Computer Sciences Commons^™

The Knapsack Subproblem Of The Algorithm To Compute The Erdos-Selfridge Function, Brianna Sorenson

Undergraduate Honors Thesis Collection

This thesis summarizes the methodology of a new algorithm to compute the Erdos-Selfridge function which uses a wheel sieve, shows that a knapsack algorithm can be used to minimize the work needed to compute these values by selecting a subset of rings for use in the wheel, and compares the results of several different knapsack algorithms in this particular scenario.

Artificial Intelligence-Enhanced Decision Support For Informing Global Sustainable Development: A Human-Centric Ai-Thinking Approach, Meng-Leong How, Sin Mei Cheah, Yong-Jiet Chan, Aik Cheow Khor, Eunice Mei Ping Say

CCX Research

Sustainable development is crucial to humanity. Utilization of primary socio-environmental data for analysis is essential for informing decision making by policy makers about sustainability in development. Artificial intelligence (AI)-based approaches are useful for analyzing data. However, it was not easy for people who are not trained in computer science to use AI. The significance and novelty of this paper is that it shows how the use of AI can be democratized via a user-friendly human-centric probabilistic reasoning approach. Using this approach, analysts who are not computer scientists can also use AI to analyze sustainability-related EPI data. Further, this human-centric probabilistic …

Process Data Analytics Using Deep Learning Techniques, Majid Moradi Aliabadi

Wayne State University Theses

In chemical manufacturing plants, numerous types of data are accessible, which could be process operational data (historical or real-time), process design and product quality data, economic and environmental (including process safety, waste emission and health impact) data. Effective knowledge extraction from raw data has always been a very challenging task, especially the data needed for a type of study is huge. Other characteristics of process data such as noise, dynamics, and highly correlated process parameters make this more challenging.

In this study, we introduce an attention-based RNN for multi-step-ahead prediction that can have applications in model predictive control, fault diagnosis, …

A Survey On Recognizing Textual Entailment As An Nlp Evaluation, Adam Poliak

Computer Science Faculty Research and Scholarship

Recognizing Textual Entailment (RTE) was proposed as a unified evaluation framework to compare semantic understanding of different NLP systems. In this survey paper, we provide an overview of different approaches for evaluating and understanding the reasoning capabilities of NLP systems. We then focus our discussion on RTE by highlighting prominent RTE datasets as well as advances in RTE dataset that focus on specific linguistic phenomena that can be used to evaluate NLP systems on a fine-grained level. We conclude by arguing that when evaluating NLP systems, the community should utilize newly introduced RTE datasets that focus on specific linguistic phenomena.

Context-Aware System For Glycemic Control In Diabetic Patients Using Neural Networks, Owais Bhat, Dawood A. Khan

Turkish Journal of Electrical Engineering and Computer Sciences

Diabetic patients are quite hesitant in engaging in normal physiological activities due to difficulties associated with diabetes management. Over the last few decades, there have been advancements in the computational power of embedded systems and glucose sensing technologies. These advancements have attracted the attention of researchers around the globe developing automatic insulin delivery systems. In this paper, a method of closed-loop control of diabetes based on neural networks is proposed. These neural networks are used for making predictions based on the clinical data of a patient. A neural network feedback controller is also designed to provide a glycemic response by …

A Power And Area Efficient Approximate Carry Skip Adder For Error Resilient Applications, Sujit Patel, Bharat Garg, Shireesh Kumar Rai

Turkish Journal of Electrical Engineering and Computer Sciences

The compute-intensive multimedia applications on portable devices require power and area efficient arithmetic units. The adder is a prime building block of these arithmetic units and limits the overall performance. Therefore, this paper analyzes the logic operations of the state-of-the-art adders and presents a novel low complexity adder segment with new carry prediction logic by removing the redundant logic and sharing the common operations. Further, a new power and area efficient approximate carry skip (PAEA-CSK) adder is proposed using the novel adder segment. The effectiveness of the proposed PAEA-CSK adder is evaluated and compared over the existing adders by implementing …

