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Phase/Interfacial-Engineered Two-Dimensional-Layered WSe2 Films by a Plasma-Assisted Selenization Process: Modulation of Oxygen Vacancies in Resistive Random-Access Memory

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ACS Applied Materials and Interfaces 2023年第28期15卷 33858-33867页

作者： Chaudhary, Mayur Shih, Yu-Chuan Tang, Shin-Yi Yang, Tzu-Yi Kuo, Tzu-Wen Chung, Chia-Chen Shen, Ying-Chun Anbalagan, Aswin kumar Lee, Chih-Hao Hou, Tuo-Hung He, Jr-Hau Chueh, Yu-Lun Department of Materials Science and Engineering National Tsing Hua University Hsinchu30013 Taiwan International Intercollegiate Ph.D. Program National Tsing Hua University Hsinchu30013 Taiwan College of Semiconductor Research National Tsing Hua University Hsinchu30013 Taiwan Department of Physics National Sun Yat-Sen University Kaohsiung80424 Taiwan Department of Engineering and System Science National Tsing Hua University Hsinchu30013 Taiwan Department of Electronic Engineering National Yang Ming Chiao Tung University Hsinchu30013 Taiwan Department of Materials Science and Engineering City University of Hong Kong Hong Kong999077 Hong Kong Frontier Research Center on Fundamental and Applied Sciences of Matters National Tsing Hua University Hsinchu30013 Taiwan Semiconductor Research Center Hon Hai Research Institute Taipei11492 Taiwan

Here, we propose phase and interfacial engineering by inserting a functional WO3 layer and selenized it to achieve a 2D-layered WSe2/WO3 heterolayer structure by a plasma-assisted selenization process. The 2D-layered WSe2/WO3 heterolayer was coupled with an Al2O3 film as a resistive switching (RS) layer to form a hybrid structure, with which Pt and W films were used as the top and bottom electrodes, respectively. The device with good uniformity in SET/RESET voltage and high low-/high-resistance window can be obtained by controlling a conversion ratio from a WO3 film to a 2D-layered WSe2 thin film. The Pt/Al2O3/(2D-layered WSe2/WO3)/W structure shows remarkable improvement to the pristine Pt/Al2O3/W and Pt/Al2O3/2D-layered WO3/W in terms of low SET/RESET voltage variability (−20/20)%, multilevel characteristics (uniform LRS/HRS distribution), high on/off ratio (104-105), and retention (∼105 s). The thickness of the obtained WSe2 was tuned at different gas ratios to optimize different 2D-layered WSe2/WO3 (%) ratios, showing a distinctive trend of reduced and uniform SET/RESET voltage variability as 2D-layered WSe2/WO3 (%) changes from 90/10 (%) to 45/55 (%), respectively. The electrical measurements confirm the superior ability of the metallic 1T phase of the 2D-layered WSe2 over the semiconducting 2H phase. Through systemic studies of RS behaviors on the effect of 1T/2H phases and 2D-layered WSe2/WO3 ratios, the low-temperature plasma-assisted selenization offers compatibility with the temperature-limited 3D integration process and also provides much better thickness control over a large area. © 2023 American Chemical Society.

关键词： Aluminum oxide

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Multi Task Classification Using Deep Learning Approaches for Big Five Personality Traits Prediction: A Review

Multi Task Classification Using Deep Learning Approaches for...

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International Conference on Information Technology, Computer and Electrical engineering (ICITACEE)

作者： Salamun Rohman Nudin Rahmat Gernowo Maman Somantri Adi Wibowo Doctoral Program of Information System School of Postgraduate Studies Diponegoro University Semarang Indonesia Department of Physics Faculty of Science and Mathematics Diponegoro University Semarang Indonesia Department of Electrical Engineering Faculty of Engineering Diponegoro University Semarang Indonesia Department of Informatics Faculty of Science and Mathematics Diponegoro University Semarang Indonesia

