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SSRN 2023年

作者： Nigdelioglu, Ebru Toprak, Elif Guney Akkurt, Melike Erol Barkana, Duygun Kazanci, Murat Uyaver, Sahin Calik, Nurullah Istanbul Medeniyet University Nanoscience and Nanoengineering Program Graduate School Istanbul Medeniyet University Istanbul34700 Turkey Istanbul Medeniyet University School of Engineering and Natural Sciences Department of Biomedical Engineering Istanbul Turkey Istanbul34700 Turkey Yeditepe University Faculty of Engineering Department of Electrical and Electronics Engineering Kayışdagı Istanbul34755 Turkey Marmara University Faculty of Technology Department of Computer Engineering Maltepe Istanbul34854 Turkey

Phenylalanine is an aromatic essential amino acid that exhibits the tendency to self-aggregate into fibrillar structures in its enantiomerically pure form. This observation was indicated as the underlying mechanism of phenylketonuria, which is a genetic condition associated with various neurological, physical, and developmental issues, characterized with phenylalanine buildup in the brain. The presence of D-phenylalanine was demonstrated previously to inhibit the formation of fibrils by L-phenlyalanine, indicating its potential use in phenylketonuria treatment. In this study, several combinations of D and L-phenylalanine were examined with the help of state-of-the-art deep learning methods for their fibril forming capacity, demonstrating the usefulness and accuracy of deep learning methods in distinguishing between different self-assembled structures. © 2023, The Authors. All rights reserved.

关键词： Self assembly

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First Demonstration of HZO-LNOI Integrated Ferroelectric Electro-Optic Modulator and Memory to Enable Reconfigurable Photonic Systems

First Demonstration of HZO-LNOI Integrated Ferroelectric Ele...

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International Electron Devices Meeting (IEDM)

作者： Zefeng Xu Chun-Kuei Chen Hong-Lin Lin Yuan Gao Wei Ke Baochang Xu Pavel Dmitriev Carlan Arbiz Evgeny Zamburg Steven Touzard Xinlun Cai James Lee Suresh Venkatesan Aaron Danner Aaron Voon-Yew Thean Department of Electrical and Computer Engineering National University of Singapore (NUS) Integrative Sciences and Engineering Program NUS Graduate School Singapore Next-Generation Hybrid μ-Electronics Center (SHINE) Singapore School of Electronics and Information Technology Sun Yat-Sen University China 510275 Singapore Centre for Quantum Technologies NUS POET Technologies

We have successfully demonstrated, for the first time, an innovative back-end-of-line (BEOL) compatible electro-optic modulator and memory (EOMM) based on Lithium Niobate on Insulator (LNOI) micro-ring resonator (MRR) integrated with Ferroelectric Hafnium Zirconate Hf 0.5 Zr 0.5 O (HZO) non-volatile analog memory. High non-volatile memory and modulation performances are both achieved in a single compact device, exhibiting high extinction ratio of 13.3 dB, excellent efficiency of 66pm/V, stable nine-state switching, record-high endurance exceeding 10 9 cycles. This is accomplished by utilizing Pockels effect in LNOI, induced by electric-field effect from remnant HZO ferroelectric polarization. We studied the system implementation of reconfigurable chiplet-interposer photonic interconnect, enabled by the EOMM and EOMM with hybrid thermal-optical modulation. Our model shows a potential 70% energy efficiency improvement over conventional electrical interposer interconnect. We have also tested the integration of the EOMM with POET technologies’ 400G Tx/Rx optical interposer chip and studied a limited scale demonstration of the EOMM device.

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IoT Attack Detection and Prevention Through Machine Learning System

IoT Attack Detection and Prevention Through Machine Learning...

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Communication, Security and Artificial Intelligence (ICCSAI), International Conference on

作者： Kanishk Agrawal Pavan Kumar Reddy Poli Yash Gupta Garv Juneja Adhip Kishen Bopaiah Dinesh Ashok Arani Department of IET CSE Manglayatan University Aligarh Uttar Pradesh India Managing Information Technology Implementations Program management for fortune 6 Healthcare Company USA Department of Computer Science and Information Systems Birla Institute of Technology and Science Pilani India Department of Computer Science and Engineering Maharaja Surajmal Institute of Technology Guru Gobind Singh Indraprastha University Delhi India ICT Trainer Trinity College Bangalore India Manglayatan University Aligarh Uttar Pradesh India

Attacks on web applications are constantly growing in both frequency and severity. Abundant data on the internet stimulates hackers to attempt different types of cyberattacks. Attack detection using conventional approaches and outdated data processing techniques has become outmoded as a result of this development. The purpose of this study is to investigate IoT attacks and discuss the efficient ML technique implementation strategies for restricting security risks. Among different security techniques, Machine learning (ML) systems demonstrated commendable feasibility in improving network and device security for the Internet of Things. The study with contextual research recognises and comprehends that modified “Support Vector Machine (SVM)” as well as “Random Forest (RF)” ML techniques showed optimal performance in IoT attack detection and prevention.

