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Articles 31 - 60 of 113
Full-Text Articles in Engineering
Decision Making For Improving Maritime Traffic Safety Using Constraint Programming, Saumya Bhatnagar, Akshat Kumar, Hoong Chuin Lau
Decision Making For Improving Maritime Traffic Safety Using Constraint Programming, Saumya Bhatnagar, Akshat Kumar, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Maritime navigational safety is of utmost importance to prevent vessel collisions in heavily trafficked ports, and avoid environmental costs. In case of a likely near miss among vessels, port traffic controllers provide assistance for safely navigating the waters, often at very short lead times. A better strategy is to avoid such situations from even happening. To achieve this, we a) formalize the decision model for traffic hotspot mitigation including realistic maritime navigational features and constraints through consultations with domain experts; and b) develop a constraint programming based scheduling approach to mitigate hotspots. We model the problem as a variant of …
A Framework Of Integrating Manufacturing Plants In Smart Grid Operation: Manufacturing Flexible Load Identification, Md. Monirul Islam, Zeyi Sun, Wenqing Hu, Cihan H. Dagli
A Framework Of Integrating Manufacturing Plants In Smart Grid Operation: Manufacturing Flexible Load Identification, Md. Monirul Islam, Zeyi Sun, Wenqing Hu, Cihan H. Dagli
Engineering Management and Systems Engineering Faculty Research & Creative Works
In the deregulated electricity markets run by Independent System Operator (ISO), a two-settlement (day-ahead and real-time) process is typically used to determine the electricity price to the end-use customers at different buses. In the day-ahead settlement, the demand is predicted at each bus based on the previous consumption behavior of the consumers and thus, Locational Marginal Price (LMP) can be determined and shared to the consumers. A significant gap is usually observed between the planned and real-time demands due to the uncertainties of the weather (temperature, wind-speed etc.), the intensity of business, and everyday activities. Therefore, a large price variation …
Improving Law Enforcement Daily Deployment Through Machine Learning-Informed Optimization Under Uncertainty, Jonathan David Chase, Duc Thien Nguyen, Haiyang Sun, Hoong Chuin Lau
Improving Law Enforcement Daily Deployment Through Machine Learning-Informed Optimization Under Uncertainty, Jonathan David Chase, Duc Thien Nguyen, Haiyang Sun, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Urban law enforcement agencies are under great pressure to respond to emergency incidents effectively while operating within restricted budgets. Minutes saved on emergency response times can save lives and catch criminals, and a responsive police force can deter crime and bring peace of mind to citizens. To efficiently minimize the response times of a law enforcement agency operating in a dense urban environment with limited manpower, we consider in this paper the problem of optimizing the spatial and temporal deployment of law enforcement agents to predefined patrol regions in a real-world scenario informed by machine learning. To this end, we …
Data-Driven Surgical Duration Prediction Model For Surgery Scheduling: A Case-Study For A Practice-Feasible Model In A Public Hospital, Kar Way Tan, Francis Ngoc Hoang Long Nguyen, Boon Yew Ang, Jerald Gan, Sean Shao Wei Lam
Data-Driven Surgical Duration Prediction Model For Surgery Scheduling: A Case-Study For A Practice-Feasible Model In A Public Hospital, Kar Way Tan, Francis Ngoc Hoang Long Nguyen, Boon Yew Ang, Jerald Gan, Sean Shao Wei Lam
Research Collection School Of Computing and Information Systems
Hospitals have been trying to improve the utilization of operating rooms as it affects patient satisfaction, surgery throughput, revenues and costs. Surgical prediction model which uses post-surgery data often requires high-dimensional data and contains key predictors such as surgical team factors which may not be available during the surgical listing process. Our study considers a two-step data-mining model which provides a practical, feasible and parsimonious surgical duration prediction. Our model first leverages on domain knowledge to provide estimate of the first surgeon rank (a key predicting attribute) which is unavailable during the listing process, then uses this predicted attribute and …
Simulated Annealing For The Multi-Vehicle Cyclic Inventory Routing Problem, Aldy Gunawan, Vincent F. Yu, Audrey Tedja Widjaja, Pieter Vansteenwegen
Simulated Annealing For The Multi-Vehicle Cyclic Inventory Routing Problem, Aldy Gunawan, Vincent F. Yu, Audrey Tedja Widjaja, Pieter Vansteenwegen
Research Collection School Of Computing and Information Systems
