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1. Security Risks and Challenges of Remote Working and Learning

   Gyles, Sheyla; Boonthum-Denecke, Chutima (January 2023, The 2023 ADMI Symposium)

   This report will discuss and analyze the risks and different challenges which are accompanied when completing remote work and learning. Specifically, this paper will focus on this trends’ effect, during the 2019 Coronavirus pandemic (COVID-19). The different applications that will be included in this research are Slack, Zoom, Skype, Microsoft Teams, Google Meets, Trello, Webex, and Troop Messenger. In recent months, there has been a complete increase in the amount of people worldwide that use these platforms. However, the majority of users do not fully understand security and privacy when using these different platforms. Due to this lack of knowledge, this comes with an increase in attacks. This study will further discuss the different pros and cons of each of the different platforms (mentioned above); the applications that have been breached, how often they were breached, different flaws, vulnerabilities of each system and more. This study coherently uses and assesses its credibility with the assistance of research, a user survey, and past research studies on this topic. 

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2. A Unified Real-Time Motion Generation Algorithm for Approximate Position Analysis of Planar N-Bar Mechanisms

   https://doi.org/10.1115/1.4064132  

   Lyu, Zhijie; Purwar, Anurag; Liao, Wei (June 2024, Journal of Mechanical Design)

   Abstract This paper presents a novel real-time kinematic simulation algorithm for planar N-bar linkage mechanisms, both single- and multi-degrees-of-freedom, comprising revolute and/or prismatic joints and actuators. A key feature of this algorithm is a reinterpretation technique that transforms prismatic elements into a combination of revolute joint and links. This gives rise to a unified system of geometric constraints and a general-purpose solver which adapts to the complexity of the mechanism. The solver requires only two types of methods—fast dyadic decomposition and relatively slower optimization-based—to simulate all types of planar mechanisms. From an implementation point of view, this algorithm simplifies programming without requiring handling of different types of mechanisms. This versatile algorithm can handle serial, parallel, and hybrid planar mechanisms with varying degrees-of-freedom and joint types. Additionally, this paper presents an estimation of simulation time and structural complexity, shedding light on computational demands. Demonstrative examples showcase the practicality of this method. 

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3. Conflict Avoidance in Social Navigation—a Survey

   https://doi.org/10.1145/3647983  

   Mirsky, Reuth; Xiao, Xuesu; Hart, Justin; Stone, Peter (March 2024, ACM Transactions on Human-Robot Interaction)

   A major goal in robotics is to enable intelligent mobile robots to operate smoothly in shared human-robot environments. One of the most fundamental capabilities in service of this goal is competent navigation in this “social” context. As a result, there has been a recent surge of research on social navigation; and especially as it relates to the handling of conflicts between agents during social navigation. These developments introduce a variety of models and algorithms, however as this research area is inherently interdisciplinary, many of the relevant papers are not comparable and there is no shared standard vocabulary. This survey aims at bridging this gap by introducing such a common language, using it to survey existing work, and highlighting open problems. It starts by defining the boundaries of this survey to a limited, yet highly common type of social navigation—conflict avoidance. Within this proposed scope, this survey introduces a detailed taxonomy of the conflict avoidance components. This survey then maps existing work into this taxonomy, while discussing papers using its framing. Finally, this article proposes some future research directions and open problems that are currently on the frontier of social navigation to aid ongoing and future research. 

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4. Reflexive Control Theory in Cyber Operations

   Gyles, Sheyla; Muhammad, Jean (April 2024, The 2024 ADMI Symposium.)

   This report will discuss and explore the concept of reflexive control theory (RCT) in the context of day-to-day cybersecurity operations. Specifically, this study aims to investigate and emphasize the influential role of this trend in cyberspace while simultaneously examining the manipulative tactics employed by adversaries and RCT’s effect on the public. This report will further explain the concept of RCT and aims to promote awareness to educate the public about this topic. In the realm of cybersecurity, reflexive control serves as a potent weapon, used to allow adversaries to be able to exploit vulnerabilities, influence decision-making and essentially predict their target’s actions. This research will focus on three key concepts within reflexive control theory: Behavioral Analysis, Threat Detection and Perception Management. Furthermore, this report examines the ethical dimensions and potential risks associated with the reflexive control theory technique. These findings are intended to raise awareness and propose strategies to enhance resilience against these manipulative tactics. By meticulously synthesizing existing literature, research studies, and user surveys, this report provides a comprehensive analysis of the reflexive control theory in cyber operations. 

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5. Efficient Multi-Agent Delegated Search

   Bechtel, Curtis; Dughmi, Shaddin (June 2025, Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2025))

   Consider a principal who wants to search through a space of stochastic solutions for one maximizing their utility. If the principal cannot conduct this search on their own, they may instead delegate this problem to an agent with distinct and potentially misaligned utilities. This is called delegated search, and the principal in such problems faces a mechanism design problem in which they must incentivize the agent to find and propose a solution maximizing the principal's expected utility. Following prior work in this area, we consider mechanisms without payments and aim to achieve a multiplicative approximation of the principal's utility when they solve the problem without delegation. In this work, we investigate a natural and recently studied generalization of this model to multiple agents and find nearly tight bounds on the principal's approximation as the number of agents increases. As one might expect, this approximation approaches 1 with increasing numbers of agents, but, somewhat surprisingly, we show that this is largely not due to direct competition among agents. 

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