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Deep Learning with Greedy Layer-Wise Compound Scaling for Temperature and Humidity Prediction in Solar Dryer Dome

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SSRN 2022年

作者： Cenggoro, Tjeng Wawan Elwirehardja, Gregorius Natanael Dominic, Nicholas Setiawan, Karli Eka Rahutomo, Reza Djuana, Endang Gunawan, Fergyanto E. Budiman, Arief S. Romeli, Sugiarto Pardamean, Bens Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Electrical Engineering Department Faculty of Industrial Technology Universitas Trisakti Jakarta11440 Indonesia Industrial Engineering Department BINUS Graduate Program Master of Industrial Engineering Bina Nusantara University Jakarta11480 Indonesia Department of Manufacturing and Mechanical Engineering and Technology Oregon Institute of Technology Klamath FallsOR97601 United States PT. Impack Pratama Industri Jakarta Indonesia

Drying has been an eco-friendly and cost-efficient method to reduce post-harvest losses of agricultural crops. In various countries, the technique has been widely utilized in the form of Solar Dryer Dome (SDD) buildings. Accurate indoor microclimate forecasting is very important to implement smart control systems in SDDs that can maintain the ideal conditions, as the availability of solar energy is limited only at daytimes and the temperature may drop significantly during nighttimes in remote areas. The microclimate variables that play an important role in maintaining ideal environmental conditions include temperature and relative humidity. © 2022, The Authors. All rights reserved.

关键词： Forecasting

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Alert and Response of Earthquake and Tsunami for Community Based Disaster Risk Reduction 2

Alert and Response of Earthquake and Tsunami for Community B...

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2nd International Conference on Sciences and technology Applications, ICOSTA 2020

作者： Retno Susilorini, Rr M. I. Pamudji, Andre Kurniawan Sanjaya, Ridwan Ismail, Amrizarois Amasto, Ardhito Hayyu Department of Infrastructure and Environmental Engineering Faculty of Environmental Science and Technology Soegijapranata Catholic University Semarang Indonesia Master Program of Environmental and Urban Studies Faculty of Environmental Science and Technology Soegijapranata Catholic University Semarang Indonesia Department of Information System Faculty of Computer Science Soegijapranata Catholic University Semarang Indonesia

Indonesia had been suffered by earthquake and tsunami for many centuries. Since many lives have taken by tsunami strikes, alert and response system are very important as important part of Disaster Risk Reduction, especially in area with high population density. This research conducted in Kangkung fishing village in Bandar Lampung coastal area which is an earthquake and tsunami prone area. The aim of the research is to study alert and response of Community Based Disaster Risk Reduction. The research conducted by qualitative method and purposive-descriptive approach. There were 53 respondents which participated in the survey and interview. It is reported that "Smart Resilient City"model suitable for community needs of alert and response of earthquake and tsunami disaster. This research meets conclusion that "Smart Resilient City"model may become a great solution in Community Based Disaster Risk Reduction to cope with the hazard of earthquake and tsunami comprehensively and sustainably. © Published under licence by IOP Publishing Ltd.

关键词： Surveys

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Effects of Fir-Wood Biochar on Ch4 Oxidation Rates and Methanotrophs in Landfill Cover Soils Packed at Three Different Proctor Compaction Levels

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SSRN 2023年

作者： Yi, Susan C. Heijbroek, Anne Cutz, Luis Pillay, Stephanie de Jong, Wiebren Abeel, Thomas Gebert, Julia Delft University of Technology Faculty of Mechanical Maritime and Materials Engineering Leeghwaterstraat 39 Delft2628 CB Netherlands Delft University of Technology Faculty of Electrical Engineering Mathematics and Computer Science Van Mourik Broekmanweg 6 Delft2628 XE Netherlands Broad Institute of MIT and Harvard Infectious Disease and Microbiome Program 415 Main St. CambridgeMA02142 United States