ISBN: (数字)9798350389302

ISBN: (纸本)9798350389319

This paper presents a comprehensive review of deep learning methods for the Big Five personality traits prediction using multi-task classification. The purpose of the review is to determine the performance of models developed in previous research to describe research opportunities and challenges in the future. The Big Five model is a framework in psychology that categorizes human personality into five dimensions: openness, conscientiousness, extraversion, agreeableness, and neuroticism. The review begins by analyzing 22 articles from the Science Direct, IEEE Xplore, and Scopus databases by applying screening using the Big Five Personality keywords. Then study the concepts of deep learning for model development such as: input, architecture, method, dataset, and performance to identify the strengths and limitations of each approach. The review results of the highest average accuracy by modality such as unimodal text with essay dataset (80.98 % ), unimodal image with ImageNet dataset (95.36%), unimodal audio with SSPNet dataset (79.48%), bimodal image and audio with Chalearn Video First Impression dataset (91.67 % ), multimodal text, image, and audio with Chalearn Video First Impression dataset (91.88%). The average accuracy of the Big Five Personality traits was highest (95.36 % ) and lowest (59 % ). This highlights the need for standard benchmarks, interpretable models and interdisciplinary collaboration to improve the accuracy, reliability and ethical implications of personality prediction. Future research is expected to pave the way for advancements in understanding human personality through deep learning approaches using other modalities such as EEG, GSR, and PPG.

关键词： Deep learning Accuracy Reviews Psychology Predictive models Brain modeling Multitasking Reliability Information technology Standards

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Photonic Characteristics of U-shape Micro Light-Emitting Diodes and Their Integration with Colloidal Quantum Dots

Photonic Characteristics of U-shape Micro Light-Emitting Dio...

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2023 Conference on Lasers and Electro-Optics, CLEO 2023

作者： Huang, Bo-Ming Jao, Yu-Ming Lin, Fang-Zhong Lee, Guan-Ying Huang, Chung-Ping Kuo, Hao-Chung Lin, Chien-Chung Graduated Institute of Photonics and Optoelectronics National Taiwan University Taipei City Taiwan Institute of Photonic System National Yang Ming Chiao Tung University Tainan71150 Taiwan Graduate Program of College of Photonics College of Photonics National Yang Ming Chiao Tung University Tainan City Taiwan Institute of Electro-Optical Engineering National Yang Ming Chiao Tung University Hsinchu Taiwan

An InGaN U-shape micro LED is fabricated and integrated with colloidal quantum dots. The extracted SRH coefficient showed a 3.2-time increase of surface recombination velocity, while the lifetime of the quantum dot la... 详细信息

ISBN: (纸本)9781957171258

关键词： Semiconductor quantum dots

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Optimization of Workspace Partitioning using Weighted Voronoi Diagram for Fleet of Autonomous Tractors

Optimization of Workspace Partitioning using Weighted Vorono...

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International Conference on Control, Automation and systems ( ICCAS)

作者： Changjo Kim Hyoung Il Son Department of Convergence Biosystems Engineering Chonnam National University Gwangju Republic of Korea Interdisciplinary Program in IT-Bio Convergence System Chonnam National University Gwangju Republic of Korea Research Center for Biological Cybernetics Chonnam National University Gwangju Republic of Korea

ISBN: (数字)9788993215380

ISBN: (纸本)9798331517939

The automation of agricultural systems is essential for enhancing productivity and ensuring sustainable food production. The introduction of autonomous tractors and fleet of autonomous tractors technology is important to the advancement of agricultural automation. This paper proposes an optimization method for workspace partitioning using a weighted voronoi diagram for fleet of autonomous tractors. The proposed method generates a node map based on an orchard environment, determines the centers of the areas to partition the workspace to be assigned to the k tractors, sets weights based on the specifications of each tractor, optimizes these weights, and partition the workspace to maximize work *** study validated the performance of workspace partitioning optimization through simulations and field evaluations. The results of this study expect that the proposed method can be applied to fleet of autonomous tractors technology to improve the efficiency of agricultural work.

关键词： Productivity Automation Food manufacturing Scalability Optimization methods Agricultural machinery Control systems Robots

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Energy Preservation in MANET Using Self-Adaptive CH Selection with Advanced Genetic Algorithm 1

Energy Preservation in MANET Using Self-Adaptive CH Selectio...

