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2018

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Articles 2101 - 2130 of 2925

Full-Text Articles in Computer Sciences

Essentialism, Social Construction, Or Individual Differences, Jenelys Cox, Jeff Rynhart, Shea-Tinn Yeh Jan 2018

Essentialism, Social Construction, Or Individual Differences, Jenelys Cox, Jeff Rynhart, Shea-Tinn Yeh

University Libraries: Staff Scholarship

Per the United States Department of Labor Women’s Bureau’s latest available statistics, the percentage of women employed in computer and information technology occupations was consistently lower than the average for all occupations. When broken down by selected characteristics, these numbers range from 12.4% in computer network architectures to 35.2% in web development. Is this trend reflected in the libraries? Although no comprehensive statistics are available for women in library IT, Lamont’s study does reflect the same trend in that the number of women as library IT department heads has been about one half that of men between 2004-2008. Why is …

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Research Agenda In Developing Core Reference Ontology For Human Intelligence/Machine-Intelligence Electronic Medical Records System, Ziniya Zahedi, Teddy Steven Cotter Jan 2018

Research Agenda In Developing Core Reference Ontology For Human Intelligence/Machine-Intelligence Electronic Medical Records System, Ziniya Zahedi, Teddy Steven Cotter

Engineering Management & Systems Engineering Faculty Publications

Beginning around 1990, efforts were initiated in the medical profession by the U.S. government to transition from paper based medical records to electronic medical records (EMR). By the late 1990s, EMR implementation had already encountered multiple barriers and failures. Then President Bush set forth the goal of implementing electronic health records (EHRs), nationwide within ten years. Again, progress toward EMR implementation was not realized. President Obama put new emphasis on promoting EMR and health care technology. The renewed emphasis did not overcome many of the original problems and induced new failures. Retrospective analyses suggest that failures were induced because programmers …

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Economics-Based Risk Management Of Distributed Denial Of Service Attacks: A Distance Learning Case Study, Omer Keskin, Unal Tatar, Omer Poyraz, Ariel Pinto, Adrian Gheorghe Jan 2018

Economics-Based Risk Management Of Distributed Denial Of Service Attacks: A Distance Learning Case Study, Omer Keskin, Unal Tatar, Omer Poyraz, Ariel Pinto, Adrian Gheorghe

Engineering Management & Systems Engineering Faculty Publications

Managing risk of cyber systems is still on the top of the agendas of Chief Information Security Officers (CISO). Investment in cybersecurity is continuously rising. Efficiency and effectiveness of cybersecurity investments are under scrutiny by boards of the companies. The primary method of decision making on cybersecurity adopts a risk-informed approach. Qualitative methods bring a notion of risk. However, particularly for strategic level decisions, more quantitative methods that can calculate the risk and impact in monetary values are required. In this study, a model is built to calculate the economic value of business interruption during a Distributed Denial-of-Service (DDoS) attack …

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Predictive Analytics In The Criminal Justice System: Media Depictions And Framing, Kar Mun Cheng Jan 2018

Predictive Analytics In The Criminal Justice System: Media Depictions And Framing, Kar Mun Cheng

Honors Program Theses

Artificial intelligence and algorithms are increasingly becoming commonplace in crime-fighting efforts. For instance, predictive policing uses software to predetermine criminals and areas where crime is most likely to happen. Risk assessment software are employed in sentence determination and other courtroom decisions, and they are also being applied towards prison overpopulation by assessing which inmates can be released. Public opinion on the use of predictive software is divided: many police and state officials support it, crediting it with lowering crime rates and improving public safety. Others, however, have questioned its effectiveness, citing civil liberties concerns as well as the possibility of …

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Exploring Connections Between Primitive Decomposition Of Natural Language And Hierarchical Planning, Jamie C. Macbeth, Mark Roberts Jan 2018

Exploring Connections Between Primitive Decomposition Of Natural Language And Hierarchical Planning, Jamie C. Macbeth, Mark Roberts

