Computer Engineering Commons^™

Penetration Testing In A Small Business Network, Lee Kandle

Williams Honors College, Honors Research Projects

Penetration testing on a business network consisting of three routers, one switch, and one computer. Access Control Lists (ACLs) on the routers act as the firewall(s) for the network. 10 of the twelve ACLs do not deny any form of traffic to reflect the lax security standards common in small networks. Router 1 acts as the primary router of the Attacker/Pen Tester. Router 2 represents the edge router for the business and Router 3 is the inner router closest to end-user devices. Switch 1 is connected to Router 3 with one computer connected to the switch acting as an end-user. …

Career Engine, Sai Akhil Gujja

All Capstone Projects

People's education is so widely available in this age of tough competition that openings for them in jobs are getting harder to find. Companies need people in their fields with a solid educational foundation and maximum years of job experience. Finding people who are talented, intelligent, and competent enough to be given a position at that time is challenging. Companies are working harder than ever to find people who can meet their needs.[1] Thousands of applicants are competing for one job opening. When considering these difficulties, one may come up with a strategy or approach that can help manage and …

R Stack Career, Hari Krishna Patti

All Capstone Projects

The Career Engine's main purpose is to create a platform for job searchers to find suitable and gratifying work based on their qualifications. It also connects job searchers with the recruiting process. This career engine recognizes when a job seeker applies for a job and when a company publishes a job and chooses a candidate. A career engine's principal objective is to aid job searchers in getting a quick career. In today's society, there are several employment portal platforms. In this case, we must create a web-based application utilizing the Career Engine. In this period of decline, everyone, experienced or …

Career Engine (Jobesy), Vijaya Lakshmi Patti

All Capstone Projects

In today's world, finding a job is like a rat race in every professional field. The scenario is such that finding jobs that fit the skill sets and interests takes much work for job seekers. On the other side, recruiters face similar challenges in finding the finest candidate to match their requirements.

Talent jet is a website with unique ingredients to solve all these challenges. Talent jet provides an easy and convenient search application for job seekers to find their desired job and recruiters to find suitable candidates. Talent jet will provide a platform where job seekers and recruiters can …

Career Engine, Anoop Vivek Sagar Mallavarapu

All Capstone Projects

People's education is so widely available in this age of tough competition that openings for them in jobs are getting harder to find. Companies need people in their fields with a solid educational foundation and maximum years of job experience. Finding people who are talented, intelligent, and competent enough to be given a position at that time is challenging. Companies are working harder than ever to find people who can meet their needs.[1] Thousands of applicants are competing for one job opening. When considering these difficulties, one may come up with a strategy or approach that can help manage and …

Evolution And Diffusion Of Icts In The Indian Railways: A Historical Analysis, Ramesh Subramanian

Journal of International Technology and Information Management

The Indian Railway system is one of the largest socio-technical systems in the world. It has existed for over 160 years, starting from the British Colonial times. It continues to play a critical role in present-day India. It’s continued functioning is dependent not only on the personnel who are employed in the railways, but also the technologies that go into the system. A critical technology in the functioning of the railway system is information and communications technologies (ICTs). ICTs are deployed in almost every facet of the railway system. But these ICTs did not manifest themselves recently. They have been …

Online Discussion Forum And Pre-Migration Information Seeking: An Affordance Perspective, Daniel Gulanowski, Luciara Nardon, Michael J. Hine

Journal of International Technology and Information Management

Potential immigrants increasingly rely on online technologies to access needed information as they have limited access to offline sources of information at the pre-arrival stage. The purpose of this paper is to investigate the role of online discussion forums in facilitating potential immigrants’ access to relevant information about the host country labor market. This paper draws on extant literature on computer-mediated communication and a qualitative content analysis of 363 forum discussions to explore the phenomenon of increased use of online forums by prospective immigrants to Canada to access relevant labor market information. We draw on existing concepts of technology affordances …

Jitim Table Of Contents - Vol. 31 Issue 2 - 2022

Journal of International Technology and Information Management

JITIM ToC

Assessing Performance Impact Of Digital Transformation For Instructors In The Covid-19 Era, Shailja Tripathi Dr., Shubhangi Urkude Dr.

