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检索条件"任意字段=2nd International Conference on Algorithms for Big Data, ICABD 2014"

共 223 条记录，以下是121-130 订阅

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ACM international conference Proceeding Series

ACM International Conference Proceeding Series

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2nd international conference on Software Engineering and Information Management, ICSIM 2019 - and its Workshop 2019 2nd international conference on big data and Smart Computing, ICBDSC 2019

ISBN: (纸本)9781450366427

The proceedings contain 56 papers. The topics discussed include: a scalable operational framework for requirements validation using semantic and functional models;an enhanced accuracy of a prediction model having a modified genetic algorithm with cross-average crossover;an overview of learning algorithms and inference techniques on restricted Boltzmann machines (RBMs);an analysis of parameters of convolutional neural network for fire detection;optimization of heterogeneous sensor networks with clustering mechanism using game theory algorithm;an improved initialization method using firefly movement and light intensity for better clustering performance;and a study on ELM(election pledge management for local governors model) based on machine learning-focused on on-nara document system.

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Research on Visualization of Hardware P2P Network Communication Based on STM32 2

Research on Visualization of Hardware P2P Network Communicat...

引用

2019 2nd international Symposium on Power Electronics and Control Engineering, ISPECE 2019

作者： Huiyuan, Cao Bin, Ren Renhao, Yang Department of Mechanical Engineering Dongguan Vocational and Technical College Dongguan523808 China School of Electronic Engineering and Intelligence Dongguan University of Technology Dongguan523808 China

This paper mainly studies the visual communication of P2P network based on STM32 microprocessor in the hardware direction. It illustrates the research on P2P network by many corporations and scientific research institutions. Besides, this paper points out that P2P network play an important role in the field of Internet or teaching. By designing circuit schematic diagram and PCB and selecting STM32 microprocessor, CC2530 chip, SIM800C chip, it puts up the hardware platform of this research. The other way, it uses KEIL software to write program and transplant the UCOSIII operating system, and realize the independent operation of each node. As for software, it builds the basic of P2P network communication by designing the ZIGBEE data packet protocol. In addition, it writes various data storage containers and designs trust, motivation, and encryption algorithms. Finally, the whole communication process of this research is displayed dynamically on the LCD screen in real time. In short, this study is of reference significance for future researches on P2P network at the hardware level. © Published under licence by IOP Publishing Ltd.

关键词： Liquid crystal displays

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Performance Analysis of a Dynamic Priority Scheduling Method in D2D Networks 2

Performance Analysis of a Dynamic Priority Scheduling Method...

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2nd international conference on Artificial Intelligence and big data (ICAIBD)

作者： Xin, Jianfang Zhu, Qi Liang, Guangjun Nanjing Univ Posts & Telecommun Jiangsu Key Lab Wireless Commun Nanjing 210003 Jiangsu Peoples R China Nanjing Univ Posts & Telecommun Engn Res Ctr Hlth Serv Syst Based Ubiquitous Wire Minist Educ Nanjing Jiangsu Peoples R China Anhui Polytech Univ Hefei Peoples R China

ISBN: (数字)9781728108315

ISBN: (纸本)9781728108315

In this paper, we consider a queueing model for the performance study of D2D underlay cellular network. We develop a multi-priority business model with finite buffers and priority jumps. In the considered system, priority jump strategy is set for providing transmission chance to LP data and lower dropping probability of LP queue. In addition, to show the influence of cellular users to D2D links, the probability of D2D received SINR above a certain threshold is set as success transmission probability. Then, we employ a two-dimensional Markov chain to describe queue model with priority jump for each D2D user pair. The queueing behavior is evaluated using QBD processes approach. Finally, the expressions of performance metrics are obtained and simulation results show the validity of the theoretical analysis. Moreover, the dropping probability with different jump probability are discussed by simulation analysis.

关键词： queueing model with priority jumps D2D communication Quasi-Birth-and-Death (QBD) Processes thinned Poisson point processes (PPP)

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Revisiting the Class Imbalance Issue in Software Defect Prediction 2

Revisiting the Class Imbalance Issue in Software Defect Pred...

