Identifying Key Factors Of Rail Transit Service Quality: An Empirical Analysis For Istanbul, 2017 Istanbul Technical University
Identifying Key Factors Of Rail Transit Service Quality: An Empirical Analysis For Istanbul, Erkan Isikli, Nezir Aydin, Erkan Celik, Alev Taskin Gumus
Journal of Public Transportation
Providing a high quality of service in public transportation is essential to reduce dissatisfactions stemming from traffic congestion and noise. Public transport providers need to find ways to dilute the effects of immoderate use of private cars in big cities while maintaining a sufficient level of customer satisfaction. This study aimed to identify the key service quality (SQ) factors that drive passenger satisfaction in Istanbul’s rail transit (RT) system using data obtained from an extensive survey conducted by the Istanbul Public Transportation Co. A total of 11,116 passengers who used rail transport from May 15–June 3, 2012 ...
Analysis Of Food Hub Commerce And Participation Using Agent-Based Modeling: Integrating Financial And Social Drivers, Caroline C. Krejci, Richard Stone, Michael Dorneich, Stephen B. Gilbert
Stephen B. Gilbert
Objective: Factors influencing long-term viability of an intermediated regional food supply network (food hub) were modeled using agent-based modeling techniques informed by interview data gathered from food hub participants.
Background: Previous analyses of food hub dynamics focused primarily on financial drivers rather than social factors and have not used mathematical models.
Method: Based on qualitative and quantitative data gathered from 22 customers and 11 vendors at a midwestern food hub, an agent-based model (ABM) was created with distinct consumer personas characterizing the range of consumer priorities. A comparison study determined if the ABM behaved differently than a model based on ...
Characteristics Of A Multi-User Tutoring Architecture, 2017 Iowa State University
Characteristics Of A Multi-User Tutoring Architecture, Stephen B. Gilbert, Eliot H. Winer, Joseph Holub, Trevor Richardson, Michael C. Dorneich, Michael Hoffman
Stephen B. Gilbert
Intelligent tutor systems have been quite successful in instruction of individuals (Koedinger, Anderson, Hadley, & Mark, 1997; Ritter, Kulikowich, Lei, McGuire, & Morgan, 2007; Vanlehn, et al., 2005), but multiple challenges exist when attempting to tutor a team. Sottilare, Holden, Brawner, and Goldberg (2011) describe some of the architectural challenges of team tutoring at a high level in terms of functional requirements. In this paper we describe specific challenges in terms of implementing a team architecture within the Generalized Intelligent Framework for Tutoring (GIFT), including simultaneous startup and synchronization with distributed team members, maintaining state of multiple users, and timing feedback for teams and individuals appropriately.
Incorporation Of Future Building Operating Conditions Into The Modeling Of Building–Microclimate Interaction: A Feasibility Approach, Kelly Kalvelage, Ulrike Passe, Caroline Krejci, Michael C. Dorneich
Caroline C. Krejci
This paper presents a novel modeling methodology that integrates the near building environmental conditions (or microclimate), whole-building design, and occupant behavior. Accurate predictions of the future building operating conditions lead to designs that serve the building’s purpose – to support occupants’ tasks. This study bridges the gap between human factors and architecture to include physical, cognitive, and organizational systems into building information modeling using future typical meteorological year climate data, canyon air temperature microclimate model, and a whole-building energy simulation to investigate the impact of future microclimate conditions on a “typical” single-occupant office. Additionally, to capture the effects of building ...
An Improved Convergence Analysis Of Cyclic Block Coordinate Descent-Type Methods For Strongly Convex Minimization, 2017 University of Minnesota - Twin Cities
An Improved Convergence Analysis Of Cyclic Block Coordinate Descent-Type Methods For Strongly Convex Minimization, Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Mingyi Hong
The cyclic block coordinate descent-type (CBCD-type) methods have shown remarkable computational performance for solving strongly convex minimization problems. Typical applications include many popular statistical machine learning methods such as elastic-net regression, ridge penalized logistic regression, and sparse additive regression. Existing optimization literature has shown that the CBCD-type methods attain iteration complexity of O(p · log(1/e)), where e is a pre-specified accuracy of the objective value, and p is the number of blocks. However, such iteration complexity explicitly depends on p, and therefore is at least p times worse than those of gradient descent methods. To bridge this theoretical ...
