Speaker: Oluwaseun (Francis) Lijoka
Date: May 21, 2021 (Friday)
Time: 11:00 AM
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Meeting ID: 957 6929 8984
Title: Capacity Provisioning on Dynamic Path Network
Abstract: The aim of the talk is to introduce the problem of allocating capacities to edges of a dynamic path network with n vertices, in such a way that the evacuation completion time towards a single sink node (minmax criterion) is minimized. Our algorithm determines the optimal assignment of capacities to all edges of the network from a given total budget under the assumption that the location of the sink is known. In perspective with other evacuation and sink location problems, our model is suitable for planning the evacuation of remote and sparsely populated areas. Uncovered properties and vital data structures will be discussed.
Everyone is welcome.
Bio: Francis is a PhD student in the Optimization Research Group in our department. We all know Francis, don’t we?
Speaker: Dr. Vijay Mago
Title: Social science to artificial intelligence and beyond – a journey
Date: Thr, May 30, 2019
Time: 1:00 pm – 1:50 pm
Abstract: As researchers in computer science, we always face a challenge when people ask about the application of our research; policy makers talk about how computer science can help them predict the impact of policies - knowledge translation for practitioners, and as theoretical scientists, we want to improve the existing algorithm or develop new ones - incremental research. The focus of this talk is to present the recent works at DataLAB at the Lakehead University, where we have applied our research outcomes to – a) support the student mobility between colleges and universities, b) develop law cases repository c) understand the contributory factors of success for transfer students, d) build artificial intelligent facilitator for conceptual map building, e) present a simulation framework to test the policies for homeless in Montreal, f) design a new algorithm for semantic analysis, g) design an improved algorithm to automate essay evaluation, and finally h) a mechanism to host big data on High Performance computing for near real-time searching and querying.
Biography: Vijay Mago received the Ph.D. degree in computer science from Panjab University, India, in 2010. In 2011, he joined the Modelling of Complex Social Systems Program at the IRMACS Centre of Simon Fraser University. He is currently an Associate Professor with the Department of Computer Science, Lakehead University, Thunder Bay, ON, Canada, where he teaches and conducts research in areas, including big data analytics, machine learning, natural language processing, artificial intelligence, medical decision making, and Bayesian intelligence. He has served on the program committees of many international conferences and workshops. In 2017, he joined Technical Investment Strategy Advisory Committee Meeting for Compute Ontario. He has published extensively (more than 50 peer reviewed articles) on new methodologies based on soft computing and artificial intelligence techniques to tackle complex systemic problems, such as homelessness, obesity, and crime. He currently serves as an Associate Editor for IEEE Access and BMC Medical Informatics and Decision Making and as a Co-Editor for the Journal of Intelligent Systems.
Speaker: Dr Fatih Celik.
Title: Behavior of honeybees foraging for nectar and a large scale routing protocol implementation in wireless sensor networks
Date: Wed, Oct 17, 2018
Time: 12:00 – 12:50 pm.
Insect colonies are an attractive research topic for the researcher in electrical engineering and computer science who develops and designs shortest path algorithms. Bees use energy very efficiently and have the ability to find shortest routes to their source of food. Wireless sensor networks have similarities with honeybee colonies in terms of finding shortest paths for communication and consuming energy efficiently. In this presentation, we focus on an optimal method based on swarm intelligence (SI) inspired by honeybees and the behavior of honeybee foraging for nectar. Also, we analyze a routing protocol implementation in wireless sensor networks.
Fatih Celik received his Ph.D. in Electronics and Computer Science from the University of Sakarya, Turkey. He was an Assistant Professor at Sakarya University and a visiting scholar at University of Pittsburgh, USA. His research interests include parallel and distributed simulation, modeling and simulation of large-scale networks, biologically-inspired optimization schemes, cognitive radio networks, mobile ad hoc networks and wireless sensor networks. His main research interest lies in parallel and distributed simulation and routing protocols for the wireless sensor network.
Title: Parameterized Query Complexity of Quantum Computation
Speaker: Parijat Purohit, MSc candidate, Optimization Research Group
Abstract: Our proposal is to analyze the query complexity of a problem as a function of some parameter. This extends the parameterized complexity studies in the classical setting. We illustrate the applicability of this methodology on two seemingly unrelated problems. We parameterize the degree of imbalance for an arbitrary function whether it is balanced or not. We consider the same parameterization for the self-duality of a function.
Joint work with Saurya Das (Physics), Daya Gaur, Shahadat Hossain, and Robert Benkoczi.
Work accepted for presentation as a poster at the 20th Annual Conference on Quantum Information Processing, Seattle, WA.
Title: Algorithms for Barrier Coverage with Wireless Sensors
Speaker: Dr. Xiao Zhang, City University of Hong-Kong
Abstract: Barrier coverage is a critical problem in wireless sensor networks. In the area, we study the barrier coverage problem from two perspectives, i.e., static sensors with adjustable sensing ranges and mobile sensors with fixed sensing ranges. Specifically, in the first topic, we consider the barrier coverage problem for a line interval, in which we are given a set of sensors and the goal is to determine a range assignment with the lowest possible cost. In the second topic, we consider the problem of covering a line interval by mobile sensors such that the maximum of moving cost is minimized.
Bio: Xiao Zhang received his PhD degree from Department of Computer Science in City University of Hong Kong, Hong Kong, 2016. He was a visiting scholar with the Department of Computer Science in Utah State University, Logan, Utah, USA, in 2015. His research interests include algorithms design and analysis, wireless sensor networks.
