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Articles 1 - 30 of 37
Full-Text Articles in Engineering
Optimal Collaborative Path Planning For Unmanned Surface Vehicles Carried By A Parent Boat Along A Planned Route, Ari Carisza Graha Prasetia, I-Lin Wang, Aldy Gunawan
Optimal Collaborative Path Planning For Unmanned Surface Vehicles Carried By A Parent Boat Along A Planned Route, Ari Carisza Graha Prasetia, I-Lin Wang, Aldy Gunawan
Research Collection School Of Computing and Information Systems
In this paper, an effective mechanism using a fleet of unmanned surface vehicles (USVs) carried by a parent boat (PB) is proposed to complete search or scientific tasks over multiple target water areas within a shorter time . Specifically, multiple USVs can be launched from the PB to conduct such operations simultaneously, and each USV can return to the PB for battery recharging or swapping and data collection in order to continue missions in a more extended range. The PB itself follows a planned route with a flexible schedule taking into consideration locational constraints or collision avoidance in a real-world …
Multi-User Verifiable Searchable Symmetric Encryption For Cloud Storage, Xueqiao Liu, Guomin Yang, Guomin Yang
Multi-User Verifiable Searchable Symmetric Encryption For Cloud Storage, Xueqiao Liu, Guomin Yang, Guomin Yang
Research Collection School Of Computing and Information Systems
In a cloud data storage system, symmetric key encryption is usually used to encrypt files due to its high efficiency. In order allow the untrusted/semi-trusted cloud storage server to perform searching over encrypted data while maintaining data confidentiality, searchable symmetric encryption (SSE) has been proposed. In a typical SSE scheme, a users stores encrypted files on a cloud storage server and later can retrieve the encrypted files containing specific keywords. The basic security requirement of SSE is that the cloud server learns no information about the files or the keywords during the searching process. Some SSE schemes also offer additional …
Online Traffic Signal Control Through Sample-Based Constrained Optimization, Srishti Dhamija, Alolika Gon, Pradeep Varakantham, William Yeoh
Online Traffic Signal Control Through Sample-Based Constrained Optimization, Srishti Dhamija, Alolika Gon, Pradeep Varakantham, William Yeoh
Research Collection School Of Computing and Information Systems
Traffic congestion reduces productivity of individuals by increasing time spent in traffic and also increases pollution. To reduce traffic congestion by better handling dynamic traffic patterns, recent work has focused on online traffic signal control. Typically, the objective in traffic signal control is to minimize expected delay over all vehicles given the uncertainty associated with the vehicle turn movements at intersections. In order to ensure responsiveness in decision making, a typical approach is to compute a schedule that minimizes the delay for the expected scenario of vehicle movements instead of minimizing expected delay over the feasible vehicle movement scenarios. Such …
Deep Reinforcement Learning Approach To Solve Dynamic Vehicle Routing Problem With Stochastic Customers, Waldy Joe, Hoong Chuin Lau
Deep Reinforcement Learning Approach To Solve Dynamic Vehicle Routing Problem With Stochastic Customers, Waldy Joe, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
In real-world urban logistics operations, changes to the routes and tasks occur in response to dynamic events. To ensure customers’ demands are met, planners need to make these changes quickly (sometimes instantaneously). This paper proposes the formulation of a dynamic vehicle routing problem with time windows and both known and stochastic customers as a route-based Markov Decision Process. We propose a solution approach that combines Deep Reinforcement Learning (specifically neural networks-based TemporalDifference learning with experience replay) to approximate the value function and a routing heuristic based on Simulated Annealing, called DRLSA. Our approach enables optimized re-routing decision to be generated …
Peer-Inspired Student Performance Prediction In Interactive Online Question Pools With Graph Neural Network, Haotian Li, Huan Wei, Yong Wang, Yangqiu Song, Huamin. Qu
Peer-Inspired Student Performance Prediction In Interactive Online Question Pools With Graph Neural Network, Haotian Li, Huan Wei, Yong Wang, Yangqiu Song, Huamin. Qu
Research Collection School Of Computing and Information Systems
Student performance prediction is critical to online education. It can benefit many downstream tasks on online learning platforms, such as estimating dropout rates, facilitating strategic intervention, and enabling adaptive online learning. Interactive online question pools provide students with interesting interactive questions to practice their knowledge in online education. However, little research has been done on student performance prediction in interactive online question pools. Existing work on student performance prediction targets at online learning platforms with predefined course curriculum and accurate knowledge labels like MOOC platforms, but they are not able to fully model knowledge evolution of students in interactive online …
Efficient Fine-Grained Data Sharing Mechanism For Electronic Medical Record Systems With Mobile Devices, Hui Ma, Rui Zhang, Guomin Yang, Zishuai Zong, Kai He, Yuting Xiao
Efficient Fine-Grained Data Sharing Mechanism For Electronic Medical Record Systems With Mobile Devices, Hui Ma, Rui Zhang, Guomin Yang, Zishuai Zong, Kai He, Yuting Xiao