Rule Extraction And Performance Estimation By Using Variable Neighborhoodsearch For Solar Power Plant In Konya, Yusuf Uzun, Muci̇z Özcan

Turkish Journal of Electrical Engineering and Computer Sciences

The use of renewable energy sources in the production of electricity has become inevitable in order to reduce the greenhouse gases left in the atmosphere that cause the Earth to warm up. Although countries on a national basis have implemented a number of policies to support electricity generated from renewable energy sources, investments to produce electricity without a license on a local basis are not desirable. Those who want to invest medium and small scale for the most reason expect that this work will be supported by real data. Although the electricity generated by renewable investments is generated by simulation …

Robust Optimal Operation Of Smart Distribution Grids With Renewable Basedgenerators, Omid Zare, Sadjad Galvani, Murtaza Farsadi

Turkish Journal of Electrical Engineering and Computer Sciences

Modern distribution systems are equipped with various distributed energy resources (DERs) because of the importance of local generation. These distribution systems encounter more and more uncertainties because of the ever-increasing use of renewable energies. Other sources of uncertainty, such as load variation and system components? failure, will intensify the unpredictable nature of modern distribution systems. Integrating energy storage systems into distribution grids can play a role as a flexible bidirectional source to accommodate issues from constantly varying loads and renewable resources. The overall functionality of these modern distribution systems is enhanced using communication and computational abilities in smart grid frameworks. …

Assessment Of Environmental Factors Affecting Software Reliability: A Survey Study, Alper Özcan, Çağatay Çatal, Cengi̇z Toğay, Bedi̇r Teki̇nerdoğan, Emrah Dönmez

Turkish Journal of Electrical Engineering and Computer Sciences

Currently, many systems depend on software, and software reliability as such has become one of the key challenges. Several studies have been carried out that focus on the impact of external environmental factors that impact software reliability. These studies, however, were all carried out in the same geographical context. Given the rapid developments in software engineering, this study aims to identify and reinvestigate the environmental factors that impact software reliability by also considering a different context. The environmental factors that have an impact on software reliability as reported in earlier studies have been analyzed and synthesized. Subsequently, a survey study …

Prominent Quality Attributes Of Crisis Software Systems: A Literature Review, Ahmet Ari̇f Aydin

Turkish Journal of Electrical Engineering and Computer Sciences

Developing software systems to meet user-demanded functionality is critical. Achieving the design goals by providing the needed functionality is a necessary task, and it is about figuring out a proper set of quality attributes and implementing each one by reflecting a complete set of quality attributes. This study presents popular quality attributes of crisis software systems by conducting a literature review. Each crisis software system has been studied by concentrating on crisis management phases where the system is used, design purposes, and the data processing style. The findings of this research shed light on the crisis software development process by …

A Mechanism Of Qos Differentiation Based On Offset Time And Adjusted Burstlength In Obs Networks, Viet Minh Nhat Vo, Trung Duc Pham, Thanh Chuong Dang, Van Hoa Le

Turkish Journal of Electrical Engineering and Computer Sciences

Quality of service (QoS) differentiation is an integral component of any networking system, particularly, with the current and future great diversity of users? applications and their manifold requirements. In optical burst switching (OBS) networks, there are two approaches for QoS differentiation: one is based on offset time and the other is based on burst length. This paper presents a mechanism of QoS differentiation based on both offset time and burst length, in which the offset times are calculated to achieve a complete isolation of data loss between priority classes and the burst length is adaptively adjusted according to the feedbacked …

Diagnosis Of Speed Sensor Faults In An Induction Machine Based On A Robustadaptive Super-Twisting Observer, Mohammed Zakaria Kari, Abdelkader Mechernene, Sidi Mohammed Meliani, Ibrahim Guenoune

