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Enhanced Audio Encryption Scheme: Integrating Blowfish, Hmac-Sha256, And Md5 For Secure Communication, Jenan Ayad, Noor Qaddoori, Hasanain Maytham Jan 2025

Enhanced Audio Encryption Scheme: Integrating Blowfish, Hmac-Sha256, And Md5 For Secure Communication, Jenan Ayad, Noor Qaddoori, Hasanain Maytham

Mesopotamian Journal of CyberSecurity

In today's communications, it is vital to protect audio data privacy before and after transfer. This work therefore introduces the enhanced audio encryption scheme (EAES), which employs the most effective techniques of cryptography and processes them to make it impossible for unauthorized persons or programs to access or change the contents of audio files. This method uses RSA to encrypt the Blowfish key, which is used for data encryption, the HMAC-SHA256 algorithm for integrity checks, and the Message-Digest algorithm (MD5) for the checking phase. The performance of the EAES is measured statistically via the MSE, PSNR, and correlation coefficient. For …

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Enhancing Traffic Data Security In Smart Cities Using Optimized Quantum-Based Digital Signatures And Privacy-Preserving Techniques, Tuqa Ghani Tregi, Mishall Al-Zubaidie Jan 2025

Enhancing Traffic Data Security In Smart Cities Using Optimized Quantum-Based Digital Signatures And Privacy-Preserving Techniques, Tuqa Ghani Tregi, Mishall Al-Zubaidie

Mesopotamian Journal of CyberSecurity

Securing big data in power plants is an important and fundamental step in the infrastructure of smart cities. In addition, it becomes a barrier if it is not controlled from the beginning. Security must be a combination of fast and robust properties. This research presents a traffic security system (TSS) in a smart city (SC). It is a novel paradigm meant to improve data security and integrity by means of a multilayered method. Advanced fault analysis, dual-stage pseudonymizing, quantum key distribution via the BB84 protocol, and Falcon signatures (FS) are combined in the proposed system. TSS enhances data security by …

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Learning Techniques-Based Malware Detection: A Comprehensive Review, Sarah Fouad Ali, Musaab Riyadh Abdulrazzaq, Methaq Talib Gaata Jan 2025

Learning Techniques-Based Malware Detection: A Comprehensive Review, Sarah Fouad Ali, Musaab Riyadh Abdulrazzaq, Methaq Talib Gaata

Mesopotamian Journal of CyberSecurity

The rapid proliferation of Internet of Things (IoT) devices has significantly increased the threat landscape, with malwares arising as a critical concern. Advanced learning methods such as machine learning (ML), deep learning (DL), and federated learning (FL) are essential for handling complex IoT data. ML provides tools for pattern identification and detecting anomalies. DL boosts malware detection by automatically extracting features and identifying patterns. FL enables collaborative model training across decentralized devices, ensuring data privacy, which is crucial for diverse IoT systems. This comprehensive review specifically synthesizes ML, DL and FL for malware detection in the IoT environment, highlighting key …

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Robust And Efficient Methods For Key Generation Using Chaotic Maps And A2c Algorithm, Ali A. Mahdi, Mays M. Hoobi Jan 2025

Robust And Efficient Methods For Key Generation Using Chaotic Maps And A2c Algorithm, Ali A. Mahdi, Mays M. Hoobi

Mesopotamian Journal of CyberSecurity

In the current digital landscape, information security has become a critical necessity given the escalating frequency and sophistication of cyberattacks across global computing networks. Cryptography is the science and practice of securing information by transforming it into a format that is unreadable or inaccessible to unauthorized parties. The strength of the cryptography algorithm lies in the strength of used encryption key. Recently, the nonlinear behavior of chaotic maps has been utilized as a random source to generate robust key stream bits for cryptographic purposes. The aim of this paper is to introduce an efficient and robust system for generating strong …

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Therapeutic Potential Of Brassica Carinata Microgreens Extract In Alleviating Symptoms Of Type 2 Diabetes In Wistar Rats, Lilian Nakakaawa, Ifeoluwa D. Gbala, Joel L. Bargul, Xavier Cheseto, John M. Wesonga Jan 2025

Therapeutic Potential Of Brassica Carinata Microgreens Extract In Alleviating Symptoms Of Type 2 Diabetes In Wistar Rats, Lilian Nakakaawa, Ifeoluwa D. Gbala, Joel L. Bargul, Xavier Cheseto, John M. Wesonga

