2015 Long Island Systems, Applications and Technology最新文献_第2页

Development of a microcontroller based electrical impedance tomography system 基于单片机的电阻抗层析成像系统的研制

2015 Long Island Systems, Applications and Technology Pub Date : 2015-05-01 DOI: 10.1109/LISAT.2015.7160174

Gurmeet Singh, S. Anand, Brejesh Lall, Anurag Srivastava, Vaneet Singh

引用次数: 15

A new selected points to enhance radio wave propagation strength outside the coverage area of the mobile towers in the dead spots of cellular mobile WiFi downloads 在蜂窝移动wi - fi下载的死点移动塔覆盖区域外的新选点增强无线电波传播强度

2015 Long Island Systems, Applications and Technology Pub Date : 2015-05-01 DOI: 10.1109/LISAT.2015.7160194

Zyad Nossire, J. Dichter, Navarun Gupta, J. Fathi

{"title":"A new selected points to enhance radio wave propagation strength outside the coverage area of the mobile towers in the dead spots of cellular mobile WiFi downloads","authors":"Zyad Nossire, J. Dichter, Navarun Gupta, J. Fathi","doi":"10.1109/LISAT.2015.7160194","DOIUrl":"https://doi.org/10.1109/LISAT.2015.7160194","url":null,"abstract":"Mobile phone base station (tower) provides coverage for one or more geographical areas, known as cells. A mobile phone network is made up of a base station operating in conjunction with adjacent base stations. Base stations must be carefully located in relation to each other, so each cell in the network functions efficiently to ensure minimum interference between cells and good signal quality. One of the major problems for cellular wireless devices is calls being dropped and failure in downloading data. Our research uses a new recommendation in determining tower positions. Thus, providing an easy interface to replace traditional control methods and maintain signal levels. The weak WiFi wave propagation outside tower's coverage areas is investigated at the University of Bridgeport (UB) campus. The campus serves as good experimental settings because it exemplifies typical signal dead spots, locations where little to no WiFi signal is available. In this paper, we investigate path loss propagation between the base stations and we identify and categorize these problems. We then apply our path loss propagation algorithmic models to show that signal strength is significantly improved when applying the proposed model. Finally, we show the efficiency of the proposed positions.","PeriodicalId":235333,"journal":{"name":"2015 Long Island Systems, Applications and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117214180","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

A modified region growing based algorithm to vessel segmentation in magnetic resonance angiography 一种改进的基于区域增长的磁共振血管造影血管分割算法

2015 Long Island Systems, Applications and Technology Pub Date : 2015-05-01 DOI: 10.1109/LISAT.2015.7160191

M. Almi'ani, B. Barkana

{"title":"A modified region growing based algorithm to vessel segmentation in magnetic resonance angiography","authors":"M. Almi'ani, B. Barkana","doi":"10.1109/LISAT.2015.7160191","DOIUrl":"https://doi.org/10.1109/LISAT.2015.7160191","url":null,"abstract":"The progress of medical imaging instrumentation has stirred the development of new computer-aided methods of image processing and analysis for better understanding and interpretation of medical images for differential diagnosis, intervention, and treatment monitoring. Image processing and analysis methods have been used to help physicians to make important medical decisions through physician-computer interaction. A modified region growing algorithm is proposed to extract cerebral vessels using a magnetic resonance angiography (MRA) database. To improve the performance of the image segmentation method, as a pre-processing step, image enhancement methods are applied by the gamma correction technique and spatial operations. This step improves the detection of gray-level discontinuities in MRA images. The traditional region growing method is modified by extending the neighborhood as 24 pixels and by defining a filling protocol to label vascular structure. The performance of the proposed algorithm is compared with that of the traditional region growing method and four other segmentation methods. Our proposed method outperformed the other methods. The minimum and maximum errors of the modified region growing method is calculated as zero and 0.82, respectively while the traditional region growing method has 1.85 and 21.91.","PeriodicalId":235333,"journal":{"name":"2015 Long Island Systems, Applications and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132474813","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

Model of indoor signal propagation using log-normal shadowing 使用对数正态阴影的室内信号传播模型

2015 Long Island Systems, Applications and Technology Pub Date : 2015-05-01 DOI: 10.1109/LISAT.2015.7160217

R. Desimone, Betsy Mendieta Brito, J. Baston

引用次数: 4

A novel video steganography algorithm in the wavelet domain based on the KLT tracking algorithm and BCH codes 基于KLT跟踪算法和BCH码的小波域视频隐写新算法

2015 Long Island Systems, Applications and Technology Pub Date : 2015-05-01 DOI: 10.1109/LISAT.2015.7160192

Ramadhan J. Mstafa, K. Elleithy

{"title":"A novel video steganography algorithm in the wavelet domain based on the KLT tracking algorithm and BCH codes","authors":"Ramadhan J. Mstafa, K. Elleithy","doi":"10.1109/LISAT.2015.7160192","DOIUrl":"https://doi.org/10.1109/LISAT.2015.7160192","url":null,"abstract":"Recently, video steganography has become a popular option for a secret data communication. The performance of any steganography algorithm is based on the embedding efficiency, embedding payload, and robustness against attackers. In this paper, we propose a novel video steganography algorithm in the wavelet domain based on the KLT tracking algorithm and BCH codes. The proposed algorithm includes four different phases. First, the secret message is preprocessed, and BCH codes (n, k, t) are applied in order to produce an encoded message. Second, face detection and face tracking algorithms are applied on the cover videos in order to identify the facial regions of interest. Third, the process of embedding the encoded message into the high and middle frequency wavelet coefficients of all facial regions is performed. Forth, the process of extracting the secret message from the high and middle frequency wavelet coefficients for each RGB components of all facial regions is accomplished. Experimental results of the proposed video steganography algorithm have demonstrated a high embedding efficiency and a high embedding payload.","PeriodicalId":235333,"journal":{"name":"2015 Long Island Systems, Applications and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128546392","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: 52

