Robotics and Artificial Intelligence Review

Review of E-Government program: A case study on Islamic Republic of Iraq

USMAN AAMER, Mohsin Sami, ramsha Saeed — Wed, 03 Dec 2025 05:52:33 +0000

E-Government initiatives in Iraq have the potential to reshape the way public services are delivered by improving efficiency, transparency, and citizen engagement. Despite this promise, the journey toward successful implementation faces several challenges, including weak digital infrastructure, cybersecurity threats, and resistance to change among key stakeholders. At the same time, there are important enablers—such as government support, digital literacy programs, and the growth of information and communication technology (ICT)—that can help drive progress in this area. This review explores both the barriers and facilitators of e-government adoption in Iraq, with a particular focus on its connection to sustainable development. Prior research identifies major hurdles such as limited internet coverage, low digital skills, and bureaucratic red tape, but also points to factors like policy initiatives and foreign aid that can support digital transformation. Moreover, e-governance plays a growing role in promoting sustainability by cutting down on paperwork, conserving resources, and creating more inclusive access to government services. However, there is still limited evidence-based research examining how e-government initiatives directly contribute to sustainability outcomes in Iraq. This paper highlights the need for further studies and practical strategies that can help bridge this gap, ensuring that digital governance not only modernizes the public sector but also contributes to long-term social, economic, and environmental well-being.

Enhancing Facial Emotion Recognition Using DCNN through Effective Extraction for High-Level Features

Mohsin Sami, Usman Aamer, Ramsha Saeed — Wed, 03 Dec 2025 00:00:00 +0000

Facial Emotion Recognition, or FER, is increasingly important in human-computer communication, psychology, and advanced monitoring. Researchers seek to enhance accuracy of recognition with high-level feature extraction techniques, utilizing the advancements made in deep convolutional neural networks (DCNNs). This systematic literature review (SLR) compiles and analyses forty-two (42) studies published from 2020 to 2025 across IEEE Xplore, SpringerLink, ScienceDirect, Scopus, and ACM Digital Library. The review marks trends in DCNN-based FER and analyses the datasets used within the research such as FER-2013, CK+, JAFFE, along with their respective metrics and feature extraction methods. The DCNNs were quantitatively found to outperform other architectures, although interpretable and deployable systems were lacking. Through qualitative synthesis, the major focus was placed on feature engineering with deep learning, merging models, and creating comprehensive pre-processing workflows. The review indicates that while steps have been taken toward achieving the broad-scope goals, the diversity of datasets, unified metrics, and real-time systems hinder progress. The comparison of the approaches for high-level feature extraction builds the foundation of the review, making it distinct. This SLR aims to guide future efforts by highlighting unresolved issues and recommending directions for practical and responsible FER systems.

Using Formal Verification and Model Checking in Agile Development to Improve the Quality of Software Development: Review

Wed, 03 Dec 2025 10:52:44 +0000

In this paper, analysis the efficiency of software development through modeling checking, formal verification and different tools that is supported to develop it. A lot of real-life examples are quoted in this paper. Implement different model checking techniques, STPA methods and analysis on game development, railway management system and other sectors. In the innovation and huge development in software industries, we must heavy knowledge about software engineering course and must taught in universities. Software engineering plays a vital and great role in development of software. In this paper, proposed the requirement divided approach, in which divide the requirements through filer vise, break it, priority them, numbering in specific order and convert it in requirement document. We well known that in every software development, requirements phase is major and initial phase and whole software development based on it. After that apply the testing tools to test it for quality purpose and customer satisfaction.

V2V: Securing Vehicle-to-Vehicle Communication, Architectures, Threats, and Countermeasures

Wed, 03 Dec 2025 11:09:33 +0000

The rapid evolution of the Internet of Vehicles (IoV) has transformed Vehicle-to-Vehicle (V2V) communication into a foundational component of intelligent transportation systems (ITS). However, the complexity of dynamic vehicular environments introduces significant challenges in terms of communication reliability, latency, and cybersecurity. This paper presents an enhanced framework for V2V communication that integrates a novel taxonomy of technologies, security mechanisms, and challenges, providing a comprehensive overview of the field. The proposed taxonomy classifies V2V research trends by access technology (DSRC, C-V2X, 5G NR, and VLC), security layer, and mitigation strategy. Furthermore, simulation-based validation using vehicular mobility traces is incorporated to evaluate packet delivery ratio, delay, and throughput under varying network conditions. The study also explores how Artificial Intelligence (AI) and Blockchain technologies can enhance routing efficiency, trust management, and intrusion resilience in future vehicular networks. Finally, a forward-looking vision (2025–2030) outlines emerging research opportunities in edge-intelligent, AI-driven, and blockchain-secured V2X ecosystems.

An Agent-Based Simulation Study of Guilt, Volunteering, and Social Norm Enforcement

Muhammad Junaid Anjum, Yahya Fikri, Fatima Tariq — Wed, 03 Dec 2025 11:14:42 +0000

The present study uses Agent-Based Modeling (ABM) to study the intricate dynamics among diffusion of responsibility, subjective feeling of guilt, and their interaction impact on volunteering behavior when a context of norm violation exists. The process of responsibility diffusion is what classical studies on the bystander effect as a volunteer suppressor focus on. Our model generalizes this process by adding guilt to the list of cognitive elements triggered by an agent's inaction when witnessing violation of a norm. The simulation shows that even though observing bystanders who do not assist (diffusion of responsibility) initially suppresses volunteering, internalization and subsequent diffusion of guilt significantly lowers the threshold of reacting to non-volunteering agents in future encounters. Furthermore, the model demonstrates a causal link between spontaneous, efficient volunteering and an empirically measurable reduction in the convict's behavioral tendency to engage in further acts of norm violations. These emergent, macroscopic tendencies validate the theoretical prediction that guilt is an internal constraint capable of surmounting social inertia and hence acting as the main facilitator for self-organized social norm policing and collective deterrence in a population.