2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON)最新文献_第2页

Internet of Things and Body area network-an integrated future 物联网与人体区域网络——融合的未来

2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON) Pub Date : 2017-10-01 DOI: 10.1109/UEMCON.2017.8249094

S. Chatterjee, Shreya Chatterjee, Soumyadeep Chowdhury, S. Basak, Srijan Dey, Suparna Sain, K. S. Ghosal, N. Dalmia, Sachet Sircar

引用次数: 17

A framework for data center site risk metric 数据中心站点风险度量的框架

2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON) Pub Date : 2017-10-01 DOI: 10.1109/UEMCON.2017.8248970

M. Levy, D. Raviv

引用次数: 7

Efficient infrastructure damage detection and localization using wireless sensor networks, with cluster generation for monitoring damage progression 利用无线传感器网络进行高效的基础设施损伤检测和定位，并通过集群生成监测损伤进展

2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON) Pub Date : 2017-10-01 DOI: 10.1109/UEMCON.2017.8249020

W. Contreras, S. Ziavras

{"title":"Efficient infrastructure damage detection and localization using wireless sensor networks, with cluster generation for monitoring damage progression","authors":"W. Contreras, S. Ziavras","doi":"10.1109/UEMCON.2017.8249020","DOIUrl":"https://doi.org/10.1109/UEMCON.2017.8249020","url":null,"abstract":"Structural health monitoring (SHM) involves the development of strategies to assess the condition of instrumented engineering structures. One of the most critical applications of SHM systems is civil infrastructure. For this application, it is particularly important that SHM systems be inexpensive and easy to deploy, since the maintenance of infrastructure is often inadequately funded. Wireless sensor networks (WSN) can be very useful toward this end. We present an efficient WSN-based SHM algorithm for detecting, localizing, and monitoring the progression of damage in infrastructure applications. The algorithm utilizes a novel vibration-based pattern matching technique that is very well suited for low-power WSN nodes. During a training phase, a body of reference patterns is formed from vibrations observed at sensor nodes distributed throughout the structure. During the operational phase, observed patterns are compared to the reference patterns to determine if a match exists. Through the use of an innovative distributed algorithm, a time complexity of O(logN) is achieved for the matching process. If a match does not exist, potential damage is indicated and the reference pattern closest to the observed pattern is determined using Euclidean distance. The difference between the two patterns indicates the sensor nodes at which potential damage exists. Clusters are then formed around these sensor nodes in order to monitor the progression of local damage. Simulations are performed in MATLAB for a typical bridge deployment in order to determine the degree of overlapping that occurs as clusters are generated in response to potential damage. The simulations indicate that overlapping increases gracefully as the number of nodes experiencing damage increases.","PeriodicalId":403890,"journal":{"name":"2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131046382","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

Power efficiency of cooperative broadcast in 1-D dense networks with interference 干扰下一维密集网络协同广播的功率效率

2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON) Pub Date : 2017-10-01 DOI: 10.1109/UEMCON.2017.8249069

S. Moballegh, B. Sirkeci-Mergen

引用次数: 1

PulsePrint: Single-arm-ECG biometric human identification using deep learning PulsePrint:使用深度学习的单臂- ecg生物识别人体识别

2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON) Pub Date : 2017-10-01 DOI: 10.1109/UEMCON.2017.8249111

Qingxue Zhang, Dian Zhou, Xuan Zeng

引用次数: 29

Detection and prevention of crypto-ransomware 加密勒索软件的检测和预防

2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON) Pub Date : 2017-10-01 DOI: 10.1109/UEMCON.2017.8249052

Daniel Gonzalez, T. Hayajneh

{"title":"Detection and prevention of crypto-ransomware","authors":"Daniel Gonzalez, T. Hayajneh","doi":"10.1109/UEMCON.2017.8249052","DOIUrl":"https://doi.org/10.1109/UEMCON.2017.8249052","url":null,"abstract":"Crypto-ransomware is a challenging threat that ciphers a user's files while hiding the decryption key until a ransom is paid by the victim. This type of malware is a lucrative business for cybercriminals, generating millions of dollars annually. The spread of ransomware is increasing as traditional detection-based protection, such as antivirus and anti-malware, has proven ineffective at preventing attacks. Additionally, this form of malware is incorporating advanced encryption algorithms and expanding the number of file types it targets. Cybercriminals have found a lucrative market and no one is safe from being the next victim. Encrypting ransomware targets business small and large as well as the regular home user. This paper discusses ransomware methods of infection, technology behind it and what can be done to help prevent becoming the next victim. The paper investigates the most common types of crypto-ransomware, various payload methods of infection, typical behavior of crypto ransomware, its tactics, how an attack is ordinarily carried out, what files are most commonly targeted on a victim's computer, and recommendations for prevention and safeguards are listed as well.","PeriodicalId":403890,"journal":{"name":"2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116001053","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: 28

Cellular image processing using morphological analysis 使用形态学分析的细胞图像处理

2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON) Pub Date : 2017-10-01 DOI: 10.1109/UEMCON.2017.8249037

Mousomi Roy, Shouvik Chakraborty, Kalyani Mali, Sankhadeep Chatterjee, Soumen Banerjee, Shibjit Mitra, Rajarshee Naskar, Anubhab Bhattacharjee

引用次数: 20

Efficient exact paths for dyck and semi-dyck labeled path reachability (extended abstract) dyck和半dyck标记路径可达性的有效精确路径(扩展抽象)

2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON) Pub Date : 2017-10-01 DOI: 10.1109/UEMCON.2017.8249039