All Peer-Reviewed Publications

Microgreens of Brassica plants have attracted increasing research interest in the management of the prevailing epidemic of Type 2 diabetes mellitus (T2DM) because of their high nutritional value. This study evaluated the antidiabetic effects of Brassica carinata Microgreens Ethanolic Extract (BMEE) in type-2 diabetic rats. For the normoglycemic assay, rats were divided into five groups and received a single oral dose of 100, 250, and 500 mg/kg of BMEE while the control groups received distilled water and Glibenclamide. Fasting blood glucose (FBG) levels were determined on a weekly basis for 28 days in diabetic rats after treatment with BMEE at …

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Earth Observations Reveal Impacts Of Climate Variability On Maize Cropping Systems In Sub-Saharan Africa, Adomas Liepa, Michael Thiel, Hannes Taubenböck, Doris Klein, Ingolf Steffan-Dewenter, Marcell K. Peters, Sarah Schönbrodt-Stitt, Insa Otte, Tobias Landmann, Zeyaur R. Khan, Michael Ochieng Obondo, Frank Chidawanyika, Emily A. Martin, Tobias Ullmann Jan 2025

Earth Observations Reveal Impacts Of Climate Variability On Maize Cropping Systems In Sub-Saharan Africa, Adomas Liepa, Michael Thiel, Hannes Taubenböck, Doris Klein, Ingolf Steffan-Dewenter, Marcell K. Peters, Sarah Schönbrodt-Stitt, Insa Otte, Tobias Landmann, Zeyaur R. Khan, Michael Ochieng Obondo, Frank Chidawanyika, Emily A. Martin, Tobias Ullmann

All Peer-Reviewed Publications

In Kenya, climate variability and change threaten smallholder, rainfed farms, with crop failures, yield reductions, and pest infestations. Efficient agroecological strategies, such as Push-Pull intercropping, offer documented benefits including pest control, improved soil fertility, and water conservation compared to traditional maize monocropping. To date, no studies exist comparing traditional maize monocropping and Push-Pull intercropping using earth observation tools over several growing seasons in East Africa. Our research addresses this by harmonizing Landsat 7, 8, 9 with Sentinel-2 remote sensing time series from 2016 to 2023. Phenological metrics of 15 growing seasons are extracted based on a threshold method using the …

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Enhancing Intrusion Detection Systems With Adaptive Neuro-Fuzzy Inference Systems, Jitender Sharma, Sonia ., Karan Kumar, Pankaj Jain, Pankaj Jain, Hussein Alkattan Jan 2025

Enhancing Intrusion Detection Systems With Adaptive Neuro-Fuzzy Inference Systems, Jitender Sharma, Sonia ., Karan Kumar, Pankaj Jain, Pankaj Jain, Hussein Alkattan

Mesopotamian Journal of CyberSecurity

Network security has become increasingly critical in recent years. Among the various aspects of network security and considering several approaches to network security, intrusion detection systems (IDSs) have gained considerable attention. The prominence of this factor, among other factors of network security, is due to its ability to address the complex and uncertain nature of security breaches. Whenever data flow over the network, precise categorization of normal and malicious data is necessary. Past IDS systems lack precise categorization. Thus, the present study focuses on the use of the adaptive neuro-fuzzy inference system (ANFIS) as a classifier to categorize network instances …

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Encrypting Text Messages Via Iris Recognition And Gaze Tracking Technology, Sura Abed Sarab Hussien, Basim Najim Al-Din Abed, Kamaran Adil Ibrahim Jan 2025

Encrypting Text Messages Via Iris Recognition And Gaze Tracking Technology, Sura Abed Sarab Hussien, Basim Najim Al-Din Abed, Kamaran Adil Ibrahim

Mesopotamian Journal of CyberSecurity

This study explores the integration of eye-tracking technology, specifically the gaze point (GP3) eye tracker, to develop a novel encryption and decryption model that leverages an individual's unique eye patterns as a cryptographic key. This research addresses the critical problem of balancing user-friendly encryption mechanisms with robust security. This study aims to design a gaze-based encryption system that uses the eye's binary matrix as a dynamic encryption key. The methodology involves capturing an eye image, converting it into a binary matrix, and using the extracted matrix to generate a unique iris key (IK) applied to encrypt and decrypt text messages …

