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(SI15-142) Selection of Single Sampling Plans Based on Zero Inflated Binomial Distribution using Cost Optimization
No full textEconomic design of sampling plans involves creating sampling plans that minimize the total cost associated with the inspection process while ensuring quality. It aims to address the quality risk concerns of both producer and consumer, ensuring product quality while minimizing inspection costs. This article’s objective is to design single sampling plans by attributes based on Zero-inflated Binomial (ZIB) distribution, using cost optimization principles by developing an economic model aimed at achieving optimal total cost by considering the Average Total Inspection (ATI). Numerical illustration is provided to illustrate the selection of single sampling plans under ZIB distribution that minimizes producer’s total cost. Sensitivity analysis of the parameters is discussed
Energy-Efficient Task Offloading Frameworks For Mixed Reality And Extended Reality In Edge AI Environments
No full textMixed Reality (MR) and Extended Reality (XR) technologies are increasingly integrated into real-time applications such as remote maintenance, spatial navigation, and immersive learning. However, the computational intensity of deep learning workloads, especially object detection models like YOLO, poses significant challenges for wearable XR devices with limited processing power and battery life. To address these challenges, this thesis presents a comprehensive study of adaptive offloading strategies that optimize task execution between XR devices and edge servers.
We first proposed the Binary Spatial Allocation Framework (BSAF), which introduced a real-time binary decision mechanism for XR systems. The BSAF framework evaluates scene complexity, network conditions, and system constraints to dynamically select either local execution on HoloLens 2 or edge execution using high-precision YOLOv11 models. A closed-form utility model was developed to balance accuracy, latency, and energy consumption, and Lagrangian relaxation was employed to maintain constraint feasibility. Experimental results across 100 XR scenes showed that BSAF reduced latency by up to 20% and energy usage by 36% compared to full offloading, while preserving over 90% detection accuracy.
To further enhance adaptability, we proposed SPARL-CBF, a Safe Partial Offloading framework that integrates Model-Based Reinforcement Learning (MBRL) with Control Barrier Functions (CBFs). Unlike binary strategies, SPARL-CBF learns a continuous offloading policy that dynamically adjusts task partitioning based on runtime system states such as battery level, bandwidth, and CPU load. CBFs ensure real-time constraint satisfaction by projecting unsafe actions back into feasible regions. Implemented using Proximal Policy Optimization (PPO) and deployed on a live edge-XR testbed, SPARL-CBF achieved over 94% accuracy, reduces latency, and prolongs device battery life by intelligently modulating the offloading ratio. Together, BSAF and SPARL-CBF offer a unified, constraint-aware framework for intelligent task offloading in XR systems. This thesis provides mathematical formulations, system implementations, and empirical evaluations that demonstrate how adaptive offloading can significantly improve energy efficiency and responsiveness in edge-assisted XR environments. The proposed approaches lay the groundwork for scalable, real-time XR applications in emerging domains such as healthcare, smart cities, and the metaverse.
Index Terms-- augmented reality, computer vision, deep learning, edge computing, mixed reality
(R2131) Analysis of MAP/PH/1 Retrial Inventory Queueing System with Constant Retrial Rate, Bernoulli Vacation, Breakdown, Delayed Repair, Balking, (s, S) Policy and Emergency Replenishment
No full textA single server retrial queueing-inventory model is investigated in this study. In Bernoulli vacation, after providing service to the customer, the server may opt to avail vacation or start the service to subsequent customer. During the busy period, breakdown and balking may occur. The inventory is replenished to an (s, S) policy and the replenishing time is assumed to adopt an exponential distribution. Furthermore, assume that an emergency replenishment of one item with zero lead time takes place when the on-hand inventory level decreases to zero. We integrate the emergency replenishment into the system to ensure customer satisfaction. For our system, a stability criterion was developed and the stationary probability vector was evaluated by utilizing the matrix analytical approach. This model also examined the study of busy time and performance measures. Using two and three dimensional graphs, the numerical illustrations are shown
(R2141) Analysis of MAP^I_1 , PH^(OA)_2 / PH^I_1 , PH^O_2 / 1 Retrial Inventory Queue with Two Way Communication, (s, S) Replenishment Policy, Feedback, Bernoulli Vacation and Impatient Customers
No full textThis work discusses about the topic as the two-way communication retrial inventory queue model, the (s, S) replenishment policy, immediate feedback, Bernoulli vacations, and impatient customers. The assumption we make is that arrivals follow a Markovian arrival process, and the server provides phase type services. When the server is idle and there is a positive inventory, an arriving customer immediately receives service. If not, arriving customers goes to orbit with infinite capacity. Only in the account of positive inventory the server renders rapid feedback for incoming call arrivals, otherwise customer departs. Outgoing calls will only be made by the server in the accordance with the PH distribution when idle with positive inventory, otherwise it remains idle. In this scenario, we use the (s, S) policy to replenish the items. The steady state probability vector can be determined using a matrix analytic method, and performance metrics such as busy periods, efficiency measures, cost analysis, and numerical examples are examined
(R2122) Analysis of Halo Orbits in the Elliptical R3BP with Mass Variation
No full textThe elliptic restricted three-body problem investigates the motion behaviour of the variable mass infinitesimal body under the gravitational forces of the radiated oblate primary and dipole secondary. The equations of motion of the infinitesimal body are determined using Jeans law and Meshcherskii space time transformations. Using the Lindstedt-Poincaré method, we perform the solutions of the equations of motion. With the use of these solutions and the equations of motion, we numerically illustrate the time series, phase spaces, projections and the Halo orbits