Quantized Consensus Admm For Multi-Agent Distributed Optimization, 2017 Syracuse University
Quantized Consensus Admm For Multi-Agent Distributed Optimization, Shengyu Zhu, Mingyi Hong, Biao Chen
Abstract: This paper considers multi-agent distributed optimization with quantized communication which is needed when inter-agent communications are subject to finite capacity and other practical constraints. To minimize the global objective formed by a sum of local convex functions, we develop a quantized distributed algorithm based on the alternating direction method of multipliers (ADMM). Under certain convexity assumptions, it is shown that the proposed algorithm converges to a consensus within log1+η Ω iterations, where η > 0 depends on the network topology and the local objectives, and O is a polynomial fraction depending on the quantization resolution, the distance between initial ...
Convergence Analysis Of Alternating Direction Method Of Multipliers For A Family Of Nonconvex Problems, 2017 Iowa State University
Convergence Analysis Of Alternating Direction Method Of Multipliers For A Family Of Nonconvex Problems, Mingyi Hong, Zhi-Quan Luo, Mesiam Razaviyayn
The alternating direction method of multipliers (ADMM) is widely used to solve large-scale linearly constrained optimization problems, convex or nonconvex, in many engineering fields. However there is a general lack of theoretical understanding of the algorithm when the objective function is nonconvex. In this paper we analyze the convergence of the ADMM for solving certain nonconvex consensus and sharing problems. We show that the classical ADMM converges to the set of stationary solutions, provided that the penalty parameter in the augmented Lagrangian is chosen to be sufficiently large. For the sharing problems, we show that the ADMM is convergent regardless ...
Nestt: A Nonconvex Primal-Dual Splitting Method For Distributed And Stochastic Optimization, 2017 Iowa State University
Nestt: A Nonconvex Primal-Dual Splitting Method For Distributed And Stochastic Optimization, Davood Hajinezhad, Mingyi Hong, Tuo Zhao, Zhaoran Wang
We study a stochastic and distributed algorithm for nonconvex problems whose objective consists a sum N/ nonconvex Li/N/ smooth functions, plus a nonsmooth regularizer. The proposed NonconvEx primal-dual SpliTTing (NESTT) algorithm splits the problem into N/ subproblems, and utilizes an augmented Lagrangian based primal-dual scheme to solve it in a distributed and stochastic manner. With a special non-uniform sampling, a version of NESTT achieves e-1 stationary solution using...gradient evaluations, which can be up to O(N)/ times better than the (proximal) gradient descent methods. It also achieves Q-linear convergence rate for nonconvex l1 penalized quadratic problems with polyhedral ...
Alternating Direction Method Of Multipliers For Penalized Zero-Variance Discriminant Analysis, 2017 University of Alabama - Tuscaloosa
Alternating Direction Method Of Multipliers For Penalized Zero-Variance Discriminant Analysis, Brendan P.W. Ames, Mingyi Hong
We consider the task of classification in the high dimensional setting where the number of features of the given data is significantly greater than the number of observations. To accomplish this task, we propose a heuristic, called sparse zero-variance discriminant analysis, for simultaneously performing linear discriminant analysis and feature selection on high dimensional data. This method combines classical zero-variance discriminant analysis, where discriminant vectors are identified in the null space of the sample within-class covariance matrix, with penalization applied to induce sparse structures in the resulting vectors. To approximately solve the resulting nonconvex problem, we develop a simple algorithm based ...
