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Extended Drude Model for Intraband-Transition-Induced Optical Nonlinearity

Physical Review Applied 2019年第6期11卷 064062-064062页

作者： Heng Wang Kang Du Chuhao Jiang Zhiqiang Yang Lixia Ren Wending Zhang Soo Jin Chua Ting Mei MOE Key Laboratory of Material Physics and Chemistry under Extraordinary Conditions and Shaanxi Key Laboratory of Optical Information Technology School of Science Northwestern Polytechnical University Xi’an 710072 China Department of Electrical and Computer Engineering National University of Singapore 4 Engineering Drive 3 Singapore 117583 LEES Program Singapore-MIT Alliance for Research & Technology (SMART) 1 CREATE Way #10-01 CREATE Tower Singapore 138602

No existing model has completely explained the physics of the optical nonlinearity for epsilon-near-zero materials, which have recently emerged as candidates for design and fabrication of active nanophotonic devices. We propose to extend the Drude model by adopting a weighted electron effective mass, which takes into account the electron distribution in the nonparabolic conduction band. The extended Drude model is able to interpret the cause of the nonlinearity and provide a functional relationship between the refractive index and wavelength. Both the band nonparabolicity and the temperature-dependent mobility are responsible for the intraband-transition-induced optical nonlinearity. The spectrally resolved nonlinear refractive index and nonlinear susceptibilities are obtained from this model. The results can be applied to other transparent conducting oxides and will help in the design and modeling of spectral responses of nonlinear plasmonic devices.

关键词： Electronic transitions Nonlinear optical susceptibility Optoelectronics Plasmonics Ultrafast optics Thin films Free-electron model Ultrafast pump-probe spectroscopy

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Food Self-sufficiency Decision Support Model Based on Provinces in Indonesia Using the Clustering Method

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Journal of Physics: Conference Series 2019年第1期1255卷

作者： M. Safii Mochamad Wahyudi Solikhun Muhammad Zarlis Syahril Effendi Doctoral Program Faculty of Computer Science and Information Technology Universitas Sumatera Utara Indonesia Faculty of Computer Science and Information Technology Universitas Sumatera Utara Indonesia

In Indonesia rice is a staple food as a major source of carbohydrates. Rice is also a staple food of the people of most countries in Asia and even most of the population in the world. Food security for Indonesia is closely linked to the adequacy of rice provision. The indicators of national food security are (1) the availability of food every time; (2) the ability or purchasing power of the people towards food; (3) guarantee of distribution and supply of food; and (4) the ability to import in urgent conditions. Rice as a rice-producing crop is a very important commodity for Indonesia, besides being the main food producer, rice commodity is also the main source of income from millions of farmers. The availability of rice at affordable prices to communities is an important factor for national security, security and stability. Indonesia has a large population, the fourth largest in the world after China, America and India. Dependence on rice imports has a high risk not only of food dependency on other countries, but also limited availability of rice in the international market. In 1977 Indonesia imported 2 million tons of rice and accounted for one third of the rice available on the international market, affecting the price of rice. Increased rice production can be achieved through increased productivity with the application of technology varieties and better cultivation and expansion of planting areas with increased intensity of planting and printing or opening of new rice cultivation area. Based on the above explanation, the researcher uses Data Mining Clustering with K-Means to get the assessment result of all rice production provinces. With this method the results of the research can be used as a model of decision makers for the government to give priority attention to areas that have the potential to increase rice production.

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Implementation on Indonesian property real estate industry based on service oriented architecture

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IOP Conference Series: Materials Science and Engineering 2020年第1期725卷

作者： Ahmad Nurul Fajar Nunung Nurul Qomariyah Albert Baihaqi Siregar Information Systems Management Department BINUS Graduate Program-Master of Information Systems Management Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department Faculty of Computing and Media Bina Nusantara University Jakarta Indonesia 11480 Department of Information Technology Universitas Sumatera Utara Medan Indonesia

This study focuses on the implementation of business property in real estate market. This is due to inability of the current technology to support the property products. Some people feel uncomfortable to buy houses from the online market. Buyers need to be very careful to deal with the sellers as the houses price is considered quite expensive. On the other hand, improving real estate market is still a challenge. This business still needs a physical representation, although it can be sold from the online market. In this paper, we propose the Service Oriented Architecture (SOA) system of virtual reality and drone. We use drone to help scanning the property units and then make 3D models with visual mapping so it can be run in a virtual reality environment, video 360. In real estate, business process can be developed in various ways. Our proposed SOA in this study can be used to integrate all of them.