This paper studies the Multi-Vehicle Cyclic Inventory Routing Problem (MV-CIRP) as the extension of the Single-Vehicle CIRP (SV-CIRP). The objective is to minimize both distribution and inventory costs at the customers and to maximize the collected rewards simultaneously. The problem is treated as a single objective optimization problem. A subset of customers is selected for each vehicle including the quantity to be delivered to each customer. For each vehicle, a cyclic distribution plan is developed. We construct a mathematical programming model and propose a simulated annealing (SA) metaheuristic for solving both SV-CIRP and MV-CIRP. For SV-CIRP, experimental results on benchmark …
Correlation-Sensitive Next-Basket Recommendation, Duc Trong Le, Hady Wirawan Lauw, Yuan Fang
Correlation-Sensitive Next-Basket Recommendation, Duc Trong Le, Hady Wirawan Lauw, Yuan Fang
Research Collection School Of Computing and Information Systems
Items adopted by a user over time are indicative ofthe underlying preferences. We are concerned withlearning such preferences from observed sequencesof adoptions for recommendation. As multipleitems are commonly adopted concurrently, e.g., abasket of grocery items or a sitting of media consumption, we deal with a sequence of baskets asinput, and seek to recommend the next basket. Intuitively, a basket tends to contain groups of relateditems that support particular needs. Instead of recommending items independently for the next basket, we hypothesize that incorporating informationon pairwise correlations among items would help toarrive at more coherent basket recommendations.Towards this objective, we develop a …
Joint Manufacturing And Onsite Microgrid System Control Using Markov Decision Process And Neural Network Integrated Reinforcement Learning, Wenqing Hu, Zeyi Sun, Y. Zhang, Y. Li
Joint Manufacturing And Onsite Microgrid System Control Using Markov Decision Process And Neural Network Integrated Reinforcement Learning, Wenqing Hu, Zeyi Sun, Y. Zhang, Y. Li
Mathematics and Statistics Faculty Research & Creative Works
Onsite microgrid generation systems with renewable sources are considered a promising complementary energy supply system for manufacturing plant, especially when outage occurs during which the energy supplied from the grid is not available. Compared to the widely recognized benefits in terms of the resilience improvement when it is used as a backup energy system, the operation along with the electricity grid to support the manufacturing operations in non-emergent mode has been less investigated. In this paper, we propose a joint dynamic decision-making model for the optimal control for both manufacturing system and onsite generation system. Markov Decision Process (MDP) is …
Mid To Late Season Weed Detection In Soybean Production Fields Using Unmanned Aerial Vehicle And Machine Learning, Arun Narenthiran Veeranampalayam Sivakumar
Mid To Late Season Weed Detection In Soybean Production Fields Using Unmanned Aerial Vehicle And Machine Learning, Arun Narenthiran Veeranampalayam Sivakumar
Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research
Mid-late season weeds are those that escape the early season herbicide applications and those that emerge late in the season. They might not affect the crop yield, but if uncontrolled, will produce a large number of seeds causing problems in the subsequent years. In this study, high-resolution aerial imagery of mid-season weeds in soybean fields was captured using an unmanned aerial vehicle (UAV) and the performance of two different automated weed detection approaches – patch-based classification and object detection was studied for site-specific weed management. For the patch-based classification approach, several conventional machine learning models on Haralick texture features were …
Keeping Humans In The Loop: Pooling Knowledge Through Artificial Swarm Intelligence To Improve Business Decision Making, Lynn E. Metcalf, David A. Askay, Louis B. Rosenberg
Keeping Humans In The Loop: Pooling Knowledge Through Artificial Swarm Intelligence To Improve Business Decision Making, Lynn E. Metcalf, David A. Askay, Louis B. Rosenberg
Industrial Technology and Packaging
This article explores how a collaboration technology called Artificial Swarm Intelligence (ASI) addresses the limitations associated with group decision making, amplifies the intelligence of human groups, and facilitates better business decisions. It demonstrates of how ASI has been used by businesses to harness the diverse perspectives that individual participants bring to groups and to facilitate convergence upon decisions. It advances the understanding of how artificial intelligence (AI) can be used to enhance, rather than replace, teams as they collaborate to make business decisions.