Computer Science: Faculty Publications

While recent research has shown that “classical” automated planning systems are effective tools for story generation, the success of automated story understanding systems may require integration between commonsense reasoning and more sophisticated forms of planning to make inferences and deductions about the plans and goals of story actors. Methods that decompose abstractions (i.e., tasks or language expressions) into primitives have played an important role for both automated planning systems and automated story understanding systems, but the two areas have remained largely isolated from each other with few overlaps. We argue that this little-explored connection can benefit both areas of …

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Threadable Curves, Joseph O’Rourke, Emmely Rogers Jan 2018

Threadable Curves, Joseph O’Rourke, Emmely Rogers

Computer Science: Faculty Publications

We define a plane curve to be threadable if it can rigidly pass through a point-hole in a line L without otherwise touching L. Threadable curves are in a sense generalizations of monotone curves. We have two main results. The first is a linear-time algorithm for deciding whether a polygonal curve is threadable—O(n) for a curve of n vertices—and if threadable, finding a sequence of rigid motions to thread it through a hole. We also sketch an argument that shows that the threadability of algebraic curves can be decided in time polynomial in the degree of the curve. The second …

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Multitask Allocation To Heterogeneous Participants In Mobile Crowd Sensing, Weiping Zhu, Wenzhong Guo, Zhiyong Yu, Haoyi Xiong Jan 2018

Multitask Allocation To Heterogeneous Participants In Mobile Crowd Sensing, Weiping Zhu, Wenzhong Guo, Zhiyong Yu, Haoyi Xiong

Computer Science Faculty Research & Creative Works

Task allocation is a key problem in Mobile Crowd Sensing (MCS). Prior works have mainly assumed that participants can complete tasks once they arrive at the location of tasks. However, this assumption may lead to poor reliability in sensing data because the heterogeneity among participants is disregarded. In this study, we investigate a multitask allocation problem that considers the heterogeneity of participants (i.e., different participants carry various devices and accomplish different tasks). A greedy discrete particle swarm optimization with genetic algorithm operation is proposed in this study to address the abovementioned problem. This study is aimed at maximizing the number …

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Ontology Design Patterns For Winston’S Taxonomy Of Part-Whole Relations, Cogan Shimizu, Pascal Hitzler, Clare Paul Jan 2018

Ontology Design Patterns For Winston’S Taxonomy Of Part-Whole Relations, Cogan Shimizu, Pascal Hitzler, Clare Paul

Computer Science and Engineering Faculty Publications

While the formal modeling of part-whole relationships has been of interest, and studied, in many fields including ontology modeling, as of yet there has been no dedicated ontology design pattern which goes beyond the modeling of an absolute minimum. We correct this by providing two patterns based on Winston's landmark paper, "A Taxonomy of Part-Whole Relations".

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Towards A Comprehensive Modular Ontology Ide And Tool Suite, Cogan Shimizu Jan 2018

Towards A Comprehensive Modular Ontology Ide And Tool Suite, Cogan Shimizu

Computer Science and Engineering Faculty Publications

Published ontologies frequently fall short of their promises to enable knowledge sharing and reuse. This may be due to too strong or too weak ontological commitments; one way to prevent this is to en- gineer the ontology to be modular, thus allowing users to more easily adapt ontologies to their own individual use-cases. In order to enable this engineering paradigm, there is a distinct need for developing more supporting tools and infrastructure. This increased support can be im- mediately impactful in a number of ways: Guides engineers through best practices and promote ontology design pattern discovery, sharing, and reuse. To …

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Towards A Pattern-Based Ontology For Chemical Laboratory Procedures, Cogan Shimizu, Leah Mcewen, Quinn Hirt Jan 2018

Towards A Pattern-Based Ontology For Chemical Laboratory Procedures, Cogan Shimizu, Leah Mcewen, Quinn Hirt

Computer Science and Engineering Faculty Publications

There is an increasing expectation in the academic sector for chemistry researchers to conduct risk assessment during experimental planning. However, information concerning laboratory scale chemical reactivity hazards can be difficult to parse despite ongoing efforts to compile from reported incidents. Laboratory procedures do not always directly flag possible incompatibilities among constituents or other process factors. In this paper, we present a pattern-based ontology for capturing multiple factors involved in laboratory procedures, including chemical properties, states, conditions, actions, and associated hazard classifications.