Journal of International Technology and Information Management

Digital transformation has evolved as the main issue for higher education institutions (HEIs) across the globe due to the Covid-19 outbreak. The purpose of this study is to investigate the performance impacts of digital transformation for instructors of HEIs during the pandemic. The technology-to-performance chain (TPC) model pursues to predict the influence of an information system on the performance of an individual user. Hence, TPC model is used to evaluate the performance of instructors due to digital transformation in the institutions during the Covid-19 pandemic. The data is collected from instructors of higher educational institutions. Recently, partial least squares path …

Effect Of Connection State & Transport/Application Protocol On The Machine Learning Outlier Detection Of Network Intrusions, George Yuchi, Torrey J. Wagner, Paul Auclair, Brent T. Langhals

Faculty Publications

The majority of cyber infiltration & exfiltration intrusions leave a network footprint, and due to the multi-faceted nature of detecting network intrusions, it is often difficult to detect. In this work a Zeek-processed PCAP dataset containing the metadata of 36,667 network packets was modeled with several machine learning algorithms to classify normal vs. anomalous network activity. Principal component analysis with a 10% contamination factor was used to identify anomalous behavior. Models were created using recursive feature elimination on logistic regression and XGBClassifier algorithms, and also using Bayesian and bandit optimization of neural network hyperparameters. These models were trained on a …

Modeling Iot Solutions: A Lack Of Iot Device Security, And User Education, Benjamin Newlin

Cybersecurity Undergraduate Research Showcase

The Internet of Things, more commonly known as IoT devices, is an ever growing topic, both in the marketplace and in cyber security. While new devices are released into the public every year, a lack of standardized security concepts is also growing ever so clear. By having a model or standard for IoT devices and manufacturers to follow, the customer-base of these devices will have an easier time identifying trustworthy devices as well as how to secure their own devices.

การทำนายค่าฝุ่น Pm2.5 ทั้งในเชิงแผนที่และเชิงเวลาด้วยเทคนิคการเรียนรู้เชิงลึก, ณัฏฐ์ ศิริสัมพันธ์

Chulalongkorn University Theses and Dissertations (Chula ETD)

PM2.5 เป็นอนุภาคขนาดเล็กที่มีส่วนทำให้เกิดปัญหามลพิษทางอากาศในประเทศไทย การหายใจนำฝุ่น PM2.5 เข้าไปสามารถทำให้เกิดปัญหาสุขภาพตามมาได้ เช่น โรคทางเดินหายใจและโรคหัวใจเสื่อมสภาพ รวมถึงเพิ่มความเสี่ยงต่อการเสียชีวิตก่อนวัยอันควร งานวิจัยนี้เสนอแบบจำลองที่ใช้การเรียนรู้เชิงลึกเพื่อทำนายค่าฝุ่น PM2.5 ในระดับประเทศซึ่งเป็นการทำนายทั้งในเชิงพื้นที่และเวลา โดยแบบจำลองที่นำเสนอมีชื่อว่า SimVP-CFLL-ML มีพื้นฐานมาจากแบบจำลองการทำนายวิดีโอที่เรียกว่า "SimVP" และเพื่อเพิ่มประสิทธิภาพในการทำนายค่าฝุ่น PM2.5 ในช่วงที่มีค่าฝุ่นสูง SimVP ได้มีการพัฒนาเพิ่มเติมสองประการ คือ 1.Cross-Feature Learning Layer (CFLL) ซึ่งใช้ 1x1 convolution layer เพื่อเรียนรู้ความสัมพันธ์ของคุณลักษณะและ 2.Masking Layer (ML) ซึ่งใช้สำหรับคำนวณค่าลอสเฉพาะส่วนที่สำคัญที่ต้องการทำนาย โดยในที่นี้คือส่วนที่เป็นประเทศไทย การทดลองดำเนินการโดยใช้ข้อมูลที่เก็บรวบรวมจากกรมควบคุมมลพิษของประเทศไทยและโครงการ Sensor For All (SFA) ผลการทดลองแสดงให้เห็นว่าแบบจำลองของเราเหนือกว่าแบบจำลองพื้นฐานทั้งหมด โดยเฉพาะในกรณีที่ต้องการจำแนกช่วงที่ค่าฝุ่นมีค่าสูง แบบจำลองของเราได้ผลลัพธ์ค่าคะแนน F1 สูงกว่าแบบจำลองพื้นฐานที่ดีที่สุดถึง 3.51%

ระบบสนับสนุนการจัดเก็บและวิเคราะห์ข้อมูลลำดับซ้ำเรียงต่อเนื่องแบบสั้นสำหรับนิติวิทยาศาสตร์, ณัฏฐชัย กุลธรรมนิตย์

Chulalongkorn University Theses and Dissertations (Chula ETD)