Factors Influencing Revenue Collection For Preventative Maintenance Of Community Water Systems: A Fuzzy-Set Qualitative Comparative Analysis, Liesbet Olaerts, Jeffrey P. Walters, Karl G. Linden, Amy Javernick-Will, Adam Harvey
Factors Influencing Revenue Collection For Preventative Maintenance Of Community Water Systems: A Fuzzy-Set Qualitative Comparative Analysis, Liesbet Olaerts, Jeffrey P. Walters, Karl G. Linden, Amy Javernick-Will, Adam Harvey
Faculty Publications - Biomedical, Mechanical, and Civil Engineering
This study analyzed combinations of conditions that influence regular payments for water service in resource-limited communities. To do so, the study investigated 16 communities participating in a new preventive maintenance program in the Kamuli District of Uganda under a public–private partnership framework. First, this study identified conditions posited as important for collective payment compliance from a literature review. Then, drawing from data included in a water source report and by conducting semi-structured interviews with households and water user committees (WUC), we identified communities that were compliant with, or suspended from, preventative maintenance service payments. Through qualitative analyses of these data …
Economic Model Predictive Control And Process Equipment: Control-Induced Thermal Stress In A Pipe, Helen Durand
Economic Model Predictive Control And Process Equipment: Control-Induced Thermal Stress In A Pipe, Helen Durand
Chemical Engineering and Materials Science Faculty Research Publications
Recent work on economic model predictive control (EMPC) has indicated that some processes may be operated in a more economically-optimal fashion under a time-varying operating policy than under a steady-state operating policy. However, a concern for time-varying operation is how such a change in operating policy might impact the equipment within which the processes being controlled are carried out. While under steady-state operation, the operating conditions to which equipment would regularly be exposed can be estimated, this would be more difficult to assess thoroughly a priori under time-varying operation. It could be explored whether the EMPC could be made aware …
Seven Hci Grand Challenges, Constantine Stephanidis, Gavriel Salvendy, Margherita Antona, Jessie Chen, Jianming Dong, Vincent Duffy, Xiaowen Fang, Cali Fidopiastis, Gino Fragomeni, Limin Fu, Yinni Guo, Don Harris, Andri Ioannou, Kyeong-Ah (Kate) Jeong, Shin'ichi Konomi, Heidi Kromker, Masaaki Kurosu, James Lewis, Aaron Marcus, Gabriele Meiselwitz, Abbas Moallem, Hirohiko Mori, Fiona Fui-Hoon Nah, Stavroula Ntoa, Pei-Luen Rau, Dylan Schmorrow, Keng Siau, Norbert Streitz, Wentao Wang, Sakae Yamamoto, Panayiotis Zaphiris, Jia Zhou
Seven Hci Grand Challenges, Constantine Stephanidis, Gavriel Salvendy, Margherita Antona, Jessie Chen, Jianming Dong, Vincent Duffy, Xiaowen Fang, Cali Fidopiastis, Gino Fragomeni, Limin Fu, Yinni Guo, Don Harris, Andri Ioannou, Kyeong-Ah (Kate) Jeong, Shin'ichi Konomi, Heidi Kromker, Masaaki Kurosu, James Lewis, Aaron Marcus, Gabriele Meiselwitz, Abbas Moallem, Hirohiko Mori, Fiona Fui-Hoon Nah, Stavroula Ntoa, Pei-Luen Rau, Dylan Schmorrow, Keng Siau, Norbert Streitz, Wentao Wang, Sakae Yamamoto, Panayiotis Zaphiris, Jia Zhou
Faculty Publications
This article aims to investigate the Grand Challenges which arise in the current and emerging landscape of rapid technological evolution towards more intelligent interactive technologies, coupled with increased and widened societal needs, as well as individual and collective expectations that HCI, as a discipline, is called upon to address. A perspective oriented to humane and social values is adopted, formulating the challenges in terms of the impact of emerging intelligent interactive technologies on human life both at the individual and societal levels. Seven Grand Challenges are identified and presented in this article: Human-Technology Symbiosis; Human-Environment Interactions; Ethics, Privacy and Security; …
Maquiladoras In Central America: An Analysis Of Workforce Schedule, Productivity And Fatigue., Jose L. Barahona
Maquiladoras In Central America: An Analysis Of Workforce Schedule, Productivity And Fatigue., Jose L. Barahona
Masters Theses & Specialist Projects
