Digital Commons Network^™

A Mathematical Model Of Juvenile Delinquency In The New York State, Oluwasegun Micheal Ibrahim

Articles

This report presents a mathematical model of juvenile delinquency in the New York State. In particular, we develop a juvenile delinquency system of non-linear differential equations using the mathematical epidemiology framework. In constructing this model, we assume that juvenile delinquency can be studied as a socially infectious disease. The stability of the juvenile delinquency-free equilibrium of the model is examined using the standard non-linear dynamical systems theory technique. We carried out a data fitting based on real-life data from the New York State Criminal Justice Services. The research result reveals that the formulated model conforms with the available data and …

Analysis Of Strain Correction Procedures For Single Fiber Tensile Testing, Amy Engelbrecht-Wiggans, Amanda L. Forster

Articles

Accurate strain measurement for single fibers is critical for many engineering applications. Typically, the crosshead displacement is used to calculate strain when performing mechanical testing, however there are complicating factors: slack in the specimen or slipping/seating in the grips, other grip effects, and load frame compliance. These are addressed in various testing standards for single fibers, such as ASTM Standards D3822, “Standard Test Method for Tensile Properties of Single Textile Fibers” and C1557, “Standard Test Method for Tensile Strength and Young's Modulus of Fibers”. In this work, an analysis of single fiber test data has been performed to examine both …

Capacity Building For Organizational Resilience: Integrating Standards On Risk, Disruption And Continuity In The Curriculum, Lisa Greenwood, Dawn Hess, Yewande S. Abraham, Jennifer Schneider

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Disruption is an inevitable factor in business and society, while inability to mitigate and manage risk can cause irreparable damage to business, the economy, and our ways of life. The COVID-19 pandemic has heightened interest in standards-based strategies for risk management and crisis preparedness to enhance organizational and societal resilience. University curricula that integrate national and international standards offer students a rich skill-set for effective performance in their careers. Moving forward, we must cultivate capable professionals who understand the challenges and risks facing society, and who grasp standards and systems for strategic planning, response, and recovery to promote organizational resilience …

Extraction, Quantification, Characterization, And Application In Food Packaging Of Chitin And Chitosan From Mushrooms: A Review, Buliyaminu A. Alimi, Shivani Pathania, Jude Wilson, Brendan Duffy, Jesus Maria Frias

Articles

The application of chitin in food systems is limited by its insolubility in some common solvents and poor degradability. Hence, it is deacetylated to obtain chitosan, an industrially important derivative with excellent biological properties. Fungal-sourced chitosan is gaining prominence and industrial attraction because of its superior functional and biological properties, and vegan appeal. Further, the absence of such compounds as tropomyosin, myosin light chain, and arginine kinase, which are known to trigger allergic reactions, gives it an edge over marine-sourced chitosan in food and pharmaceutical applications. Mushrooms are macro-fungi with a significant content of chitin, with many authors reporting the …

Informationalism Beyond Managerialism, Salome Viljoen

Articles

It is now commonplace to observe that digital platforms are both affecting and reshaping markets. The focus of this Article is not the anticompetitive effects of digital platforms upon the markets they enter. It instead focuses on digital platforms themselves as market mechanisms. Information—especially datafied information about people and their behavior—and information technologies have transformed how many markets function in the digital economy. Markets have become market machines: highly engineered and computationally intensive market-like mechanisms that make up a key layer of technological infrastructure within digital platforms.

Understanding And Predicting Cognitive Improvement Of Young Adults In Ischemic Stroke Rehabilitation Therapy, Helard Becerra Martinez, Katryna Cisek, Alejandro Garcia-Rudolph, John Kelleher, Andrew Hines

Articles

Accurate early predictions of a patient's likely cognitive improvement as a result of a stroke rehabilitation programme can assist clinicians in assembling more effective therapeutic programs. In addition, sufficient levels of explainability, which can justify these predictions, are a crucial requirement, as reported by clinicians. This article presents a machine learning (ML) prediction model targeting cognitive improvement after therapy for stroke surviving patients. The prediction model relies on electronic health records from 201 ischemic stroke surviving patients containing demographic information, cognitive assessments at admission from 24 different standardized neuropsychology tests (e.g., TMT, WAIS-III, Stroop, RAVLT, etc.), and therapy information collected …

Discovering Child Sexual Abuse Material Creators’ Behaviors And Preferences On The Dark Web, Vuong Ngo, Rahul Gajula, Christina Thorpe, Susan Mckeever

Articles

Background: Producing, distributing or discussing child sexual abuse materials (CSAM) is often committed through the dark web in order to remain hidden from search engines and regular users. Additionally, on the dark web, the CSAM creators employ various techniques to avoid detection and conceal their activities. The large volume of CSAM on the dark web presents a global social problem and poses a significant challenge for helplines, hotlines and law enforcement agencies.