Turkish Journal of Electrical Engineering and Computer Sciences

The present paper aims to determine a robust sensor fault-tolerant controller based on fuzzy logic using a robust adaptive super-twisting observer for the control of an induction machine and an inverter set by a state estimation method. The speed sensor is considered in the present case. The modular structure of the fault-tolerant control (FTC) scheme allows integrating this sensor within the existing closed-loop system, and the observer can therefore be designed independently. This article presents a new method to develop a fuzzy decision system that provides faulttolerant control. This paper also aims at detecting the mechanical speed sensor faults. The …

A Collaborative Online Micro: Bit K-12 Teacher Pd Workshop, Roisin Faherty, Karen Nolan, Keith Quille

Conference Papers

This poster describes the use of online technology to deliver K12 teacher professional development (PD) during the COVID-19 pandemic in Ireland. Traditionally these sessions are delivered in person, with a focus on hand-on activities, but the sudden changes faced by the closures in Ireland required an alternative approach for delivering these sessions. The PD session presented in this poster was a more technically challenging micro:bit workshop, which was delivered online using the micro:bit classroom. This is typically used as an in-class, one to many instructor tool, and trialing this as a PD collaborative tool, was a novel approach. This poster …

Poincaré Embeddings In The Task Of Named Entity Recognition, David Muñoz, Fernando Pérez Téllez, David Pinto

Conference Papers

Hyperbolic embeddings have become important in many natural language processing tasks due to their great ability to capture latent hierarchical data and to encode valuable syntactic and semantic information. We study and consider the ability of Poincaré embeddings to get the most similar nodes to a given node when trying to recognize named entities in a set of text documents. In this paper, we propose a classifier model for the NER (Named Entity Recognition) task by implementing Poincaré embeddings and by using the most frequent n-grams and their Part-of-Speech (POS) structures from the training dataset. We found that POS structures …

Road Network Simplification For Location-Based Services, Abdeltawab Hendawi, John A. Stankovic, Ayman Taha, Shaker El-Sappagh, Amr A. Ahmadain, Mohamed Ali

Articles

Road-network data compression or simplification reduces the size of the network to occupy less storage with the aim to fit small form-factor routing devices, mobile devices, or embedded systems. Simplification (a) reduces the storage cost of memory and disks, and (b) reduces the I/O and communication overhead. There are several road network compression techniques proposed in the literature. These techniques are evaluated by their compression ratios. However, none of these techniques takes into consideration the possibility that the generated compressed data can be used directly in Map-matching operation which is an essential component for all location-aware services. Map-matching matches a …

Representation Learning With Autoencoders For Electronic Health Records, Najibesadat Sadatijafarkalaei

Wayne State University Theses

Increasing volume of Electronic Health Records (EHR) in recent years provides great opportunities for data scientists to collaborate on different aspects of healthcare research by applying advanced analytics to these EHR clinical data. A key requirement however

is obtaining meaningful insights from high dimensional, sparse and complex clinical data. Data science approaches typically address this challenge by performing feature learning in order to build more reliable and informative feature representations from clinical data followed by supervised learning. In this research, we propose a predictive modeling approach based on deep feature representations and word embedding techniques. Our method uses different deep …

An Investigation Of The Factors That Contribute To The Perceived Likelihood Of Compliance With The Hipaa Security Rule Among Healthcare Covered Entities And Business Associates, James Furstenberg

CCAC Theses and Dissertations

The Health Insurance Portability and Accountability Act (HIPAA) Security Rule (SR) mandate provides a national standard for the safeguard of electronically protected health information (ePHI). SR compliance enforcement efforts started in 2005; however, U.S.-based covered entities and business associates (CEs & BAs) remain challenged to comply with the HIPAA SR regulatory strategy. Although there is a significant volume of academic research on HIPAA compliance, research specific to the SR is sparse.