Textile factories or Maquiladoras are very abundant and predominant in Central American economies. However, they all do not have the same standardized work schedule or routines. Most of the Maquiladoras only follow schedules and regulations established by the current labor laws without taking into consideration many variables within their organization that could affect their overall performance. As a result, the purpose of the study is to analyze the current working structure of a textile Maquiladora and determine the most suitable schedule that will abide with the current working structure but also increase production levels, employee morale and decrease employee fatigue. …
Model And Analysis Of Labor Supply For Ride-Sharing Platforms In The Presence Of Sample Self-Selection And Endogeneity, Hao Sun, Hai Wang, Zhixi Wan
Model And Analysis Of Labor Supply For Ride-Sharing Platforms In The Presence Of Sample Self-Selection And Endogeneity, Hao Sun, Hai Wang, Zhixi Wan
Research Collection School Of Computing and Information Systems
With the popularization of ride-sharing services, drivers working as freelancers on ride-sharing platforms can design their schedules flexibly. They make daily decisions regard- ing whether to participate in work, and if so, how many hours to work. Factors such as hourly income rate affect both the participation decision and working-hour decision, and evaluation of the impacts of hourly income rate on labor supply becomes important. In this paper, we propose an econometric framework with closed-form measures to estimate both the participation elasticity (i.e., extensive margin elasticity) and working-hour elasticity (i.e., intensive margin elasticity) of labor supply. We model the sample …
Entropy Based Independent Learning In Anonymous Multi-Agent Settings, Tanvi Verma, Pradeep Varakantham, Hoong Chuin Lau
Entropy Based Independent Learning In Anonymous Multi-Agent Settings, Tanvi Verma, Pradeep Varakantham, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Efficient sequential matching of supply and demand is a problem of interest in many online to offline services. For instance, Uber, Lyft, Grab for matching taxis to customers; Ubereats, Deliveroo, FoodPanda etc for matching restaurants to customers. In these online to offline service problems, individuals who are responsible for supply (e.g., taxi drivers, delivery bikes or delivery van drivers) earn more by being at the ”right” place at the ”right” time. We are interested in developing approaches that learn to guide individuals to be in the ”right” place at the ”right” time (to maximize revenue) in the presence of other …
Zac: A Zone Path Construction Approach For Effective Real-Time Ridesharing, Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet
Zac: A Zone Path Construction Approach For Effective Real-Time Ridesharing, Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet
Research Collection School Of Computing and Information Systems
Real-time ridesharing systems such as UberPool, Lyft Line, GrabShare have become hugely popular as they reduce the costs for customers, improve per trip revenue for drivers and reduce traffic on the roads by grouping customers with similar itineraries. The key challenge in these systems is to group the right requests to travel in available vehicles in real-time, so that the objective (e.g., requests served, revenue or delay) is optimized. The most relevant existing work has focussed on generating as many relevant feasible (with respect to available delay for customers) combinations of requests (referred to as trips) as possible in real-time. …
Zinc Ferrite Based Gas Sensors: A Review, Kaidi Wu, Jianzhi Li, Chao Zhang
Zinc Ferrite Based Gas Sensors: A Review, Kaidi Wu, Jianzhi Li, Chao Zhang
Manufacturing & Industrial Engineering Faculty Publications and Presentations
Flammable, explosive and toxic gases, such as hydrogen, hydrogen sulfide and volatile organic compounds vapor, are major threats to the ecological environment safety and human health. Among the available technologies, gas sensing is a vital component, and has been widely studied in literature for early detection and warning. As a metal oxide semiconductor, zinc ferrite (ZnFe2O4) represents a kind of promising gas sensing material with a spinel structure, which also shows a fine gas sensing performance to reducing gases. Due to its great potentials and widespread applications, this article is intended to provide a review on the latest development in …
Amplifying The Collective Intelligence Of Teams With Swarm Ai, David Askay, Lynn E. Metcalf, Louis B. Rosenberg, Gregg Willcox, David Baltaxe