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Design Securing Online Payment Transactions Using Stegblock Through Network Layers

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IOP Conference Series: Materials Science and Engineering 2020年第1期879卷

作者： E Ardhianto A Trisetyarso W Suparta B S Abbas C H Kang Computer Science Departement BINUS Graduate Program – Doctor of Computer Science Bina Nusantara University Jakarta Indonesia. Faculty of Information Technology Universitas Stikubank Semarang Indonesia. Departement of Informatics Universitas Pembangunan Jaya South Tangerang Banten Indonesia

The aim of this work is designing a safe online payment activities scheme using steganography techniques with stegblock concept. These works are implemented at the computers network layers. The stegblock will convert the transactions data which sent among network into other data's form, it means the data such as ID Number, Account Number, Passwords and others are converted with other data called cover. Finally, the system sends the cover without the real data, it just represented data and able to read by the receiver. The result shows that this design provides data security, undetectability, and integrity for payment transactions using networks.

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Ensembling Handcarafted Features to Representation Learning for Content Based Image Classification

Ensembling Handcarafted Features to Representation Learning ...

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IEEE Punecon

作者： Rik Das Khushbu Kumari P.K. Manjhi Sudeep D. Thepade Dept.of Post Graduate Program-Information Technology Xavier Institute of Social Service Ranchi Jharkhand India Dept.of Computer Applications Yogoda Satsanga Mahavidyalaya Ranchi Jharkhand India Dept.of Mathematics Vinoba Bhave University Hazaribag Jharkhand India Computer Engineering Dept. Pimpri Chinchwad College of Engineering Maharashtra India

ISBN: (数字)9781728119243

ISBN: (纸本)9781728119250

Content Based Image Classification (CBIC) has garnered massive interest within research community for it's applications and significances in multiple areas. This paper has explored a robust feature vector definition scheme based on fusion of handcrafted features to neural network based feature extraction, popularly known as representation learning. The extracted handcrafted features are primarily evaluated with classification results to identify the best color space for significant descriptor definition. Further, feature vector extraction using pre-trained Convolution Neural Network is exercised for evaluating classification performance with representation learning features. Finally, an early fusion of handcrafted feature and representation learning feature is accomplished to examine the classification performance of the model. The test bed is prepared using Wang dataset having 10 different categories of 1000 images. Six different color spaces are explored to finalize the best fit for feature extraction with the proposed handcrafted technique. Performance analyses of the proposed model have turned out to be superior compared to state-of-the-art techniques and have established the importance of fusion based approach in enhancing the accuracy of content based image classification.

关键词： Colour Intervals Color Space Hand-Crafted Features Representation Learning Fusion Classification color spaces Image classification Fusion reactions Fusion, biological Taxonomy FUSION fusion (melting) Feature extraction Learning based test bed Neural network Eigenvector

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Work in Progress – Establishing a Master program in Cyber Physical Systems: Basic Findings and Future Perspectives

Work in Progress – Establishing a Master Program in Cyber P...

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International Conference on Promising Electronic Technologies (ICPET)

作者： Isam Ishaq Rashid Jayousi Salaheddin Odeh Ezzaldeen Edwan Asmaa Shaheen Mohamed Elnaggar Ahmed Elagha Samy Salamah Christian Weber Hasan Abu Rasheed Raimund Kirner Martina Doolan Hamidreza Ahmadian Roman Obermaisser Dhiah el Diehn I. Abou-Tair Ala Khalifeh Sahel Alouneh Zaid Alhalhouli Khalid Alemerien Faiez Gargouri Bassem Bouaziz Nadia Aloui Mohammad Saleh Computer Engineering and Science Departments Al-Quds University Jerusalem Palestine Engineering Program and Computer Department Palestine Technical College - Deir El-Balah Deir El-Balah Palestine Institute of Knowledge Based Systems & Knowledge Management University of Siegen Siegen Germany University of Siegen Siegen Germany School of Engineering and Computer Science University of Hertfordshire Hatfield UK Chair of Embedded Systems University of Siegen Siegen Germany German Jordanian University Amman Jordan School of Electrical Engineering and Information Technology German Jordanian University Amman Jordan Computer and Information Technology Department Tafila Technical University Tafila Jordan Higher Institute of Computer Science and Multimedia University of Sfax Sfax Tunisia Higher Institute of Applied Sciences and Technology of Mateur University of Carthage Mateure Tunisia KTH Royal Institute of Technology Stockholm Sweden

This paper reports on the basic findings and future perspectives of a capacity building project funded by the European Union. The International Master of Science on Cyber Physical Systems (MS@CPS) is a collaborative project that aims to establish a master program in cyber physical systems (CPS). A consortium composed of nine partners proposed the project. Three partners are European and from Germany, UK and Sweden; while the other six partners are from the South Mediterranean region and include: Palestine, Jordan and Tunisia. The consortium is led by the University of Siegen in Germany who also manages the implementation of the work packages. CPS is an emerging engineering subject with significant economic and societal implications, which motivated the consortium to propose the establishment of a master program to offer educational and training opportunities at graduate level in the fields of CPS. In this paper, CPS as a field of study is presented with an emphasis on its importance, especially with regard to meeting local needs. A brief description of the project is presented in conjunction with the methodology for developing the courses and their learning outcomes.

