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Visualization of Programming Skill Structure by Log-Data Analysis with Decision Tree

Procedia computer Science 2019年 159卷 582-589页

作者： Shinichi Oeda Mutsumi Chieda Department of Information and Computer Engineering National Institute of Technology Kisarazu College 11-1 Kiyomidaihigashi 2-chome Kisarazu City Chiba Japan Advanced Course of Control and Information Engineering National Institute of Technology Kisarazu College 11-1 Kiyomidaihigashi 2-chome Kisarazu City Chiba Japan

To evaluate the ability of a programmer in universities or staff agencies, evaluators conduct examination in which applicants solve problems, or they refer to the applicants’ GitHub and review their code. However, the collected source code is evaluated by a human under present conditions. This leads to two problems: many source codes cannot be evaluated simultaneously, and it is difficult to maintain consistency in the evaluation criteria among evaluators. We propose methods to estimate the current skill of the programmer, which can be used by the evaluators to understand an applicant’s skill by analyzing the collected source code automatically. In particular, this study visualizes the feature of the students’ source code in term of quarters using a decision tree to estimate the programming skill.

关键词： Programming lesson Beginner Programmer Decision Tree Random Forest Latent Skill EDM(Educational Data Mining)

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Implementation of AES algorithm to secure data in smart devices

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AIP Conference Proceedings 2020年第1期2282卷

作者： S. Aruna K. Meenakshi 1Department of Computer Science and Engineering SRM Institute of Science and Technology Chennai India 2Department of Computer Science and Engineering SRM Institute of Science and Technology Chennai India

This paper presents the idea of securing the smart devices used at our home or work spaces. Smart mirrors are devices which are equipped with peripherals such as a one-way mirror placed on top of LED monitor, Raspberry pi, Microphones and Speakers. Smart mirrors eliminate the need for checking our phones for latest news or updates. It provides the necessary information such as clock, calendar, news, weather reports. It displays all the notifications of our mobile devices which is connected via LAN. It interacts with the user through verbal commands and provides compliments as well. It has a web interface which can be used by the user/owner of the smart mirror to configure, start/stop the service. The data stored in the device is encrypted using 128-bit AES Algorithm. The encryption is done through a USB device which stores the 128-bit long key.

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Master equations and quantum trajectories for squeezed wave packets

arXiv

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arXiv 2021年

作者： Gross, Jonathan A. Baragiola, Ben Stace, T.M. Combes, Joshua Center for Quantum Information and Control University of New Mexico AlbuquerqueNM87131-0001 United States Institut Quantique Université de Sherbrooke SherbrookeQCJ1K 2R1 Canada Centre for Quantum Computation & Communication Technology School of Science RMIT University MelbourneVIC3000 Australia ARC Centre for Engineered Quantum System Department of Physics University of Queensland BrisbaneQLD4072 Australia Department of Electrical Computer and Energy Engineering University of Colorado Boulder BoulderCO80309 United States

The interaction between matter and squeezed light has mostly been treated within the approximation that the field correlation time is small. Methods for treating squeezed light with more general correlations currently involve explicitly modeling the systems producing the light. We develop a general purpose input-output theory for a particular form of narrowband squeezed light-a squeezed wave-packet mode-that only cares about the statistics of the squeezed field and the shape of the wave packet. This formalism allows us to derive the input-output relations and the master equation. We also consider detecting the scattered field using photon counting and homodyne measurements which necessitates the derivation of the stochastic master equation. The non Markovian nature of the field manifests itself in the master equation as a coupled hierarchy of equations. We illustrate these with consequences for the decay and resonance fluorescence of two-level atoms in the presence of such fields. Copyright © 2021, The Authors. All rights reserved.

关键词： Wave packets

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Halal industry 4.0 model for SMEs

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AIP Conference Proceedings 2022年第1期2617卷

作者： Raja Mohd Tariqi Raja Lope Ahmad Wan Azlan Wan Hassan Suziyanti Marjudi Azhar Hamid Mohd Fahmi Mohamad Amran 1Computing Department Faculty of Communication Visual Art and Computing University Selangor 45600 Bestari Jaya Selangor Malaysia 2Software Engineering Department Faculty of Computer Science & Information Technology Universiti Tun Hussein Onn Malaysia 86400 Johor Malaysia 3Computer Science Department Faculty of Science and Defense Technology Universiti Pertahanan Nasional Malaysia Kem Sungai Besi 57000 Kuala Lumpur Malaysia