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A Comprehensive Study Of Energy, Exergy, Exergoeconomic, And Exergoenvironment Analysis Of Combined Cycle Power Plant, Ahmed Sarhan Abdulsitar, Arkan Fawzi Saeed, Hatem Hasan Ismaeel Jan 2025

A Comprehensive Study Of Energy, Exergy, Exergoeconomic, And Exergoenvironment Analysis Of Combined Cycle Power Plant, Ahmed Sarhan Abdulsitar, Arkan Fawzi Saeed, Hatem Hasan Ismaeel

Babylonian Journal of Mechanical Engineering

One of the most effective ways to generate electricity in the thermal power plant is with a Combined Cycle Power Plant (CCPP), which uses both gas and steam turbines to their full potential. This research employs energy, exergy, exergoeconomic, and exergoenvironmental analyses to assess the CCPP performance. Energy analysis indicates the plant's overall efficiency, while exergy analysis identifies losses due to system irreversibilities and proposes methods for enhancement. Exergoeconomic analysis, which integrates thermodynamic and economic factors, quantifies the financial impact of exergy losses and identifies cost-effective improvement strategies. Reducing emissions of pollutants and greenhouse gases is possible through the use …

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Design And Fabrication Of An Integrated Solar Still And Uv/Pasteurization System For Domestic Use, Majid H. Ali, D A. Al-Saadi, V V. Ostrikov Jan 2025

Design And Fabrication Of An Integrated Solar Still And Uv/Pasteurization System For Domestic Use, Majid H. Ali, D A. Al-Saadi, V V. Ostrikov

Babylonian Journal of Mechanical Engineering

Water, that miraculous liquid, is the fundamental foundation upon which life on Earth is based. The first human civilizations were founded on water, and wherever water is found, civilization is found. Given the increasing population, rising living standards, and developments that have led to increased water pollution and limited water resources, and given the expected rise in fuel and electricity prices in the future, and to rationalize electricity consumption, the use of solar energy is an effective solution for desalination and sterilization of water.In this research, a solar-powered desalination and sterilization system was designed and manufactured to make water potable. …

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Overview Of The Ciciot2023 Dataset For Internet Of Things Intrusion Detection Systems, Wisam Ali Hussein Salman, Chan Huah Yong Jan 2025

Overview Of The Ciciot2023 Dataset For Internet Of Things Intrusion Detection Systems, Wisam Ali Hussein Salman, Chan Huah Yong

Mesopotamian Journal of Big Data

The rapid expansion of the use of the Internet of Things (IoT) has encouraged many attackers to exploit the vulnerabilities in these networks to violate data privacy or disrupt service; they are easy targets due to the diversity of devices within the network, which has led to the loss of unified security standards. intrusion detection system (IDS) play a pivotal role in securing IoT networks by monitoring inbound and outbound traffic to these networks and issuing a security alarm when there is an attack; moreover, they respond directly to these security threats to prevent them from harming the network and …

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Coupling A Dual Tree - Complex Wavelet Transform With K-Means To Clustering The Epileptic Seizures In Eeg Signals, Raid Lafta, Rasha Hallem Razzaq Jan 2025

Coupling A Dual Tree - Complex Wavelet Transform With K-Means To Clustering The Epileptic Seizures In Eeg Signals, Raid Lafta, Rasha Hallem Razzaq

Mesopotamian Journal of Big Data

Electroencephalography (EEG) signals are routinely recorded in clinical settings for the diagnosis of epilepsy, that is, brain electrical disorders, by a neurologist. Nevertheless, both the reliability and safety of GB analysis of EEG parameters are not satisfactory. Therefore, identifying the effectiveness of EEG for diagnosis is a considerable challenge for hospitals. This study was conducted to improve the efficiency of detecting epileptic seizures in EEG signals by combining three methodologies: the double tree complex wavelet transform (DT-CWT), K means clustering, and the ChaCha20 encryption algorithm. EEG segments are initially partitioned into regular segments, each of which is further partitioned into …

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A Comparative Study Of Rfid System Performance In Large-Scale Network Planning Facility, Ali Abdulqader Al Qisi, Azli Bin Nawawi, Adel Muhsin Elewe Jan 2025