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Metrics For Evaluating Quality Of Embeddings For Ontological Concepts, Faisal Alshargi, Saeedeh Shekarpour, Tommaso Soru, Amit P. Sheth Jan 2018

Metrics For Evaluating Quality Of Embeddings For Ontological Concepts, Faisal Alshargi, Saeedeh Shekarpour, Tommaso Soru, Amit P. Sheth

Kno.e.sis Publications

Although there is an emerging trend towards generating embeddings for primarily unstructured data and, recently, for structured data, no systematic suite for measuring the quality of embeddings has been proposed yet. This deficiency is further sensed with respect to embeddings generated for structured data because there are no concrete evaluation metrics measuring the quality of the encoded structure as well as semantic patterns in the embedding space. In this paper, we introduce a framework containing three distinct tasks concerned with the individual aspects of ontological concepts: (i) the categorization aspect, (ii) the hierarchical aspect, and (iii) the relational aspect. Then, …

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Knowledge Sharing Among Academics In Higher Education Institutions In Saudi Arabia, Fahad M. Alsaadi Jan 2018

Knowledge Sharing Among Academics In Higher Education Institutions In Saudi Arabia, Fahad M. Alsaadi

CCAC Theses and Dissertations

The Ministry of Higher Education (MOHE) in Saudi Arabia aims to move toward a knowledge-based economy and many knowledge management (KM) and knowledge sharing (KS) initiatives have been taken to accelerate the achievement of this goal. Despite the substantial body of research into KS in the business environment, research that investigates factors that promote KS practices among academics in higher education institutions (HEIs) is generally limited, but particularly in Saudi Arabia. To bridge this gap, the goal was to explore what individual and organizational factors contribute to a person’s willingness to share knowledge and develop a profile of the current …

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Identifying Factors Contributing Towards Information Security Maturity In An Organization, Madhuri M. Edwards Jan 2018

Identifying Factors Contributing Towards Information Security Maturity In An Organization, Madhuri M. Edwards

CCAC Theses and Dissertations

Information security capability maturity (ISCM) is a journey towards accurate alignment of business and security objectives, security systems, processes, and tasks integrated with business-enabled IT systems, security enabled organizational culture and decision making, and measurements and continuous improvements of controls and governance comprising security policies, processes, operating procedures, tasks, monitoring, and reporting. Information security capability maturity may be achieved in five levels: performing but ad-hoc, managed, defined, quantitatively governed, and optimized. These five levels need to be achieved in the capability areas of information integrity, information systems assurance, business enablement, security processes, security program management, competency of security team, security …

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Database Streaming Compression On Memory-Limited Machines, Damon F. Bruccoleri Jan 2018

Database Streaming Compression On Memory-Limited Machines, Damon F. Bruccoleri

CCAC Theses and Dissertations

Dynamic Huffman compression algorithms operate on data-streams with a bounded symbol list. With these algorithms, the complete list of symbols must be contained in main memory or secondary storage. A horizontal format transaction database that is streaming can have a very large item list. Many nodes tax both the processing hardware primary memory size, and the processing time to dynamically maintain the tree. This research investigated Huffman compression of a transaction-streaming database with a very large symbol list, where each item in the transaction database schema’s item list is a symbol to compress. The constraint of a large symbol list …

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Standardizing Instructional Definition And Content Supporting Information Security Compliance Requirements, Theresa Curran Jan 2018

Standardizing Instructional Definition And Content Supporting Information Security Compliance Requirements, Theresa Curran