P. Bradford

{"title":"Efficient exact paths for dyck and semi-dyck labeled path reachability (extended abstract)","authors":"P. Bradford","doi":"10.1109/UEMCON.2017.8249039","DOIUrl":"https://doi.org/10.1109/UEMCON.2017.8249039","url":null,"abstract":"Consider any two vertices in a weighted digraph. The exact path length problem is to determine if there is a path of a given fixed cost between these vertices. This paper focuses on the exact path problem for costs −1,0 or +1 between all pairs of vertices. This special case is also restricted to original edge weights from {−1, +1}. In this special case, this paper gives an O(nω log2 n) exact path solution, where ω is the best exponent for matrix multiplication. Basic variations of this algorithm determine which pairs of digraph nodes have Dyck or semi-Dyck labeled paths between them, assuming two terminals or parenthesis. Therefore, determining reachability for Dyck or semi-Dyck labeled paths costs O(nω log2 n). Both the exact path and labeled path solutions can be improved by poly-log factors, but these improvements are not given here. To find Dyck or semi-Dyck reachability in a labeled digraph, each edge has a single symbol on it. A path label is made by concatenating all symbols along the path. Cycles are allowed without any repeated edges. These paths have the same number of balanced parenthesizations (semi-Dyck languages) or have an equal numbers of matching symbols (Dyck languages). The exact path length problem has many applications. These applications include the labeled path problems given here, which in turn, have many applications.","PeriodicalId":403890,"journal":{"name":"2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130034303","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: 8

Topology maintenance of Ad Hoc wireless sensor networks with an optimum distributed power saving scheduling learning automata based algorithm 基于最优分布式节能调度学习自动机算法的Ad Hoc无线传感器网络拓扑维护

2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON) Pub Date : 2017-10-01 DOI: 10.1109/UEMCON.2017.8249027

Shekufeh Shafeie, M. Meybodi

{"title":"Topology maintenance of Ad Hoc wireless sensor networks with an optimum distributed power saving scheduling learning automata based algorithm","authors":"Shekufeh Shafeie, M. Meybodi","doi":"10.1109/UEMCON.2017.8249027","DOIUrl":"https://doi.org/10.1109/UEMCON.2017.8249027","url":null,"abstract":"The scheduling of nodes in a wireless Ad Hoc Sensor network is getting them to alternate between the sleeping and active mode. If this process of adjusting the wake/sleep schedule of all nodes that is, a topology management mechanism, is maintained in an optimal manner, further energy can be saved, which will have a direct impact on prolonging the lifetime of the network. So, in this paper a distributed power saving coordination algorithm for multi-hop ad hoc wireless networks based on learning automata without significantly diminishing the quality of services of the network such as capacity or connectivity of the network is proposed such that all nodes in the network that are equipped with learning automata don't need to be synchronized with each other. Learning automata abilities such as low computational load, usability in distributed environments with ambiguous information, and adaptability to changes via low environmental feedbacks are all, factors that can provide the mentioned optimal manner for nodes; and cause better fitness with local techniques in ad hoc wireless networks. The proposed protocol, SpanLAQ, consists of two phases: coordinator announcement and coordinator withdrawal which are based on learning automata to ensure fairness, and to make local decisions on whether a node is going to sleep or joining to a forwarding backbone as a coordinator. So, using learning automata with passing of time causes a decrease in energy consumption and an improvement of the network lifetime in SpanLAQ protocol with an 802.11 network in power saving mode, in comparison to other similar protocols such as Span and without any topology management protocols. Simulation results with a practical energy model also show that the above result is being achieved with some improvements in capacity, connectivity and communication latency.","PeriodicalId":403890,"journal":{"name":"2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129159920","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

Image based skin disease detection using hybrid neural network coupled bag-of-features 基于图像的混合神经网络耦合特征袋的皮肤病检测

2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON) Pub Date : 2017-10-01 DOI: 10.1109/UEMCON.2017.8249038

Shouvik Chakraborty, Kalyani Mali, Sankhadeep Chatterjee, Sumit Anand, Aavery Basu, Soumen Banerjee, Mitali Das, Abhishek Bhattacharya

{"title":"Image based skin disease detection using hybrid neural network coupled bag-of-features","authors":"Shouvik Chakraborty, Kalyani Mali, Sankhadeep Chatterjee, Sumit Anand, Aavery Basu, Soumen Banerjee, Mitali Das, Abhishek Bhattacharya","doi":"10.1109/UEMCON.2017.8249038","DOIUrl":"https://doi.org/10.1109/UEMCON.2017.8249038","url":null,"abstract":"The current work proposes a neural based detection method of two different skin diseases using skin imaging. Skin images of two diseases namely Basel Cell Carcinoma and Skin Angioma are utilized. SIFT feature extractor has been employed followed by a clustering phase on feature space in order to reduce the number of features suitable for neural based models. The extracted bag-of-features modified dataset is used to train metaheuristic supported hybrid Artificial Neural Networks to classify the skin images in order to detect the diseases under study. A well-known multi objective optimization technique called Non-dominated Sorting Genetic Algorithm — II is used to train the ANN (NN-NSGA-II). The proposed model is further compared with two other well-known metaheuristic based classifier namely NN-PSO (ANN trained with PSO) and NN-CS (ANN trained with Cuckoo Search) in terms of testing phase confusion matrix based performance measuring metrics such as accuracy, precision, recall and F-measure. Experimental results indicated towards the superiority of the proposed bag-of-features enabled NN-NSGA-II model.","PeriodicalId":403890,"journal":{"name":"2017 IEEE 8th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference (UEMCON)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132322104","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: 33