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2nd international conference on Electrical, Computer and Communication Engineering, ECCE 2019

作者： Sohan, Md. Fahimuzzman Kabir, Md Alamgir Jabiullah, Md. Ismail Rahman, Sheikh Shah Mohammad Motiur Department of Software Engineering Daffodil International University Dhaka Bangladesh Department of Computer Science Engineering Daffodil International University Dhaka Bangladesh Department of Computer Science City University of Hong Kong Hong Kong

ISBN: (纸本)9781538691113

Software defect prediction is related to the testing area of software industry. Several methods have been developed for the prediction of bugs in software source codes. The objective of this study is to find the inconsistency of performance between imbalances and balance data set and to find the distinction of performance between single classifier and aggregate classifier (voting). In this investigation, eight publicly available data sets have collected, also seven algorithms and hard voting are used for finding precision, recall and F-1 score to predict software defect. In these collected data, two sets are almost balanced. For this investigation, these balanced data sets have converted into imbalanced sets as average non-defective and defective ratio of the other 6 data sets. The experiment result shows that performance of the two balanced data sets is lower than other six sets. After conversion of two data sets, the performance has increased as like as other six data sets. Another observation is the performance metric that shows the results of precision, recall and F1-score for voting are 0.92, 0.84 and 0.87 respectively, which are better than other single classifier. This study has been able to shows that- imbalance of non-defective and defective classes have a big impact on software defect prediction and the voting is the best performer among the classifiers. © 2019 IEEE.

关键词： Forecasting

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A Comparative Study of Machine Learning Approaches for Recommending University Faculty

A Comparative Study of Machine Learning Approaches for Recom...

引用

Sustainable Technologies for Industry 4.0 (STI), international conference on

作者： Nabila Kamal Farhana Sarker Khondaker A. Mamun Advanced Intelligent Multidisciplinary Systems Lab United International University Dhaka Bangladesh University of Liberal Arts Bangladesh (ULAB) Dhaka Bangladesh

ISBN: (数字)9781665404891

ISBN: (纸本)9781665404907

Academic program selection is a vital decision as it plays a substantial role in enhancing opportunities in career paths. Numerous researches utilizing psychometrics have been conducted in recent years, and result reveals an evident association between academic fields and personality traits of students. To assist students in making an informed academic decision, this study analyzes the differences amongst the students of nine study programs in Bangladesh and envisages the appropriate academic choice among these nine fields for the prospective students by analyzing their academic grades, personality traits, and intelligence. For the experiment, we have collected data from 103 participants and used students' academic grades, big-5 personality traits, and Factor B (Reasoning) of 16PF to develop classification models by utilizing two classification approaches. Results show that the Hierarchical classification approach using Random Forest Classifier outperformed the One-level Random Forest classifier approach by obtaining 96.1% accuracy for the 1st-level and 92.86%, 89.29%, and 94.74% respectively for 2nd-level. The findings of this study demonstrate that the proposed framework has great potential in assisting prospective students to make an informed decision to determine the suitable higher study options while unlocking human potential.

关键词： Industries Engineering profession Heuristic algorithms Forestry data models Cognition Random forests

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Molecular Docking of Alkaloid Compound SA2014 towards Cyclin D1 Protein in Cancer using Firefly Algorithm 2

Molecular Docking of Alkaloid Compound SA2014 towards Cyclin...

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2nd international conference on Applied and Industrial Mathematics and Statistics (ICoAIMS)

作者： Fikriya, Zulfa Afiq Irawan, Mohammad Isa Nurhayati, Awik Puji Dyah Inst Teknol Sepuluh Nopember Dept Math Surabaya Indonesia Inst Teknol Sepuluh Nopember Dept Biol Surabaya Indonesia

Molecular docking or ligand binding in proteins is a developing field of computing. Molecular docking can be used to find the most appropriate interaction pattern between protein receptors and ligands and become the basis for the drug discovery and design based structures. The development of efficient docking methods and algorithms will be very useful in drug discovery simulation. Firefly algorithm is one of the method that can be used for molecular docking simulations. Firefly algorithm is used to find the optimal conformation of proteins and ligands so that the binding energy of the whole system is minimized. In this research, protein-ligand complexes from the Protein data Bank (PDB) were used to test the performance of the algorithm. The results show that the firefly algorithm can be used to solve molecular docking. Then this algorithm is used to solve molecular docking of alkaloid compounds SA2014 from Cinachyrella anomala sea sponges towards cyclin D1 protein in cancer. The results show that the SA2014 ligand affinity for cyclin D1 protein was higher than doxorubicin (a type of chemotherapy drug) so that the SA2014 compound have a great potential as an anticancer.