CCAC Theses and Dissertations

Information security (IS)-related risks affect global public and private organizations on a daily basis. These risks may be introduced through technical or human-based activities, and can include fraud, hacking, malware, insider abuse, physical loss, mobile device misconfiguration or unintended disclosure. Numerous and diverse regulatory and contractual compliance requirements have been mandated to assist organizations proactively prevent these types of risks. Two constants are noted in these requirements. The first constant is requiring organizations to disseminate security policies addressing risk management through secure behavior. The second constant is communicating policies through IS awareness, training and education (ISATE) programs. Compliance requirements direct …

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Wireless Sensor Network Clustering With Machine Learning, Larry Townsend Jan 2018

Wireless Sensor Network Clustering With Machine Learning, Larry Townsend

CCAC Theses and Dissertations

Wireless sensor networks (WSNs) are useful in situations where a low-cost network needs to be set up quickly and no fixed network infrastructure exists. Typical applications are for military exercises and emergency rescue operations. Due to the nature of a wireless network, there is no fixed routing or intrusion detection and these tasks must be done by the individual network nodes. The nodes of a WSN are mobile devices and rely on battery power to function. Due the limited power resources available to the devices and the tasks each node must perform, methods to decrease the overall power consumption of …

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Assessing The Role Of Critical Value Factors (Cvfs) On Users’ Resistance Of Urban Search And Rescue Robotics, Marion A. Brown Jan 2018

Assessing The Role Of Critical Value Factors (Cvfs) On Users’ Resistance Of Urban Search And Rescue Robotics, Marion A. Brown

CCAC Theses and Dissertations

Natural and manmade disasters have brought urban search and rescue (USAR) robots to the technology forefront as a means of providing additional support for search and rescue workers. The loss of life among victims and rescue workers necessitates the need for a wider acceptance of this assistive technology. Disasters, such as hurricane Harvey in 2017, hurricane Sandy in 2012, the 2012 United States tornadoes that devastated 17 states, the 2011 Australian floods, the 2011 Japan and 2010 Haiti earthquakes, the 2010 West Virginia coal mine explosions, the 2009 Typhoon caused mudslides in Taiwan, the 2001 Collapse of the World Trade …

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Detecting Fake News In Social Media Networks, Monther Aldwairi, Ali Alwahedi Jan 2018

Detecting Fake News In Social Media Networks, Monther Aldwairi, Ali Alwahedi

All Works

© 2018 The Authors. Published by Elsevier Ltd. Fake news and hoaxes have been there since before the advent of the Internet. The widely accepted definition of Internet fake news is: fictitious articles deliberately fabricated to deceive readers'. Social media and news outlets publish fake news to increase readership or as part of psychological warfare. Ingeneral, the goal is profiting through clickbaits. Clickbaits lure users and entice curiosity with flashy headlines or designs to click links to increase advertisements revenues. This exposition analyzes the prevalence of fake news in light of the advances in communication made possible by the emergence …

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Deep Learning-Based Framework For Autism Functional Mri Image Classification, Xin Yang, Saman Sarraf, Ning Zhang Jan 2018

Deep Learning-Based Framework For Autism Functional Mri Image Classification, Xin Yang, Saman Sarraf, Ning Zhang

Journal of the Arkansas Academy of Science

The purpose of this paper is to introduce deep learning-based framework LeNet-5 architecture and implement the experiments for functional MRI image classification of Autism spectrum disorder. We implement our experiments under the NVIDIA deep learning GPU Training Systems (DIGITS). By using the Convolutional Neural Network (CNN) LeNet-5 architecture, we successfully classified functional MRI image of Autism spectrum disorder from normal controls. The results show that we obtained satisfactory results for both sensitivity and specificity.

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Travel To Extraterrestrial Bodies Over Time: Some Exploratory Analyses Of Mission Data, Venkat Kodali, Rohith Kumar Reddy Duggirala, Richard S. Segall, Hyacinthe Aboudja, Daniel Berleant Jan 2018

Travel To Extraterrestrial Bodies Over Time: Some Exploratory Analyses Of Mission Data, Venkat Kodali, Rohith Kumar Reddy Duggirala, Richard S. Segall, Hyacinthe Aboudja, Daniel Berleant

Journal of the Arkansas Academy of Science

This paper discusses data pertaining to space missions to astronomical bodies beyond earth. The analyses provide summarizing facts and graphs obtained by mining data about (1) missions launched by all countries that go to the moon and planets, and (2) Earth satellites obtained from a Union of Concerned Scientists (UCS) dataset and lists of publically available satellite data.

