Detecting Cyberattacks In Industrial Control Systems Using Online Learning Algorithms,
2019
Singapore Management University
Detecting Cyberattacks In Industrial Control Systems Using Online Learning Algorithms, Guangxia Li, Yulong Shen, Peilin Zhao, Xiao Lu, Jia Liu, Yangyang Liu, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
Industrial control systems are critical to the operation of industrial facilities, especially for critical infrastructures, such as refineries, power grids, and transportation systems. Similar to other information systems, a significant threat to industrial control systems is the attack from cyberspace-the offensive maneuvers launched by "anonymous" in the digital world that target computer-based assets with the goal of compromising a system's functions or probing for information. Owing to the importance of industrial control systems, and the possibly devastating consequences of being attacked, significant endeavors have been attempted to secure industrial control systems from cyberattacks. Among them are intrusion detection systems that …
Mixed-Dish Recognition With Contextual Relation Networks,
2019
Chinese Academy of Sciences
Mixed-Dish Recognition With Contextual Relation Networks, Lixi Deng, Jingjing Chen, Qianru Sun, Xiangnan He, Sheng Tang, Zhaoyan Ming, Yongdong Zhang, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Mixed dish is a food category that contains different dishes mixed in one plate, and is popular in Eastern and Southeast Asia. Recognizing individual dishes in a mixed dish image is important for health related applications, e.g. calculating the nutrition values. However, most existing methods that focus on single dish classification are not applicable to mixed-dish recognition. The new challenge in recognizing mixed-dish images are the complex ingredient combination and severe overlap among different dishes. In order to tackle these problems, we propose a novel approach called contextual relation networks (CR-Nets) that encodes the implicit and explicit contextual relations among …
Topicsummary: A Tool For Analyzing Class Discussion Forums Using Topic Based Summarizations,
2019
Singapore Management University
Topicsummary: A Tool For Analyzing Class Discussion Forums Using Topic Based Summarizations, Swapna Gottipati, Venky Shankararaman, Renjini Ramesh
Research Collection School Of Computing and Information Systems
This Innovative Practice full paper, describes the application of text mining techniques for extracting insights from a course based online discussion forum through generation of topic based summaries. Discussions, either in classroom or online provide opportunity for collaborative learning through exchange of ideas that leads to enhanced learning through active participation. Online discussions offer a number of benefits namely providing additional time to reflect and synthesize information before writing, providing a natural platform for students to voice their ideas without any one student dominating the conversation, and providing a record of the student’s thoughts. An online discussion forum provides a …
On Analysing Supply And Demand In Labor Markets: Framework, Model And System,
2019
Singapore Management University
On Analysing Supply And Demand In Labor Markets: Framework, Model And System, Hendrik Santoso Sugiarto, Ee-Peng Lim, Ngak Leng Sim
Research Collection School Of Computing and Information Systems
The labor market refers to the market between job seekers and employers. As much of job seeking and talent hiring activities are now performed online, a large amount of job posting and application data have been collected and can be re-purposed for labor market analysis. In the labor market, both supply and demand are the key factors in determining an appropriate salary for both job applicants and employers in the market. However, it is challenging to discover the supply and demand for any labor market. In this paper, we propose a novel framework to built a labor market model using …
Deep Hashing By Discriminating Hard Examples,
2019
Singapore Management University
Deep Hashing By Discriminating Hard Examples, Cheng Yan, Guansong Pang, Xiao Bai, Chunhua Shen, Jun Zhou, Edwin Hancock
Research Collection School Of Computing and Information Systems
This paper tackles a rarely explored but critical problem within learning to hash, i.e., to learn hash codes that effectively discriminate hard similar and dissimilar examples, to empower large-scale image retrieval. Hard similar examples refer to image pairs from the same semantic class that demonstrate some shared appearance but have different fine-grained appearance. Hard dissimilar examples are image pairs that come from different semantic classes but exhibit similar appearance. These hard examples generally have a small distance due to the shared appearance. Therefore, effective encoding of the hard examples can well discriminate the relevant images within a small Hamming distance, …
