2008 IEEE Conference on Technologies for Homeland Security最新文献_第2页

Border Crossing Detection and Tracking through Localized Image Processing 基于局部图像处理的边界检测与跟踪

2008 IEEE Conference on Technologies for Homeland Security Pub Date : 2008-05-12 DOI: 10.1109/THS.2008.4534473

A. Greenblatt, K. Panetta, S. Agaian

引用次数: 8

DS CDMA Radio Transmissions Detection DS CDMA无线电传输检测

2008 IEEE Conference on Technologies for Homeland Security Pub Date : 2008-05-12 DOI: 10.1109/THS.2008.4534419

R. Katulski, J. Stefanski, R. Studanski, R. Was

引用次数: 5

Intelligent Searching using Sentence Context 基于句子上下文的智能搜索

2008 IEEE Conference on Technologies for Homeland Security Pub Date : 2008-05-12 DOI: 10.1109/THS.2008.4534428

A. Chickinsky

{"title":"Intelligent Searching using Sentence Context","authors":"A. Chickinsky","doi":"10.1109/THS.2008.4534428","DOIUrl":"https://doi.org/10.1109/THS.2008.4534428","url":null,"abstract":"Fusion centers have access to terra bytes of information from both businesses and federal, state and local governments. The information ranges from computer generated databases to collections of notes with transcript of interviews performed by law enforcement personnel. Searching notes and transcripts is difficult and time consuming because humans do not use a comment set of phrases. Phrases vary due to past experiences, origin of birth and generational differences. Search engines try to compensate for these differences by performing context searches. Context searches replace specific words in the search request with other predetermined words. One can reduce false positives with an intelligent search based on grammar and English sentence structure. Intelligent sentence searching converts the each document into a set of simple sentences using only words in the predefined dictionary. These simple sentences capture the essence of the document. The conversion methodology uses synonyms, idiomatic expressions, grammar, patterns of speech and word location to create a searchable index. Because of the limited dictionary and elimination of most ambiguities, searches can be free of false positives. This paper describes the sentence context methodology, examples, and test results for a representative law enforcement report.","PeriodicalId":366416,"journal":{"name":"2008 IEEE Conference on Technologies for Homeland Security","volume":"47-48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134082567","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

Protecting Military Perimeters from Approaching Human and Vehicle Using Biologically Realistic Dynamic Synapse Neural Network 利用生物逼真的动态突触神经网络保护军事边界免受人类和车辆接近

2008 IEEE Conference on Technologies for Homeland Security Pub Date : 2008-05-12 DOI: 10.1109/THS.2008.4534426

Hyung-Ook Park, A. Dibazar, T. Berger

{"title":"Protecting Military Perimeters from Approaching Human and Vehicle Using Biologically Realistic Dynamic Synapse Neural Network","authors":"Hyung-Ook Park, A. Dibazar, T. Berger","doi":"10.1109/THS.2008.4534426","DOIUrl":"https://doi.org/10.1109/THS.2008.4534426","url":null,"abstract":"The goal of this study is to detect and classify approaching human threats or vehicles, e.g. suicide bombers nearing a secured zone such as military bases. More specifically, this research is focused on (i) developing a vibration recognition system that can detect systematic vibration events; the entity might be a medium, human, animal, or a passenger vehicle, and (ii) discriminating between such a series of events vs. background and a single vibration event, e.g., falling of a tree limb. We have employed a seismic sensor to detect vibrations generated by footsteps and vehicles. A geophone is an inexpensive sensor which provides easy and instant deployment as well as long range detection capability. We have also designed a low power, low noise, and low cost hardware solution to process seismic waves locally where the sensor is located and wireless capability of the system makes it to communicate with a remote command center. Temporal features of the vibration signals were modeled by the dynamic synapse neural network (DSNN) using data recorded in the deserts of Joshua Tree, CA. The system showed 1.7% false recognition rate for the recognition of human footsteps, 6.7% for vehicle, and 0.0% for background. The models were able to reject quadrupedal animal's footsteps (in this study a trained dog). The system rejected dog's footsteps with 0.02% false recognition rate.","PeriodicalId":366416,"journal":{"name":"2008 IEEE Conference on Technologies for Homeland Security","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115198637","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: 16

Performance Analysis of Dual-Homed Fault-Tolerant Routing in Wireless Sensor Networks 无线传感器网络中双主容错路由性能分析

2008 IEEE Conference on Technologies for Homeland Security Pub Date : 2008-05-12 DOI: 10.1109/THS.2008.4534499

N. Jain, V. Vokkarane, Jianping Wang

引用次数: 12

Enhancing Cargo Container Security during Transportation: A Mesh Networking Based Approach 提高集装箱运输过程中的安全性:一种基于网状网络的方法