The commitment between SMEs and stakeholders is very important in coordinating interrelated Halal business functions. However, Halal SMEs players have major obstacles in integrating information that can support their stakeholders with operational and functional requirements. Moreover, there are scanty supply chain comprehensive models that can engage Halal SMEs participants for digitalization. Therefore, the purpose of this study is to construct the Halal Industry 4.0 Model (HI4.0) in order to improve business engagement among SMEs within the Halal Industry 4.0 supply chain. Analysis and evaluation were conducted based on application of previous research work by using systematic literature review and thematic analysis to identify the elements and processes involved in the implementation of Halal related businesses. The outcomes show that HI4.0 consists of five main components which are Halal Knowledge Repository, Halal Supply Chain Management Systems Implementation Framework, Halal Smart Application Ecosystem, Halal Infrastructure, and Halal Integrity Assurance System. The findings contribute to the Halal Industry 4.0 framework development in which the model can benefit stakeholders' engagement with governing bodies, consumers and SMEs.

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Feasibility study of a coherent feedback squeezer

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Physical Review A 2020年第3期101卷 033802-033802页

作者： Shota Yokoyama Daniel Peace Warit Asavanant Takeyoshi Tajiri Ben Haylock Moji Ghadimi Mirko Lobino Elanor H. Huntington Hidehiro Yonezawa Centre for Quantum Computation and Communication Technology and School of Engineering and Information Technology The University of New South Wales Canberra ACT 2600 Australia Centre for Quantum Computation and Communication Technology and Centre for Quantum Dynamics Griffith University Brisbane QLD 4111 Australia Department of Applied Physics School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-8656 Japan School of Engineering and Information Technology The University of New South Wales Canberra ACT 2600 Australia Institute of Industrial Science The University of Tokyo 4-6-1 Komaba Meguro-ku Tokyo 153-8505 Japan Centre for Quantum Dynamics Griffith University Brisbane QLD 4111 Australia Queensland Micro and Nanotechnology Centre Griffith University Brisbane QLD 4111 Australia Centre for Quantum Computation and Communication Technology and Research School of Electrical Energy and Materials Engineering College of Engineering and Computer Science Australian National University Canberra ACT 2600 Australia

We investigate a coherent feedback squeezer that uses quantum coherent feedback (measurement-free) control. Our squeezer is simple, easy to implement, robust to the gain fluctuation, and broadband compared to the existing squeezers because of the negative coherent feedback configuration. We conduct a feasibility study that looks at the stability conditions for a feedback system to optimize the designs of real optical devices. The feasibility study gives fabrication tolerance necessary for designing and realizing the actual device. Our formalism for the stability analysis is not limited to optical systems but can be applied to the other bosonic systems.

关键词： Quantum feedback Quantum information processing with continuous variables Quantum optics

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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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Development of high batteries charges management system

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AIP Conference Proceedings 2021年第1期2339卷

作者： Liew Hui Fang Rosemizi Abd Rahim Nur Shazwanie Abdul Shukor 1Department of Electrical Engineering Faculty of Engineering Technology Universiti Malaysia Perlis Sungai Chuchuh 02100 Padang Besar (U) Perlis Malaysia 2School of Computer and Communication Engineering Universiti Malaysia Perlis Pauh Putra Campus 02600 Arau Perlis Malaysia

Nowadays, most smartphone use lithium rechargeable batteries because this kind of battery is mostly common used and they have some good features, such as high energy density, a long life cycle, wide operating range in temperature, and the quality of being robust against short circuit, but a couple of extenuating circumstance can cause them to explode. Based on the limitations that have been highlighted previously, this project aims to develop a high speed batteries charger management system to monitor the current into and/or out of the cell. This project will consist of two main parts, which are the development batteries charges system and monitoring batteries charges system. They are various type of batteries in this world but for this project, it will be focusing on the three type of performance comparison between the Lithium-Ion (Li-Ion), Nickel-Metal Hydride (NiMh) and Nickel Cadmium (NiCd) battery. From this high speed batteries charger will monitoring by using Arduino board, it will get a data to display on the I2C LCD without have to measure manually the batteries charges system. The using of this batteries management system charger will make human life more efficient, easy and convenience. One of the primary tasks for the batteries management system is to monitor the cell capacity battery. The following sections also describe the design for measuring battery voltage, current, and cell capacity as well as measuring other important parameters.