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Multiclass Classification Of Risk Factors For Cervical Cancer Using Artificial Neural Networks, Abdullah Al Mamun Jan 2018

Multiclass Classification Of Risk Factors For Cervical Cancer Using Artificial Neural Networks, Abdullah Al Mamun

College of Graduate Studies: Theses & Dissertations

World Health Organization statistics show that cervical cancer is the fourth most frequent cancer in women with an estimated 530,000 new cases in 2012. Cervical cancer diagnosis typically involves liquid-based cytology (LBC) followed by a pathologist review. The accuracy of decision is therefore highly influenced by the expert’s skills and experience, resulting in relatively high false positive and/or false negative rates. Moreover, given the fact that the data being analyzed is highly dimensional, same reviewer’s decision is inherently affected by inconsistencies in interpreting the data. In this study, we use an Artificial Neural Network based model that aims to considerably …

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Isolated Mobile Malware Observation, Augustine Paul Jan 2018

Isolated Mobile Malware Observation, Augustine Paul

College of Graduate Studies: Theses & Dissertations

The idea behind Bring Your Own Device (BYOD) it that personal mobile devices can be used in the workplace to enhance convenience and flexibility. This development encourages organizations to allow access of personal mobile devices to business information and systems for businesses operation. However, BYOD opens a firm to various security risks such as data contamination and the exposure of user interest to criminal activities. Mobile devices were not designed to handle intense data security and advanced security features are frequently turned off. Using personal mobile devices can also expose a system to various forms of security threats like malware. …

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การจำแนกประเภทข้อความโฆษณาบนเฟซบุ๊กโดยใช้เทคนิคการสุ่มเพิ่มตัวอย่างกลุ่มน้อย, ศุภมงคล อัครดำรงค์รัตน์ Jan 2018

การจำแนกประเภทข้อความโฆษณาบนเฟซบุ๊กโดยใช้เทคนิคการสุ่มเพิ่มตัวอย่างกลุ่มน้อย, ศุภมงคล อัครดำรงค์รัตน์

Chulalongkorn University Theses and Dissertations (Chula ETD)