Objective: Identifying CSAM discussions on the dark web and uncovering associated metadata insights into characteristics, behaviours and motivation of CSAM creators.

Participants and Setting: We have conducted an …

Biogeography Based Optimization With Salp Swarm Optimizer Inspired Operator For Solving Non-Linear Continuous Optimization Problems, Vanita Garg, Kusum Deep, Khalid Abdulaziz Alnowibet, Hossam Zawbaa, Ali Wagdy Mohamed

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In this paper, a novel attempt is made to incorporate the two effective algorithm strategies, where BBO has a strong exploration and Salp Swarm Algorithm (SSA) is used for exploitation of the search space. The proposed algorithm is tested on IEEE CEC 2014 and statistical, convergence graphs are given. The proposed algorithm is also applied to 10 real life problems and compared with its counterpart algorithm. Results obtained by above experiments have demonstrated the outperformance of the hybrid version of BBO over other algorithms.

Learnings From A National Cyberattack Digital Disaster During The Sars-Cov-2 Pandemic In A Pediatric Emergency Medicine Department, Fiona Leonard, Hugh O'Reilly, Carol Blackburn, Laura Melody, Dani Hall, Eleanor Ryan, Kate Bruton, Pamela Doyle, Bridget Conway, Michael Barrett

Articles

Objective: The primary objective was to analyze the impact of the national cyberattack in May 2021 on patient flow and data quality in the Paediatric Emergency Department (ED), amid the SARS-CoV-2 (COVID-19) pandemic. Methods: A single site retrospective time series analysis was conducted of three 6-week periods: before, during, and after the cyberattack outage. Initial emergent workflows are described. Analysis includes diagnoses, demographic context, key performance indicators, and the gradual return of information technology capability on ED performance. Data quality was compared using 10 data quality dimensions. Results: Patient visits totaled 13 390. During the system outage, patient experience times …

New Fxlmat-Based Algorithms For Active Control Of Impulsive Noise, Alina Mirza, Farkhanda Afzal, Ayesha Zeb, Abdul Wakeel, Waqar Shahid Qureshi, Ali Akgul

Articles

In the presence of non-Gaussian impulsive noise (IN) with a heavy tail, active noise control (ANC) algorithms often encounter stability problems. While adaptive filters based on the higher-order error power principle have shown improved filtering capability compared to the least mean square family algorithms for IN, however, the performance of the filtered-x least mean absolute third (FxLMAT) algorithm tends to degrade under high impulses. To address this issue, this paper proposes three modifications to enhance the performance of the FxLMAT algorithm for IN. To improve stability, the first alteration i.e. variable step size FxLMAT (VSSFxLMAT)algorithm is suggested that incorporates the …

A Comparison Of Feature Selection Methodologies And Learning Algorithms In The Development Of A Dna Methylation-Based Telomere Length Estimator, Trevor Doherty, Emma Dempster, Eilis Hannon, Jonathan Mill, Richie Poulton, David Corcoran, Karen Sugden, Ben Williams, Avshalom Caspi, Terrie E. Moffitt, Sarah Jane Delany, Therese Murphy Dr

Articles

The field of epigenomics holds great promise in understanding and treating disease with advances in machine learning (ML) and artificial intelligence being vitally important in this pursuit. Increasingly, research now utilises DNA methylation measures at cytosine–guanine dinucleotides (CpG) to detect disease and estimate biological traits such as aging. Given the challenge of high dimensionality of DNA methylation data, feature-selection techniques are commonly employed to reduce dimensionality and identify the most important subset of features. In this study, our aim was to test and compare a range of feature-selection methods and ML algorithms in the development of a novel DNA methylation-based …

Argframe: A Multi-Layer, Web, Argument-Based Framework For Quantitative Reasoning, Lucas Rizzo

Articles

Multiple systems have been proposed to perform computational argumentation activities, but there is a lack of options for dealing with quantitative inferences. This multi-layer, web, argument-based framework has been proposed as a tool to perform automated reasoning with numerical data. It is able to use boolean logic for the creation of if-then rules and attacking rules. In turn, these rules/arguments can be activated or not by some input data, have their attacks solved (following some Dung or rank-based semantics), and finally aggregated in different fashions in order to produce a prediction (a number). The framework is implemented in PHP for …