Amplifying The Collective Intelligence Of Teams With Swarm Ai, David Askay, Lynn E. Metcalf, Louis B. Rosenberg, Gregg Willcox, David Baltaxe
Industrial Technology and Packaging
Group decision-making is strengthened by the varied knowledge and perspectives that each member brings, yet teams often fail to capitalize on their diversity. This paper describes how Swarm AI, a novel collaborative intelligence technology modeled on the decision-making process of honey bee swarms, enables networked human groups to more effectively leverage their combined insights. Through an empirical study conducted on 60 small teams, each of 3 to 6 members, we demonstrate the capacity of Swarm AI to significantly amplify the collective intelligence of human groups. A well-known testing instrument—the Reading the Mind in the Eyes (RME) test —was used to …
”Cyberworld” As A Theme For A University-Wide First-Year Common Course, Kristen Przyborski, Frank Breitinger, Lauren Beck, Ronald S. Harichandran
”Cyberworld” As A Theme For A University-Wide First-Year Common Course, Kristen Przyborski, Frank Breitinger, Lauren Beck, Ronald S. Harichandran
Engineering and Applied Science Education Faculty Publications
Nowadays we all live in a cyber world and use the internet for emailing, banking, streaming video, shopping, reading news, or other activities. Given all the time people spend online, it is important that all students (regardless of their major) learn some basics about living in a cyber world, e.g., strategies for online safety, impact of artificial intelligence, digital forensics or ancestry.com. To facilitate students from many majors to learn about important issues related to the internet, eight faculty from a variety of disciplines at the University of New Haven integrated the theme of Cyber World into our team-taught, first-year …
Eml Indices To Assess Student Learning Through Integrated E-Learning Modules, Ronald S. Harichandran, Nadiye O. Erdil, Maria-Isabel Carnasciali, Cheryl Q. Li, Aadityasinh Rana
Eml Indices To Assess Student Learning Through Integrated E-Learning Modules, Ronald S. Harichandran, Nadiye O. Erdil, Maria-Isabel Carnasciali, Cheryl Q. Li, Aadityasinh Rana
Engineering and Applied Science Education Faculty Publications
The University of New Haven has facilitated the development and integration of e-learning modules on entrepreneurial topics into regular engineering and computer science courses. In addition to faculty at the University of New Haven, over three years 77 faculty at 53 other universities in the US have also integrated these modules into their courses. Starting in fall 2017, rubrics were developed so that student work related to topics covered in the modules could be assessed directly by instructors. Topics covered by each module were also mapped to learning outcomes published in the KEEN Framework [1]. An Entrepreneurial Minded Learning (EML) …
Assessing The Growth In Entrepreneurial Mind-Set Acquired Through Curricular And Extra-Curricular Components, Cheryl Q. Li, Ronald S. Harichandran, Nadiye O. Erdil, Maria-Isabel Carnasciali, Jean Nocito-Gobel
Assessing The Growth In Entrepreneurial Mind-Set Acquired Through Curricular And Extra-Curricular Components, Cheryl Q. Li, Ronald S. Harichandran, Nadiye O. Erdil, Maria-Isabel Carnasciali, Jean Nocito-Gobel
Engineering and Applied Science Education Faculty Publications
In an effort to develop an entrepreneurial mindset in our engineering students, the University of New Haven has adopted both curricular and extra-curricular approaches. The curricular components include: 1. Several e-Learning modules covering specific entrepreneurial concepts integrated into the regular engineering and computer science curricula. Available online, each module contains readings, short videos, and self-assessment exercises. Students complete these self-paced modules outside of the classroom over a two-week period. Instructors normally engage students on the content of the module through online or in-class discussions and in-class contextual activities. 2. An elective course on business principles and entrepreneurship that incorporates four …
Assessing An Online Engineering Ethics Module From Experiential Learning Perspective, Gokhan Egilmez, Philip Viscomi, Maria-Isabel Carnasciali
Assessing An Online Engineering Ethics Module From Experiential Learning Perspective, Gokhan Egilmez, Philip Viscomi, Maria-Isabel Carnasciali
Engineering and Applied Science Education Faculty Publications