2008 IEEE Conference on Technologies for Homeland Security Pub Date : 2008-05-12 DOI: 10.1109/THS.2008.4534429

Su Jin Kim, G. Deng, S.K.S. Gupta, M. Murphy-Hoye

{"title":"Enhancing Cargo Container Security during Transportation: A Mesh Networking Based Approach","authors":"Su Jin Kim, G. Deng, S.K.S. Gupta, M. Murphy-Hoye","doi":"10.1109/THS.2008.4534429","DOIUrl":"https://doi.org/10.1109/THS.2008.4534429","url":null,"abstract":"Cargo containers which transport 90 percent of the world's trade transit the countries of the world daily. Despite the vulnerability of cargo containers, only about 5 percent of the over 10 million cargo containers entering the U.S. each year can be inspected now. Our primary goal is to develop the smart container security system using RFID and Wireless Sensor Networks in order to enhance the cargo container security. In addition, the end-to-end visibility via this networked tracking and sensing capability can bring additional commercial benefits to supply chain and chain of custody. In this paper, we first propose a dynamic mesh container network among neighboring containers. Since a group of containers moves together, we can take advantages of interaction between them via this mesh container network instead of focusing an individual container. Second, we introduce the concept of Mobile Edge Computing Devices (MECD) which is the interface between distributed sensors and the end server in order to reduce processing and bandwidth requirements to the end servers. MECDs can give scalability, flexibility, reliability, and cost-efficiency to our cargo container security system.","PeriodicalId":366416,"journal":{"name":"2008 IEEE Conference on Technologies for Homeland Security","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121988800","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: 21

Fingerprint Recognition Algorithms for Partial and Full Fingerprints 部分指纹和全指纹的指纹识别算法

2008 IEEE Conference on Technologies for Homeland Security Pub Date : 2008-05-12 DOI: 10.1109/THS.2008.4534494

S. Mil'shtein, A. Pillai, A. Shendye, C. Liessner, M. Baier

{"title":"Fingerprint Recognition Algorithms for Partial and Full Fingerprints","authors":"S. Mil'shtein, A. Pillai, A. Shendye, C. Liessner, M. Baier","doi":"10.1109/THS.2008.4534494","DOIUrl":"https://doi.org/10.1109/THS.2008.4534494","url":null,"abstract":"An urgent need to develop accurate biometric recognition system is expressed by governmental agencies at the local, state, and federal levels, as well as by private commercial companies. Fingerprinting is the most practical and widely used biometric technique. The pattern of ridges and valleys of each fingerprint is unique. The minutiae based algorithm is widely used for fingerprint authentication. One of the significant parts of this algorithm is the classification of fingerprints which allows minimizing significantly the number of fingerprints referenced for each identification procedure. However, the minutiae algorithm has some serious drawbacks. If the core of a fingerprint is not visible, then identification cannot proceed. Yet in some cases, partial fingerprints need to be identified. We recently developed a novel contactless line scanner for recognition of fingerprint pattern that converts a three dimensional object like a finger into a two dimensional image with minimal distortion. This novel imaging technique based on a line by line scanned image required the development of a new recognition algorithm. In this study, we propose two new algorithms. The first algorithm, called the spaced frequency transformation algorithm (SFTA), is based on taking the fast Fourier transform of the images. The second algorithm, called the line scan algorithm (LSA), was developed to compare partial fingerprints and reduce the time taken to compare full fingerprints. A combination of SFTA and LSA provides a very efficient recognition technique.","PeriodicalId":366416,"journal":{"name":"2008 IEEE Conference on Technologies for Homeland Security","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128404816","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: 37

Performance Analysis of Highly Available Ad Hoc Surveillance Networks Based on Dropped Units 基于丢弃单元的高可用Ad Hoc监控网络性能分析

2008 IEEE Conference on Technologies for Homeland Security Pub Date : 2008-05-12 DOI: 10.1109/THS.2008.4534435

A. Wolff, S. Subik, C. Wietfeld

引用次数: 20

Next Generation Data Fusion Open Source Intelligence (OSINT) System Based on MPEG7 基于MPEG7的下一代数据融合开源智能(OSINT)系统

2008 IEEE Conference on Technologies for Homeland Security Pub Date : 2008-05-12 DOI: 10.1109/THS.2008.4534420

M. Pfeiffer, M. Ávila, G. Backfried, N. Pfannerer, J. Riedler

引用次数: 5

Associating Moving Objects Across Non-overlapping Cameras: A Query-by-Example Approach 跨非重叠摄像机关联移动对象:按例查询方法

2008 IEEE Conference on Technologies for Homeland Security Pub Date : 2008-05-12 DOI: 10.1109/THS.2008.4534515

I. Cohen, Yunqian Ma, B. Miller

引用次数: 6