This study addressed the research gap by designing a unique conceptual model that assessed factors affecting CEs & BAs compliance (or non-compliance) with the SR regulatory strategy. The primary …

Organizational Culture And Knowledge Transfer In Enterprise Social Media, Garry Blackstock

CCAC Theses and Dissertations

Enterprise social media (ESM), digital platforms used within organizations to facilitate knowledge sharing and collaboration, are valuable tools that can help organizations gain a competitive advantage. Efficient retention, dissemination, and transfer of knowledge is an industry differentiator, and companies are spending a tremendous amount of resources on ESM to achieve this discriminating advantage. The behavior of transferring knowledge, especially tacit knowledge, can be a challenging task. Discordant organizational culture has been identified as a barrier to efficient knowledge transfer, whether it is explicit or tacit. Despite ESM’s positive track record of promoting communication, it lacks the efficiency to facilitate knowledge …

Sns Use, Risk, And Executive Behavior, Andrew Green

CCAC Theses and Dissertations

Andrew Green April 2020 Personal social networking sites (SNS) are popular outlets for people to share information about themselves, their family and friends, and their personal and professional lives. On the surface, the information shared may seem to be innocuous or nonthreatening. However, prior studies have shown that cybercriminals can take information shared via personal SNS and use it to conduct attacks against organizations. Organization executives are of particular interest to cybercriminals because they have access to sensitive data, and they also have the ability to command actions from their subordinates. The purpose of this study was to explore what …

Reducing Bittorrent Download Time Via Handshake-Based Switching, Elliotte Kim

CCAC Theses and Dissertations

Peer-to-peer networking overcomes the single point of failure and bandwidth limitations inherent to the centralized server model of file-sharing. It is both a popular means of sharing digital content and a major consumer of internet traffic, with BitTorrent being the most-used protocol. As such, significant research has gone into improving peer-to-peer performance in order to reduce both download times and networking costs. One aspect that can affect performance is the client’s selection of peers to download from, as the time spent downloading from even a single poor-performing peer can impact the overall download duration.

A recent peer selection strategy explored …

Examining The Creation Of Information Privacy Culture In Healthcare Organizations To Achieve Collective Hipaa Compliance Practice, Osborne Obeng

CCAC Theses and Dissertations

The digitization and transfer of patient records has increased the risk of patient data being improperly handled by healthcare organizations. In light of this growing concern, the United States government and state authorities have implemented various regulations to mitigate the privacy concerns. Beside privacy regulations, healthcare organizations have been forced by other pressures such as organization’s competitive pressures, resources, ethical responsibilities, and legitimacy to implement privacy safeguards. However, surveys show that healthcare organizations fail to achieve information privacy compliance. This study examined the creation of information privacy culture from the different occupational communities in healthcare organizations to help achieve information …

Smart Privacy For Iot: Privacy Embedded Design For Home Automation Systems, Love James

CCAC Theses and Dissertations

The emerging paradigm shift in technology to make everyday devices more intelligent than previously considered also known as internet of things (IoT) has further elevated the importance of privacy not only in theory but also in practice. The intrusive nature of these devices and in particular, the home automation system is also beginning to raise privacy concerns which might impact their usage either by deterring potential users from adopting the technology or discouraging existing users from the continued use of these home automation systems.

This study was an empirical and quantitative study that evaluates the impact of users’ behavior when …

Improvements To Iterated Local Search For Microaggregation, Tracy Bierman

CCAC Theses and Dissertations

Microaggregation is a disclosure control method that uses k-anonymity to protect confidentiality in microdata while seeking minimal information loss. The problem is NP-hard. Iterated local search for microaggregation (ILSM) is an effective metaheuristic algorithm that consistently identifies better quality solutions than extant microaggregation methods. The present work presents improvements to local search, the perturbation operations and acceptance criterion within ILSM.

The first, ILSMC, targets changed clusters within local search (LS) to avoid vast numbers of comparison tests, significantly reducing execution times. Second, a new probability distribution yields a better perturbation operator for most cases, significantly reducing the number of iterations …

An Empirical Assessment Of Audio/Visual/Haptic Alerts And Warnings To Mitigate Risk Of Phishing Susceptibility In Emails On Mobile Devices, Molly Marie Cooper

CCAC Theses and Dissertations

Phishing emails present a threat to both personal and organizational data. Phishing is a cyber-attack using social engineering. About 94% of cybersecurity incidents are due to phishing and/or social engineering. A significant volume of prior literature documented that users are continuing to click on phishing links in emails, even after phishing awareness training. It appears there is a strong need for creative ways to alert and warn users to signs of phishing in emails.

