Digital Commons Network^™

Rcae_Bfv: Retrieve Encrypted Images Using Convolution Autoencoder And Bfv, Emad M. Alsaedi, Alaa Kadhim

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Content-Based Image Retrieval (CBIR) is an actual application in computer vision, which retrieves similar images from a database. Deep Learning (DL) is essential in many applications, including image retrieval applications. However, encryption techniques are used to protect data privacy because these data are vulnerable to being viewed by unauthorized parties while being transmitted over unsecured channels. This paper includes two parts for images retrieval. In the first part, features of all images of a Canadian Institute for Advanced Research CIFAR-10 dataset were extracted and stored on the Server-side. In the second part, the Brakerski/Fan-Vercauteren (BFV) homomorphic encryption scheme method for …

Intelligent Parameter Tuning Using Deep Q-Network In Adaptive Queue Management Systems, Ayman Basheer Yousif, Hassan Jaleel, Ghaida Muttasher

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Network traffic has risen in recent years to the point that it is obviously and astonishingly in 2020, with the increase predicted to double in the following days. Up to 23 Teraa bit every month is an incredible amount. The Active Queue Management (AQM) algorithm is one of the most significant study areas in network congestion control; nevertheless, new self-learning network management algorithms are needed on nodes to cope with the huge quantity of traffic and minimize queuing latency, used reinforcement learning for automatic adaptive parameter with the AQM algorithm for effective network management, and present a novel AQM algorithm …

Hybridized Dimensionality Reduction Method For Machine Learning Based Web Pages Classification, Thabit Sulaiman Sabbah

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Feature space high dimensionality is a well-known problem in text classification and web mining domains, it is caused mainly by the large number of vocabularies contained within web documents. Several methods were applied to select the most useful and important features over the years; however, the performance of such methods is still improvable from different aspects such as the computational cost and accuracy. This research presents an enhanced cosine similarity-based hybridization of two efficient feature selection methods for higher classification performance. The reduced feature sets are generated using the Random Projection (RP) and the Principal Component Analysis (PCA) methods, individually, …

Unmasking Deepfakes Based On Deep Learning And Noise Residuals, Wildan J. Hadi, Suhad M., Ayad R. Abbas

Iraqi Journal of Computers, Communications, Control and Systems Engineering

The main reason for the emergence of a deepfake (deep learning and fake) term is the eVolution in artificial intelligence techniques, especially deep learning. Deep learning algorithms, which auto-solve problems when giving large sets of data, are used to swap faces in digital media to create fake media with a realistic appearance. To increase the accuracy of distinguishing a real video from fake one, a new model has been developed based on deep learning and noise residuals. By using Steganalysis Rich Model (SRM) filters, we can gather a low-level noise map that is used as input to a light ConVolution …

Automatic Quality Of Experience Measuring For Video Conference In Real-Time, Roaa E. Alhassany, Rana F.

Iraqi Journal of Computers, Communications, Control and Systems Engineering

In recent years, especially with COVID-19, video conference applications have become very important. Millions of peoples around the world have become to communicate with each other through using video conference applications. The most critical factor in the performance success of video conference applications is the user's perception of the quality of the experience. In this work, an Extreme Learning Machine (ELM) model was proposed for predicting video quality of experience. The proposed system extracts several features from videos that have a significant impact on the quality of the experience. The model performance was validated with unseen data. Spearman’s Rank Correlation …

Optimizing Artificial Neural Networks Using Levychaotic Mapping On Wolf Pack Optimization Algorithm For Detect Driving Sleepiness, Sarah Saadoon Jasim, Alia Karim, Scott Turner

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Artificial Neural Networks (ANNs) are utilized to solve a variety of problems in many domains. In this type of network, training and selecting parameters that define networks architecture play an important role in enhancing the accuracy of the network's output; Therefore, Prior to training, those parameters must be optimized. Grey Wolf Optimizer (GWO) has been considered one of the efficient developed approaches in the Swarm Intelligence area that is used to solve real-world optimization problems. However, GWO still faces a problem of the slump in local optimums in some places due to insufficient diversity. This paper proposes a novel algorithm …

The Techniques Of Based Internet Key Exchange (Ike) Protocol To Secure Key Negotiation, Zainab Kareem Mahyob, Raheem Abdulsahib, Suhiar Mohammed Zeki

Iraqi Journal of Computers, Communications, Control and Systems Engineering

The Internet is a massive network that connects millions of users from all over the world and the data transmitted via it needs great protection, especially since that are in the age of big data. To solve part of this problem, IPsec was utilized, which is a set of protocols necessary to offer security to units of the Internet in general and the IP layer in particular. It is mostly based on major exchange protocols. The most frequent mechanism for transferring key materials and establishing security linkages between two entities is Internet Key Exchange (IKE). In the present work, it …

