Tala Talaei Khoei

• PhD in Electrical Engineering
• Northeastern University

The Model Context Protocol (MCP), recently introduced by Anthropic, proposes a standardized framework for integrating large language models (LLMs) with dynamic external systems. This survey reviews the foundational architecture of MCP, including its client-server model, standardized messaging protocols, dynamic tool discovery, and security mechanis...

This paper introduces an integrated approach to object tracking in computer vision by combining the Single Shot MultiBox Detector (SSD) with Long Short-Term Memory (LSTM) networks, specifically tailored for dynamic applications like vehicle tracking. By leveraging LSTM’s temporal modeling capabilities alongside SSD’s robust object identification, t...

Large Language Models (LLMs) have revolutionized artificial intelligence (AI) by enabling human like text generation and natural language understanding. However, their reliance on static training data limits their ability to respond to dynamic, real time queries, resulting in outdated or inaccurate outputs. Retrieval Augmented Generation (RAG) has...

Large Language Models (LLMs) have transformed numerous domains by providing advanced capabilities in natural language understanding, generation, and reasoning. Despite their groundbreaking applications across industries such as research, healthcare, and creative media, their rapid adoption raises critical concerns regarding sustainability. This sur...

Text-to-SQL systems facilitate smooth interaction with databases by translating natural language queries into Structured Query Language (SQL), bridging the gap between non-technical users and complex database management systems. This survey provides a comprehensive overview of the evolution of AI-driven text-to-SQL systems, highlighting their found...

The application of artificial intelligence (AI) in civil engineering presents a transformative approach to enhancing design quality and safety. This paper investigates the potential of the advanced LLM GPT4 Turbo vision model in detecting architectural flaws during the design phase, with a specific focus on identifying missing doors and windows. Th...

In this paper, we conduct a comprehensive SWOT analysis of prompt engineering techniques within the realm of Large Language Models (LLMs). Emphasizing linguistic principles, we examine various techniques to identify their strengths, weaknesses, opportunities, and threats. Our findings provide insights into enhancing AI interactions and improving la...

Emotional Artificial Intelligence (Emotional AI), with its advanced capability to detect, analyze, and interpret human emotions, presents a groundbreaking opportunity for enhancing various aspects of policing and criminology. This paper delves into the integration of Emotional AI in these fields, highlighting its potential to revolutionize crime de...

Data reduction plays a pivotal role in managing and analyzing big data, which is characterized by its volume, velocity, variety, veracity, value, variability, and visibility. However, several surveys have been conducted to summarize these techniques in the field of big data, and there are several concerns that require attention, such as limited dis...

This research introduces an innovative mathematical learning approach that integrates generative AI to cultivate a structured learning rather than quick solution. Our method combines chatbot capabilities and generative AI to offer interactive problem-solving exercises, enhancing learning through a stepby-step approach for varied problems, advocatin...

This paper explores the significant shift towards agentic workflows in the application of Large Language Models (LLMs), moving away from traditional, linear interactions between users and AI. Through a case study analysis, we highlight the effectiveness of agentic workflows, which facilitate a more dynamic and iterative engagement, in improving out...

Recent research in the field of Large Language Models (LLMs) has given a new direction to the capabilities of AI agents for solving complex problems. This paper attempts to explore one such use case to investigate LLMs-based AI agents’ role in immersive technology, specifically focusing on GPT-4’s vision capabilities in Augmented Reality (AR). The...

Machine learning techniques have emerged as a transformative force, revolutionizing various application domains, particularly cybersecurity. The development of optimal machine learning applications requires the integration of multiple processes, such as data pre-processing, model selection, and parameter optimization. While existing surveys have sh...

The current development in deep learning is witnessing an exponential transition into automation applications. This automation transition can provide a promising framework for higher performance and lower complexity. This ongoing transition undergoes several rapid changes, resulting in the processing of the data by several studies, while it may lea...

