2019 International Conference on Intelligent Sustainable Systems (ICISS)最新文献

A review on Hyperspectral Image Classification using SVM combined with Guided Filter 基于支持向量机和引导滤波的高光谱图像分类研究进展

2019 International Conference on Intelligent Sustainable Systems (ICISS) Pub Date : 2019-02-01 DOI: 10.1109/ISS1.2019.8908043

Kirti Gaur, Pankaj A. Mohrut

引用次数: 2

FPGA based Implementation of Low power CORDIC architecture 基于FPGA的低功耗CORDIC架构实现

2019 International Conference on Intelligent Sustainable Systems (ICISS) Pub Date : 2019-02-01 DOI: 10.1109/ISS1.2019.8907946

S. Inguva, J. Seventline

{"title":"FPGA based Implementation of Low power CORDIC architecture","authors":"S. Inguva, J. Seventline","doi":"10.1109/ISS1.2019.8907946","DOIUrl":"https://doi.org/10.1109/ISS1.2019.8907946","url":null,"abstract":"The coordinate rotation digital computer (CORDIC) is a shift-add algorithm used for rotating vectors in a plane. Several techniques are proposed in the literature for calculation of trigonometric functions which requires large memory usage. Due to the flexibility, CORDIC algorithm is best alternative and allows high quantization accuracy by maximizing word length. The linear-rate convergence creates the major problem in CORDIC algorithm with the source of word-length and iteration speed. The power consumption is also a major issues which affects the performance due to array of shift-add operations. For further improvement, in this paper, we propose a low power and high speed CORDIC design with an improved power control and hardware reduction techniques. We employ the canonical signed-digit (CSD) technique and Hcub algorithm for reducing the number of shifters and adder/subtractor in the design. Then, we proposed an adder based on the advanced Boolean logic technique. These three techniques are used to redesign the entire CORDIC logic stages in [16] thereby contributing in power consumption reduction. The functionality of proposed CORDIC algorithm is assessed through FPGA implementations. The simulation result shows that the proposed method has higher frequency of 78.91 %, 83.42%, 79.89% and 77.01 % when compared with other architectures.","PeriodicalId":111366,"journal":{"name":"2019 International Conference on Intelligent Sustainable Systems (ICISS)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115209134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

A Review on Different Data Mining Algorithms and Selection Methods 不同数据挖掘算法及选择方法综述

2019 International Conference on Intelligent Sustainable Systems (ICISS) Pub Date : 2019-02-01 DOI: 10.1109/ISS1.2019.8908048

Kavita Kaithwas, P. Borkar

引用次数: 0

A review on Internet of things 物联网综述

2019 International Conference on Intelligent Sustainable Systems (ICISS) Pub Date : 2019-02-01 DOI: 10.1109/ISS1.2019.8908105

Charushila Raskar, S. Nema

引用次数: 59

Hybrid technique for analysis of the faults in an underground cable 地下电缆故障分析的混合技术

2019 International Conference on Intelligent Sustainable Systems (ICISS) Pub Date : 2019-02-01 DOI: 10.1109/ISS1.2019.8907976

P. Ray, D. Mishra

引用次数: 0

Mean Threshold Shortest Job Round Robin CPU Scheduling Algorithm 平均阈值最短作业轮询CPU调度算法

2019 International Conference on Intelligent Sustainable Systems (ICISS) Pub Date : 2019-02-01 DOI: 10.1109/ISS1.2019.8908071

Pragati Pathak, Prashant S. Kumar, Kumkum Dubey, Prince Rajpoot, Shobhit Kumar

引用次数: 2

Software in the Loop Simulation of Formation Flying of Multi Rotor UAV 多旋翼无人机编队飞行的环内软件仿真

2019 International Conference on Intelligent Sustainable Systems (ICISS) Pub Date : 2019-02-01 DOI: 10.1109/ISS1.2019.8908015

