2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET)最新文献

Advanced monitoring system for digital cable distribution network 先进的数字电缆配电网监控系统

2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET) Pub Date : 2017-03-22 DOI: 10.1109/WISPNET.2017.8300035

Nanda Kishora Holla, S. Yellampalli

引用次数: 0

Speech based human emotion recognition using MFCC 基于语音的MFCC人类情感识别

2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET) Pub Date : 2017-03-22 DOI: 10.1109/WISPNET.2017.8300161

M. Likitha, Sri Raksha R. Gupta, K. Hasitha, A. U. Raju

{"title":"Speech based human emotion recognition using MFCC","authors":"M. Likitha, Sri Raksha R. Gupta, K. Hasitha, A. U. Raju","doi":"10.1109/WISPNET.2017.8300161","DOIUrl":"https://doi.org/10.1109/WISPNET.2017.8300161","url":null,"abstract":"Speech is a complex signal consisting of various information, such as information about the message to be communicated, speaker, language, region, emotions etc. Speech Processing is one of the important branches of digital signal processing and finds applications in Human computer interfaces, Telecommunication, Assistive technologies, Audio mining, Security and so on. Speech emotion recognition is important to have a natural interaction between human being and machine. In speech emotion recognition, emotional state of a speaker is extracted from his or her speech. The acoustic characteristic of the speech signal is Feature. Feature extraction is the process that extracts a small amount of data from the speech signal that can later be used to represent each speaker. Many feature extraction methods are available and Mel Frequency Cepstral Coefficient (MFCC) is the commonly used method. In this paper, speaker emotions are recognized using the data extracted from the speaker voice signal. Mel Frequency Cepstral Coefficient (MFCC) technique is used to recognize emotion of a speaker from their voice. The designed system was validated for Happy, sad and anger emotions and the efficiency was found to be about 80%.","PeriodicalId":224631,"journal":{"name":"2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117326009","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: 103

A novel clustering protocol for wireless sensor networks 一种新的无线传感器网络聚类协议

2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET) Pub Date : 2017-03-22 DOI: 10.1109/WISPNET.2017.8299793

Khalid A. Darabkh, Wala's S. Al-Rawashdeh, Mohammed Hawa, Ramzi R. Saifan, A. Khalifeh

引用次数: 39

Development of a low cost nitrate detection soil sensor 低成本硝酸盐检测土壤传感器的研制

2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET) Pub Date : 2017-03-22 DOI: 10.1109/WISPNET.2017.8299968

R. J. Sänket, Abhijit Baviskar, Shwetambari S. Ahire, S. Mapare

{"title":"Development of a low cost nitrate detection soil sensor","authors":"R. J. Sänket, Abhijit Baviskar, Shwetambari S. Ahire, S. Mapare","doi":"10.1109/WISPNET.2017.8299968","DOIUrl":"https://doi.org/10.1109/WISPNET.2017.8299968","url":null,"abstract":"Agriculture is one of the key sectors in India wherein harmful pesticides and fertilizers are heavily used nowadays. They contribute largely to the soil and water contamination. Usually, farmers make excessive use of these supplies which in return can cause negative effects to the environment. So watching the agricultural environment is important in order to maintain the stability of the soil. Modern measures to tackle these issues of contamination generally need tough operational ways which involve heavy investments. This study gives a substitute method for the detection of contamination by designing an array based sensor with the combination of capacitive and inductive electromagnetic fields for monitoring the content in agricultural soils and contamination. The purpose is to fabricate this array design of the sensor on printed circuit board (double-sided PCB FR4). A set of demonstrations were conducted to study the characteristic features of the sensor. The performance of the system was observed where the sensors were tested with various soil samples mixed with a different concentration of nitrate in proportion with water. Based on the results obtained, the sensor array can be used to measure contamination in the soils and the data obtained from the experiment is compared.","PeriodicalId":224631,"journal":{"name":"2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127030164","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: 3