Who, Where, And What To Wear?: Extracting Fashion Knowledge From Social Media,
2019
Singapore Management University
Who, Where, And What To Wear?: Extracting Fashion Knowledge From Social Media, Yunshan Ma, Xun Yang, Lizi Liao, Yixin Cao, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Fashion knowledge helps people to dress properly and addresses not only physiological needs of users, but also the demands of social activities and conventions. It usually involves three mutually related aspects of: occasion, person and clothing. However, there are few works focusing on extracting such knowledge, which will greatly benefit many downstream applications, such as fashion recommendation. In this paper, we propose a novel method to automatically harvest fashion knowledge from social media. We unify three tasks of occasion, person and clothing discovery from multiple modalities of images, texts and metadata. For person detection and analysis, we use the off-the-shelf …
Cognitive And Social Interaction Analysis In Graduate Discussion Forums,
2019
Singapore Management University
Cognitive And Social Interaction Analysis In Graduate Discussion Forums, Mallika Gokarn Nitin, Swapna Gottipati, Venky Shankararaman
Research Collection School Of Computing and Information Systems
Discussion forums play a key role in building knowledge repositories in an education institute. Asynchronous discussion forums enable part-time graduate professionals to have a better learning experience. This paper reports how a carefully curated discussion forum enhances the cognitive and social interactions among students in a graduate information systems course. In particular, we analyse the cognitive and social interactions and their impact on the student grades. To our surprise, the graduate students with their limited time resources, have higher order cognitive contributions and reasonable amount of social posts. We present the discussion forum design, cognitive and social behaviour analysis, grade …
Collaborative Online Ranking Algorithms For Multitask Learning,
2019
Singapore Management University
Collaborative Online Ranking Algorithms For Multitask Learning, Guangxia Li, Peilin Zhao, Tao Mei, Peng Yang, Yulong Shen, Julian K. Y. Chang, Steven C. H. Hoi
Research Collection School Of Computing and Information Systems
There are many applications in which it is desirable to rank or order instances that belong to several different but related problems or tasks. Although unique, the individual ranking problem often shares characteristics with other problems in the group. Conventional ranking methods treat each task independently without considering the latent commonalities. In this paper, we study the problem of learning to rank instances that belong to multiple related tasks from the multitask learning perspective. We consider a case in which the information that is learned for a task can be used to enhance the learning of other tasks and propose …
Weakly-Supervised Deep Anomaly Detection With Pairwise Relation Learning,
2019
Singapore Management University
Weakly-Supervised Deep Anomaly Detection With Pairwise Relation Learning, Guansong Pang, Anton Van Den Hengel, Chuanhua Shen
Research Collection School Of Computing and Information Systems
This paper studies a rarely explored but critical anomaly detection problem: weakly-supervised anomaly detection with limited labeled anomalies and a large unlabeled data set. This problem is very important because it (i) enables anomalyinformed modeling which helps identify anomalies of interests and address the notorious high false positives in unsupervised anomaly detection, and (ii) eliminates the reliance on large-scale and complete labeled anomaly data in fullysupervised settings. However, the problem is especially challenging since we have only limited labeled data for a single class, and moreover, the seen anomalies often cannot cover all types of anomalies (i.e., unseen anomalies). We …
Who, Where, And What To Wear?: Extracting Fashion Knowledge From Social Media,
2019
Singapore Management University
Who, Where, And What To Wear?: Extracting Fashion Knowledge From Social Media, Yunshan Ma, Xun Yang, Lizi Liao, Yixin Cao, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Fashion knowledge helps people to dress properly and addresses not only physiological needs of users, but also the demands of social activities and conventions. It usually involves three mutually related aspects of: occasion, person and clothing. However, there are few works focusing on extracting such knowledge, which will greatly benefit many downstream applications, such as fashion recommendation. In this paper, we propose a novel method to automatically harvest fashion knowledge from social media. We unify three tasks of occasion, person and clothing discovery from multiple modalities of images, texts and metadata. For person detection and analysis, we use the off-the-shelf …