Today, engineers play a crucial role in the direction of technology, research, social wellbeing, and economic growth, thus the lives of people. An engineer’s professional responsibility for complying with ethical standards and conduct is essential to the needs and requirements of individuals, organizations, and the society. Educating the future engineering workforce and establishing effective and timely policies that ensure engineering professional’s compliance with requirements are two important pillars of sustaining the ethical knowledge and practice in engineering profession. In this study, the researchers focused on investigating the learning effectiveness of an online ethics module developed for and implemented in a …
An Exploratory Study Of Engineering Students’ Misconceptions About Technical Communication, Cheryl Q. Li, Judy Randi, Jenna Sheffield
An Exploratory Study Of Engineering Students’ Misconceptions About Technical Communication, Cheryl Q. Li, Judy Randi, Jenna Sheffield
Engineering and Applied Science Education Faculty Publications
This paper reports results of a mixed methods study that examined engineering students’ acquisition of technical communication skills over time. In particular, this exploratory study aimed to identify persistent errors, lingering misconceptions, and challenges engineering students faced when they attempted to apply their knowledge and skills in new contexts. The 12 participants were drawn from engineering courses in which students were required to compose technical memoranda in response to requests for information from supervisors or clients. This integrated approach addresses content and communication in the same course. The study included a longitudinal analysis of four technical memoranda written across two …
Motivating Students For Learning Using Scaffolding And A Variety Of Assignments, Nadiye O. Erdil
Motivating Students For Learning Using Scaffolding And A Variety Of Assignments, Nadiye O. Erdil
Engineering and Applied Science Education Faculty Publications
This paper discusses the impacts of various course assignments and activities that were used to increase student motivation and learning. The courses selected for the study are Quality Analysis and Design of Experiments courses, which are offered as required courses in the industrial engineering graduate program at the University of New Haven. The assignments and activities include term project, term paper, homework, in-class exercises, quizzes, exams, library training and factory visit. In an earlier pilot study in the Quality Analysis course, scaffolding -an instructional strategy that enables students to build on prior experience and knowledge as they work towards mastering …
Coordinating Supply And Demand On An On-Demand Service Platform With Impatient Customers, Jiaru Bai, Kut C. So, Christopher S. Tang, Xiqun Chen, Hai Wang
Coordinating Supply And Demand On An On-Demand Service Platform With Impatient Customers, Jiaru Bai, Kut C. So, Christopher S. Tang, Xiqun Chen, Hai Wang
Research Collection School Of Computing and Information Systems
We consider an on-demand service platform using earning sensitive independent providers with heterogeneous reservation price (for work participation) to serve its time and price sensitive customers with heterogeneous valuation of the service. As such, both the supply and demand are "endogenously'' dependent on the price the platform charges its customers and the wage the platform pays its independent providers. We present an analytical model with endogenous supply (number of participating agents) and endogenous demand (customer request rate) to study this on-demand service platform. To coordinate endogenous demand with endogenous supply, we include the steady-state waiting time performance based on a …
Geometric Top-K Processing: Updates Since Mdm'16 [Advanced Seminar], Kyriakos Mouratidis
Geometric Top-K Processing: Updates Since Mdm'16 [Advanced Seminar], Kyriakos Mouratidis
Research Collection School Of Computing and Information Systems
The top-k query has been studied extensively, and is considered the norm for multi-criteria decision making in large databases. In recent years, research has considered several complementary operators to the traditional top-k query, drawing inspiration (both in terms of problem formulation and solution design) from the geometric nature of the top-k processing model. In this seminar, we will present advances in that stream of work, focusing on updates since the preliminary seminar on the same topic in MDM'16.