A survey on types of machine learning techniques in intrusion prevention systems 入侵防御系统中机器学习技术的研究

2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET) Pub Date : 2017-03-22 DOI: 10.1109/WISPNET.2017.8300169

Soubhik Das, M. Nene

{"title":"A survey on types of machine learning techniques in intrusion prevention systems","authors":"Soubhik Das, M. Nene","doi":"10.1109/WISPNET.2017.8300169","DOIUrl":"https://doi.org/10.1109/WISPNET.2017.8300169","url":null,"abstract":"The computation technology is evolving. The data transmitted and generated using them are growing exponentially. The traffic on these networks requires surveillance. Effective network traffic surveillance, packet analysis and rules to define the traffic flow are in place using various intrusion detection and prevention systems. However, the security issues and concerns are dictating the need to evolve with the novel and ‘human-like’ methods to mitigate them. Normal methods and techniques may prove too tedious, and sometimes will not even render fruitful results. In that case, the techniques that can think, act and mimic human beings assure the possibilities of resolving the concerns where the domain of artificial intelligence plays a critical role. Also, there is a crucial need to design real-time models that can analyze & handle bigger, more complex data; and deliver faster as well as accurate results. Machine learning is a subfield which possesses all of the attributes. Intrusion preventions IDPS's integrate methods that help to prevent intrusive and non-intrusive data packets [2]. According to survey, most of the intrusion prevention methods rely heavily on humans to analyze data and classify into intrusive and non-intrusive networks. When the data to compute is very large, computing methods such as Computational intelligence and its constituent are essential to use as humans have their own shortcomings. Computational intelligence and machine learning are widely used to detect the intrusions, which in turn help in preventing the same. Pattern recognition uses algorithms to handle very large data sets. In this paper, a survey is done that on various machine learning and computational intelligence techniques that envisage using IDPS.","PeriodicalId":224631,"journal":{"name":"2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET)","volume":"204 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123521703","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: 23

Experimental investigations on monopole loop antenna with dual band characteristics 双频特性单极环形天线的实验研究

2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET) Pub Date : 2017-03-22 DOI: 10.1109/WISPNET.2017.8299836

L. Meenu, S. Aiswarya, S. Menon

引用次数: 10

Modeling of satellite communication systems design with physical layer security 具有物理层安全的卫星通信系统设计建模

2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET) Pub Date : 2017-03-22 DOI: 10.1109/WISPNET.2017.8300047

Yuan Gao, Hong Ao, Quan Zhou, Zeng Feng, Weigui Zhou, Yi Li, Xiangyang Li

{"title":"Modeling of satellite communication systems design with physical layer security","authors":"Yuan Gao, Hong Ao, Quan Zhou, Zeng Feng, Weigui Zhou, Yi Li, Xiangyang Li","doi":"10.1109/WISPNET.2017.8300047","DOIUrl":"https://doi.org/10.1109/WISPNET.2017.8300047","url":null,"abstract":"It has practical significance to carry out research on physical layer security in satellite communication under the condition that our country has paid high attention to technology research on integrated space-terrestrial network information security. This paper addresses multiservice satellite communication using physical layer security, proposes a novel design subject to different speed and data transfer rate demand among fixed, portable, vehicle, shipborne and airborne receivers. For fixed receivers, this paper proposes a resource optimization method of satellite communication using physical layer security subject to different data transfer rate demand in many receivers. For portable, vehicle and shipborne receivers at low speed, this paper uses mean physical layer secrecy capacity to characterize the secure performance of satellite communication using physical layer security. For airborne receivers at high speed, this paper analyzes the impact of the high-speed relative motion between the satellite and the receiver on channel model, which is combined with mean physical layer secrecy capacity to characterize the secure performance of satellite communication using physical layer security.","PeriodicalId":224631,"journal":{"name":"2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134107884","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: 11