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Design of artificial piezo-leaf wind energy harvesting system monitoring based on Blynk apps

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AIP Conference Proceedings 2021年第1期2339卷

作者： Liew Hui Fang Resemi Abd Rahim Siti Naimah 1Department of Electrical Engineering Faculty of Engineering Technology Universiti Malaysia Perlis Sungai Chuchuh 02100 Padang Besar (U) Perlis Malaysia 2School of Computer and Communication Engineering Universiti Malaysia Perlis Pauh Putra Campus 02600 Arau Perlis Malaysia

This project presents a novel artificial piezo-leaf wind power harvester an improved approach using piezoelectric effect for an automatic monitoring system developed. This project used a piezo ceramic sensor as the main device to generate energy from waste energy of wind. Piezo ceramic is a material that will convert from the vibration with sufficient energy to an electrical energy. The piezo ceramic sensor installed in series and parallel for as much as possible till it can regulate voltage up to 1.0 V which by detect the vibration of wind and convert into electrical energy. The challenge of the previous renewable energy is energy crisis, the low input of rectifier circuit and lastly and method to monitoring the system. However, the purpose of this project is to develop the simplest an d practice the usage of renewable energy. Besides, piezo can convert mechanical energy (motion) to electrical energy for sensing or energy harvesting. Moreover, to develop the artificial piezo-leaf by using a piezo mechanism. Next, the AC-DC harvesting circuit were construct to function as transform alternating current (AC) input signal into direct current (DC) output signal. They are used in power electronic applications where the power input of 50 Hz sine-wave AC voltage that requires power conversion for a DC output. The piezo ceramic sensor will be connected with full-wave rectifier and the output result will shows the parameters of voltage at the LCD display after connected with Arduino R3. Hence, the monitoring system has been implemented by using Wi-Fi that can be connected directly and parameter monitor and control by using Bylnk apps. Indeed, it can save more cost, time and energy.

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Utilization of DenseNet201 for diagnosis of breast abnormality

Utilization of DenseNet201 for diagnosis of breast abnormali...

引用

Machine Vision and Applications

作者： Yu, Xiang Zeng, Nianyin Liu, Shuai Zhang, Yu-Dong Department of Informatics University of Leicester LeicesterLE1 7RH United Kingdom School of Computer Science and Technology Henan Polytechnic University JiaozuoHenan454000 China Department of Instrumental and Electrical Engineering Xiamen University Xiamen361005 China College of Information Science and Engineering Hunan Normal University Changsha410000 China

As one of the leading killers of females, breast cancer has become one of the heated research topics in the community of clinical medical science and computer science. In the clinic, mammography is a publicly accepted technique to detect early abnormalities such as masses and distortions in breast leading to cancer. Interpreting the images, however, is time-consuming and error-prone for radiologists considering artificial factors including potential fatigue. To improve radiologists’ working efficiency, we developed a semi-automatic computer-aided diagnosis system to classify mammograms into normality and abnormality and thus to ease the process of making a diagnosis of breast cancer. Through transferring deep convolutional neural network DenseNet201 on the basis of suspicious regions provided by radiologists into our system, we obtained the network we termed DenseNet201-C, which achieved a high diagnostic accuracy of 92.73%. The comparison results between our method and the other five methods show that our method achieved the highest accuracy. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： computer aided diagnosis Clinical research Convolutional neural networks Deep neural networks Diseases Gait analysis Transfer learning Breast abnormalities Breast Cancer Comparison result computer aided diagnosis systems Diagnostic accuracy Medical science Potential fatigue Working efficiency

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PGD-UNet: A Position-Guided Deformable Network for Simultaneous Segmentation of Organs and Tumors

arXiv

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arXiv 2020年

作者： Li, Ziqiang Zhu, Yaping Pan, Hong Qin, A.K. School of Automation Southeast University No.2 Sipailou Nanjing210096 China School of Information and Communication Engineering Communication University of China No.1 Dingfuzhuang East Street Beijing100024 China Department of Computer Science and Software Engineering Swinburne University of Technology John St HawthornVIC3122 Australia

Precise segmentation of organs and tumors plays a crucial role in clinical applications. It is a challenging task due to the irregular shapes and various sizes of organs and tumors as well as the significant class imbalance between the anatomy of interest (AOI) and the background region. In addition, in most situation tumors and normal organs often overlap in medical images, but current approaches fail to delineate both tumors and organs accurately. To tackle such challenges, we propose a position-guided deformable UNet, namely PGD-UNet, which exploits the spatial deformation capabilities of deformable convolution to deal with the geometric transformation of both organs and tumors. Position information is explicitly encoded into the network to enhance the capabilities of deformation. Meanwhile, we introduce a new pooling module to preserve position information lost in conventional max-pooling operation. Besides, due to unclear boundaries between different structures as well as the subjectivity of annotations, labels are not necessarily accurate for medical image segmentation tasks. It may cause the overfitting of the trained network due to label noise. To address this issue, we formulate a novel loss function to suppress the influence of potential label noise on the training process. Our method was evaluated on two challenging segmentation tasks and achieved very promising segmentation accuracy in both tasks. Copyright © 2020, The Authors. All rights reserved.

关键词： Convolution

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