Stress Shielding In Cemented Hip Implants Assessed From Computed Tomography, Bharadwaj Cheruvu, Indresh Venkatarayappa, Tarun Goswami
Stress Shielding In Cemented Hip Implants Assessed From Computed Tomography, Bharadwaj Cheruvu, Indresh Venkatarayappa, Tarun Goswami
Biomedical, Industrial & Human Factors Engineering Faculty Publications
Background: Aseptic loosening is the major cause of revisions for hip replacement. This mode of failure is often caused by stress shielding. Stress shielding in the femur occurs when some of the loads are taken by the prosthesis and shielded from going to the bone. There is little information regarding the stress shielding among cemented hip implants. Purpose: The purpose of this study is to investigate the effect of stress shielding on the proximal femur with a femoral prosthesis. Methods: A patient had undergone open reduction and internal fixation (ORIF) due to a comminuted reversed oblique fracture of the right …
Modeling The Economic Machine Using Bayesian Inference And Statistical Networks, And Optimal Portfolio Construction Using Operations Research, Richard Yang
ENGS 88 Honors Thesis (AB Students)
In this paper, we propose a network-based model to attempt to connect modern macroeconomic theory with real world economic observations and trends. We find that by extending macroeconomic theory with credit leveraging/deleveraging thresholds, we are able to explain economic cycles in addition to long-term growth. Furthermore, we specifically explore the growth-inflation view of the macro economy as a basis for optimal portfolio construction and efficient asset trading. Connecting our network-based macroeconomic model and our optimal portfolio construction algorithm, we create a novel macroeconomic asset-trading framework.
Bmap/G/C Queueing Model With Group Clearance Useful In Telecommunications Systems – A Simulation Approach, Srinivas Chakravarthy, Alexander Rumyantsev
Bmap/G/C Queueing Model With Group Clearance Useful In Telecommunications Systems – A Simulation Approach, Srinivas Chakravarthy, Alexander Rumyantsev
Industrial & Manufacturing Engineering Publications
Queueing models in which customers or messages arrive in batches with inter-arrival times of batches possibly correlated and services rendered in batches of varying sizes play an important role in telecommunication systems. Recently queueing models of BMAP/G/1-type in which a new type of group clearance was studied using embedded Markov renewal process as well as continuous time Markov chain whose generator has a very special structure. In this paper, we generalize these models to multi-server systems through simulation approach. After validating the simulation model for the single server case, we report our simulated results for much more general situations.
Vision Sensor Based Action Recognition For Improving Efficiency And Quality Under The Environment Of Industry 4.0, Zipeng Wang, Ruwen Qin, Jihong Yan, Chaozhong Guo
Vision Sensor Based Action Recognition For Improving Efficiency And Quality Under The Environment Of Industry 4.0, Zipeng Wang, Ruwen Qin, Jihong Yan, Chaozhong Guo
Engineering Management and Systems Engineering Faculty Research & Creative Works
In the environment of industry 4.0, human beings are still an important influencing factor of efficiency and quality which are the core of product life cycle management. Hence, monitoring and analyzing humans' actions are essential. This paper proposes a vision sensor based method to evaluate the accuracy of operators' actions. Each action of operators is recognized in real time by a Convolutional Neural Network (CNN) based classification model in which hierarchical clustering is introduced to minimize the effects of action uncertainty. Warnings are triggered when incorrect actions occur in real time and applications of action analysis of workers on a …