Enhancing The Prediction For Shunt‑Dependent Hydrocephalus After Aneurysmal Subarachnoid Hemorrhage Using A Machine Learning Approach, Dietmar Frey, Adam Hilbert, Anton Früh, Vince Istvan Madai, Tabea Kossen, Julia Kiewitz, Jenny Sommerfeld, Peter Vajkoczy, Meike Unteroberdörster, Esra Zihni, Sophie Charlotte Brune, Stefan Wolf, Nora Franziska Dengler

Articles

Early and reliable prediction of shunt-dependent hydrocephalus (SDHC) after aneurysmal subarachnoid haemorhage (a SAH) may decrease the duration of in-hospital stay and reduce the risk of catheter-associated meningitis. Machine learning (ML) may improve predictions of SDHC in comparison to traditional non-ML methods. ML models were trained for CHESS and SDASH and two combined individual feature sets with clinical, radiographic, and laboratory variables. Seven different algorithms were used including three types of generalized linear models (GLM) as well as a tree boosting (Cat Boost) algorithm, a Nave Bayes (NB) classifier, and a multilayer perceptron (MLP) artificial neural net. The discrimination of …

Understanding The Interplay Between Immigrant Nascent Entrepreneurship And Cross-Cultural Adaptation, Lucia Walsh, Thomas M. Cooney

Articles

Purpose – All entrepreneurs face challenges during their venture start-up process, but immigrant entrepreneurs face additional and distinctive challenges due to their contextual newness. This paper focuses on understanding the intertwined journeys of nascent entrepreneurship and cross-cultural adaptation of immigrants in a small Western European country where immigrant entrepreneurship is still a relatively new phenomenon.

Design/methodology/approach – The induction-driven, 18-month longitudinal empirical inquiry focused on six early-stage nascent entrepreneurs. Qualitative methods included participant observation during an enterprise program, qualitative interviews and ongoing informal communication.

Findings – The data uncovered the interplay between the nascent immigrant entrepreneurship and crosscultural adaptation. This …

Biomolecules From Macroalgae-Nutritional Profile And Bioactives For Novel Food Product Development, Laura E. Healy, Xianglu Zhu, Milica Pojić, Carl Sullivan, Uma Tiwari, James Curtin, Brijesh K Tiwari

Articles

Seaweed is in the spotlight as a promising source of nutrition for humans as the search for sustainable food production systems continues. Seaweed has a well-documented rich nutritional profile containing compounds such as polyphenols, carotenoids and polysaccharides as well as proteins, fatty acids and minerals. Seaweed processing for the extraction of functional ingredients such as alginate, agar, and carrageenan is well-established. Novel pretreatments such as ultrasound assisted extraction or high-pressure processing can be incorporated to more efficiently extract these targeted ingredients. The scope of products that can be created using seaweed are wide ranging: from bread and noodles to yoghurt …

Portable Hepa Filtration Successfully Augments Natural-Ventilation-Mediated Airborne Particle Clearance In A Legacy Design Hospital Ward, Mehael Fennelly, S. Hellebust, J. Wenger, D. O'Connor, G.W. Griffith, B.J. Plant, A.P.C. Microbiome Institute

Articles

As the severe acute respiratory syndrome coronavirus-2 pandemic has proceeded, ventilation has been recognized increasingly as an important tool in infection control. Many hospitals in Ireland and the UK do not have mechanical ventilation and depend on natural ventilation. The effectiveness of natural ventilation varies with atmospheric conditions and building design. In a challenge test of a legacy design ward, this study showed that portable air filtration significantly increased the clearance of pollutant aerosols of respirable size compared with natural ventilation, and reduced spatial variation in particle persistence. A combination of natural ventilation and portable air filtration is significantly more …

The Virtuous Executive, Alan Rozenshtein

Articles

As currently conceived, executive power law and scholarship detach the identity of the President from the powers and duties of the presidency. Whether an official was properly dismissed without cause, whether a pardon was validly issued, whether a foreign policy debacle rose to the level of an impeachable offense—the answers to all these questions are not supposed to depend on the President’s personal characteristics.

