2016 IEEE Long Island Systems, Applications and Technology Conference (LISAT)最新文献_第2页

H-LEACH: Hybrid-low energy adaptive clustering hierarchy for wireless sensor networks H-LEACH:无线传感器网络的混合-低能量自适应聚类结构

2016 IEEE Long Island Systems, Applications and Technology Conference (LISAT) Pub Date : 2016-04-29 DOI: 10.1109/LISAT.2016.7494136

A. Razaque, Satwic Mudigulam, K. Gavini, Fathi H. Amsaad, M. Abdulgader, G. S. Krishna

引用次数: 54

Penetration testing: Concepts, attack methods, and defense strategies 渗透测试:概念、攻击方法和防御策略

2016 IEEE Long Island Systems, Applications and Technology Conference (LISAT) Pub Date : 2016-04-29 DOI: 10.1109/LISAT.2016.7494156

M. Denis, Carlos Zena, T. Hayajneh

引用次数: 89

The creation and certification of software cybersecurity standards 软件网络安全标准的创建和认证

2016 IEEE Long Island Systems, Applications and Technology Conference (LISAT) Pub Date : 2016-04-29 DOI: 10.1109/LISAT.2016.7494112

C. Warren Axelrod

引用次数: 2

Predicting and analyzing water quality using Machine Learning: A comprehensive model 使用机器学习预测和分析水质:一个综合模型

2016 IEEE Long Island Systems, Applications and Technology Conference (LISAT) Pub Date : 2016-04-29 DOI: 10.1109/LISAT.2016.7494106

Yafra Khan, C. S. See

{"title":"Predicting and analyzing water quality using Machine Learning: A comprehensive model","authors":"Yafra Khan, C. S. See","doi":"10.1109/LISAT.2016.7494106","DOIUrl":"https://doi.org/10.1109/LISAT.2016.7494106","url":null,"abstract":"The deteriorating quality of natural water resources like lakes, streams and estuaries, is one of the direst and most worrisome issues faced by humanity. The effects of un-clean water are far-reaching, impacting every aspect of life. Therefore, management of water resources is very crucial in order to optimize the quality of water. The effects of water contamination can be tackled efficiently if data is analyzed and water quality is predicted beforehand. This issue has been addressed in many previous researches, however, more work needs to be done in terms of effectiveness, reliability, accuracy as well as usability of the current water quality management methodologies. The goal of this study is to develop a water quality prediction model with the help of water quality factors using Artificial Neural Network (ANN) and time-series analysis. This research uses the water quality historical data of the year of 2014, with 6-minutes time interval. Data is obtained from the United States Geological Survey (USGS) online resource called National Water Information System (NWIS). For this paper, the data includes the measurements of 4 parameters which affect and influence water quality. For the purpose of evaluating the performance of model, the performance evaluation measures used are Mean-Squared Error (MSE), Root Mean-Squared Error (RMSE) and Regression Analysis. Previous works about Water Quality prediction have also been analyzed and future improvements have been proposed in this paper.","PeriodicalId":223140,"journal":{"name":"2016 IEEE Long Island Systems, Applications and Technology Conference (LISAT)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124176234","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: 55

Impacts of meaningful use and what's next: The Next Generation Accountable Care Organization model 有意义使用的影响和下一步:下一代负责任的医疗组织模式

2016 IEEE Long Island Systems, Applications and Technology Conference (LISAT) Pub Date : 2016-04-29 DOI: 10.1109/LISAT.2016.7494110