关键词： computer science Internet of Things Industries Knowledge engineering Embedded systems Europe Collaboration

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Syllables sound signal classification using multi-layer perceptron in varying number of hidden-layer and hidden-neuron 2

Syllables sound signal classification using multi-layer perc...

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2nd International Conference on Engineering and technology for Sustainable Development, ICET4SD 2017

作者： Kristomo, Domy Hidayat, Risanuri Soesanti, Indah Department of Electrical Engineering and Information Technology Universitas Gadjah Mada Grafika Street No. 2 Yogyakarta55281 Indonesia Study Program of Computer Engineering STMIK Akakom Yogyakarta Raya Janti Street 143 Karang Jambe Yogyakarta55198 Indonesia

The research on signal processing of syllables sound signal is still the challenging tasks, due to non-stationary, speaker-dependent, variable context, and dynamic nature factor of the signal. In the process of classification using multi-layer perceptron (MLP), the process of selecting a suitable parameter of hidden neuron and hidden layer is crucial for the optimal result of classification. This paper presents a speech signal classification method by using MLP with various numbers of hidden-layer and hidden-neuron for classifying the Indonesian Consonant-Vowel (CV) syllables signal. Five feature sets were generated by using Discrete Wavelet Transform (DWT), Renyi Entropy, Autoregressive Power Spectral Density (AR-PSD) and Statistical methods. Each syllable was segmented at a certain length to form a CV unit. The results show that the average recognition of WRPSDS with 1, 2, and 3 hidden layers were 74.17%, 69.17%, and 63.03%, respectively. © The Authors, published by EDP Sciences, 2018.

关键词： Neurons

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Evaluation of Maturity Level of information and Communication technology (ICT) Governance with CobIT 5.0 Case Study: STMIK Pelita Nusantara Medan

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Journal of Physics: Conference Series 2019年第1期1255卷 012046-012046页

作者： Sihotang, Hengki Tamando Efendi, Syahril Jollyta, Deny Husain Zarlis, M Doctoral Program Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan-Indonesia Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan-Indonesia

In entering competition the quality and predicate best the national and the quality of graduates, college trying to use information technology as an instrument for might win this competition. That IT can be used to fulfill and support the system in college, it needs assessment from information technology regularly. One method of conducting evaluation of the performance of the department of information technology is to use the framework Cobit 5 as yardstick efficiency in the use of information technology currently consisting of 5 (five) domain namely: EDM, APO, DSS, MEA A measuring instrument his as. With this method, researchers trying to make it a blueprint as the end result of utilization of information technology in college, so the management can plan exactly how of development of information technologies company to the next few years. An evaluation, known level capabilities inside the area mea and APO is entirely located at the level of 1 (performed) with the level of the target to be achieved is the level of 3 (established). Weakness governance information technology in STMIK Pelita Nusantara Medan is the lack of formalization rules and procedures management information technology. To reduce the gap between capability the current level was level and capability to be achieved, so STMIK Pelita Nusantara Medan must meet PA2.1, PA2.2, PA3.1 and PA3.2, that capability the current level was that is at the level of 1 could rise to the level of 3. Along with that, STMIK Pelita Nusantara Medan moved closer to the purpose..

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DeePMD-kit v2: A software package for Deep Potential models