Sample Approximation-Based Deflation Approaches For Chance Sinr-Constrained Joint Power And Admission Control, 2017 Chinese Academy of Sciences
Sample Approximation-Based Deflation Approaches For Chance Sinr-Constrained Joint Power And Admission Control, Ya-Feng Liu, Mingyi Hong, Enbin Song
Consider the joint power and admission control (JPAC) problem for a multiuser single-input single-output (SISO) interference channel. Most existing works on JPAC assume the perfect instantaneous channel state information (CSI). In this paper, we consider the JPAC problem with the imperfect CSI, i.e., we assume that only the channel distribution information (CDI) is available. We formulate the JPAC problem into a chance (probabilistic)-constrained program, where each link's SINR outage probability is enforced to be less than or equal to a specified tolerance. To circumvent the computational difficulty of the chance SINR constraints, we propose to use the ...
Asynchronous Distributed Admm For Large-Scale Optimization—Part Ii: Linear Convergence Analysis And Numerical Performance, 2017 The Chinese University of Hong Kong
Asynchronous Distributed Admm For Large-Scale Optimization—Part Ii: Linear Convergence Analysis And Numerical Performance, Tsung-Hui Chang, Wei-Cheng Lao, Mingyi Hong, Xiangfeng Wang
The alternating direction method of multipliers (ADMM) has been recognized as a versatile approach for solving modern large-scale machine learning and signal processing problems efficiently. When the data size and/or the problem dimension is large, a distributed version of ADMM can be used, which is capable of distributing the computation load and the data set to a network of computing nodes. Unfortunately, a direct synchronous implementation of such algorithm does not scale well with the problem size, as the algorithm speed is limited by the slowest computing nodes. To address this issue, in a companion paper, we have proposed ...
Joint Downlink Base Station Association And Power Control For Max-Min Fairness: Computation And Complexity, 2017 Southeast University
Joint Downlink Base Station Association And Power Control For Max-Min Fairness: Computation And Complexity, Qingjiang Shi, Mingyi Hong, Xiqi Gao, Enbin Song, Yunlong Cai, Weiqiang Xu
The performance of full-duplex (FD) relay systems can be greatly impacted by the self-interference (SI) at relays. By exploiting multiple antennas, the spectral efficiency of FD relay systems can be enhanced through spatial SI mitigation. This paper studies joint source transmit beamforming and relay processing to achieve rate maximization for FD multiple-input-multiple-output (MIMO) amplify-and-forward (AF) relay systems with consideration of relay processing delay. The problem is difficult to solve mainly due to the SI constraint induced by the relay processing delay. In this paper, we first present a sufficient condition under which the relay amplification matrix has rank-one structure. Then ...
Decomposition By Successive Convex Approximation: A Unifying Approach For Linear Transceiver Design In Heterogeneous Networks, Mingyi Hong, Qiang Li, Ya-Feng Liu
No abstract provided.
Sinr Constrained Beamforming For A Mimo Multi-User Downlink System: Algorithms And Convergence Analysis, 2017 Zhejiang University
Sinr Constrained Beamforming For A Mimo Multi-User Downlink System: Algorithms And Convergence Analysis, Oingjang Shi, Meisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo
Consider a multiple-input multiple-output (MIMO) downlink multi-user channel. A well-studied problem in such a system is the design of linear beamformers for power minimization with the quality of service (QoS) constraints. The most representative algorithms for solving this class of problems are the so-called minimum mean square error (MMSE)-second-order cone programming (SOCP) algorithm [Visotksy and Madhow, “Optimum Beamforming Using Transmit Antenna Arrays,” Proc. IEEE Veh. Technol. Conf., May 1999, vol. 1, pp. 851-856] , [Wong, Zheng, and Ng, “Convergence Analysis of Downlink MIMO Antenna System Using Second-Order Cone Programming,” Proc. 62nd IEEE Veh. Technol. Conf., Sep. 2005, pp. 492-496] and ...