ลำดับซ้ำเรียงต่อเนื่องแบบสั้น (Short Tandem Repeat) หรือเอสทีอาร์ (STR) เป็นลำดับที่ซ้ำกันเป็นชุด ๆ ที่พบได้ในจีโนม (Genome) ของมนุษย์และมีประโยชน์มากในนิติวิทยาศาสตร์ เช่น การยืนยันตัวบุคคล การหาความสัมพันธ์ทางเครือญาติ เทคโนโลยีการลำดับเบสยุคใหม่ (Next-Generaton Sequencing: NGS) เช่น ForenSeq Signature Prep สามารถหาลำดับ STRs และให้ข้อมูลเชิงลึกเกี่ยวกับโครงสร้างประชากรได้ ถึงแม้ว่าเอสทีอาร์ที่ได้จากเทคโนโลยีนี้จะมีประโยชน์มากมาย แต่ไม่มีแพลตฟอร์มซอฟต์แวร์โอเพ่นซอร์สใดที่รวมการจัดการและการวิเคราะห์ข้อมูลของเอสทีอาร์ไว้ในแพลตฟอร์มเดียว ผู้ใช้งานอาจต้องใช้หลายโปรแกรมในการวิเคราะห์ข้อมูลเอสทีอาร์ จากนั้นรวบรวมผลลัพธ์ลงในฐานข้อมูลแยกหรือโฟลเดอร์ระบบไฟล์ เพื่อแก้ไขปัญหาดังกล่าว ระบบที่นำเสนอ STRategy เป็นเว็บแอพพลิเคชันที่มีระบบการจัดการและวิเคราะห์ข้อมูลเอสทีอาร์ โดย STRategy อนุญาตให้ผู้ใช้งานเก็บข้อมูลลงฐานข้อมูลหลังจากนั้นระบบจะวิเคราะห์และแสดงผลข้อมูลโดยอัตโนมัติ ระบบนี้ถูกออกแบบให้ใช้ในองค์กรหรือห้องปฏิบัติการ จึงมีระบบการกำหนดสิทธิผู้ใช้ระบบตามบทบาท (Role Based Access Control) เพื่อให้ผู้ใช้งานเข้าถึงข้อมูลตามสิทธิของแต่ละบุคคลเท่านั้น ระบบถูกออกแบบให้มีความยืดหยุ่นสูง และได้ปฏิบัติตามแนวคิดสถาปัตยกรรม 3-เลเยอร์ หลักการออกแบบโปรแกรมเชิงวัตถุ รวมถึงมีการใช้แบบรูป (Design patterns) ต่าง ๆ เพื่อรองรับการเพิ่มโมดูลการวิเคราะห์และโมดูลการแสดงผล รวมถึงการพัฒนาต่อยอดได้ง่ายในอนาคต

Development Of An Explainability Scale To Evaluate Explainable Artificial Intelligence (Xai) Methods, Stephen Mccarthy

Dissertations

Explainable Artificial Intelligence (XAI) is an area of research that develops methods and techniques to make the results of artificial intelligence understood by humans. In recent years, there has been an increased demand for XAI methods to be developed due to model architectures getting more complicated and government regulations requiring transparency in machine learning models. With this increased demand has come an increased need for instruments to evaluate XAI methods. However, there are few, if none, valid and reliable instruments that take into account human opinion and cover all aspects of explainability. Therefore, this study developed an objective, human-centred questionnaire …

An Approach For Performance Prediction Of Saturated Brushed Permanent Magnetdirect Current (Dc) Motor From Physical Dimensions, Rasul Tarvirdilu, Reza Zeinali, Hulusi̇ Bülent Ertan

Turkish Journal of Electrical Engineering and Computer Sciences

An analytical approach for performance prediction of saturated brushed permanent magnet direct current (DC) motors is proposed in this paper. In case of a heavy saturation in the stator back core of electrical machines, some flux completes its path through the surrounding air, and the conventional equivalent circuit cannot be used anymore. This issue has not been addressed in the literature. The importance of considering the effect of the flux penetrating the surrounding air is shown in this paper using finite element simulations and experimental results, and an analytical approach is proposed to consider this effect on magnet operating point …

Evaluation Of Automated Eye Blink Artefact Removal Using Stacked Dense Autoencoder, Matthew Rigney

Dissertations

The presence of artefacts in Electroencephalograph (EEG) signals can have a considerable impact on the information they portray. In this comparative study, the automated removal of eye blink artefacts using the constrained latent representation of a stacked dense autoencoders (SDAE) and comparing its ability to that of the manual independent component analysis (ICA) approach was evaluated. A comparative evaluation of 5 stacked dense autoencoder architectures lead to a chosen architecture for which the ability to automatically detect and remove eye blink artefacts were both statistically and humanistically evaluated. The ability of the stacked dense autoencoder was statistically evaluated with the …