The main goal of the experiments in this study was to measure participants’ time for recognizing signs of phishing in emails, thus, reducing susceptibility to phishing …

Sns As An Educational Tool: Effect On Academic Performance And Learners’ Perceptions, Nawwaf Mohssen Altalhi

CCAC Theses and Dissertations

With Social Networking Sites (SNSs) being extensively used by students, there has been extensive research in relation to their ability to enhance students’ academic performance in various learning environments, although the advent of research on online learning is a recent development.

Studies regarding the use of SNSs indicated that there was a negative relationship between students’ use of SNSs and students’ academic performance. However, it is unknown whether the implementation of an instructional training course utilizing SNSs as an educational tool might lead to improvements in students’ academic performance. Many students have admitted to not knowing how to properly use …

A Hierarchical Temporal Memory Sequence Classifier For Streaming Data, Jeffrey Barnett

CCAC Theses and Dissertations

Real-world data streams often contain concept drift and noise. Additionally, it is often the case that due to their very nature, these real-world data streams also include temporal dependencies between data. Classifying data streams with one or more of these characteristics is exceptionally challenging. Classification of data within data streams is currently the primary focus of research efforts in many fields (i.e., intrusion detection, data mining, machine learning). Hierarchical Temporal Memory (HTM) is a type of sequence memory that exhibits some of the predictive and anomaly detection properties of the neocortex. HTM algorithms conduct training through exposure to a stream …

An Approach To Twitter Event Detection Using The Newsworthiness Metric, Jonathan Adkins

CCAC Theses and Dissertations

No abstract provided.

Detecting Rogue Manipulation Of Smart Home Device Settings, David Zeichick

CCAC Theses and Dissertations

Smart home devices control a home’s environmental and security settings. This includes devices that control home thermostats, sprinkler systems, light bulbs, and home appliances. Malicious manipulation of the settings of these devices by an outside adversary has caused emotional distress and could even cause physical harm. For example, researchers have reported that there is a rise in domestic abuse perpetrated via smart home devices; victims have reported their thermostat settings being unwittingly manipulated and being locked out of their house due to their smart lock code being changed. Rapid adoption of smart home devices by consumers has led to an …

Development Of Criteria For Mobile Device Cybersecurity Threat Classification And Communication Standards (Ctc&Cs), Emmanuel Jigo

CCAC Theses and Dissertations

The increasing use of mobile devices and the unfettered access to cyberspace has introduced new threats to users. Mobile device users are continually being targeted for cybersecurity threats via vectors such as public information sharing on social media, user surveillance (geolocation, camera, etc.), phishing, malware, spyware, trojans, and keyloggers. Users are often uninformed about the cybersecurity threats posed by mobile devices. Users are held responsible for the security of their device that includes taking precautions against cybersecurity threats. In recent years, financial institutions are passing the costs associated with fraud to the users because of the lack of security.

The …

Unix Administrator Information Security Policy Compliance: The Influence Of A Focused Seta Workshop And Interactive Security Challenges On Heuristics And Biases, John Palmer Mcconnell

CCAC Theses and Dissertations

Information Security Policy (ISP) compliance is crucial to the success of healthcare organizations due to security threats and the potential for security breaches. UNIX Administrators (UXAs) in healthcare Information Technology (IT) maintain critical servers that house Protected Health Information (PHI). Their compliance with ISP is crucial to the confidentiality, integrity, and availability of PHI data housed or accessed by their servers. The use of cognitive heuristics and biases may negatively influence threat appraisal, coping appraisal, and ultimately ISP compliance behavior. These failures may result in insufficiently protected servers and put organizations at greater risk of data breaches and financial loss. …