarang English Literature Study Program Semarang Indonesia

ISBN: (纸本)9798350378368

The emergence of OpenAI's ChatGPT is paying a lot of attention to Generative AI and its impact on Academic integrity. Generative AI is a system designed to generate content or output such as text, image, audio, simulation, video and code based on their respective training data. ChatGPT itself is in the form of a chatbot where users can communicate with AI through dialogue applications via text. GPT 3 API is the technology behind the ChatGPT. However, interaction via text is not as flexible as dialogue using voice. Therefore, speech-to-text technology is needed to interface between the user and the AI. Chatbot AI powered by GPT3 with the optional voice UI powered by Google Text to Speech clearly benefits accessibility and usability. The output of dialogue between human users and AI can be done through text or sound. This research attempts to implement a Text to Speech and vice versa Speech to Text as a User Interface on a Gen-AI using the GPT 3 API so that it will be more user-friendly and accessible. This research opens many possibilities for human-AI interaction (HAX) in implementing virtual assistants. A seamless dialogue between humans and AI will be our goal in the future. © 2024 IEEE.

关键词： ChatGPT Generative AI Speech to Text Text to Speech

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computer Vision-based Instance Segmentation and Data Augmentation for Construction Site Safety Compliance 24

Computer Vision-based Instance Segmentation and Data Augment...

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24th International Arab Conference on Information Technology, ACIT 2023

作者： Dimaano, Kim Xyrus A. Alon, Alvin Sarraga Batangas State University Tneu Computer Engineering Program Batangas City Philippines Batangas State University Tneu Digital Transformation Center Batangas City Philippines

ISBN: (纸本)9798350384307

Construction safety compliance requires modern technological innovations for effective monitoring and risk mitigation. This study presents an innovative approach for addressing safety problems in construction environments that combines Transfer Learning-based Instance Segmentation and Data Augmentation approaches with YOLOv8. The model succeeds at properly recognizing and segmenting safety-critical objects within complex construction site images, with a remarkable mean Average Precision (mAP) of 94.4%. The key framework is YOLOv8, which is well-known for its real-time object recognition capabilities, allowing for exact identification of safety-related elements across diverse construction landscapes. Through transfer learning, the model enhances its capacity to identify and distinguish safety-critical elements by tailoring pre-existing knowledge to the intricacies of construction site scenarios. The model is made more resilient and adaptive by advanced data augmentation techniques, which guarantees that it works well under a variety of environmental circumstances that are common at construction sites. By advancing computer vision technologies specifically designed for safety applications in high-risk work environments, this study goals to significantly advance real-time safety monitoring and compliance enforcement by laying the groundwork for better safety protocols and preventive measures in dynamic construction environment. © 2023 IEEE.

关键词： construction site safety data augmentation instance segmentation object detection YOLOv8

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QoE Comparison between Multi-User OFDMA and Reliable Groupcast for Wireless LAN Audiovisual Transmission

QoE Comparison between Multi-User OFDMA and Reliable Groupca...

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IEEE Region 10 Symposium

作者： Daiki Deguchi Toshiro Nunome Department of Engineering Computer Science Program Graduate School of Engineering Nagoya Institute of Technology Nagoya Japan

ISBN: (数字)9798350364866

ISBN: (纸本)9798350364873

This paper compares video and audio QoE of OFDMA multi-user transmission and reliable groupcast over wireless LAN. We assume video and audio transmission to several terminals simultaneously. As a reliable groupcast method, we employ Unsolicited Retry, a technique of IEEE 802.11aa GroupCast with Retries. We utilize IEEE 802.11ax for OFDMA transmission. We evaluate application-level QoS by computer simulation. We then assess QoE through a subjective experiment with video and audio streams generated by the output timing obtained from the simulation. We notice that each method has a situation to be applied appropriately.

关键词： Degradation Wireless LAN Receivers Quality of service Streaming media Media Timing Reliability Quality of experience Streams

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