Application of biochar to landfill cover soils can purportedly improve methane (CH4) oxidation rates. However, understanding of the combined effects of soil texture, compaction, and biochar on activity and composition of the methanotrophs is limited. The amendment of wood biochar on two differently textured landfill cover soils at three compaction levels of the Proctor density were explored by analyzing changes in soil physical properties relevant to methane oxidation, the effects on CH4 oxidation rates and on the composition of the methanotrophic community. Loose soils with and without biochar were pre-incubated to equally elevate the CH4 oxidation rates. Hereafter, soils were compacted and re-incubated. Methane oxidation rates, gas diffusivity, water retention characteristics and pore size distribution were analyzed on the compacted soils. Abundance of methanotrophic bacteria (MOB) was determined at the end of both the pre-incubation tests and the incubation tests of the packed samples. Biochar significantly increased porosity at all compaction levels, resulting in enhanced diffusion coefficients. Also, a re-distribution in pore sizes was observed. Increased gas diffusivity from low compaction and amendment of biochar, however, did not reflect higher methane oxidation rates due to high diffusive oxygen fluxes over the limited height of the compacted soil specimens. All soils, with and without biochar, were strongly dominated by type II methanotrophs. In the sandy soil, biochar amendment strongly increased MOB abundance, which could be attributed to a corresponding increase in the abundance of Methylocystis species, while in the clayey soil no such response was observed. Compaction did not change the community composition in either soil. Biochar addition to landfill cover soils may not always enhance methanotrophic activity and hence reduce fugitive methane emissions with the effect being soil-specific. However, especially in finer and more compacted soils, biochar

关键词： Compaction

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Grafted AlGaAs/GeSn Optical Pumping Laser Operating up to 130 K

arXiv

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arXiv 2024年

作者： Zhou, Jie Vincent, Daniel Acharya, Sudip Ojo, Solomon Abrand, Alireza Liu, Yang Gong, Jiarui Liu, Dong Haessly, Samuel Shen, Jianping Xu, Shining Li, Yiran Lu, Yi Stanchu, Hryhorii Mawst, Luke Claflin, Bruce Mohseni, Parsian K. Ma, Zhenqiang Yu, Shui-Qing Department of Electrical and Computer Engineering University of Wisconsin - Madison Madison53706 United States Department of Electrical Engineering University of Arkansas FayettevilleAR72701 United States Microelectronics-Photonics Program University of Arkansas FayettevilleAR72701 United States Department of Electrical and Microelectronic Engineering Rochester Institute of Technology RochesterNY14623 United States Air Force Research Laboratory Wright-Patterson AFB OH45433 United States

Group IV GeSn double-heterostructure (DHS) lasers offer unique advantages of a direct bandgap and CMOS compatibility. However, further improvements in laser performance have been bottlenecked by limited junction properties of GeSn through conventional epitaxy and wafer bonding. This work leverages semiconductor grafting to synthesize and characterize optically pumped ridge edge-emitting lasers (EELs) with an AlGaAs nanomembrane (NM) transfer-printed onto an epitaxially grown GeSn substrate, interfaced by an ultrathin Al2O3 layer. The grafted AlGaAs/GeSn DHS lasers show a lasing threshold of 11.06 mW at 77 K and a maximum lasing temperature of 130 K. These results highlight the potential of the grafting technique for enhancing charge carrier and optical field confinements, paving the way for room-temperature electrically injected GeSn lasers. Copyright © 2024, The Authors. All rights reserved.

关键词： Wafer bonding

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Strategic Planning and Knowledge Management Approaches as input to remote area strategic plans: A Case study in Aru Islands Regency Maluku Province 8

Strategic Planning and Knowledge Management Approaches as in...

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8th International Conference on ICT for Smart Society, ICISS 2021

作者： Irena Gutandjala, Ilona Harso Supangkat, Suhono Lumban Gaol, Ford Rianti, Benny Bina Nusantara University BINUS Graduate Program-Computer Science Computer Science Department Jakarta11480 Indonesia Bandung Institute of Technology Smart City and Community Innovation Center School of Electrical and Informatics Engineering Bandung Indonesia Information Systems Department BINUS Online Learning Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781665416979

Knowledge is an important asset in an organization. Aru Islands District is one of the districts in Maluku Province. The Government of Aru Islands District Maluku has a vision and mission as outlined in the Regional Strategic Plan or commonly referred to as RENSTRA. This vision and mission are an activity that requires a policy direction that is planned and integrated with the strategic environment of all related aspects. The strategic plan is then realized with the implementation of the government with regional autonomy which is the modern governance in realizing quality public services, fast, easy, fair and unlimited for the welfare and progress of the region. In this research will be used a strategic approach as input from the analysis with knowledge management and assessment of the condition of Aru district. © 2021 IEEE.

关键词： Strategic planning

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Innovative Integration of Machine Learning Predictive Models Within Blockchain Frameworks for Supply Chain Fault Tolerance 1st

Innovative Integration of Machine Learning Predictive Models...