Analysis of video streaming using LTE technology 基于LTE技术的视频流分析

2015 Long Island Systems, Applications and Technology Pub Date : 2015-05-01 DOI: 10.1109/LISAT.2015.7160213

Andre Santos, Edson Pinheiro, R. Mateus, A. Odeh, Eman Abdel Fattah

引用次数: 1

An efficient message authentication and source privacy with a hidden generator point based on ECC 一种基于ECC的高效消息认证和带有隐藏生成点的源隐私

2015 Long Island Systems, Applications and Technology Pub Date : 2015-05-01 DOI: 10.1109/LISAT.2015.7160220

Remah Alshinina, K. Elleithy

引用次数: 3

Fixed point performance of interpolation/extrapolation algorithms for resource constrained wireless sensors 资源受限无线传感器插值/外推算法的定点性能

2015 Long Island Systems, Applications and Technology Pub Date : 2015-05-01 DOI: 10.1109/LISAT.2015.7160175

B. Beheshti

{"title":"Fixed point performance of interpolation/extrapolation algorithms for resource constrained wireless sensors","authors":"B. Beheshti","doi":"10.1109/LISAT.2015.7160175","DOIUrl":"https://doi.org/10.1109/LISAT.2015.7160175","url":null,"abstract":"Date collection in wireless networks is performed by sampling the phenomenon to be measured at recurring intervals in time. In situations where the sensors must operate over a very long time without the possibility of battery replacement, the sleep cycle for these sensors must be as long as possible (and the longest the design allows). Longer sleep cycles, while extending battery life may be too long for the sampling rate required to collect data - i.e. more frequent wake ups would be needed from the sensor. On the other hand, the sensors can collect samples at a lower than required rate, but interpolate data-points in between the actual measured sampled data. Interpolation implemented in floating point can be demanding in terms of energy cost to the sensors. Therefore as it is generally the case, fixed point implementations have to be introduced to reduce the energy demands due to excessive computations/instruction count due to floating point arithmetic. In this paper we present a fixed point implementation of the Neville's interpolation scheme, and present performance results as compared to the floating point (ideal) results.","PeriodicalId":235333,"journal":{"name":"2015 Long Island Systems, Applications and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126776957","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: 0

Highly efficient novel text steganography algorithms 高效新颖的文本隐写算法

2015 Long Island Systems, Applications and Technology Pub Date : 2015-05-01 DOI: 10.1109/LISAT.2015.7160209

A. Odeh, K. Elleithy, M. Faezipour, Eman Abdelfattah

引用次数: 5

A comparison of different machine learning algorithms using single channel EEG signal for classifying human sleep stages 不同机器学习算法在单通道脑电图信号分类人类睡眠阶段的比较

2015 Long Island Systems, Applications and Technology Pub Date : 2015-05-01 DOI: 10.1109/LISAT.2015.7160185

K. Aboalayon, Wafaa S. Almuhammadi, M. Faezipour

{"title":"A comparison of different machine learning algorithms using single channel EEG signal for classifying human sleep stages","authors":"K. Aboalayon, Wafaa S. Almuhammadi, M. Faezipour","doi":"10.1109/LISAT.2015.7160185","DOIUrl":"https://doi.org/10.1109/LISAT.2015.7160185","url":null,"abstract":"In recent years, the estimation of human sleep disorders from Electroencephalogram (EEG) signals have played an important role in developing automatic detection of sleep stages. A few methods exist in the market presently towards this aim. However, sleep physicians may not have full assurance and consideration in such methods due to concerns associated with systems accuracy, sensitivity and specificity. This paper presents a novel and efficient technique that can be implemented in a microcontroller device to identify sleep stages in an effort to assist physicians in the diagnosis and treatment of related sleep disorders by enhancing the accuracy of the developed algorithm using a single channel of EEG signals. First, the dataset of EEG signal is filtered and decomposed into delta, theta, alpha, beta and gamma subbands using Butterworth band-pass filters. Second, a set of sample statistical discriminating features are derived from each frequency band. Finally, sleep stages consisting of Wakefulness, Rapid Eye Movement (REM) and Non-Rapid Eye Movement (NREM) are classified using several supervised machine learning classifiers including multi-class Support Vector Machines (SVM), Decision Trees (DT), Neural Networks (NN), K-Nearest Neighbors (KNN) and Naive Bayes (NB). This paper combines REM with Stage 1 NREM due to data similarities. Performance is then compared based on single channel EEG signals that were obtained from 20 healthy subjects. The results show that the proposed technique using DT classifier efficiently achieves high accuracy of 97.30% in differentiating sleeps stages. Also, a comparison of our method with some recent available works in the literature reiterates the high classification accuracy performance.","PeriodicalId":235333,"journal":{"name":"2015 Long Island Systems, Applications and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134641059","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: 41