A. Kaviyarasu, A. Saravanakumar, K. Elumalai

引用次数: 1

Vehicle classification using LabVIEW 使用LabVIEW进行车辆分类

2019 International Conference on Intelligent Sustainable Systems (ICISS) Pub Date : 2019-02-01 DOI: 10.1109/ISS1.2019.8907978

B. Srinivas, B. Lavanya

引用次数: 0

A Survey on Placement of Sensor Nodes in Deployment of Wireless Sensor Networks 无线传感器网络部署中传感器节点布局研究

2019 International Conference on Intelligent Sustainable Systems (ICISS) Pub Date : 2019-02-01 DOI: 10.1109/ISS1.2019.8907968

K. Swetha, V. Lahari, G.V.V. Manikrisha, K. Sai

{"title":"A Survey on Placement of Sensor Nodes in Deployment of Wireless Sensor Networks","authors":"K. Swetha, V. Lahari, G.V.V. Manikrisha, K. Sai","doi":"10.1109/ISS1.2019.8907968","DOIUrl":"https://doi.org/10.1109/ISS1.2019.8907968","url":null,"abstract":"Wireless Sensor Networks (WSN) denotes a set of geometrically dispersed and identified sensor nodes for recording and maintaining the environment and physical states and manages the obtained information at the center. The number of nodes and their locations is directly proportional to the coverage area of the sensor nodes and are referred as coverage pints. The placement of sensor nodes has become an important challenge in covering a small parametric and physical change that occurs in particular location. In wireless networks such issues were based on placement of sensor nodes. This influences the performance of wireless sensor network storage connectivity and resilience. For wireless Sensors many deployment schemes has been proposed. This paper describes about the comparative analysis of the various deployment strategies of sensor nodes with the random placement in these networks using voronoi diagram. The random deployment of sensor nodes in WSN will be helpful for avoiding some of the problems in applications like crowd management, occurrence of accidents etc. By maintaining the network connectivity the proposed algorithm decreases the redundancy and removes the isolated nodes. Lastly, the to heal coverage holes the algorithm tries to divide the field into different voronoi cells and tries to deploy nodes were ever required and thus nodes are moved into their local best positions according to Voronoi partition.","PeriodicalId":111366,"journal":{"name":"2019 International Conference on Intelligent Sustainable Systems (ICISS)","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127962252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Implementation of IOT based Attendance Management System on Raspberry Pi 基于物联网的考勤管理系统在树莓派上的实现

2019 International Conference on Intelligent Sustainable Systems (ICISS) Pub Date : 2019-02-01 DOI: 10.1109/ISS1.2019.8908092

P. Raj

{"title":"Implementation of IOT based Attendance Management System on Raspberry Pi","authors":"P. Raj","doi":"10.1109/ISS1.2019.8908092","DOIUrl":"https://doi.org/10.1109/ISS1.2019.8908092","url":null,"abstract":"The biometric-based attendance monitoring system replaces the manual method of taking attendance and reduces the time to take attendance and avoids proxy. There are many biometric methods developed based on the fingerprint recognition, DNA matching, face recognition, Iris recognition and voice recognition. Out of all, the methods based on face recognition are proved to be the best methods. In this paper we are presenting the implementation of attendance monitoring system based on the facial recognition. In this method the image database of the classroom is created first and the database is used to train the system. Then in recognition phase the camera is fixed at the focal point in the classroom and it will capture the images, then from the captured images student's faces are recognized & compared with the database and lastly the attendance is marked based on the faces identified. The marked attendance is directly reported to the students/parents and to the faculty handling the respective course. In this method, Haar cascade classifier is used to detect the faces and captured images are compared with the database by using local binary pattern histogram algorithm. The face recognition system is implemented on the Raspberry Pi 3B hardware.","PeriodicalId":111366,"journal":{"name":"2019 International Conference on Intelligent Sustainable Systems (ICISS)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134222072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6