Scrolling Vs Paging: Reading Performance And Preference Of Reading Modes In Long-Form Online News, Richard Herlihy

Dissertations

This study explores the impact of scrolling and dynamic pagination in long-form online documents on reader performance and reader experience. Previous research has produced mixed results, indicating no difference between modes, or a positive effect favouring scrolling. Recent advances in web standards have enabled simpler, dynamic, performant methods of pagination to tailor content responsively to any screen, meriting renewed study in this area. This paper uses one such method to load subsequent online news pages instantly without buffering. In an online browser experiment with 38 participants, an increase in reading speed in the scrolling mode was found at a level …

Study On Performance Of Pruned Cnn-Based Classification Models, Mengling Deng

Electronic Theses and Dissertations

Convolutional Neural Network (CNN) is a neural network developed for processing image data. CNNs have been studied extensively and have been used in numerous computer vision tasks such as image classification and segmentation, object detection and recognition, etc. [1] Although, the CNNs-based approaches showed humanlevel performances in these tasks [2], they require heavy computation in both training and inference stages, and the models consist of millions of parameters. This hinders the development and deployment of CNN-based models for real world applications. Neural Network Pruning and Compression techniques have been proposed [3, 4] to reduce the computation complexity of trained CNNs …

Home Energy Management System Considering Effective Demand Response Strategies And Uncertainties, Marcos Tostado-Véliz, Paul Arévalo, Salah Kamel, Hossam Zawbaa, Francisco Jurado

Articles

Nowadays, load serving entities require more active participation from consumers. In this context, demand response programs and home energy management systems play a crucial role in achieving multiple goals such as peak clipping. However, the adoption of demand response initiatives typically has a negative impact on the monetary expenditures of the users. This way, a demand response program should be as effective as possible to make the different goals more easily achievable without compromising the financial requirements of the users. This paper develops a home energy management system that incorporates three novel effective demand response strategies. The effectiveness of the …

Removing Physical Presence Requirements For A Remote And Automated World - Api Controlled Patch Panel For Conformance Testing, Hunter George Wells

Honors Theses and Capstones

Quality assurance test engineers at the UNH-InterOperability Lab must run tests that require driving and monitoring a selection of DC signals. While the number of signals is numerous, there are limited ports on the test equipment, and only a few signals need patching for any given test. The selection of signals may vary between the 209 different tests and must be re-routed frequently. Currently, testers must leave their desk to manually modify the test setup in another room. This posed a considerable issue at the onset of the COVID-19 Pandemic when physical access was not possible. In order to enable …

Human Mental Workload: A Survey And A Novel Inclusive Definition, Luca Longo, Christopher D. Wickens, Gabriella Hancock, P.A. Hancock

Articles

Human mental workload is arguably the most invoked multidimensional construct in Human Factors and Ergonomics, getting momentum also in Neuroscience and Neuroergonomics. Uncertainties exist in its characterization, motivating the design and development of computational models, thus recently and actively receiving support from the discipline of Computer Science. However, its role in human performance prediction is assured. This work is aimed at providing a synthesis of the current state of the art in human mental workload assessment through considerations, definitions, measurement techniques as well as applications, Findings suggest that, despite an increasing number of associated research works, a single, reliable and …

Distributed Wireless Sensor Node Localization Based On Penguin Searchoptimization, Md Al Shayokh, Soo Young Shin

Turkish Journal of Electrical Engineering and Computer Sciences

Wireless sensor networks (WSNs) have become popular for sensing areas-of-interest and performing assigned tasks based on information on the location of sensor devices. Localization in WSNs is aimed at designating distinct geographical information to the inordinate nodes within a search area. Biologically inspired algorithms are being applied extensively in WSN localization to determine inordinate nodes more precisely while consuming minimal computation time. An optimization algorithm belonging to the metaheuristic class and named penguin search optimization (PeSOA) is presented in this paper. It utilizes the hunting approaches in a collaborative manner to determine the inordinate nodes within an area of interest. …

Motion-Aware Vehicle Detection In Driving Videos, Mehmet Kiliçarslan, Tansu Temel

Turkish Journal of Electrical Engineering and Computer Sciences

This paper focuses on vehicle detection based on motion features in driving videos. Long-term motion information can assist in driving scenarios since driving is a complicated and dynamic process. The proposed method is a deep learning based model which processes motion frame image. This image merges both spatial (frame) and temporal (motion) information. Hence, the model jointly detects vehicles and their motion from a single image. The trained model on Toyota Motor Europe Motorway Dataset reaches 83% mean average precision (mAP). Our experiments demonstrate that the proposed method has a higher mAP than a tracking-based model. The proposed method runs …