Research Collection School Of Computing and Information Systems
Sharing digital medical records on public cloud storage via mobile devices facilitates patients (doctors) to get (offer) medical treatment of high quality and efficiency. However, challenges such as data privacy protection, flexible data sharing, efficient authority delegation, computation efficiency optimization, are remaining toward achieving practical fine-grained access control in the Electronic Medical Record (EMR) system. In this work, we propose an innovative access control model and a fine-grained data sharing mechanism for EMR, which simultaneously achieves the above-mentioned features and is suitable for resource-constrained mobile devices. In the model, complex computation is outsourced to public cloud servers, leaving almost no …
Zone Path Construction (Zac) Based Approaches For Effective Real-Time Ridesharing, Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet
Zone Path Construction (Zac) Based Approaches 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 together in the "right" available vehicles in real-time, so that the objective (e.g., requests served, revenue or delay) is optimized. This challenge has been addressed in existing work by: (i) generating as many relevant feasible (with respect to the available delay for customers) combinations of requests as possible …
A Genetic Algorithm To Minimise Number Of Vehicles In An Electric Vehicle Routing Problem, Kiian Leong Bertran Queck, Hoong Chuin Lau
A Genetic Algorithm To Minimise Number Of Vehicles In An Electric Vehicle Routing Problem, Kiian Leong Bertran Queck, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Electric Vehicles (EVs) and charging infrastructure are starting to become commonplace in major cities around the world. For logistics providers to adopt an EV fleet, there are many factors up for consideration, such as route planning for EVs with limited travel range as well as long-term planning of fleet size. In this paper, we present a genetic algorithm to perform route planning that minimises the number of vehicles required. Specifically, we discuss the challenges on the violations of constraints in the EV routing problem (EVRP) arising from applying genetic algorithm operators. To overcome the challenges, techniques specific to addressing the …
A Hybrid Framework Using A Qubo Solver For Permutation-Based Combinatorial Optimization, Siong Thye Goh, Sabrish Gopalakrishnan, Jianyuan Bo, Hoong Chuin Lau
A Hybrid Framework Using A Qubo Solver For Permutation-Based Combinatorial Optimization, Siong Thye Goh, Sabrish Gopalakrishnan, Jianyuan Bo, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
In this paper, we propose a hybrid framework to solve large-scale permutation-based combinatorial problems effectively using a high-performance quadratic unconstrained binary optimization (QUBO) solver. To do so, transformations are required to change a constrained optimization model to an unconstrained model that involves parameter tuning. We propose techniques to overcome the challenges in using a QUBO solver that typically comes with limited numbers of bits. First, to smooth the energy landscape, we reduce the magnitudes of the input without compromising optimality. We propose a machine learning approach to tune the parameters for good performance effectively. To handle possible infeasibility, we introduce …
Bus Frequency Optimization: When Waiting Time Matters In User Satisfaction, Songsong Mo, Zhifeng Bao, Baihua Zheng, Zhiyong Peng
Bus Frequency Optimization: When Waiting Time Matters In User Satisfaction, Songsong Mo, Zhifeng Bao, Baihua Zheng, Zhiyong Peng
Research Collection School Of Computing and Information Systems
Reorganizing bus frequency to cater for the actual travel demand can save the cost of the public transport system significantly. Many, if not all, existing studies formulate this as a bus frequency optimization problem which tries to minimize passengers’ average waiting time. However, many investigations have confirmed that the user satisfaction drops faster as the waiting time increases. Consequently, this paper studies the bus frequency optimization problem considering the user satisfaction. Specifically, for the first time to our best knowledge, we study how to schedule the buses such that the total number of passengers who could receive their bus services …
Temporal Heterogeneous Interaction Graph Embedding For Next-Item Recommendation, Yugang Ji, Mingyang Yin, Yuan Fang, Hongxia Yang, Xiangwei Wang, Tianrui Jia, Chuan Shi
Temporal Heterogeneous Interaction Graph Embedding For Next-Item Recommendation, Yugang Ji, Mingyang Yin, Yuan Fang, Hongxia Yang, Xiangwei Wang, Tianrui Jia, Chuan Shi
Research Collection School Of Computing and Information Systems
In the scenario of next-item recommendation, previous methods attempt to model user preferences by capturing the evolution of sequential interactions. However, their sequential expression is often limited, without modeling complex dynamics that short-term demands can often be influenced by long-term habits. Moreover, few of them take into account the heterogeneous types of interaction between users and items. In this paper, we model such complex data as a Temporal Heterogeneous Interaction Graph (THIG) and learn both user and item embeddings on THIGs to address next-item recommendation. The main challenges involve two aspects: the complex dynamics and rich heterogeneity of interactions. We …