T. Piliouras, Pui Lam Raymond Yu, Liza Salloum, Jesus Chavez, Robert J. Suss, Yi Cheung, Wenqi Su

{"title":"Impacts of meaningful use and what's next: The Next Generation Accountable Care Organization model","authors":"T. Piliouras, Pui Lam Raymond Yu, Liza Salloum, Jesus Chavez, Robert J. Suss, Yi Cheung, Wenqi Su","doi":"10.1109/LISAT.2016.7494110","DOIUrl":"https://doi.org/10.1109/LISAT.2016.7494110","url":null,"abstract":"In 2009, with the passage of the American Recovery and Reinvestment Act (ARRA) and the Health Information Technology for Economic and Clinical Health Act (HITECH), the federal government authorized twenty-one billion dollars to launch the Meaningful Use program. The goal was to encourage healthcare providers to use electronic health record systems, and thereby facilitate electronic information sharing among healthcare providers, patients, and clinical data registries. The Meaningful Use program succeeded in promoting adoption of electronic health record systems - at considerable cost and with mixed results. In April 2015, the Medicare Access and CHIP Reauthorization Act of 2015 (MACRA) was signed into law by President Obama. Under provisions of MACRA, Medicare reimbursements to health care providers will be based on demonstrable improvements in patient outcomes and reduced health costs, and not for the use of electronic health record systems per se. The Centers for Medicare and Medicaid Services recently announced the Meaningful Use program will end in 2016 and will be supplanted by other initiatives, such as the Next Generation Accountable Care Organization (ACO) model. Accountable Care Organizations are composed of doctors, hospitals, and other health care providers and suppliers that voluntarily collaborate to offer coordinated, quality care at lower cost to Medicare patients. This paper discusses impacts of Meaningful Use and why meeting its goals presents formidable challenges. To comply with Meaningful Use, Medicare providers must use a certified EHR system. However, the certification process omits many key considerations critical to operational success, and does not suffice as evidence the EHR system is suitable for a particular clinical setting. Innovative, holistic solutions are needed to improve EHR interoperability, usability, and support for Health Insurance Portability and Accountability Act (HIPAA) compliance.","PeriodicalId":223140,"journal":{"name":"2016 IEEE Long Island Systems, Applications and Technology Conference (LISAT)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129152028","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

Data leakage preventation using homomorphic encryptionin cloud computing 云计算中基于同态加密的数据泄漏预防

2016 IEEE Long Island Systems, Applications and Technology Conference (LISAT) Pub Date : 2016-04-29 DOI: 10.1109/LISAT.2016.7494153

Q. B. Hani, J. Dichter

引用次数: 3

Tool to detect multipath routing when tracking path of packets 跟踪报文路径时检测多路径路由的工具

2016 IEEE Long Island Systems, Applications and Technology Conference (LISAT) Pub Date : 2016-04-29 DOI: 10.1109/LISAT.2016.7494161

Sirish Yennam, GouthamReddy Gayapu, Arun Merugu, Charan Karanam, Tarik Eltaieb

引用次数: 0

Wireless Sensor Networks (WSNs) 无线传感器网络(WSNs)

2016 IEEE Long Island Systems, Applications and Technology Conference (LISAT) Pub Date : 2016-04-29 DOI: 10.1109/LISAT.2016.7494144

Yasaroglu Pinar, A. Zuhair, Alotaibi Hamad, Akcam Resit, K. Shiva, Abuzaghleh Omar

引用次数: 18

Incorporation of weighted linear prediction technique and M/M/1 Queuing Theory for improving energy efficiency of Cloud computing datacenters 结合加权线性预测技术和M/M/1排队理论提高云计算数据中心能源效率

2016 IEEE Long Island Systems, Applications and Technology Conference (LISAT) Pub Date : 2016-04-29 DOI: 10.1109/LISAT.2016.7494148

Elham Akbari, Francis Cung, Hardik J Patel, A. Razaque, H. Dalal

{"title":"Incorporation of weighted linear prediction technique and M/M/1 Queuing Theory for improving energy efficiency of Cloud computing datacenters","authors":"Elham Akbari, Francis Cung, Hardik J Patel, A. Razaque, H. Dalal","doi":"10.1109/LISAT.2016.7494148","DOIUrl":"https://doi.org/10.1109/LISAT.2016.7494148","url":null,"abstract":"Cloud computing refers to the services supplied over the internet and the hardware and software that delivers such services. It has the capability to cover a large part of the IT industry and make software even more appealing as a service. It can also reshape how IT hardware is designed and acquired. Nevertheless, datacenters that offer cloud applications consumes a large amount of power which can substantially increase operational costs. As technology is evolving and growing at a rapid pace, more people are dependent on technology and utilizing the cloud. There's a larger demand to extend the platforms needed to improve the development of Cloud computing. As a result, in parallel with this development of infrastructure, there has also been a great deal of attention paid to energy consumption in cloud computing technology. This research will report on incorporating weighted linear prediction technique and M/M/1 Queuing Theory for enhancing the energy efficiency of cloud data centers. The goal is to simulate the effect of various workloads on energy consumption of the cloud system using CloudSim or similar software.","PeriodicalId":223140,"journal":{"name":"2016 IEEE Long Island Systems, Applications and Technology Conference (LISAT)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133087294","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

QKDP's comparison based upon quantum cryptography rules 基于量子密码规则的QKDP比较

2016 IEEE Long Island Systems, Applications and Technology Conference (LISAT) Pub Date : 2016-04-29 DOI: 10.1109/LISAT.2016.7494101

Abdulbast A. Abushgra, K. Elleithy

引用次数: 12