A Convolutional Neural Network For Detecting Covid-19 From Chest X-Ray Images, Basma Wael Abdullah, Hanaa Mohsin

Iraqi Journal of Computers, Communications, Control and Systems Engineering

since the global pandemic of COVID-19 has spread out, the use of Artificial Intelligence to analyze Chest X-Ray (CXR) image for COVID-19 diagnosis and patient treatment is becoming more important. This research hypothesized that using COVID19 radiographic changes in the X-Ray images. Artificial Intelligence (AI) systems may extract certain graphical elements regarding COVID-19 and offer a clinical diagnosis ahead of pathogenic test; therefore, saving vital time for disease prevention. Employing 2614 CXR radiographs from Kaggle data collection of verified COVID-19 cases and healthy persons, a new ConVolutional Neural Network (CNN) model that is inspired by the Xception architecture was presented …

Meerkat Clan-Based Feature Selection In Random Forest Algorithm For Iot Intrusion Detection, Adil Yousef Hussein, Ahmed T.

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Hackers can conduct more destructive cyber-attacks thanks to the rapid spread of Internet of Things (IoT) devices, posing significant security risks for users. Through a malicious process, the attacker intended to exhaust the capital of the target IoT network. Researchers and company owners are concerned about the reliability of IoT networks, which is taken into account because it has a significant impact on the delivery of facilities provided by IoT systems and the security of user groups. The intrusion prevention system ensures that the network is protected by detecting malicious activity. In this paper, the focus is on predicting attacks …

Collision Prediction Based On Vehicular Communication System, Abdulqader Falhi Jabbar, Rana Fareed, Asia Ali Salman

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Road traffic accidents are one of the leading causes of mortality globally. Reducing the number of traffic-related incidents has become a serious socio-economic and public health problem, given the ever-increasing number of cars on the road. As a result, this paper proposes an intelligent vehicle prediction communication mechanism that alerts drivers to any autos that may be overtaking or bypassing the targeted vehicle. The primary goal of this paper is to leverage modern Internet of Things (IoT) and wireless sensor technologies to predict any potential accident that may occur as a result of car accidents. This paper proposes the Collision …

A Framework For Predicting Airfare Prices Using Machine Learning, Heba Mohammed Fadhil, Mohammed Najm, Mohammed Issam Younis

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult Issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive …

Snow3g Modified By Using Pll Algorithms In Magic Cube, Rana Mohammed Zaki, Hala Bahjat

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Thomas and Patrik are working on a stream cipher called SNOW 3G. In 2006, it was chosen as the centerpiece of a new set of confidentiality and integrity algorithms for the Universal Mobile Telecommunications System (UMTS). In 2008, Böhm published an article named "Statistical Evaluation of Stream Cipher SNOW 3G." He put the randomness of the SNOW 3G key stream generator to the test. As a randomness test tool, Böhm uses the NIST test statistics package, which consists of three kinds of tests: lengthy key stream data, short key stream data, and initialization vector data. Only the short key stream …

Advancing Philanthropic Strategy Through Evaluative Thinking: One Foundation’S Approach, Christine Baker, Margaret Eigsti, Kathryn Racine, Laurence O’Connell

The Foundation Review

The Sisters of Charity Foundation of Cleveland supports Catholic sisters and their ministries in northeast Ohio through the grantmaking, partnership, capacitybuilding, and evaluation efforts of its Catholic Sisters Program Area. The decline of sisters actively engaged in ministry, due both to their rising median age and a decades-long decline in their overall numbers, called for a reconsideration and likely revision of the CSPA existing theory of change.

Unlike other strategic approaches at the foundation, such as ending homelessness or improving health equity, transitioning from sister-led to lay-led leadership of ministries remained largely unexplored: Basic research was lacking, and model practices …

Engaging Community To Build A Community Dashboard, Tanya Upthegrove Gregory, Liz Gordillo

The Foundation Review

The Ruth Mott Foundation’s mission is to advocate, stimulate, and support community vitality in our community of Flint, Michigan. The goal of the foundation’s 2016–2025 strategic plan is that residents of north Flint neighborhoods create and sustain opportunities to contribute and thrive. As a place-based grantmaker, the foundation uses community-level data internally to establish baseline data. Those data, in combination with local relationships and knowledge of other community initiatives, guide the foundation’s grantmaking strategy in the community’s context and assist with data-driven decision-making. Externally, the dashboard supports community engagement through access to local data. The foundation partnered with the Dorothy …

Front Matter

The Foundation Review

No abstract provided.