arXiv

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arXiv 2023年

作者： Zeng, Jinzhe Zhang, Duo Lu, Denghui Mo, Pinghui Li, Zeyu Chen, Yixiao Rynik, Marián Huang, Li'ang Li, Ziyao Shi, Shaochen Wang, Yingze Ye, Haotian Tuo, Ping Yang, Jiabin Ding, Ye Li, Yifan Tisi, Davide Zeng, Qiyu Bao, Han Xia, Yu Huang, Jiameng Muraoka, Koki Wang, Yibo Chang, Junhan Yuan, Fengbo Bore, Sigbjørn Løland Cai, Chun Lin, Yinnian Wang, Bo Xu, Jiayan Zhu, Jia-Xin Luo, Chenxing Zhang, Yuzhi Goodall, Rhys E.A. Liang, Wenshuo Singh, Anurag Kumar Yao, Sikai Zhang, Jingchao Wentzcovitch, Renata Han, Jiequn Liu, Jie Jia, Weile York, Darrin M. Weinan, E. Car, Roberto Zhang, Linfeng Wang, Han Laboratory for Biomolecular Simulation Research Institute for Quantitative Biomedicine Department of Chemistry and Chemical Biology Rutgers University PiscatawayNJ08854 United States AI for Science Institute Beijing100080 China DP Technology Beijing100080 China Academy for Advanced Interdisciplinary Studies Peking University Beijing100871 China HEDPS CAPT College of Engineering Peking University Beijing100871 China College of Electrical and Information Engineering Hunan University Changsha China Yuanpei College Peking University Beijing100871 China Program in Applied and Computational Mathematics Princeton University PrincetonNJ08540 United States Department of Experimental Physics Comenius University Mlynská Dolina F2 Bratislava842 48 Slovakia Center for Quantum Information Institute for Interdisciplinary Information Sciences Tsinghua University Beijing100084 China Center for Data Science Peking University Beijing100871 China ByteDance Research Zhonghang Plaza No. 43 North 3rd Ring West Road Haidian District Beijing China College of Chemistry and Molecular Engineering Peking University Beijing100871 China Baidu Inc. Beijing China Key Laboratory of Structural Biology of Zhejiang Province School of Life Sciences Westlake University Zhejiang Hangzhou China Westlake AI Therapeutics Lab Westlake Laboratory of Life Sciences and Biomedicine Zhejiang Hangzhou China Department of Chemistry Princeton University PrincetonNJ08544 United States SISSA Scuola Internazionale Superiore di Studi Avanzati Trieste34136 Italy Laboratory of Computational Science and Modeling Institute of Materials École Polytechnique Fédérale de Lausanne Lausanne1015 Switzerland Department of Physics National University of Defense Technology Hunan Changsha410073 China State Key Lab of Processors Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China School of Electronics Engineerin

DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials (MLP) known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version of DeePMD-kit offers numerous advanced features such as DeepPot-SE, attention-based and hybrid descriptors, the ability to fit tensile properties, type embedding, model deviation, Deep Potential - Range Correction (DPRc), Deep Potential Long Range (DPLR), GPU support for customized operators, model compression, non-von Neumann molecular dynamics (NVNMD), and improved usability, including documentation, compiled binary packages, graphical user interfaces (GUI), and application programming interfaces (API). This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, the article benchmarks the accuracy and efficiency of different models and discusses ongoing developments. © 2023, CC BY-NC-ND.

关键词： Molecular dynamics

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Bridge Sub Structure Defect Inspection Assistance by using Deep Learning

Bridge Sub Structure Defect Inspection Assistance by using D...

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IEEE International Conference on Awareness Science and technology

作者： Pravee Kruachottikul Kittikul Kovitanggoon Nagul Cooharojananone Donnaphat Trakulwaranont Gridsada Phanomchoeng Kanokwan Atchariyachanvanich Thira Chavarnakul Technopreneurship and Innovation Management Program Graduate School Chulalongkorn University Bangkok Thailand Department of Mathematics and Computer Science Chulalongkorn University Bangkok Thailand Department of Mechanical Engineering Chulalongkorn University Bangkok Thailand Department of Commerce Chulalongkorn University Bangkok Thailand Faculty of Information Technology King Mongkut’s Institute of Technology Ladkrabang Bangkok Thailand

Road transportation is the most popular transportation in Thailand, which the top two highest traffic are the region-to-region highways;and then inter-city highways. Therefore, the regular maintenance is required to maintain the good condition due to road safety. The most significant process of bridge inspection procedures is sub structure inspection, which requires visual inspection as an initial step. This process is used to quick determine the damage severity i.e. appearance and crack that may cause damage to the structure strength. The current process requires that the experienced maintenance engineer to be on the field in order to visual inspect and estimate whether the maintenance is required. Yet, due to the limitation of number of expert engineers to be on the field, the photo verification is introduced to assist them so that they are no need on every inspection site. However, using human to verify has no standard and uncontrollable. They need to have experience and good knowledge. As well as it is highly depended on individual decisionmaking skill. Thus, in this paper, the deep learning technique will be presented to assist the expert for quality inspection process of bridge sub structure images. That is using image enhancement and then image splitting and overlapping for image pre-processing. After that applying CNNs for object classification. As a result, the total accuracy is 89% based on 3926 dataset.

关键词： Bridges Inspection Machine learning Maintenance engineering Convolution Training Concrete

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