นักการตลาดนิยมทำการตลาดผ่านสื่อสังคมออนไลน์มากขึ้นในปัจจุบัน เนื่องจากแพลตฟอร์มโซเชียลมีเดียได้รับความนิยมอย่างมากและมีผู้ใช้งานเป็นจำนวนหลายล้านคน โดยเฉพาะเฟซบุ๊กซึ่งเป็นแพลตฟอร์มที่ได้รับความนิยมสูงสุดในประเทศไทย อย่างไรก็ตามผู้คิดค้นโฆษณาต้องมีความเข้าใจพฤติกรรมของผู้บริโภคเพื่อให้สามารถคิดค้นถ้อยคำโฆษณาที่ดี ตัวแบบ AISAS เป็นตัวแบบหนึ่งซึ่งถูกนำเสนอโดยบริษัทเดนท์สึเพื่ออธิบายพฤติกรรมของผู้บริโภค ตัวแบบดังกล่าวนิยามสถานะที่เกิดขึ้นหลังจากผู้บริโภคเห็นโฆษณาของสินค้าทั้งหมดห้าสถานะ ได้แก่ ความใส่ใจ (Attention) ความสนใจ (Interest) การค้นหา (Search) การลงมือกระทำ (Action) และการแบ่งปัน (Share) วิทยานิพนธ์นี้ได้พัฒนาตัวแบบการเรียนรู้ของเครื่องเพื่อใช้จำแนกประเภทโฆษณาภาษาไทยจากเฟซบุ๊กออกเป็นสถานะตามตัวแบบ AISAS เพื่อเป็นประโยชน์ต่อผู้ลงโฆษณา อย่างไรก็ตาม ข้อมูลที่ถูกรวบรวมมาเพื่อการเรียนรู้เป็นข้อมูลที่ไม่สมดุล เนื่องจากตัวอย่างที่เป็นคลาสบวกมีจำนวนน้อย ทำให้ตัวแบบมีประสิทธิภาพต่ำในการทำนายตัวอย่างบวก เพื่อเพิ่มประสิทธิภาพของตัวแบบ ผู้วิจัยได้นำเทคนิคการสุ่มเพิ่มตัวอย่างกลุ่มน้อย เทคนิคการคัดเลือกคุณลักษณะมาใช้ อีกทั้งได้เสนอเทคนิคการเพิ่มคุณลักษณะใหม่ซึ่งเป็นคำคล้ายคลึง ประยุกต์ใช้ร่วมกับตัวแบบจำแนกประเภทนาอีฟเบย์ การถดถอยโลจิสติกส์ และซัพพอร์ตเวกเตอร์แมชชีน และได้นำเทคนิคการสร้างข้อความมาประยุกต์ใช้ร่วมกับตัวแบบจำแนกประเภทแอลเอสทีเอ็ม ผลการทดลองพบว่าหลังการประยุกต์ใช้เทคนิคต่าง ๆ ทุกตัวแบบจำแนกประเภทสามารถทำนายตัวอย่างคลาสบวกเป็นจำนวนมากขึ้นและถูกต้องมากขึ้นในเกือบทุกชุดข้อมูล โดยสังเกตได้จากค่าความแม่นและค่าระลึกที่เพิ่มขึ้น เทคนิคการเพิ่มคุณลักษณะใหม่ซึ่งเป็นคำคล้ายคลึงทำให้บางตัวแบบมีค่าระลึกเพิ่มขึ้น เทคนิคการสร้างข้อความทำให้ตัวแบบแอลเอสทีเอ็มได้รับค่าระลึกสูงแต่ค่าความแม่นต่ำ อย่างไรก็ตามทุกเทคนิคทำให้ค่าความถูกต้องต่ำลงในชุดข้อมูลส่วนใหญ่

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Is Working With What We Have Enough?, Brian Cusack, Bryce Antony Jan 2018

Is Working With What We Have Enough?, Brian Cusack, Bryce Antony

Australian Digital Forensics Conference

Augmented reality (AR) digital environments have introduced a new complexity to digital investigation where augmented overlays of real objects may be momentary, changed, distorted and evade the usual methods for evidence collection. It is possible an investigator applying standard investigation methods factually reports a real situation and its digital context but has none of the relevant evidence. In this situation the potential for a fair hearing is low and the chance of retrial high. Such situations are unacceptably dangerous and require redress. In this paper the AR condition is considered in terms of its complexity and management during an investigation. …

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Digital Forensics Investigative Framework For Control Rooms In Critical Infrastructure, Brian Cusack, Amr Mahmoud Jan 2018

Digital Forensics Investigative Framework For Control Rooms In Critical Infrastructure, Brian Cusack, Amr Mahmoud

Australian Digital Forensics Conference

In this paper a cyber-forensic framework with a detailed guideline for protecting control systems is developed to improve the forensic capability for big data in critical infrastructures. The main objective of creating a cyber-forensic plan is to cover the essentials of monitoring, troubleshooting, data reconstruction, recovery, and the safety of classified information. The problem to be addressed in control rooms is the diversity and quantity of data, and for investigators, bringing together the different skill groups for managing data and device diversity. This research embraces establishing of a new digital forensic model for critical infrastructures that supports digital forensic investigators …

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Slade: A Smart Large-Scale Task Decomposer In Crowdsourcing, Yongxin Tong, Lei Chen, Zimu Zhou, H. V. Jagadish, Lidan Shou Jan 2018

Slade: A Smart Large-Scale Task Decomposer In Crowdsourcing, Yongxin Tong, Lei Chen, Zimu Zhou, H. V. Jagadish, Lidan Shou