A Comparative Study Of Rfid System Performance In Large-Scale Network Planning Facility, Ali Abdulqader Al Qisi, Azli Bin Nawawi, Adel Muhsin Elewe

Mesopotamian Journal of Big Data

Big data in manufacturing fields present several challenges leads to reduce profitability and missed opportunity for innovation. One of the used strategies is the use of radio frequency identification system.  considered a business strategy to increase productivity, speed up decision-making, and enhance production monitoring and control while preserving the structure and integrity of current manufacturing systems. The present research compares five artificial inelegant algorithms based on RFID system in facility layout design to investigate the fitness of each algorithm in manufacturing big data processing. The objective functions have been used are the minimum number of required readers, minimum readers overlap, …

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Intelligent Techniques For Autism Spectrum Disorder Diagnosis: A Review, Ekraam Jabier, Ali Fadhil Marhoon, Ammar A. Aldair Jan 2025

Intelligent Techniques For Autism Spectrum Disorder Diagnosis: A Review, Ekraam Jabier, Ali Fadhil Marhoon, Ammar A. Aldair

Mesopotamian Journal of Big Data

Autism spectrum disorder (ASD) is a neurodevelopmental disorder whose prevalence has increased drastically around the world due to the shortcomings of the traditional method of diagnosis, which has been shown to be unsustainable since it is usually time-consuming, expensive, and subjective to clinical interpretation. These difficulties make finding more scalable, efficient, and objective methods of diagnosis incredibly expedient. This review explores the impacts of intelligent technologies such as artificial intelligence (AI), machine learning (ML), deep learning (DL), and Internet of Things (IoT) sensor-supported systems and the revolution they are bringing into the diagnosis of ASD. This work reviews the recent …

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Utilizing Graph Theory Algorithms For The Modeling And Analysis Of Covid-19 Infection Dynamics, Ioannis Adamopoulos, Antonios Valamontes, Niki Syrou, Jovanna Adamopoulou, Antonios Bardavouras Jan 2025

Utilizing Graph Theory Algorithms For The Modeling And Analysis Of Covid-19 Infection Dynamics, Ioannis Adamopoulos, Antonios Valamontes, Niki Syrou, Jovanna Adamopoulou, Antonios Bardavouras

Mesopotamian Journal of Artificial Intelligence in Healthcare

The COVID-19 outbreak has shown how urgently good models are needed to understand and project the dissemination of infectious diseases. Graph theory's excellent basis for presenting and analyzing complex networks helps one to grasp COVID-19 transmission dynamics. This work investigates the simulation and evaluation of the COVID-19 spread using multiple graph theory approaches. We utilize algorithms, including centrality assessments, community detection, and epidemic spreading models, to identify significant transmission channels and viable intervention sites; we also study the usage of network-building strategies to show relationships between individuals and communities. By incorporating real-world data with graph-based models, we demonstrate how these …

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Parkinson's Disease Detection Using Deep Learning Approach Based On Wearable Sensor-Based Daily Monitoring, Bahaulddin N. Adday, Khalid Shaker, Ihsan Salman, Hothefa Shaker Jan 2025

Parkinson's Disease Detection Using Deep Learning Approach Based On Wearable Sensor-Based Daily Monitoring, Bahaulddin N. Adday, Khalid Shaker, Ihsan Salman, Hothefa Shaker

Mesopotamian Journal of Artificial Intelligence in Healthcare

Parkinson's disease (PD) is a movement disorder characterized by motor dysfunction commonly bradyphemia, tremor, rigidity, akinesia, or slowness of movement. Noting that motor states can fluctuate in PD the primary aim of this current paper was to differentiate multiple states using wearable sensors in the patients and detection of this PD based on deep learning (CNN). Methodology: In this paper, the researchers recorded the signals of the accelerometer and gyroscope fixed on the wrist of PD in their regular daily functioning after using this dataset collection. The deep learning architecture developed was to optimize a CNN for analyzing the sensor …

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The Next Frontier In Computer Science, Trends And Research Opportunities, Mostafa Abdulghafoor Mohammed, Z. T. Al-Qaysi, Tahsien Al-Quraishi Jan 2025

The Next Frontier In Computer Science, Trends And Research Opportunities, Mostafa Abdulghafoor Mohammed, Z. T. Al-Qaysi, Tahsien Al-Quraishi

Mesopotamian Journal of Computer Science

No abstract provided.