关键词： Proteins

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Competitive Landscape and Industry Prospects of Techniques in the Intersection of Computer Science and Genomics: An Analysis Based on Patent data 19

Competitive Landscape and Industry Prospects of Techniques i...

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Proceedings of the 2019 2nd international conference on algorithms, Computing and Artificial Intelligence

作者： Juan He Hongying Zhang Lin Qiao Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen P R China Department of Computer Science and Technology Tsinghua University Beijing P R China

ISBN: (纸本)9781450372619

Computer technology represented by artificial intelligence and big data has begun to combine with genetic technology, and has gradually played an increasingly important role in the fields of gene sequencing, disease diagnosis, and drug development. The intersection of computer science and genomics brings new opportunities for technological innovation in the medical field. In this context, this paper analyzes the published patents in the intersection of computer science and genomics, focusing on the comprehensive competitiveness of countries/regions, the R&D capability of major patent applicants, the content of patented technology and the industrial application of these technologies. Based on the above research, this paper points out China's competitive landscape and industry prospects in this field, and then puts forward relevant suggestions.

关键词： Artificial Intelligence

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Competitive landscape and industry prospects of techniques in the intersection of computer science and genomics: An analysis based on patent data 2

Competitive landscape and industry prospects of techniques i...

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2nd international conference on algorithms, Computing and Artificial Intelligence, ACAI 2019

作者： He, Juan Zhang, Hongying Qiao, Lin Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen China Department of Computer Science and Technology Tsinghua University Beijing China

ISBN: (纸本)9781450372619

关键词： Genome

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Proceedings - 2017 2nd international conference on Recent Trends and Challenges in Computational Models, ICRTCCM 2017

Proceedings - 2017 2nd International Conference on Recent Tr...

引用

2nd international conference on Recent Trends and Challenges in Computational Models, ICRTCCM 2017

ISBN: (纸本)9781509047994

The proceedings contain 68 papers. The topics discussed include: resource scheduling algorithms in cloud environment - a survey;survey: handling on difficulties in Internet of things (IoT) applications and its challenges;social influence algorithms and emotion classification for prediction of human behavior: a survey;towards comprehensive understanding of event detection and video summarization approaches;an intelligent agent and FSO based efficient routing algorithm for wireless sensor network;uav assisted automated remote monitoring and control system for smart water bodies;a graph-based mathematical model for an efficient load balancing and fault tolerance in cloud computing;a survey on efficient extraction of named entities from new domains using big data analytics;landcover mapping and change detection of geographical area on the map;mining target opinions from online reviews using semi-supervised word alignment model;author similarity identification using citation context and proximity;design and implementation of the monitoring and control system for unified power quality conditioner using soft computing method;efficient multi-keyword search over encrypted data in untrusted cloud environment;a study on vehicle to vehicle collision prevention using fog, cloud, big data and elliptic curve security based on threshold energy efficient protocol in wireless sensor network;and a robust and efficient three-factor authentication and session key agreement mechanism for SIP.

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2nd international conference on data Mining and big data, DMBD 2017

2nd International Conference on Data Mining and Big Data, DM...

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2nd international conference on data Mining and big data, DMBD 2017

ISBN: (纸本)9783319618449

The proceedings contain 53 papers. The special focus in this conference is on data Mining and big data. The topics include: Mining relationship between user purposes and product features towards purpose-oriented recommendation;finding top-k fuzzy frequent itemsets from databases;association rule mining in healthcare analytics;correlation analysis of diesel engine performance testing data based on mixed-copula method;incremental adaptive time series prediction for power demand forecasting;cascade spatial autoregression for air pollution prediction;machine learning techniques for prediction of pre-fetched objects in handling big data storage;spectral-spatial mineral classification of lunar surface using band parameters with active learning;learning analytics for SNS-integrated virtual learning environment;a decision tree of ignition point for simple inflammable chemical compounds;analyzing consumption behaviors of pet owners in a veterinary hospital;design of a dynamic electricity trade scheduler based on genetic algorithms;increasing coverage of information spreading in social networks with supporting seeding;template based industrial big data information extraction and query system;a solution for mining big data based on distributed data streams and its classifying algorithms;design of a quality-aware data capture system;machine learning in data lake for combining data silos;exploring potential use of mobile phone data resource to analyze inter-regional travel patterns in Japan;study a join query strategy over data stream based on sliding windows;post-marketing drug safety evaluation using data mining based on FAERS and accelerating redis with RDMA over infiniband.

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