The Yin And Yang Of Equity-Centered Philanthropy, Douglas Easterling, Laura Mcduffee, Sabina Gesell

The Foundation Review

Foundations face two competing imperatives when they commit to advancing equity. On the one hand, they are counseled to support and follow the lead of community-based groups that are on the front lines of social change. On the other hand, they are also being challenged to use their power and influence to act boldly to change inequitable structures, policies, and institutions. These two orientations, yin and yang, can take a foundation in different directions and thus cause confusion and internal conflict.

The challenge for a foundation is to balance and integrate the two orientations into a comprehensive and effective approach …

Learning As We Go: How Emergent Process Supports Sustainable Community And Philanthropic Change, Elizabeth Myrick, Rachel Mosher-Williams, Laurie Zierer

The Foundation Review

Beginning in 2014, PA Humanities, one of 56 state and territorial humanities councils across the country, drew upon the work of Orton Family Foundation to deploy the Community Heart & Soul method, which centers community planning and civic engagement around connecting people to each other, and to the many assets of the places they live, through individual storytelling and collective narrative building.

Between 2015 and 2018, PA Humanities awarded matching grants to three locations in Pennsylvania — Greater Carlisle, Meadville, and Williamsport — to pilot PA Heart & Soul, a humanities-based, resident-driven community planning process that cultivates a shared sense …

Back Matter

The Foundation Review

No abstract provided.

Tfr 14.3 Full Issue

The Foundation Review

No abstract provided.

Sustainability Hub Newsletter - September 2022, Jacqueline Jergensen, Neyda Gilman, Jennifer Embree

Library Sustainability Resources

In the September 2022 issue of the Sustainability Hub Newsletter, we review the different features of our Sustainability Hub this semester, including our book collection, Terracycling station, Seed Library, Citizen Science Kits, online resources, and more! We also make suggestions on which seeds to plant this fall, and which plants may be ready for harvesting! Keep reading for a featured video on the Binghamton University Greenhouse and our announcements this month!

Strategies For Scaleable Communication And Coordination In Multi-Agent (Uav) Systems, Jonathan Ponniah, Or D. Dantsker

Faculty Research, Scholarly, and Creative Activity

A system is considered in which agents (UAVs) must cooperatively discover interest-points (i.e., burning trees, geographical features) evolving over a grid. The objective is to locate as many interest-points as possible in the shortest possible time frame. There are two main problems: a control problem, where agents must collectively determine the optimal action, and a communication problem, where agents must share their local states and infer a common global state. Both problems become intractable when the number of agents is large. This survey/concept paper curates a broad selection of work in the literature pointing to a possible solution; a unified …

Mitigating Cascading Failures In Power Grids Via Markov Decision-Based Load-Shedding With Dc Power Flow Model, Pankaz Das, Rezoan Ahmed Shuvro, Kassie Povinelli, Francesco Sorrentino, Majeed M. Hayat

Electrical and Computer Engineering Faculty Research and Publications

Despite the reliability of modern power systems, large blackouts due to cascading failures (CFs) do occur in power grids with enormous economic and societal costs. In this article, CFs in power grids are theoretically modeled proposing a Markov decision process (MDP) framework with the aim of developing optimal load-shedding (LS) policies to mitigate CFs. The embedded Markov chain of the MDP, established earlier to capture the dynamics of CFs, features a reduced state-space and state-dependent transition probabilities. We introduce appropriate actions affecting the dynamics of CFs and associated costs. Optimal LS policies are computed that minimize the expected cumulative cost …

Imagining Urban Transformation In Kenya, Rose Cairns, Joel Onyango, Andy Stirling, Phil Johnstone

All Peer-Reviewed Publications

This paper examines the diverse ways in which science and technology are implicated in collective imaginations of urban futures in Kenya. Despite calls for a ‘deep reimagining’ of African urbanisation (UN Habitat 2014), globalised narratives of urban ‘smartness’ are intersecting with pan-African tendencies toward top-down Master Planning to constrain spaces for collective imagining of urban futures. Using the conceptual lens of sociotechnical imaginaries and the methodological approach of Q method, we hope to open up and navigate the space of tension between the violence of narratives of failure and crisis in African cities, and the sometimes ‘blinding power’ of certain …

E-Cigarette Addiction And Harm Perception: Does Initiation Flavor Choice Matter?, Man Hung, Andrew Spencer, Eric S. Hon, Val Joseph Cheever, Frank W. Licari, Ryan Moffat, Clarissa Goh, Ben Raymond, Martin S. Lipsky

Institute on Aging Publications

Introduction

The 21st century was marked by a dramatic increase in adolescent e-cigarette use in the United States (US). The popularity of non-traditional flavor types, including fruit and pastry, is thought to contribute toward growing product use nationally, leading to a variety of federal and state regulations limiting the use of non-traditional flavors in the US. The relationship between flavor type and increased adolescent use suggests a possible link between flavor use and addiction and harm perception. This study assessed if the flavor type used when initiating e-cigarette use predicted addiction and harm perceptions.