Asynchronous Distributed Admm For Large-Scale Optimization—Part I: Algorithm And Convergence Analysis, 2017 The Chinese University of Hong Kong
Asynchronous Distributed Admm For Large-Scale Optimization—Part I: Algorithm And Convergence Analysis, Tsung-Hui Chang, Mingyi Hong, Wei-Cheng Liao, Xiangfeng Wang
Aiming at solving large-scale optimization problems, this paper studies distributed optimization methods based on the alternating direction method of multipliers (ADMM). By formulating the optimization problem as a consensus problem, the ADMM can be used to solve the consensus problem in a fully parallel fashion over a computer network with a star topology. However, traditional synchronized computation does not scale well with the problem size, as the speed of the algorithm is limited by the slowest workers. This is particularly true in a heterogeneous network where the computing nodes experience different computation and communication delays. In this paper, we propose ...
A Unified Algorithmic Framework For Block-Structured Optimization Involving Big Data: With Applications In Machine Learning And Signal Processing, Mingyi Hong, Meisam Razaviyayn, Zhi-Quan Luo
This article presents a powerful algorithmic framework for big data optimization, called the block successive upper-bound minimization (BSUM). The BSUM includes as special cases many well-known methods for analyzing massive data sets, such as the block coordinate descent (BCD) method, the convex-concave procedure (CCCP) method, the block coordinate proximal gradient (BCPG) method, the nonnegative matrix factorization (NMF) method, the expectation maximization (EM) method, etc. In this article, various features and properties of the BSUM are discussed from the viewpoint of design flexibility, computational efficiency, parallel/distributed implementation, and the required communication overhead. Illustrative examples from networking, signal processing, and machine ...
Community-Engaged Operations Research: Trends, New Frontiers And Opportunities, 2017 University of Massachusetts - Boston
Community-Engaged Operations Research: Trends, New Frontiers And Opportunities, Michael P. Johnson Jr.
Michael P. Johnson
Visual Inspection Of Casting Surfaces, 2017 Iowa State University
Visual Inspection Of Casting Surfaces, Frank E. Peters, Richard T. Stone, Kristopher Patrick Watts, Peihan Zhong, Alexander John Clemons
Richard T. Stone
Visual inspection of casting surfaces is a critical processing step in the metalcasting process. Measurement error can be significant, causing overprocessing or poor quality received by the customer. Many factors affect the human operator's ability to effectively inspect castings. Cognitive ability is one such factor, which can be identified through a simple test. Rastering training was shown to improve the percentage of casting surface which gets inspected. Discrimination between acceptable and unacceptable surfaces continues to be problematic.
Virtual Reality Integrated Welder Training, 2017 Iowa State University
Virtual Reality Integrated Welder Training, Richard T. Stone, Kristopher Patrick Watts, Peihan Zhong
Richard T. Stone
Training in the welding industry is a critical and often costly endeavor; this study examines the training potential, team learning, material consumption, and cost implications of using integrated virtual reality technology as a major part of welder training. In this study, 22 participants were trained using one of two separate methods (traditional training (TT) and virtual reality integrated training (VRI)). The results demonstrated that students trained using 50% virtual reality had training outcomes that surpassed those of traditionally trained students across four distinctive weld qualifications (2F, 1G, 3F, 3G). In addition, the VRI group demonstrated significantly higher levels of team ...
Advances In Composite Manufacturing Of Helicopter Parts, 2017 Embry-Riddle Aeronautical University
Advances In Composite Manufacturing Of Helicopter Parts, Tobias A. Weber, Hans-Joachim K. Ruff-Stahl
International Journal of Aviation, Aeronautics, and Aerospace
This study investigates and compares different methods for improving standard autoclave composite manufacturing in order to find suitable approaches to a more efficient composite production. The goal is not only a reduction in manufacturing times and costs but also quality enhancement. Improved part quality while decreasing costs enables a manufacturer of composite parts to expand its market share, especially in the helicopter market, which has been constantly shrinking over the last two years. Various approaches such as improved tooling technology, the use of automated systems for lamination as well as outsourcing are examined to provide an overview of possible advancements ...