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A Deep Learning Approach For Identifying Malicious Activities In The Industrial Internet Of Things, Mohammed Amin Almaiah, Fuad Ali El-Qirem, Rami Shehab, Khaled Sulieman Momani Jan 2025

A Deep Learning Approach For Identifying Malicious Activities In The Industrial Internet Of Things, Mohammed Amin Almaiah, Fuad Ali El-Qirem, Rami Shehab, Khaled Sulieman Momani

Mesopotamian Journal of Computer Science

Data-driven decision-making, real-time connectivity, and automation have transformed industrial operations with the Industrial Internet of Things. However, the integration also introduces substantial cybersecurity vulnerabilities, making IIoT networks a prime target for malicious activities. Cyber threats are evolving and becoming more sophisticated, which makes traditional security mechanisms inadequate. An approach using deep learning to detect malicious activities in IIoT environments is examined. It is investigated whether Deep Feed Forward neural networks, autoencoders, and convolutional neural networks are effective at detecting anomalies and mitigating cyber threats. NSL-KDD and UNSW-NB15 benchmark datasets are used to evaluate the proposed model's accuracy, precision, and detection …

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Woa-Covid-19: Whale Optimization Algorithm For Selection Of Multi-Examination Features Based On Covid-19 Infections, Karrar Hameed Abdulkareem, Mazin Abed Mohammed, Zaid Abdi Alkareem Alyasseri, Dawood Zahi Khutar, Osama Ahmad Alomari Jan 2025

Woa-Covid-19: Whale Optimization Algorithm For Selection Of Multi-Examination Features Based On Covid-19 Infections, Karrar Hameed Abdulkareem, Mazin Abed Mohammed, Zaid Abdi Alkareem Alyasseri, Dawood Zahi Khutar, Osama Ahmad Alomari

Mesopotamian Journal of Computer Science

Since its emergence in late 2019, COVID-19 (Coronavirus Disease 2019) has become one of the most critical global health threats, claiming millions of lives and placing many more at serious risk. The complexity of diagnosing COVID-19 lies in the wide range of clinical and examination features involved, prompting researchers to explore various advanced diagnostic methods. However, one of the main challenges is identifying the most relevant features that can streamline and improve diagnostic accuracy. In this study, we propose a feature selection approach based on the Whale Optimization Algorithm (WOA) to identify key examination indicators associated with COVID-19. We used …

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Self-Attention Enhanced Dual Bigru For Arabic Fake News Detection, Baqer M. Merzah, Jafar Razmara, Jaber Karimpour Jan 2025

Self-Attention Enhanced Dual Bigru For Arabic Fake News Detection, Baqer M. Merzah, Jafar Razmara, Jaber Karimpour

Mesopotamian Journal of Computer Science

The rapid proliferation of social media platforms has greatly amplified the dissemination of fake news, representing significant obstacles to public trust and evidence-based decision-making, particularly for the Arabic-speaking population. Meeting the challenge of Arabic fake news detection is a problem compounded by the complex morphological nature of the language, as well as limited resources. This study presents a hybrid deep learning framework that integrates two Bidirectional Gated Recurrent Units (BiGRUs) along with an attention mechanism for efficiently detecting misinformation in Arabic news. The method leverages FastText word embeddings for disambiguating the intricate semantics of the Arabic language. The model is …

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Diabetes At A Glance: Assessing Ai Strategies For Early Diabetes Detection And Intervention Via A Mobile App, Ayad Hameed Mousa, Ibrahim Oday Alrubaye, Mayameen S. Kadhim, Ahmed Dheyaa Radhi, Mudatheer M. Al-Slivani, Rusul Mansoor Al-Amri, Liaw Geok Pheng Jan 2025

Diabetes At A Glance: Assessing Ai Strategies For Early Diabetes Detection And Intervention Via A Mobile App, Ayad Hameed Mousa, Ibrahim Oday Alrubaye, Mayameen S. Kadhim, Ahmed Dheyaa Radhi, Mudatheer M. Al-Slivani, Rusul Mansoor Al-Amri, Liaw Geok Pheng