Automatic Fashion Knowledge Extraction From Social Media,
2019
Singapore Management University
Automatic Fashion Knowledge Extraction From Social Media, Yunshan Ma, Lizi Liao, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Fashion knowledge plays a pivotal role in helping people in their dressing. In this paper, we present a novel system to automatically harvest fashion knowledge from social media. It unifies three tasks of occasion, person and clothing discovery from multiple modalities of images, texts and metadata. A contextualized fashion concept learning model is applied to leverage the rich contextual information for improving the fashion concept learning performance. At the same time, to counter the label noise within training data, we employ a weak label modeling method to further boost the performance. We build a website to demonstrate the quality of …
Who, Where, And What To Wear?: Extracting Fashion Knowledge From Social Media,
2019
Singapore Management University
Who, Where, And What To Wear?: Extracting Fashion Knowledge From Social Media, Yunshan Ma, Xun Yang, Lizi Liao, Yixin Cao, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Fashion knowledge helps people to dress properly and addresses not only physiological needs of users, but also the demands of social activities and conventions. It usually involves three mutually related aspects of: occasion, person and clothing. However, there are few works focusing on extracting such knowledge, which will greatly benefit many downstream applications, such as fashion recommendation. In this paper, we propose a novel method to automatically harvest fashion knowledge from social media. We unify three tasks of occasion, person and clothing discovery from multiple modalities of images, texts and metadata. For person detection and analysis, we use the off-the-shelf …
End-To-End Deep Reinforcement Learning For Multi-Agent Collaborative Exploration,
2019
Singapore Management University
End-To-End Deep Reinforcement Learning For Multi-Agent Collaborative Exploration, Zichen Chen, Budhitama Subagdja, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Exploring an unknown environment by multiple autonomous robots is a major challenge in robotics domains. As multiple robots are assigned to explore different locations, they may interfere each other making the overall tasks less efficient. In this paper, we present a new model called CNN-based Multi-agent Proximal Policy Optimization (CMAPPO) to multi-agent exploration wherein the agents learn the effective strategy to allocate and explore the environment using a new deep reinforcement learning architecture. The model combines convolutional neural network to process multi-channel visual inputs, curriculum-based learning, and PPO algorithm for motivation based reinforcement learning. Evaluations show that the proposed method …
Multi-Agent Collaborative Exploration Through Graph-Based Deep Reinforcement Learning,
2019
Singapore Management University
Multi-Agent Collaborative Exploration Through Graph-Based Deep Reinforcement Learning, Tianze Luo, Budhitama Subagdja, Ah-Hwee Tan, Ah-Hwee Tan
Research Collection School Of Computing and Information Systems
Autonomous exploration by a single or multiple agents in an unknown environment leads to various applications in automation, such as cleaning, search and rescue, etc. Traditional methods normally take frontier locations and segmented regions of the environment into account to efficiently allocate target locations to different agents to visit. They may employ ad hoc solutions to allocate the task to the agents, but the allocation may not be efficient. In the literature, few studies focused on enhancing the traditional methods by applying machine learning models for agent performance improvement. In this paper, we propose a graph-based deep reinforcement learning approach …
Fusion Of Multimodal Embeddings For Ad-Hoc Video Search,
2019
Singapore Management University
Fusion Of Multimodal Embeddings For Ad-Hoc Video Search, Danny Francis, Phuong Anh Nguyen, Benoit Huet, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
The challenge of Ad-Hoc Video Search (AVS) originates from free-form (i.e., no pre-defined vocabulary) and freestyle (i.e., natural language) query description. Bridging the semantic gap between AVS queries and videos becomes highly difficult as evidenced from the low retrieval accuracy of AVS benchmarking in TRECVID. In this paper, we study a new method to fuse multimodal embeddings which have been derived based on completely disjoint datasets. This method is tested on two datasets for two distinct tasks: on MSR-VTT for unique video retrieval and on V3C1 for multiple videos retrieval.