Energy efficient wireless sensor network using neural network based smart sampling and reliable routing protocol 节能无线传感器网络采用基于神经网络的智能采样和可靠的路由协议

2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET) Pub Date : 2017-03-22 DOI: 10.1109/WISPNET.2017.8300128

C. Vinutha, N. Nalini, B. Veeresh

{"title":"Energy efficient wireless sensor network using neural network based smart sampling and reliable routing protocol","authors":"C. Vinutha, N. Nalini, B. Veeresh","doi":"10.1109/WISPNET.2017.8300128","DOIUrl":"https://doi.org/10.1109/WISPNET.2017.8300128","url":null,"abstract":"The potential growth and successful convergence of different technologies like Wireless communications, micro electro Mechanical systems (MEMS) and Digital electronics have leveraged to realise the concept of sensor networks with the collaborative efforts of large number of low powered, low cost and small sized sensor nodes used for short distance, multihop communications. Efficient utilization of node's battery energy to improve the network lifetime is the fundamental challenge in Wireless Sensor Network (WSN) [5]. The periodic control signal overheads exchanged between the base station & the sensor nodes add substantial amount of burden in energy expenditure. The other major energy issues lies in packet losses and the subsequent retransmissions, while minimizing the control signal overhead charges. To mitigate this problem, we propose the combined design of non uniform sampling and reliable routing for efficient energy saving and fast data communication in the system while minimizing control signal overhead charges. Our work enhances the reliability in packet transmission by predicting energy robust and near-by nodes in the data forwarding path towards the destination, using back propagation neural network algorithm. We have demonstrated through simulation results the improvement in battery energy consumption without trading off with the speed of data communication which is achieved at the cost of minimal overhead charges.","PeriodicalId":224631,"journal":{"name":"2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134392174","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: 12

An etiology of Inferior Alveolar Nerve on third molar using dental image processing 应用牙图像处理分析第三磨牙下牙槽神经的病因

2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET) Pub Date : 2017-03-22 DOI: 10.1109/WISPNET.2017.8299739

Tirth K. Dalsaniya, K. Jain

引用次数: 0

Extracting the features of emotion from EEG signals and classify using affective computing 从脑电信号中提取情感特征，并利用情感计算进行分类

2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET) Pub Date : 2017-03-22 DOI: 10.1109/WISPNET.2017.8300118

R. Chinmayi, G. Nair, M. Soundarya, D. Poojitha, Gayathri Venugopal, Jishnu Vijayan

{"title":"Extracting the features of emotion from EEG signals and classify using affective computing","authors":"R. Chinmayi, G. Nair, M. Soundarya, D. Poojitha, Gayathri Venugopal, Jishnu Vijayan","doi":"10.1109/WISPNET.2017.8300118","DOIUrl":"https://doi.org/10.1109/WISPNET.2017.8300118","url":null,"abstract":"The extraction of features, for the recognition of affective states through various means such as gestures of the body, facial images and electroencephalogram (EEG), is very important in affective computing. The brain-machine interface (BMI) using emotions, are used in medical robots, neuroergonomics, and auto-navigation and security systems. Emotions can be identified using analysis of scalp EEGs. The EEG data with audio-visual stimulus is collected and analyzed to extract the features of five emotions viz., happy, sad, fear, neutral and disgust. The raw EEG data is used to create the database, EEG_Amrita_emote. Features of EEG data are extracted using independent component analysis (ICA), and are classified using K Nearest Neighbor (KNN) algorithm. Cluster centroids are identified using k-Mean Clustering. The spectral energy of emotional activities in the brain is taken as one of the features. The EEG data is collected from male subjects of age group between 20 and 30. The locations of high intensity spectral energy is calculated for every emotion. The primary centroids of emotions are happy at (26.58, −99.97), neutral at (−69.18, 12.89), sad at (66.45, 29.52), fear at (74.22, −9.65) and disgust at (63.05, 38.68) respectively.","PeriodicalId":224631,"journal":{"name":"2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124555464","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: 10