(R2094) On MDS Bisymmetric Rhotrices using Self-dual Bases and Conjugate Elements of Finite Fields
No full textBisymmetric matrices have wide range of applications in statistics, engineering problems, information theory and computer science including coding theory and cryptography. In cryptography, a rhotrix being a couple matrix doubles the security of the cryptosystem. Here, we construct maximum distance separable (MDS) bisymmetric rhotrices using self-dual bases and conjugate elements of finite fields. MDS rhotrices are very crucial for the designing of block ciphers and hash functions in cryptography
Off-Grid Renewable Energy Generation Supervisory And Data Acquisition (Sada) Using Extended Reality
Full text linkSupervisory and Data Acquisition (SADA) systems are an imperative component for the operation of intelligent power systems. In this study, control room duties were performed remotely through extended reality (XR) technology. Multiple monitor setups can be eliminated, and the use of peripheral devices was reduced. XR technology allows for the combination of real and digital environments, which will help to eliminate physical control room setups while enhancing the mobility and comfort of operators. The implementation of XR technology will provide enhancements in communications through built-in text chats, voice calls, video calls, and screen casting capabilities. The XR SADA system proposed utilized the Apple Vision Pro. For the SADA system to function properly, the off-grid power generation system must have the appropriate supporting infrastructure. This includes devices such as smart meters, inverters, sensors, and battery storage systems that can transmit grid data via Internet connectivity. The Apple Vision Pro headset accesses the online data servers of the Internet of Things (IoT) devices through an Internet web browser or device applications. Once accessed, the data windows may be configured according to the operator’s preference. That data is then exported and analyzed for the creation of real-time grid alerts, which provide notifications within the operator’s vision. The XR SADA system is designed to be easily setup and utilized, which will lead to faster response times, and improve the protection of the off-grid system.
Index Terms—Extended Reality (XR), solar power generation, Supervisory and Data Acquisition (SADA)
Vision To Reality: Groundbreaking Impacts Of Artificial Intelligence On Key Performance Indicators In The Built Environment
Full text linkAs construction transitions into an era shaped by Industry 4.0 and data-driven decision-making, Artificial Intelligence (AI) emerges as a transformative tool with the potential to enhance key performance indicators (KPIs) such as schedule adherence, cost management, quality assurance, safety, resource allocation, and customer satisfaction. However, few studies have empirically assessed the direct influence of AI adoption on operational performance or examined the innovation diffusion factors that facilitate its integration. This gap underscores the need to align AI initiatives with broader organizational strategies, ensuring that technological adoption translates into measurable improvements in construction performance.
This quantitative study investigated two core research questions: (1) How does the level of AI adoption impact performance in construction? (2) How do diffusion-related factors, relative advantage, compatibility, complexity, trialability, and observability, influence AI adoption in construction firms? Data was collected using a structured survey of professionals across various construction industry sectors. The study assessed both measurement and structural models using Partial Least Squares Structural Equation Modeling (PLS-SEM).
The results showed that factors related to diffusion play a big role in how AI gets adopted, and that adopting AI had a strong and positive impact on performance. The model explained a great amount of variance in performance. The Diffusion of Innovation and Endogenous Growth theories help explain the role of internal support and stakeholder views on AI adoption on construction projects.
This research contributes to the growing body of literature on AI in the built environment, offering insights for industry leaders and policymakers seeking to harness AI’s potential for measurable performance gains. AI offers a strategic plan to align innovation with business goals for lasting results.
Keywords: artificial intelligence, construction technology, key performance indicators, Diffusion of Innovation, technology adoptio
Beyond Trauma: Understanding Resilience, Trauma, School Climate, Externalizing And, Internalizing Behaviors In Youth Expelled To Disciplinary Alternative Education Programs
No full textSchools often struggle to meet the needs of students experiencing mental health outcomes, which can lead to exclusionary discipline practices (Chafouleas, 2021; Johnson et al., 2021; Peguero et al., 2016; Zhou et al., 2023). Although a substantial number of students face disproportionate removal from school due to externalized behaviors (U.S. Commission on Civil Rights, 2019), one aspect of exclusionary discipline, namely disciplinary alternative school education programs (DAEPs), has received limited attention in research (Bender et al., 2016; Pierce et al., 2021; Tajalli et al., 2014). It is critical to thoroughly assess DAEPs because there is concern that these practices may exacerbate mental health outcomes for racially and ethnically minoritized youth (Johnson et al., 2021; Panuccio et al., 2022; Scully et al., 2019).
This study employed a moderated mediation analysis involving 151 racially and ethnically marginalized youth enrolled in a DAEP to assess the association between trauma, that is, posttraumatic stress symptoms, resilience, school climate, and externalizing and internalizing behaviors. Participants\u27 ages ranged from 11 to 17 years.
The sample consisted of 101 males and 51 females. Results revealed that posttraumatic stress symptoms had a significant association with both internalizing and externalizing behaviors, with resilience partially mediating these relationships. School climate did not significantly moderate the indirect effect of resilience, though the indirect effect was significant across all levels of school climate. These findings underscore the importance of resilience in mitigating adverse mental health outcomes and highlight the need for trauma-informed interventions within DAEPs.
Keywords: posttraumatic stress symptoms, resilience, school climate, exclusionary discipline, disciplinary alternative education programs, internalizing behaviors, externalizing behaviors, racially and ethnically marginalized youth, trauma-informed intervention