Mesopotamian Journal of Computer Science

Diabetes is a widespread disease worldwide that does not differentiate between children and adults. It also affects the elderly and pregnant women. However, early detection of the disease facilitates its control to avoid the effects resulting from delayed diagnosis. With the emergence of artificial intelligence represented by machine learning techniques and its use in most sectors, accordingly, the adoption of machine learning techniques to help in disease prediction has become a necessity. This study proposes a machine learning algorithm-based approach for diabetes prediction. This study uses three datasets, two of which are private and the other includes the Pima Indians …

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Enhancing Routing Efficiency In Vanets By Leveraging 5g To Mitigate Congestion, Yusor Rafid Bahar Al-Mayouf, Omar Adil Mahdi, Heba Hussain Hadi, Suleman Khan, Mazin Abed Mohammed Jan 2025

Enhancing Routing Efficiency In Vanets By Leveraging 5g To Mitigate Congestion, Yusor Rafid Bahar Al-Mayouf, Omar Adil Mahdi, Heba Hussain Hadi, Suleman Khan, Mazin Abed Mohammed

Mesopotamian Journal of Computer Science

Transportation networks impact millions of people daily. Their efficiency immediately affects travel time, safety, and environmental sustainability. Unfortunately, various issues hinder the expected performance and efficiency of these networks. Traffic congestion is an up-to-date issue in the urban environment. Fuel consumption is high because travel time has increased, which has a passive environmental impact. Extensive research has been conducted to progress the intelligent transportation systems installed on communication networks and information to treat this congestion. However, there is a significant amount of affront residue in combining real-time data, estimation analytics, and 5G abilities effectively. This paper offers a novel routing …

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Roi – Enhancing Detection Of Citrus Disease Based On Yolov10, Raya N. Ismail, Armaneesa Naaman Hasoon, Israa Rafaa Abdulqader, Salwa Khalid Abdulateef Jan 2025

Roi – Enhancing Detection Of Citrus Disease Based On Yolov10, Raya N. Ismail, Armaneesa Naaman Hasoon, Israa Rafaa Abdulqader, Salwa Khalid Abdulateef

Mesopotamian Journal of Computer Science

One of the most important fruit crops in the world is citrus. However, some citrus diseases spread rapidly, which is why early detection at an accurate stage is important for timely intervention. YOLO-based object detection models, such as the latest YOLOv10, where small lesions are difficult to identify among noisy backgrounds, have recently been developed, yet their accuracy tends to degrade. Therefore, we proposed a citrus disease detection model by integrating the region of interest (ROI) for object segmentation with the YOLOv10 model, thus addressing the issues of low detection accuracy and slow inference time. The proposed model was trained …

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Green Regionalism In World Trade Law, Pasha L. Hsieh Jan 2025

Green Regionalism In World Trade Law, Pasha L. Hsieh

Research Collection Yong Pung How School Of Law

Multifaceted geopolitical conflicts have led to disruptions in the trade regime and multilateral negotiations. As a paradigm shift, green regionalism has emerged as a new normative process for regional economic frameworks to integrate and operationalize environmental sustainability. The article offers the first interdisciplinary analysis of green regionalism in world trade law. It argues that green regionalism, which has evolved amid various waves of global regionalism, constructs the normative foundation for 'Trade and Sustainability 2.0'. The article employs the concept of recognition in international relations to unveil the motivations and actions of major states in catalyzing green regionalism. Legal and political …

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Ai Characterisations And Their Legal Implications, Jerrold Tsin Howe Soh Jan 2025

Ai Characterisations And Their Legal Implications, Jerrold Tsin Howe Soh

Research Collection Yong Pung How School Of Law

This chapter examines the difficult legal characterisation problems that artificially intelligent systems raise and explores how different characterisations of artificial intelligence (AI) shape practical legal outcomes. Three reasons are offered for the legal difficulty with characterising AI. First, answers to characterisation problems are inherently subjective and perspective-driven, particularly when the subject is an intangible technological system. Second, AI technology is especially difficult to define since the field typically proceeds on inexact anthropomorphic metaphors. Third, AI characterisation problems raise difficult sub-problems, particularly in determining how autonomous an AI system is. The chapter thus argues that a range of plausible AI characterisations …

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Introducing Sustainable Development Goals In College Curricula: A Way Forward, Christy Ashley, Jason D. Oliver, Hillary Leonard Jan 2025

Introducing Sustainable Development Goals In College Curricula: A Way Forward, Christy Ashley, Jason D. Oliver, Hillary Leonard