Title: Local Search Algorithms for Data Placement Problem
Speaker: Anamay Sarkar, NIT Rourkela, MITACS Globalink Fellow in the Optimization Research Group
Abstract: I will talk about Local Search based Approximation Algorithms for the data placement problem. One of the local search operators is based on the assignment problem and the second one is based on the operators for the Un-capacitated facility location problem. I will report some experimental results on the data set obtained from the OR library. This work was done as part of Mitacs Globalink internship.
Bio: Anamay Sarkar is pursuing B. Tech in Computer Science and Engineering and is currently in his final year at NIT Rourkela. His past internship was at “IIT Delhi” in the area of Approximation Algorithms under Prof Naveen Garg. He is currently the branch topper after 3rd year.
Title: A Comparison of Rotation Parameterisations for Bundle Adjustment.
Speaker: Nurgul Aimati, MSc candidate, UofL Optimization Research Group.
Time & Location: Wednesday, March 23, 2016 in room D633
Bundle Adjustment is an iterative process where 3D information is estimated from 2D image measurements. Typically, the position of object points are estimated simultaneously with the position and orientation of the cameras. While the object points and camera positions have a straightforward “natural” parameterisation, several possibilities exist for the rotation. In this thesis, seven parameterisation of the rotation were investigated; Euler angles (two variants), the Rodriguez representation, the axis-and-angle representation, unit quaternions, and two variants of the direction cosine matrix (DCM).
Title: Cellular Automaton Based Algorithms in Wireless Communication
Speaker: Dr. Salimur Choudhury, Mathematics and Computer Science, Algoma University, Sault Ste. Marie, ON
Location and time: 1 pm, Room B756
Abstract: The cellular automaton is a bioinspired model used to model different physical systems including wireless communication. One of the main advantages of using cellular automaton based algorithms is that they need very little local information to compute a solution. In this talk, several optimization problems in wireless sensor networks and RFID (radio frequency identification) networks along with the corresponding cellular automaton based algorithms will be presented. The problems include sleep-awake scheduling of sensors, mobile sensors dispersion, and elimination of redundant readers in RFID system.
Bio: Dr. Salimur Choudhury is an assistant professor in the department of Mathematics and Computer Science at Algoma University, Sault Ste. Marie, ON. He is also an adjunct assistant professor in the school of computing at Queen’s University, Kingston, ON. His research interests include designing algorithms for wireless communication systems including sensor networks, RFID networks, device to device communication systems, etc. Dr. Choudhury completed PhD from School of Computing, Queen’s University in 2012 and Masters from the Department of Mathematics and Computer Science, University of Lethbridge in 2008. He has experience teaching at several other universities in USA and Bangladesh. He also worked at IBM Canada Software Lab in Markham, ON.
Title: Approximation Algorithms for Cumulative VRP with Stochastic Demands
Speaker: Rishi Ranjan Singh, Department of Information Technology, Indian Institute of Information Technology Allahabad (IIT – Allahabad), India.
Location and time: B716, Friday Feb 12, 9 am
Abstract: In this talk we describe randomized approximation algorithms for metric stochastic cumulative VRP for split and unsplit deliveries. The approximation ratios are \(2(1 + \alpha)\) and 7 respectively, where \(\alpha\) is the approximation ratio for the metric TSP. The approximation factor is further reduced for trees and paths. We use and extend the results in [Technical note - approximation algorithms for VRP with stochastic demands. Operations Research, 2012] and [Routing vehicles to minimize fuel consumption. Operations Research Letters, 2013].
This work, to appear in the proceedings of CALDAM 2016, is jointly with D.R. Gaur and A. Mudgal.
Bio: Mr. Singh is a Visiting Faculty in the Department of Information Technology at IIIT Allahabd, India. He submitted his PhD in the Department of Computer Science and Engineering at IIT Ropar, India in 2015. He received his B. Tech (Hons.) in Computer Science and Engineering from UPTU Lucknow, India in 2011. He is interested in approximation algorithms for vehicle routing problems, social and complex network analysis, discrete optimization.
Title: Evolutionary Algorithmic Deployment of Radio Beacons for Indoor Positioning
Speaker: Dr. Peter Chen, Memorial University of Newfoundland by video-conference.
Location and time: B716, Wednesday Dec 9, 12:30pm – 13:30pm.
In mobile computing, the location awareness of a mobile device or its user enables numerous personalized and social services such as recommendation of products and sharing current locations on social networks. Extending positioning services to indoor environments augments the value of the mobile communication market vastly. Due to serious signal attenuation, navigation satellite are incapable, and a common approach is to use or deploy small-scale radio frequency transmitters. When deploying these radio beacons, it is crucial to use a small number of them to provide high-quality positioning service. As this turns out a difficult optimization problem, the system administrators would benefit from have a spectrum of solutions with different tradeoffs between cost and quality. This talk provides an Evolutionary Algorithm (EA) framework to fulfill this need. Using a cost-quality adjustment parameter, he EA framework is able to provide a set of solution options to meet varying requirements balancing cost and quality. This property is resulted by the parallel population-based search of EAs, and can be very useful in real-world engineering applications.
Bio: Yuanzhu Chen is an Associate Professor in the Department of Computer Science, Memorial University of Newfoundland, St. John’s, Newfoundland. He received his Ph.D. from Simon Fraser University in 2004 and B.Sc. from Peking University in 1999, both in Computer Science. He was a Visiting Professor to Dartmouth College in 2011-2012. Between 2004 and 2005, he was a post-doctoral researcher at Simon Fraser University. His research interests include wireless networking, mobile computing, optimization of graph problems, and information retrieval.