This Article argues that this veil of ignorance is incompatible with a correct understanding of Article II. To properly empower good Presidents and constrain bad ones, constitutional actors must take into account the President’s personal characteristics. …

Platinum Nanoparticles Inhibit Intracellular Ros Generation And Protect Against Cold Atmospheric Plasma-Induced Cytotoxicity, Sebnem Gunes, Zhonglei He, David Van Acken, Renee Malone, Patrick Cullen, James Curtin

Articles

Platinum nanoparticles (PtNPs) have been investigated for their antioxidant abilities in a range of biological and other applications. The ability to reduce off-target cold atmospheric plasma (CAP) cytotoxicity would be useful in Plasma Medicine; however, little has been published to date about the ability of PtNPs to reduce or inhibit the effects of CAP. Here we investigate whether PtNPs can protect against CAP-induced cytotoxicity in cancerous and non-cancerous cell lines. PtNPs were shown to dramatically reduce intracellular reactive species (RONS) production in U-251 MG cells. However, RONS generation was unaffected by PtNPs in medium without cells. PtNPs protect …

Workplace Accident Analysis In The Algerian Oil And Gas Industry, Hamza Zerrouki

Articles

A total of 42,032 workplace accidents were reported in 2021 by the Algerian National Social Insurance Fund for Salaried Workers in Algeria, of which 38,225 were accidents within the workplace and 3807 were related to traffic accidents or other reasons. Most of these accidents were recorded in the building and construction field, followed by the oil and gas company exploration and drilling, which comes at the forefront of the Sonatrach company. This study aims to analyze accidents in the workplace using quantitative and qualitative methods to determine the corresponding causes. Our study was carried out in collaboration with Sonatrach in …

Optimizing Human Performance To Enhance Safety: A Case Study In An Automotive Plant, Maria Chiara Leva, Michaela Demichela, Carlos Albarran Morillo, Franco Modaffari, Lorenzo Comberti

Articles

Human factors play a relevant role in the dynamic work environments of the manufacturing sector in terms of production efficiency, safety, and sustainable performance. This is particularly relevant in assembly lines where humans are widely employed alongside automated and robotic agents. In this situation, operators’ ability to adapt to different levels of task complexity and variability in each workstation has a strong impact on the safety, reliability, and efficiency of the overall production process. This paper presents an application of a theoretical and empirical method used to assess the matching of different workers to various workstations based on a quantified …

Recovery Of Protein From Industrial Hemp Waste (Cannabis Sativa, L.) Using High-Pressure Processing And Ultrasound Technologies, Eduarda M. Cabral

Articles

Hemp seeds are currently used mainly for oil extraction, generating waste that could be potentially exploited further as a source of proteins and other bio-actives. This study aims to valorise hemp waste (Cannabis sativa, L.) from previous oil extraction as a source of protein by analysing the effect of high-pressure processing (HPP) pre-treatments (0–600 MP a; 4–8 min) combined with conventional or ultrasound-assisted extraction (UAE) methods on protein recovery/purity, amino acid composition, and protein structure. Overall, maximum protein recovery (62%) was achieved with HPP (200 MP a, 8 min) with UAE. The highest protein purity (76%) was achieved with HPP …

Enhancing Control Room Operator Decision Making: An Application Of Dynamic Influence Diagrams In Formaldehyde Manufacturing, Joseph Mietkiewicz, Anders L. Madsen

Articles

Intoday’s rapidly evolving industrial landscape, control room operators must grapple with an ever-growing array of tasks and respon sibilities. One major challenge facing these operators is the potential for task overload, which can lead to decision fatigue and increased reliance on cognitive biases. To address this issue, we propose the use of dynamic influence diagrams (DID) as the core of our decision support system. By monitoring the process over time and identifying anomalies, DIDs can recommend the most effective course of action based on a probabilistic assessment of future outcomes. Instead of letting the operator choose or search for the …

Series-Fed Omnidirectional Mm-Wave Dipole Array, Neeraj Kumar Maurya, Max Ammann, Patrick Mcevoy

Articles

THE rapid expansion in the millimeter-wave (mm-wave) frequency domain has completely changed the course of wireless communication. One of the most important steps to make smart cities, the Internet-of-Things (IoT), smart homes, and vehicular communication a reality is to use mm-wave frequencies for wireless applications. The rise in the number of wireless appliances has also led to a rise in data traffic [1]. The adoption of mm-wave frequencies enabled several gigahertz of bandwidth, allowing data rate and latency limits to be exceeded. The availability of a broad electromagnetic spectrum and frequency reusability are the most important characteristics of mm-wave deployment …

Exploiting Multimode Antennas For Mimo And Aoa Estimation In Size-Constrained Iot Devices, Abel Zandamela, Alessandro Chiumento Alessandro Chiumento, Alessandro Chiumento, Nicola Marchetti, Max Ammann, Adam Narbudowicz