Querying Recurrent Convoys Over Trajectory Data, Munkh-Erdene Yadamjav, Zhifeng Bao, Baihua Zheng, Farhana M. Choudhury, Hanan Samet
Querying Recurrent Convoys Over Trajectory Data, Munkh-Erdene Yadamjav, Zhifeng Bao, Baihua Zheng, Farhana M. Choudhury, Hanan Samet
Research Collection School Of Computing and Information Systems
Moving objects equipped with location-positioning devices continuously generate a large amount of spatio-temporal trajectory data. An interesting finding over a trajectory stream is a group of objects that are travelling together for a certain period of time. Existing studies on mining co-moving objects do not consider an important correlation between co-moving objects, which is the reoccurrence of the movement pattern. In this study, we define a problem of finding recurrent pattern of co-moving objects from streaming trajectories and propose an efficient solution that enables us to discover recent co-moving object patterns repeated within a given time period. Experimental results on …
Social Participation Performance Of Wheelchair Users Using Clustering And Geolocational Sensor's Data, Yukun Yin, Kar Way Tan
Social Participation Performance Of Wheelchair Users Using Clustering And Geolocational Sensor's Data, Yukun Yin, Kar Way Tan
Research Collection School Of Computing and Information Systems
For wheelchair users, social participation and physical mobility play a significant part in determining their mental health and quality of life outcomes. However, little is known about how wheelchair users move about and engage in social interactions within their life-spaces. In this project, we investigate the social participation performance of the wheelchair users based on a combination of geolocational and lifestyle survey data collected over a period of three months. This paper adopts a multi-variate approach combining geolocational travel patterns and various factors such as independence, willingness and self-perception to provide multi-faceted analysis to their lifestyles. We provide profiles of …
Learning Transferrable Parameters For Long-Tailed Sequential User Behavior Modeling, Jianwen Yin, Chenghao Liu, Weiqing Wang, Jianling Sun, Steven C. H. Hoi
Learning Transferrable Parameters For Long-Tailed Sequential User Behavior Modeling, Jianwen Yin, Chenghao Liu, Weiqing Wang, Jianling Sun, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Sequential user behavior modeling plays a crucial role in online user-oriented services, such as product purchasing, news feed consumption, and online advertising. The performance of sequential modeling heavily depends on the scale and quality of historical behaviors. However, the number of user behaviors inherently follows a long-tailed distribution, which has been seldom explored. In this work, we argue that focusing on tail users could bring more benefits and address the long tails issue by learning transferrable parameters from both optimization and feature perspectives. Specifically, we propose a gradient alignment optimizer and adopt an adversarial training scheme to facilitate knowledge transfer …
Adaptive Large Neighborhood Search For Vehicle Routing Problem With Cross-Docking, Aldy Gunawan, Audrey Tedja Widjaja, Pieter Vansteenwegen, Vincent F. Yu
Adaptive Large Neighborhood Search For Vehicle Routing Problem With Cross-Docking, Aldy Gunawan, Audrey Tedja Widjaja, Pieter Vansteenwegen, Vincent F. Yu
Research Collection School Of Computing and Information Systems
Cross-docking is considered as a method to manage and control the inventory flow, which is essential in the context of supply chain management. This paper studies the integration of the vehicle routing problem with cross-docking, namely VRPCD which has been extensively studied due to its ability to reducethe overall costs occurring in a supply chain network. Given a fleet of homogeneous vehicles for delivering a single type of product from suppliers to customers through a cross-dock facility, the objective of VRPCD is to determine the number of vehicles used and the corresponding vehicle routes, such that the vehicleoperational and transportation …
Skin-Mimo: Vibration-Based Mimo Communication Over Human Skin, Dong Ma, Yuezhong Wu, Ming Ding, Mahbub Hassan, Wen Hu
Skin-Mimo: Vibration-Based Mimo Communication Over Human Skin, Dong Ma, Yuezhong Wu, Ming Ding, Mahbub Hassan, Wen Hu
Research Collection School Of Computing and Information Systems
We explore the feasibility of Multiple-Input-Multiple-Output (MIMO) communication through vibrations over human skin. Using off-the-shelf motors and piezo transducers as vibration transmitters and receivers, respectively, we build a 2x2 MIMO testbed to collect and analyze vibration signals from real subjects. Our analysis reveals that there exist multiple independent vibration channels between a pair of transmitter and receiver, confirming the feasibility of MIMO. Unfortunately, the slow ramping of mechanical motors and rapidly changing skin channels make it impractical for conventional channel sounding based channel state information (CSI) acquisition, which is critical for achieving MIMO capacity gains. To solve this problem, we …
Closing The Data-Decisions Loop: Deploying Artificial Intelligence For Dynamic Resource Management, Pradeep Varakantham
Closing The Data-Decisions Loop: Deploying Artificial Intelligence For Dynamic Resource Management, Pradeep Varakantham
Asian Management Insights
Improving predictions and allocations to determine the optimal matching of demand and supply in a dynamic, uncertain future.