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1st International Conference on Advanced Network Technologies and Computational Intelligence, ICANTCI 2024

作者： Kaur, Jatinder Rusho, Maher Ali Yogi, Kottala Sri Soni, Mukesh Raparthi, Mohan Garg, Yakshit Department of Computer Science and Engineering Lovely Professional University Jalandhar Phagwara India Degree Program University of Colorado Boulder Boulder United States Telangana Hyderabad India Dr. D. Y. Patil Vidyapeeth Pune India Dr. D. Y. Patil School of Science and Technology Tathawade Pune India Alphabet Life Science Texas Dallas75063 India Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura India

ISBN: (纸本)9783031860683

The creative incorporation of machine learning predictive models into blockchain frameworks appears as a game-changing approach for augmenting fault tolerance and increasing operational resilience in the dynamic environment of supply chain management. The potential, results, and implications of the integration are examined in this paper, providing a holistic perspective on its effect on contemporary supply networks. The essay starts by discussing the ever-changing difficulties encountered by supply chain networks operating in the modern global economy. Fault tolerance in the supply chain is becoming a pressing issue, calling for creative solutions to minimize interruptions and maximize efficiency. The importance of using machine learning predictive models into blockchain frameworks is outlined in the introduction, which also provides context for the rest of the paper. Methods used to test the integration's usefulness are described in the research paper. Logical regression, random forests, CNNs, SVMs, and LSTM models are all part of this category of cutting-edge machine learning methods. Machine learning algorithms in blockchain frameworks may protect supply networks from catastrophic breakdowns. The suggested strategy beats conventional models in accuracy (92%), precision (88%), recall (93%), F1-Score (90%), MAE (0.12), and MSE (0.15). The recommended method has a higher MSE than traditional models. The findings suggest that supply chain networks anticipate future occurrences and identify issues *** a result, businesses will be able to prevent and correct problems like shipment delays and stock-outs. The danger of data tampering and fraudulent activities has also been reduced thanks to the use of blockchain technology, which has improved data integrity and trust among supply chain players. This impact is shown by a 30% decrease in data tampering events inside the supply chain. The revolutionary potential of the novel integration of machine learning prediction

关键词： Supply chain management

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Optimizing Photovoltaic Power Production in Partial Shading Conditions Using Dandelion Optimizer (DO)-Based MPPT Method

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Processes 2023年第8期11卷

作者： Sajid, Injila Gautam, Ayushi Sarwar, Adil Tariq, Mohd Liu, Hwa-Dong Ahmad, Shafiq Lin, Chang-Hua Sayed, Abdelaty Edrees Department of Electrical Engineering ZHCET Aligarh Muslim University Aligarh202002 India Department of Electrical and Computer Engineering Florida International University MiamiFL33174 United States Undergraduate Program of Vehicle and Energy Engineering National Taiwan Normal University Taipei106 Taiwan Industrial Engineering Department College of Engineering King Saud University Riyadh11421 Saudi Arabia Department of Electrical Engineering National Taiwan University of Science and Technology Taipei106 Taiwan

This research proposes the dandelion optimizer (DO), a bioinspired stochastic optimization technique, as a solution for achieving maximum power point tracking (MPPT) in photovoltaic (PV) arrays under partial shading (PS) conditions. In such scenarios, the overall power output of the PV array is adversely affected, with shaded cells generating less power and consuming power themselves, resulting in reduced efficiency and local hotspots. While bypass diodes can be employed to mitigate these effects by redirecting current around shaded cells, they may cause multiple peaks, making MPPT challenging. Therefore, metaheuristic algorithms are suggested to effectively optimize power output and handle multiple peaks. The DO algorithm draws inspiration from the long-distance movement of a dandelion seed, which relies on the force of the wind. By utilizing this bioinspired approach, the DO algorithm can successfully capture the maximum power point (MPP) under different partial shading scenarios, where traditional MPPT algorithms often struggle. An essential contribution of this research lies in the examination of the performance of the proposed algorithm through simulation and real-time hardware-in-the-loop (HIL) results. Comparing the DO algorithm with the state-of-the-art algorithms, including particle swarm optimization (PSO) and cuckoo search (CS), the DO algorithm outperforms them in terms of power tracking efficiency, tracking duration, and the maximum power tracked. Based on the real-time HIL results, the DO algorithm achieves the highest average efficiency at 99.60%, surpassing CS at 96.46% and PSO at 94.74%. These findings demonstrate the effectiveness of the DO algorithm in enhancing the performance of MPPT in PV arrays, particularly in challenging partial shading conditions. © 2023 by the authors.

关键词： Efficiency

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