Articles

This work proposes compact multimode Multiple-Input–Multiple-Output (MIMO) antennas for Angle of Arrival (AoA) estimation in miniaturized Internet of Things (IoT) systems. The method excites different orthogonal radiating modes (TM 21 , TM 02 , and TM 31 modes) for beamforming capabilities, and the AoA performance is investigated using the Multiple Signal Classification (MUSIC) algorithm, executed using numerical and experimental data. The technique is tested at 2.238GHz , while using an antenna diameter

Pattern And Polarization Diversity Multisector Annular Antenna For Iot Applications, Abel Zandamela, Nicola Marchetti, Max Ammann, Adam Narbudowicz

Articles

This work proposes a small pattern and polarization diversity multisector annular antenna with electrical size and profile of ka = 1.2 and 0.018λ, respectively. The antenna is planar and comprises annular sectors that are fed using different ports to enable digital beamforming techniques, with efficiency and gain of up to 78% and 4.62 dBi, respectively. The cavity model analysis is used to describe the design concept and the antenna diversity. The proposed method can produce different polarization states (e.g., linearly and circularly polarized patterns) and pattern diversity characteristics covering the elevation plane. Owing to its small electrical size, low-profile and …

Subnetwork Ensembling And Data Augmentation: Effects On Calibration, A. Çağrı Demir, Simon Caton, Pierpaolo Dondio

Articles

Deep Learning models based on convolutional neural networks are known to be uncalibrated, that is, they are either overconfident or underconfident in their predictions. Safety-critical applications of neural networks, however, require models to be well-calibrated, and there are various methods in the literature to increase model performance and calibration. Subnetwork ensembling is based on the over-parametrization of modern neural networks by fitting several subnetworks into a single network to take advantage of ensembling them without additional computational costs. Data augmentation methods have also been shown to enhance model performance in terms of accuracy and calibration. However, ensembling and data augmentation …

Gated Deep Reinforcement Learning With Red Deer Optimization For Medical Image Classification, Narayanan Ganesh, Sambandan Jayalakshmi, Rama Chandran Narayanan, Miroslav Mahdal, Hossam Zawbaa, Ali Wagdy Mohamed

Articles

The brain is one of the most important and complex organs in the body, consisting of billions of individual cells. Uncontrolled growth and expansion of aberrant cell populations within or around the brain are the main causes of brain tumors. These cells have the potential to harm healthy cells and impair brain function [1]. Tumors can be detected using medical imaging techniques, which are considered the most popular and accurate way to classify different types of cancer, and this procedure is even more crucial as it is noninvasive [2]. Magnetic resonance imaging (MRI) is one such medical imaging technique that …

Ontology-Based Case Study Management Towards Bridging Training And Actual Investigation Gaps In Digital Forensics, Hung Q. Ngo, Nhien-An Le-Khac

Articles

The training programs in digital forensics have contributed many case study models to guide digital forensic analyses. However, they only account for a small number of real cases and they are usually too abstract while actual cybercrime investigations are more diverse and complex. This gap leads to difficulties in giving immediate and straightforward actions for law enforcement during cybercrime investigations. In this paper, we propose an ontology-based knowledge map model, which is a foundation model for building a case study management system for Digital Forensic Intelligence (DFINT) and Open Source Intelligence (OSINT) in digital forensics. The main idea of this …

Pattern And Polarization Diversity Multisector Annular Antenna For Iot Applications, Abel Zandamela, Nicola Marchetti, Max Ammann, Adam Narbudowicz, Wroclaw University Of Science And Technology

Articles

This work proposes a small pattern and polarization diversity multisector annular antenna with electrical size and profile of ka=1.2 and 0.018λ, respectively. The antenna is planar and comprises annular sectors that are fed using different ports to enable digital beamforming techniques, with efficiency and gain of up to 78%and 4.62 dBi, respectively. The cavity model analysis is used to describe the design concept and the antenna diversity. The proposed method can produce different polarization states (e.g., linearly and circularly polarized patterns) and pattern diversity characteristics covering the elevation plane. Owing to its small electrical size, low-profile and diversity properties, the …

Comparing And Extending The Use Of Defeasible Argumentation With Quantitative Data In Real-World Contexts, Lucas Rizzo, Luca Longo

Articles

Dealing with uncertain, contradicting, and ambiguous information is still a central issue in Artificial Intelligence (AI). As a result, many formalisms have been proposed or adapted so as to consider non-monotonicity. A non-monotonic formalism is one that allows the retraction of previous conclusions or claims, from premises, in light of new evidence, offering some desirable flexibility when dealing with uncertainty. Among possible options, knowledge-base, non-monotonic reasoning approaches have seen their use being increased in practice. Nonetheless, only a limited number of works and researchers have performed any sort of comparison among them. This research article focuses on evaluating the inferential …