Transferring And Regularizing Prediction For Semantic Segmentation, Yiheng Zhang, Zhaofan Qiu, Ting Yao, Chong-Wah Ngo, Dong Liu, Tao Mei
Transferring And Regularizing Prediction For Semantic Segmentation, Yiheng Zhang, Zhaofan Qiu, Ting Yao, Chong-Wah Ngo, Dong Liu, Tao Mei
Research Collection School Of Computing and Information Systems
Semantic segmentation often requires a large set of images with pixel-level annotations. In the view of extremely expensive expert labeling, recent research has shown that the models trained on photo-realistic synthetic data (e.g., computer games) with computer-generated annotations can be adapted to real images. Despite this progress, without constraining the prediction on real images, the models will easily overfit on synthetic data due to severe domain mismatch. In this paper, we novelly exploit the intrinsic properties of semantic segmentation to alleviate such problem for model transfer. Specifically, we present a Regularizer of Prediction Transfer (RPT) that imposes the intrinsic properties …
Towards Distributed Node Similarity Search On Graphs, Tianming Zhang, Yunjun Gao, Baihua Zheng, Lu Chen, Shiting Wen, Wei Guo
Towards Distributed Node Similarity Search On Graphs, Tianming Zhang, Yunjun Gao, Baihua Zheng, Lu Chen, Shiting Wen, Wei Guo
Research Collection School Of Computing and Information Systems
Node similarity search on graphs has wide applications in recommendation, link prediction, to name just a few. However, existing studies are insufficient due to two reasons: (i) the scale of the real-world graph is growing rapidly, and (ii) vertices are always associated with complex attributes. In this paper, we propose an efficiently distributed framework to support node similarity search on massive graphs, which considers both graph structure correlation and node attribute similarity in metric spaces. The framework consists of preprocessing stage and query stage. In the preprocessing stage, a parallel KD-tree construction (KDC) algorithm is developed to form a newly …
Sensing, Computing, And Communications For Energy Harvesting Iots: A Survey, Dong Ma, Guohao Lan, Mahbub Hassan, Wen Hu, Sajal K. Das
Sensing, Computing, And Communications For Energy Harvesting Iots: A Survey, Dong Ma, Guohao Lan, Mahbub Hassan, Wen Hu, Sajal K. Das
Research Collection School Of Computing and Information Systems
With the growing number of deployments of Internet of Things (IoT) infrastructure for a wide variety of applications, the battery maintenance has become a major limitation for the sustainability of such infrastructure. To overcome this problem, energy harvesting offers a viable alternative to autonomously power IoT devices, resulting in a number of battery-less energy harvesting IoTs (or EH-IoTs) appearing in the market in recent years. Standards activities are also underway, which involve wireless protocol design suitable for EH-IoTs as well as testing procedures for various energy harvesting methods. Despite the early commercial and standards activities, IoT sensing, computing and communications …
Goods Consumed During Transit In Split Delivery Vehicle Routing Problems: Modeling And Solution, Wenzhe Yang, Di Wang, Wei Pang, Ah-Hwee Tan, You Zhou
Goods Consumed During Transit In Split Delivery Vehicle Routing Problems: Modeling And Solution, Wenzhe Yang, Di Wang, Wei Pang, Ah-Hwee Tan, You Zhou
Research Collection School Of Computing and Information Systems
This article presents the modeling and solution of an extended type of split delivery vehicle routing problem (SDVRP). In SDVRP, the demands of customers need to be met by efficiently routing a given number of capacitated vehicles, wherein each customer may be served multiple times by more than one vehicle. Furthermore, in many real-world scenarios, consumption of vehicles en route is the same as the goods being delivered to customers, such as food, water and fuel in rescue or replenishment missions in harsh environments. Moreover, the consumption may also be in virtual forms, such as time spent in constrained tasks. …
Hierarchical Multiagent Reinforcement Learning For Maritime Traffic Management, Arambam James Singh, Akshat Kumar, Hoong Chuin Lau