A Futuristic Approach To Generate Random Bit Sequence Using Dynamic Perturbedchaotic System, Sathya Krishnamoorthi, Premalatha Jayapaul, Vani Rajasekar, Rajesh Kumar Dhanaraj, Celestine Iwendi

Turkish Journal of Electrical Engineering and Computer Sciences

Most of the web applications require security which in turn requires random numbers. Pseudo-random numbers are required with good statistical properties and efficiency. Use of chaotic map to dynamically perturb another chaotic map that generates the random bit output is introduced in this work. Perturbance is introduced to improvise the chaotic behaviour of a base map and increase the periodicity. PRNG with this architecture is devised to generate random bit sequence from initial keyspace. The statistical properties of newly constructed PRNG are tested with NIST SP 800-22 statistical test suite and were shown to have good randomness. To ensure its …

A Simple Dual-Band Quasi-Yagi Antenna With Defected Ground Structures, Göksel Turan, Hayretti̇n Odabaşi

Turkish Journal of Electrical Engineering and Computer Sciences

In this article, a dual-band compact quasi-Yagi antenna with defected ground structure (DGS) is proposed. The proposed antenna has a simple feeding mechanism consists of a microstrip and transmission line. Half of the driver and director elements are printed on the opposite side of the substrate to ensure good coupling between the antenna elements and achieve a stable radiation pattern. The ground plane is modified with one rectangular slot below the microstrip line to form dual-band operation. Also rectangular slots placed on the sides of the ground plane to improve the matching. The proposed antenna works at $f_{1}=3.35$ and $f_{2}=6.15$ …

Editorial: Assuring Trustworthiness Of Autonomous Systems As Intelligent And Ethical Teammates, Siddhartha Bhattacharyya, Meredith Carroll

Aeronautics Faculty Publications

Editorial on the Research Topic Assuring trustworthiness of autonomous systems as intelligent and ethical teammates

Temporal Bagging: A New Method For Time-Based Ensemble Learning, Göksu Tüysüzoğlu, Derya Bi̇rant, Volkan Kiranoğlu

Turkish Journal of Electrical Engineering and Computer Sciences

One of the main problems associated with the bagging technique in ensemble learning is its random sample selection in which all samples are treated with the same chance of being selected. However, in time-varying dynamic systems, the samples in the training set have not equal importance, where the recent samples contain more useful and accurate information than the former ones. To overcome this problem, this paper proposes a new time-based ensemble learning method, called temporal bagging (T-Bagging). The significant advantage of our method is that it assigns larger weights to more recent samples with respect to older ones, so it …

Dynamic Instance-Wise Decision-Making For Machine Learning, Yasitha Warahena Liyanage

Legacy Theses & Dissertations (2009 - 2024)

In a typical supervised machine learning setting, the predictions on all test instances are based on a common subset of features discovered during model training. However, using a different subset of features that are most informative for each test instance individually may improve not only the quality of prediction but also the overall interpretability of the model. To this end, in this dissertation, we study the problem of optimizing the trade-off between instance-level sparsity and the quality of prediction using a dynamic instance-wise decision-making approach. Specifically, this approach sequentially reviews features one at a time for each data instance given …

Design And Analysis Of Marangoni-Driven Robotic Surfers, Mitchel L. Timm

Dissertations, Master's Theses and Master's Reports

We designed and experimentally studied the dynamics of two robotic systems that surf along the water-air interface. The robots were self-propelled by means of creating and maintaining a surface tension gradient resulting from an asymmetric release of isopropyl alcohol (IPA). The imbalance in the distribution of surface tension surrounding the robots generates a propulsive force commonly referred to as Marangoni propulsion. First, we considered a single surfer, which was custom-made with novel control mechanisms that allow for both forward motion and steering to be remotely adjusted solely through the manipulation of local surface stresses. We analyzed the performance of this …

Lpvit: A Transformer Based Model For Pcb Image Classification And Defect Detection, Kang An, Yanping Zhang

Computer Science Faculty Scholarship

PCB (printed circuit board) is an extremely important component of all electronic products, which has greatly facilitated human life. Meanwhile, tons of PCBs in the waste streams become a waste of resources, which puts the recycling and reuse of PCBs in urgent need. In the manufacturing and recycling of electronic products, the classification of PCBs, recognition of sub-components, and defect detection have been the key technology. Traditional manual detection and classification are subjective and rely on individuals’ experience. With the development of artificial intelligence, lots of research efforts have been dedicated to the automated detection and recognition of PCBs. In …