Methods

The study utilized data from …

Auditing Google's Search Headlines As A Potential Gateway To Misleading Content: Evidence From The 2020 Us Election, Himanshu Zade, Morgan Wack, Yuanrui Zhang, Kate Starbird, Ryan Calo, Jason Young, Jevin D. West

Articles

The prevalence and spread of online misinformation during the 2020 US presidential election served to perpetuate a false belief in widespread election fraud. Though much research has focused on how social media platforms connected people to election-related rumors and conspiracy theories, less is known about the search engine pathways that linked users to news content with the potential to undermine trust in elections. In this paper, we present novel data related to the content of political headlines during the 2020 US election period. We scraped over 800,000 headlines from Google's search engine results pages (SERP) in response to 20 election-related …

Entropy Analysis Of Sutterby Nanofluid Flow Over A Riga Sheet With Gyrotactic Microorganisms And Cattaneo–Christov Double Diffusion, M. Faizan, F. Ali, K. Loganathan, A. Zaib, C. A. Reddy, Sara I. Abdelsalam

Basic Science Engineering

In this article, a Riga plate is exhibited with an electric magnetization actuator consisting of permanent magnets and electrodes assembled alternatively. This exhibition produces electromagnetic hydrodynamic phenomena over a fluid flow. A new study model is formed with the Sutterby nanofluid flow through the Riga plate, which is crucial to the structure of several industrial and entering advancements, including thermal nuclear reactors, flow metres and nuclear reactor design. This article addresses the entropy analysis of Sutterby nanofluid flow over the Riga plate. The Cattaneo–Christov heat and mass flux were used to examine the behaviour of heat and mass relaxation time. …

Effect Of Crm On Neurobiology Via Eeg And Biofeedback, Sophia Truong

Loma Linda University Electronic Theses, Dissertations & Projects

We reviewed the literature on mindfulness and its effects on psychological functioning. EEG studies have shown that different approaches to meditation, including MBSR, guided imagery, etc. have been associated with better interoception, increases in left frontal activity, and better stress regulation. These findings were used to create a study protocol that utilizes a somatically based intervention, the Community Resiliency Model (CRM) to decrease test taking anxiety in graduate school students.

Sweet Pea: An Integrated Postpartum Mental Health Program For Mothers & Their Partners, Robynn L. Mays

Loma Linda University Electronic Theses, Dissertations & Projects

The Sweet Pea: Postpartum Parenthood Program is a postpartum depression and anxiety intervention to provide support for mothers and their supportive partners for 16- weeks of therapy. Through group, individual, and couples therapy, parents can discuss their symptoms of postpartum depression and anxiety in three different settings. The parents will have the support from their Postpartum Care Team (PCT) which includes: their Case Manager and Clinical Therapist. Parents will also receive health care and social services provided through PCT to ensure the proper support through their postpartum parenting journey. The Sweet Pea Program is based on the concepts of the …

Force Comparison Of Rotational Tooth Movements For Loop-Design And Traditional Aligners, Robert Olsen

Loma Linda University Electronic Theses, Dissertations & Projects

Introduction

This study aimed to evaluate the force (F) and torque (Tq) exerted on a rotated canine and molar tooth by two different aligner systems. An ArchForm loop clear aligner (AFL) was compared to a traditional clear aligner (T) with the force (F) and torque (Tq) compared. A reduction in F and Tq with AFL aligners could possibly decrease the incidence of Orthodontic Root Resorption (ORR), while also creating more effective forces for tooth movement.

Materials and Methods

Two types of T aligners varying by material thickness were compared to two types of AFL aligners varying by loop width. All …

Covid-19 Vaccination Clinic Success: An Interdisciplinary Application Of Simulation And Modeling., Tammy Toscos Phd, Victor P. Cornet Ms, Michelle Charles, Erica Cumbee Mpa, Charlotte Gabet, Ethel Massing, R. Scott Stienecker Md

Health Services and Informatics Research

Proceedings of the 2022 International Symposium on Human Factors and Ergonomics in Health Care.

This paper shares a case study of a rapid cycle of process improvement, physical simulation, and simulation software development to stand up a mass COVID-19 vaccination site. The resulting standard work, clinic setup and simulation software tool were designed and implemented by an interdisciplinary team at a moderate size not-for-profit health system.

This unique example of a simulation and modeling implementation led to a high throughput vaccination clinic with an outstanding patient experience.