Intrusion Detection Systems are expected to detect and prevent malicious activities in a network, such as a smart grid. However, they are the main systems targeted by cyber-attacks. A number of approaches have been proposed to classify and detect these attacks, including supervised machine learning. However, these models require large labeled datas...

GPS spoofing attacks are a severe threat to unmanned aerial vehicles. These attacks manipulate the true state of the unmanned aerial vehicles, potentially misleading the system without raising alarms. Several techniques, including machine learning, have been proposed to detect these attacks. Most of the studies applied machine learning models witho...

One of the significant challenges that smart grid networks face is cyber-security. Several studies have been conducted to highlight those security challenges. However, the majority of these surveys classify attacks based on the security requirements, confidentiality, integrity, and availability, without taking into consideration the accountability...

Smart grid provides several benefits, such as reliability and affordability. Despite its benefits, this network has several shortcomings, including a lack of security. DoS attacks are considered one of the main damaging cyber-attacks on these networks. For this purpose, several techniques have been proposed to detect such attacks. However, the...

Advances made in Unmanned Aircraft Vehicles (UAVs) have increased rapidly in the last decade resulting in new applications in both civil and military spheres. However, with the growth in the usage of these systems, various cybersecurity challenges arose unveiling the vulnerabilities of UAV wireless networks. Among the attacks that threaten the netw...

Unmanned aerial vehicles are prone to several cyber-attacks, including Global Positioning System spoofing. Several techniques have been proposed for detecting such attacks. However, the recurrence and frequent Global Positioning System spoofing incidents show a need for effective security solutions to protect unmanned aerial vehicles. In this paper...

Smart grid is an emerging technology that delivers intelligently to the end-users through two-way communication. However, this technology can be subject to several cyber-attacks due to this network's inherent weaknesses. One practical solution to secure smart grid networks is using an intrusion detection system (IDS). IDS improves the smart grid’s...

Alzheimer's disease (AD) affects fifty million people worldwide and is the sixth cause of death in the United States. However, there is no cure or treatment for patients with AD; thus, it is important to detect this disease at an early stage to improve patients' lives qualities. Several studies have been proposed to detect and differentiate between...

Encryption algorithms play an essential role in network security. They are one type of countermeasure that can prevent unauthorized access of data. Although the security robustness of the algorithm is the focal point in choosing one, other performance metrics are also important, especially for resource-constrained technologies like unmanned aerial...

We consider the problem of covering a planar environment, possibly containing unknown obstacles, using a robot of square size D×D attached to a fixed point S by a cable of finite length L. The environment is discretized into 4-connected grid cells with resolution proportional to the robot size. Starting at S, the task of the robot is to visit each...

There have been widespread critiques towards the lack of contextual approaches in the adoption theories. This paper argues that independent living plays a significant role in adoption of assistive technologies such as robots among seniors. Therefore, the present article introduces perceived transfer effects as a cognitive process in which elderly r...

This paper presents two interventions to improve the peer learning practice in an Information System course; namely (1) class-based peer tutoring in small groups and (2) discussions on Facebook group of the course. The article aims at comparing the correlations between the learning outcomes with class-based peer tutoring as well as with Facebook en...

There has been extensive research on the use of social networking sites, particularly Facebook, for enhancing student engagement. However, a detailed discussion on contexts has been largely ignored. The main objective of this paper is to examine the role of learning context in the success of student engagement by the use of social networking sites....

This paper undertakes a systematic review to gain insight into existing studies on the application of Social Network Sites (SNS). Our systematic review of studies from 1995 to 2012 examines the background and trend of research in the area and provides critical factors that organizations should consider for effectively use social networking sites to...

This paper undertakes a systematic review to gain insight into existing studies on the application of Social Network Sites (SNS). Our systematic review of studies from 1995 to 2012 examines the background and trend of research in the area and provides critical factors that organizations should consider for effectively use social networking sites to...

With the rapid propagation of Web Services and the increase of functionally similar Web Services, the issue of selecting them based on their quality attributes is becoming very popular among the research community and practitioners. Quality of Services (QoS) are distinguishing factors for users in selecting Web Services, when there are multiple Web...