Research Collection School Of Computing and Information Systems

Crowdsourcing has been shown to be effective in a wide range of applications, and is seeing increasing use. A large-scale crowdsourcing task often consists of thousands or millions of atomic tasks, each of which is usually a simple task such as binary choice or simple voting. To distribute a large-scale crowdsourcing task to limited crowd workers, a common practice is to pack a set of atomic tasks into a task bin and send to a crowd worker in a batch. It is challenging to decompose a large-scale crowdsourcing task and execute batches of atomic tasks, which ensures reliable answers at …

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Social Collaborative Media In Software Development, Didi Surian, David Lo Jan 2018

Social Collaborative Media In Software Development, Didi Surian, David Lo

Research Collection School Of Computing and Information Systems

In this entry, we discuss various collaborative media which are commonly used among software developers. We start by discussing common communication channels developers used. These communication channels are discussed in two groups: public and enterprise-wide media. We then elaborate project management media in coordinating and managing project activities. Finally, we discuss a number of online knowledge resources, i.e., collaborative/individual knowledge resources and social networks.

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Consortium Blockchain-Based Sift: Outsourcing Encrypted Feature Extraction In The D2d Network, Xiaoqin Feng, Jianfeng Ma, Tao Feng, Yinbin Miao, Ximeng Liu Jan 2018

Consortium Blockchain-Based Sift: Outsourcing Encrypted Feature Extraction In The D2d Network, Xiaoqin Feng, Jianfeng Ma, Tao Feng, Yinbin Miao, Ximeng Liu

Research Collection School Of Computing and Information Systems

Privacy-preserving outsourcing algorithms for feature extraction not only reduce users' storage and computation overhead but also preserve the image privacy. However, the existing schemes still suffer from deficiencies induced by security, applications, efficiency and storage. To solve the problems, we implement a consortium chain-based outsourcing feature extraction scheme over encrypted images by using the smart contract, distributed autonomous corporation (DAC), sharding technique, and device to device (D2D) communication, which is secure, widely applied, highly efficient, and has less storage overhead. First, the effectiveness, security, and performance of our scheme are analyzed. Then, the efficiency and storage overhead of our scheme …

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Extraction Of Patterns In Selected Network Traffic For A Precise And Efficient Intrusion Detection Approach, Priya Naran Rabadia Jan 2018

Extraction Of Patterns In Selected Network Traffic For A Precise And Efficient Intrusion Detection Approach, Priya Naran Rabadia

Theses: Doctorates and Masters

This thesis investigates a precise and efficient pattern-based intrusion detection approach by extracting patterns from sequential adversarial commands. As organisations are further placing assets within the cyber domain, mitigating the potential exposure of these assets is becoming increasingly imperative. Machine learning is the application of learning algorithms to extract knowledge from data to determine patterns between data points and make predictions. Machine learning algorithms have been used to extract patterns from sequences of commands to precisely and efficiently detect adversaries using the Secure Shell (SSH) protocol. Seeing as SSH is one of the most predominant methods of accessing systems it …

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Containment Control Of Heterogeneous Systems With Non-Autonomous Leaders: A Distributed Optimal Model Reference Approach, Yongliang Yang, Shusen Cheng, Yixin Yin, Donald C. Wunsch Jan 2018

Containment Control Of Heterogeneous Systems With Non-Autonomous Leaders: A Distributed Optimal Model Reference Approach, Yongliang Yang, Shusen Cheng, Yixin Yin, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

This paper presents a distributed optimal model reference adaptive control approach for solving containment control of heterogeneous multi-agent systems (MASs) with non-autonomous leaders. First, a fully distributed adaptive observer is designed to provide for each agent the desired reference trajectory by estimating the convex hull spanned by leaders. The distributed observer dynamics serves as a reference model for each follower to synchronize. The global communication graph information or the leader dynamics is not required to design the observer. In contrast to existing model reference adaptive controllers (MRAC) for single-agent systems and containment control solutions for MASs, the proposed MRAC approach …

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