Hierarchical Multiagent Reinforcement Learning For Maritime Traffic Management, Arambam James Singh, Akshat Kumar, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Increasing global maritime traffic coupled with rapid digitization and automation in shipping mandate developing next generation maritime traffic management systems to mitigate congestion, increase safety of navigation, and avoid collisions in busy and geographically constrained ports (such as Singapore's). To achieve these objectives, we model the maritime traffic as a large multiagent system with individual vessels as agents, and VTS (Vessel Traffic Service) authority as a regulatory agent. We develop a hierarchical reinforcement learning approach where vessels first select a high level action based on the underlying traffic flow, and then select the low level action that determines their future …
Enhancing Cellular Communications For Uavs Via Intelligent Reflective Surface, Dong Ma, Ming Ding, Mahbub Hassan
Enhancing Cellular Communications For Uavs Via Intelligent Reflective Surface, Dong Ma, Ming Ding, Mahbub Hassan
Research Collection School Of Computing and Information Systems
Intelligent reflective surfaces (IRSs) capable of reconfiguring their electromagnetic absorption and reflection properties in real-time are offering unprecedented opportunities to enhance wireless communication experience in challenging environments. In this paper, we analyze the potential of IRS in enhancing cellular communications for UAVs, which currently suffers from poor signal strength due to the down-tilt of base station antennas optimized to serve ground users. We consider deployment of IRS on building walls, which can be remotely configured by cellular base stations to coherently direct the reflected radio waves towards specific UAVs in order to increase their received signal strengths. Using the recently …
Route Choice Behaviour And Travel Information In A Congested Network: Static And Dynamic Recursive Models, Giselle De Moraes Ramos, Tien Mai, Winnie Daamen, Emma Frejinger
Route Choice Behaviour And Travel Information In A Congested Network: Static And Dynamic Recursive Models, Giselle De Moraes Ramos, Tien Mai, Winnie Daamen, Emma Frejinger
Research Collection School Of Computing and Information Systems
Travel information has the potential to influence travellers choices, in order to steer travellers to less congested routes and alleviate congestion. This paper investigates, on the one hand, how travel information affects route choice behaviour, and on the other hand, the impact of the travel time representation on the interpretation of parameter estimates and prediction accuracy. To this end, we estimate recursive models using data from an innovative data collection effort consisting of route choice observation data from GPS trackers, travel diaries and link travel times on the overall network. Though such combined data sets exist, these have not yet …
Two Can Play That Game: An Adversarial Evaluation Of A Cyber-Alert Inspection System, Ankit Shah, Arunesh Sinha, Rajesh Ganesan, Sushil Jajodia, Hasan Cam
Two Can Play That Game: An Adversarial Evaluation Of A Cyber-Alert Inspection System, Ankit Shah, Arunesh Sinha, Rajesh Ganesan, Sushil Jajodia, Hasan Cam
Research Collection School Of Computing and Information Systems
Cyber-security is an important societal concern. Cyber-attacks have increased in numbers as well as in the extent of damage caused in every attack. Large organizations operate a Cyber Security Operation Center (CSOC), which forms the first line of cyber-defense. The inspection of cyber-alerts is a critical part of CSOC operations (defender or blue team). Recent work proposed a reinforcement learning (RL) based approach for the defender’s decision-making to prevent the cyber-alert queue length from growing large and overwhelming the defender. In this article, we perform a red team (adversarial) evaluation of this approach. With the recent attacks on learning-based decision-making …
Attribute-Based Cloud Data Integrity Auditing For Secure Outsourced Storage, Yong Yu, Yannan Li, Bo Yang, Willy Susilo, Guomin Yang, Jian Bai
Attribute-Based Cloud Data Integrity Auditing For Secure Outsourced Storage, Yong Yu, Yannan Li, Bo Yang, Willy Susilo, Guomin Yang, Jian Bai
Research Collection School Of Computing and Information Systems