The Vid3oc And Intvid Datasets For Video Super Resolution And Quality Mapping,
2019
Singapore Management University
The Vid3oc And Intvid Datasets For Video Super Resolution And Quality Mapping, S. Kim, G. Li, D. Fuoli, M. Danelljan, Zhiwu Huang, S. Gu, R. Timofte
Research Collection School Of Computing and Information Systems
The current rapid advancements of computational hardware has opened the door for deep networks to be applied for real-time video processing, even on consumer devices. Appealing tasks include video super-resolution, compression artifact removal, and quality enhancement. These problems require high-quality datasets that can be applied for training and benchmarking. In this work, we therefore introduce two video datasets, aimed for a variety of tasks. First, we propose the Vid3oC dataset, containing 82 simultaneous recordings of 3 camera sensors. It is recorded with a multi-camera rig, including a high-quality DSLR camera, a high-end smartphone, and a stereo camera sensor. Second, we …
Evaluation Of Sigfox Lpwan For Sensor-Enabled Homes To Identify At Risk Community Dwelling Seniors,
2019
Singapore Management University
Evaluation Of Sigfox Lpwan For Sensor-Enabled Homes To Identify At Risk Community Dwelling Seniors, Crys Tan, Hwee-Pink Tan
Research Collection School Of Computing and Information Systems
It is projected that Singapore will become superaged (where 20% of its population will comprise seniors) by 2025. Although various community programs are available to promote active ageing among seniors who are well, provide befriending services for seniors at risk of isolation and care and support for frail and vulnerable seniors, it is not easy to differentiate between `well' seniors and `at risk' seniors. While privacy-preserving z-wave based sensor-enabled homes have been piloted in 100 homes of seniors living alone and have been successful in the timely detection of at-risk seniors, they have limited scalability due to high costs, reliability …
Blockchain In Internet Of Things (Iot),
2019
Arkansas State University
Blockchain In Internet Of Things (Iot), Debrath Banerjee
Student Theses and Dissertations
Nowadays, Blockchain is not an enigmatic technical term rather a technology that holds promise as a way not only to record financial transactions but also to decentralize infrastructure and build a trust layer for business logic. Currently blockchain development is undoubtedly empowering many financial sectors. However non-financial application areas have incredibly grown complex due to the involvement of IoT. So, although they intend to reshape the model, still lots of uncertainty exist in terms of effectiveness. In convergence of blockchain and IoT, there is no definite design model. We have developed a blockchain based IoT platform to replace the traditional …
Why Reinventing The Wheels? An Empirical Study On Library Reuse And Re-Implementation,
2019
Singapore Management University
Why Reinventing The Wheels? An Empirical Study On Library Reuse And Re-Implementation, Bowen Xu, Le An, Ferdian Thung, Foutse Khomh, David Lo
Research Collection School Of Computing and Information Systems
Nowadays, with the rapid growth of open source software (OSS), library reuse becomes more and more popular since a large amount of third- party libraries are available to download and reuse. A deeper understanding on why developers reuse a library (i.e., replacing self-implemented code with an external library) or re-implement a library (i.e., replacing an imported external library with self-implemented code) could help researchers better understand the factors that developers are concerned with when reusing code. This understanding can then be used to improve existing libraries and API recommendation tools for researchers and practitioners by using the developers concerns identified …
Amazon Alexa + Linked Open Data: Theorizing Concerning Relationships Between (Surveillant) Smart-Home Voice Assistants And Linked Open Data,
2019
CUNY Central
Amazon Alexa + Linked Open Data: Theorizing Concerning Relationships Between (Surveillant) Smart-Home Voice Assistants And Linked Open Data, Michelle Nitto
Publications and Research
No abstract provided.