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1st International Conference on Advanced engineering and Technologies, ICONNIC 2023

作者： Indriyono, Bonifacius Vicky Pamungkas, Natalinda Abbas, Fatima Hashim Mintorini, Ery Almohamadi, Mohammed Mahmood, Sarmad Nozad Alani, Sameer Alkhayyat, Ahmed H. Rachmawanto, Eko Hari University of Dian Nuswantoro Information System Kediri Indonesia Al-Mustaqbal University College Medical Laboratories Techniques Department Hillah51001 Iraq University of Dian Nuswantoro Visual Communication Design Kediri Indonesia College of Information Technology Imam Ja'afar Al-Sadiq University Al-Muthanna66002 Iraq Computer Technology Engineering College of Engineering Technology Al-Kitab University Iraq University of Mashreq Research Center Medical Laboratories Techniques Baghdad Iraq College of Technical Engineering University of Mashreq the Islamic University Najaf Iraq University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia

ISBN: (纸本)9798350306484

Mobile Adhoc Networks (MANETs) is an emerging technology in both the industrial and academic research. The major drawback in MANETs is improving the battery capacity. MANETs are dynamic in nature therefore during communication it consumes more energy that reduces the overall energy efficiency of the network. Many past and present researches are concern about this problem. In this paper, Energy Preservation in MANETs using Self-Adaptive Cluster Head Selection with Advanced Genetic Algorithm (EPMSA-CHAG) approach is proposed where the CH selection is performed using two segments;they are initial parameter based on CH selection and Advanced Genetic Algorithm (AGA) based CH selection. At the initial stage the parameters which are considered for the CH selection are node degree, node stability, distance, residual energy, and speed and delivery rate. Using these parameters are the best fit for CH selection is chosen then in order to find the optimal best fit from the best fit calculation, Advanced Genetic Algorithm (AGA). The proposed EPMSA-CHAG approach is simulated using NS2 and the parameters which are considered for the performance analysis are packet delivery rate, energy efficiency, end to end delay, routing overhead and throughput. The methods that are taken for the comparative analysis are HLSPM-CHSR and HAMBO-CHLD. From the results calculated it is proven that the proposed EPMSA-CHAG approach achieved high packet delivery rate, energy efficiency and throughput as well as lower end to end delay and routing overhead when compared with the earlier methods HLSPM-CHSR and HAMBO-CHLD. © 2023 IEEE.

关键词： Energy efficiency

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Application for Airport Tenant Selection Using Weighted Product-based Decision Support system

Application for Airport Tenant Selection Using Weighted Prod...

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2023 International Conference on Electrical and Information Technology, IEIT 2023

作者： Sumari, Arwin Datumaya Wahyudi Saputra, Muhamad Andika Ayuningtyas, Astika Sudarmadi, Catur Adisutjipto Institute of Aerospace Technology Aerospace Intelligent System and Data Engineering Research Group Yogyakarta Indonesia Politeknik Negeri Malang Cognitive Artificial Intelligence Research Group Malang Indonesia Adisutjipto Institute of Aerospace Technology Informatics Study Program Faculty of Industrial Technology Yogyakarta Indonesia Adisutjipto Institute of Aerospace Technology Aerospace Health Informatics Research Group Faculty of Industrial Technology Yogyakarta Indonesia

ISBN: (纸本)9798350327298

This research aims to develop an application for selecting the best new tenant at PT Angkasa Pura II Sultan Thaha Jambi Airport Branch by utilizing Weighted Product (WP) method as the decision support system. Our approach is descriptive research with data analysis technique using four prospective tenants coded A-1 to A-4. The data was collected through observation, interviews, documentation, and literature study. The steps for selecting the best new tenant using the WP method include determining the criteria, sorting the suitability of alternatives and criteria, determining the weight of each criterion and its normalization, calculating the score, S value as an alternative preference, and calculating the ranking, V value as the final alternative preference. Based on the final calculation results, the new tenant coded A-4 is the best alternative based on the data collected from the Financial Management (FHFM) Unit and the Commercial Unit, with a value of V-4 is 0.294. © 2023 IEEE.