Markets, Globalization & Development Review

The commentary proposes a blueprint to help guide curriculum innovations, partnerships, and teaching interventions that incorporate the United Nations sustainable development goals (SDGs) into the curriculum. It suggests the utilization of AACSB’s Societal Impact Canvas with Ancona et al.’s (2007) Leadership Capabilities (Sensemaking, Relating, Visioning, Inventing) to provide a blueprint for mission-aligned SDG integration at a local level. It provides an illustrative example from the University of Rhode Island (USA), where the focus is on the Blue Economy. It aims to provide practical guidance for how a college or university can efficiently organize to gain stakeholder input that helps enhance …

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Risk Management, Internal Audit Function, And Corporate Performance, Ahmad Saiful Azlin Puteh Salin, Zubaidah Ismail, Malcolm Smith, Suryani Abdul Raman, Norliana Omar, Siti Marlia Shamsudin Jan 2025

Risk Management, Internal Audit Function, And Corporate Performance, Ahmad Saiful Azlin Puteh Salin, Zubaidah Ismail, Malcolm Smith, Suryani Abdul Raman, Norliana Omar, Siti Marlia Shamsudin

Research outputs 2022 to 2026

The purpose of this study is to determine the relationship between risk management practices and the internal audit function with the performance of companies. It is interesting to examine how competitive advantage can be achieved when the company is able to face and adapt to a complex business environment via robust risk management practices and an internal audit function. This study uses archival analysis on the annual report of the top 500 publicly listed companies in Bursa Malaysia, which represent approximately 65 percent of the total market capitalization. Both independent variables, namely risk management and internal audit function, are measured …

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The Key Role Of Feedback In Institutional Readiness For Programmatic Assessment, Michelle Pedlow, David Boud Jan 2025

The Key Role Of Feedback In Institutional Readiness For Programmatic Assessment, Michelle Pedlow, David Boud

Research outputs 2022 to 2026

Programmatic assessment for learning represents a shift from fragmented, summative assessment practices to integrated, developmental systems where feedback is central to learning. This paper argues that feedback is foundational to programmatic assessment (PAx) implementation. Using feedback as an analytical lens, it examines institutional readiness for the deep structural and cultural shifts that PAx requires, drawing on a qualitative case study of course coordinators across three disciplines at an Australian university. Five interrelated barriers were identified: fragmented feedback, summative assessment reliance, workload constraints, absence of coordinated feedback pathways, and unconstrained educator autonomy. These reflect structural and cultural misalignments with PAx principles. …

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The Metaverse And Sport Fandom: Revolutionising Sport Consumption, Ashlee Morgan, Anthony Kerr Jan 2025

The Metaverse And Sport Fandom: Revolutionising Sport Consumption, Ashlee Morgan, Anthony Kerr

Research outputs 2022 to 2026

This article explores the potential transformative impact of the metaverse on sport consumption. While traditional sport environments cultivate a sense of communitas and liminality, where attendees experience unity and solidarity, the digital shift is redefining these dynamics. The metaverse offers new ways for sport consumers to engage, experience, and enter into an exchange. We present a model that conceptualises the multifaceted elements reshaping how sport is consumed, while also providing a framework to critically assess the implications of this transformation. We address both the opportunities and challenges presented with the expansion of virtual sport consumption and highlight legal and ethical …

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From The Icu Bedside: Applying The Transnational Clinical Academic Doctorate Lens To A Clinically Embedded Phd Journey, Gideon U. Johnson Jan 2025

From The Icu Bedside: Applying The Transnational Clinical Academic Doctorate Lens To A Clinically Embedded Phd Journey, Gideon U. Johnson

Research outputs 2022 to 2026

Aim: To critically reflect on a transnational, clinically embedded doctoral journey undertaken during and after the COVID-19 pandemic, and to draw conceptual and systemic lessons for doctoral education and clinical academic nursing pathways. Background: Reflective accounts of doctoral study exist, yet few examine practice-based PhDs conducted across different countries and health systems during a global crisis. This paper analyses one such pathway—enrolment at an Australian university with research embedded within the UK National Health Service—to explore resilience, identity formation, mentorship ecologies and organisational conditions that support or hinder clinical academic development. Method: Using analytic autoethnography and reflective case study logic, …

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