Outsourced storage such as cloud storage can significantly reduce the burden of data management of data owners. Despite of a long list of merits of cloud storage, it triggers many security risks at the same time. Data integrity, one of the most burning challenges in secure cloud storage, is a fundamental and pivotal element in outsourcing services. Outsourced data auditing protocols enable a verifier to efficiently check the integrity of the outsourced files without downloading the entire file from the cloud, which can dramatically reduce the communication overhead between the cloud server and the verifier. Existing protocols are mostly based …
Incorporating A Reverse Logistics Scheme In A Vehicle Routing Problem With Cross-Docking Network: A Modelling Approach, Audrey Tedja Widjaja, Aldy Gunawan, Panca Jodiawan, Vincent F. Yu
Incorporating A Reverse Logistics Scheme In A Vehicle Routing Problem With Cross-Docking Network: A Modelling Approach, Audrey Tedja Widjaja, Aldy Gunawan, Panca Jodiawan, Vincent F. Yu
Research Collection School Of Computing and Information Systems
Reverse logistics has been implemented by various companies because of its ability to gain more profit and maintain the competitiveness of the company. However, extensive studies on the vehicle routing problem with cross-docking (VRPCD) only considered the forward flow instead of the reverse flow. Motivated by the ability of a VRPCD network to minimize the distribution cost in the forward flow, this research incorporates the reverse logistics scheme in a VRPCD network, namely the VRP with reverse cross-docking (VRP-RCD). We propose a VRP-RCD mathematical model for a four-level supply chain network that involves suppliers, cross-dock, customers, and outlets. The main …
How To And How Much? Teaching Ethics In An Interaction Design Course, Bimlesh Wadhwa, Eng Lieh Ouh, Benjamin Gan
How To And How Much? Teaching Ethics In An Interaction Design Course, Bimlesh Wadhwa, Eng Lieh Ouh, Benjamin Gan
Research Collection School Of Computing and Information Systems
How much is sufficient and how should one teach ethics in an Interaction Design curriculum in undergraduate computing program has been a point of dilemma for many HCI educators. We conducted a preliminary study using a mixed method to gather perception on ethics in our interaction design courses at two of the leading Singapore Universities. We answer three research questions specific to an undergraduate HCI course: Is there a need for ethics? Is there sufficient ethics coverage? and how to teach ethics? We surveyed 140 students and interviewed six teachers in two Singapore Universities. Our findings suggest that 92% of …
Vehicle Routing Problem For Multi-Product Cross-Docking, Aldy Gunawan, Audrey Tedja Widjaja, Benjamin Gan, Vincent F. Yu, Panca Jodiawan
Vehicle Routing Problem For Multi-Product Cross-Docking, Aldy Gunawan, Audrey Tedja Widjaja, Benjamin Gan, Vincent F. Yu, Panca Jodiawan
Research Collection School Of Computing and Information Systems
Cross-docking is a logistic technique that can reduce costs occurred in a supply chain network while increasing the flow of goods, thus shortening the shipping cycle. Inside a cross-dock facility, the goods are directly transferred from incoming vehicles to outgoing vehicles without storing them in-between. Our research extends and combines this cross-docking technique with a well-known logistic problem, the vehicle routing problem (VRP), for delivering multiple products and addresses it as the VRP for multi-product cross-docking (VRP-MPCD). We developed a mixed integer programming model and generated two sets of VRP-MPCD instances, which are based on VRPCD instances. The instances are …
Feature Agglomeration Networks For Single Stage Face Detection, Jialiang Zhang, Xiongwei Wu, Steven C. H. Hoi, Jianke Zhu
Feature Agglomeration Networks For Single Stage Face Detection, Jialiang Zhang, Xiongwei Wu, Steven C. H. Hoi, Jianke Zhu
Research Collection School Of Computing and Information Systems
Recent years have witnessed promising results of exploring deep convolutional neural network for face detection. Despite making remarkable progress, face detection in the wild remains challenging especially when detecting faces at vastly different scales and characteristics. In this paper, we propose a novel simple yet effective framework of “Feature Agglomeration Networks” (FANet) to build a new single-stage face detector, which not only achieves state-of-the-art performance but also runs efficiently. As inspired by Feature Pyramid Networks (FPN) (Lin et al., 2017), the key idea of our framework is to exploit inherent multi-scale features of a single convolutional neural network by aggregating …