关键词： Decision support systems

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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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Field Evaluation of a Prioritized Path-Planning Algorithm for Heterogeneous Agricultural Tasks of Multi-UGVs

Field Evaluation of a Prioritized Path-Planning Algorithm fo...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Yuseung Jo Hyoung Il Son Department of Convergence Biosystems Engineering Chonnam National University Gwangju Republic of Korea Interdisciplinary Program in IT-Bio Convergence System Chonnam National University Gwangju Republic of Korea Research Center for Biological Cybernetics Chonnam National University Gwangju Republic of Korea

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

This paper introduces a prioritized path-planning algorithm for heterogeneous tasks performed by multiple unmanned ground vehicles (UGVs) in agricultural environments. The algorithm considers varying robot priorities, thereby extending the traditional multi-agent path finding (MAPF) approach. The proposed algorithm is evaluated in scenarios occurring during representative agricultural operations: harvesting and transportation. An experimental validation is conducted in agriculture-like settings by using multiple simultaneous localization and mapping systems and navigation systems. The results revealed that the path of agent 1 , which was assigned the highest priority in both the indoor and outdoor environments, was shortened considerably (3.38 m, 3.6 m, and 5.6 m, respectively). Especially in the face scenario, the sum of changes in distance, calculated using the proposed algorithm was negative, meaning that traffic congestion in the multi-robot system used in the experiment was alleviated without the need for inter-robot communication.

关键词： Simultaneous localization and mapping Navigation Transportation Symbols Path planning Reliability Task analysis

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Offensive Chinese Text Detection Based on Multi-Feature Fusion

Offensive Chinese Text Detection Based on Multi-Feature Fusi...

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Computer engineering and Intelligent Communications (ISCEIC), International Symposium on

作者： Na Li Shaomei Li Jiahao Hong Academy of Cyberspace Security Zhengzhou University Zhengzhou China National Engineering Research Center for Digital Program-Controlled Switching System Strategic Support Force Information Engineering University Zhengzhou China School of Computer and Artificial Intelligence Zhengzhou University Zhengzhou China

To purify the online environment, it is essential to identify objectionable content, including offensive texts. However, some offensive texts are expressed in a more subtle manner, making it difficult to detect their literal characteristics. To enhance the effectiveness of detecting offensive Chinese text, we propose a multi-feature fusion-based method. First, we combine the word vectors obtained from Wobert with the character vectors obtained from ALBERT. The attention mechanism assigns greater importance to key features within the word vectors. Next, we merge the fusion vector with the sentence vector generated by ALBERT, which encompasses contextual semantics and syntactic information. This results in a new fusion vector that captures information at the character, word, and sentence levels. Finally, we employ a fully connected layer to process the three-level fusion vector and obtain the detection outcome. Experimental results demonstrate that this approach provides a comprehensive characterization of offensive text by fusing information from multiple levels. It substantially enhances the detection performance for offensive Chinese text.

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Minimizing the Number of Stunting Prevalence Using the Euclid Algorithm Clustering Approach

Minimizing the Number of Stunting Prevalence Using the Eucli...

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International Conference of Computer Science and Information Technology

作者： Muhammad Zarlis Tanty Oktavia Relita Buaton Ferda Ernawan Kevin Andrian Department BINUS Graduate Program - Master of Information System Management Information System Management Bina Nusantara University Jakarta Indonesia Informatics Engineering STMIK Kaputama Binjai Indonesia Faculty of Computing Universiti Malaysia Pahang Al-Sultan Abdullah Pekan Malaysia Department of Information Systems Management BINUS Graduate Program-Master of Information Systems Management Bina Nusantara University Jakarta Indonesia

Superior and quality human resources are based on healthy human resources with indicators of adequate nutritional intake according to age development. However, the world still faces the problem of hunger and malnutrition today. According to a UNICEF report, the number of people suffering from malnutrition in the world will reach 767.9 million people in 2021. The World Health Organization (WHO) said that malnutrition is a dangerous threat to the health of the world's population. Stunting also has an impact in Indonesia, the prevalence of toddlers experiencing stunting in Indonesia is 24.4% in 2021. The solution created is to classify and cluster the prevalence of stunting to produce a pattern that can be used as best practice to be transmitted to other affected areas. The algorithm used is Euclid. The Euclid algorithm can cluster stunting prevalence data into 4 clusters with the very little category at 79%, the little category at 67%, the many categories at 51%, and the very much category at 21%. The results of the classification and clustering of the best stunting prevalence in cluster one with a very small number, can be used as a source of accurate and updated information that can be used by the government in its efforts to optimize stunting handling in each district/city based on artificial intelligence which can provide handling and optimization patterns. stunting in every district/city.

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