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Qlens: Visual Analytics Of Multi-Step Problem-Solving Behaviors For Improving Question Design, Meng XIA, Reshika P. VELUMANI, Yong WANG, Huamin QU, Xiaojuan MA 2021 Singapore Management University

Qlens: Visual Analytics Of Multi-Step Problem-Solving Behaviors For Improving Question Design, Meng Xia, Reshika P. Velumani, Yong Wang, Huamin Qu, Xiaojuan Ma

Research Collection School Of Information Systems

With the rapid development of online education in recent years, there has been an increasing number of learning platforms that provide students with multi-step questions to cultivate their problem-solving skills. To guarantee the high quality of such learning materials, question designers need to inspect how students’ problem-solving processes unfold step by step to infer whether students’ problem-solving logic matches their design intent. They also need to compare the behaviors of different groups (e.g., students from different grades) to distribute questions to students with the right level of knowledge. The availability of fine-grained interaction data, such as mouse movement trajectories ...


Visual Analysis Of Discrimination In Machine Learning, Qianwen WANG, Zhenghua XU, Zhutian CHEN, Yong WANG, Yong WANG, Huamin Qu 2021 Singapore Management University

Visual Analysis Of Discrimination In Machine Learning, Qianwen Wang, Zhenghua Xu, Zhutian Chen, Yong Wang, Yong Wang, Huamin Qu

Research Collection School Of Information Systems

The growing use of automated decision-making in critical applications, such as crime prediction and college admission, has raised questions about fairness in machine learning. How can we decide whether different treatments are reasonable or discriminatory? In this paper, we investigate discrimination in machine learning from a visual analytics perspective and propose an interactive visualization tool, DiscriLens, to support a more comprehensive analysis. To reveal detailed information on algorithmic discrimination, DiscriLens identifies a collection of potentially discriminatory itemsets based on causal modeling and classification rules mining. By combining an extended Euler diagram with a matrix-based visualization, we develop a novel set ...


Implementation Of Smartphone Navigation Features By Combined Forces In Determining The Hazards Of Terrorism In Poso, Mahturai Rian Fitra Mrf, Arthur Josias Simon Runturambi Ajsr 2021 SKSG Universitas Indonesia

Implementation Of Smartphone Navigation Features By Combined Forces In Determining The Hazards Of Terrorism In Poso, Mahturai Rian Fitra Mrf, Arthur Josias Simon Runturambi Ajsr

Journal of Terrorism Studies

The presence of armed terrorist groups in Poso can threaten security conditions in the country because their activities are considered quite dangerous for the surrounding community. This terrorist group did not hesitate to kill civilians who tried to deny its existence. Therefore, various joint military operations have been launched to crush this armed terrorist group, such as Camar Maleo and Tinombala. However, until now this terrorist group is difficult to destroy, due to the condition of the operating area in the form of dense tropical rainforest and steep slopes. This makes it difficult for troops to carry out chases and ...


Spatial Analysis Of Big Data Industrial Agglomeration And Development In China, Yanru LU, Kai CAO 2021 Singapore Management University

Spatial Analysis Of Big Data Industrial Agglomeration And Development In China, Yanru Lu, Kai Cao

Research Collection School Of Information Systems

Nowadays, our daily life constantly creates and needs to utilize tremendous amounts of datasets. Fortunately, the technologies of the internet, both in software and hardware, have the capability to transmit, store, and operate big data. With China being the most populous country in the world, developing the big data industry is, therefore, seen as an urgent task. As generating industrial agglomeration is important for forming a mature industry, this study aims to characterize the phenomenon of big data industrial agglomeration in China, and to identify the factors for developing the big data industry using spatial analysis approaches and GIS technology ...


Cat Tracks – Tracking Wildlife Through Crowdsourcing Using Firebase, Tracy Ho 2020 San Jose State University

Cat Tracks – Tracking Wildlife Through Crowdsourcing Using Firebase, Tracy Ho

Master's Projects

Many mountain lions are killed in the state of California every year from roadkill. To reduce these numbers, it is important that a system be built to track where these mountain lions have been around. One such system could be built using the platform-as-a-service, Firebase. Firebase is a platform service that collects and manages data that comes in through a mobile application. For the development of cross-platform mobile applications, Flutter is used as a toolkit for developers for both iOS and Android. This entire system, Cat Tracks is proposed as a crowdsource platform to track wildlife, with the current focus ...


Data: The Good, The Bad And The Ethical, John D. Kelleher, Filipe Cabral Pinto, Luis M. Cortesao 2020 Technological University Dublin

Data: The Good, The Bad And The Ethical, John D. Kelleher, Filipe Cabral Pinto, Luis M. Cortesao

Articles

It is often the case with new technologies that it is very hard to predict their long-term impacts and as a result, although new technology may be beneficial in the short term, it can still cause problems in the longer term. This is what happened with oil by-products in different areas: the use of plastic as a disposable material did not take into account the hundreds of years necessary for its decomposition and its related long-term environmental damage. Data is said to be the new oil. The message to be conveyed is associated with its intrinsic value. But as in ...


The Algorithm Project Research And Modeling Of Information Systems, Victoria Kuznetsova, Ким Елена, С.Б. Довлетова, Михриддин Рахимов, Gulnora Muxtorova 2020 “Bulletin of TUIT: Management and Communication Technologies”

The Algorithm Project Research And Modeling Of Information Systems, Victoria Kuznetsova, Ким Елена, С.Б. Довлетова, Михриддин Рахимов, Gulnora Muxtorova

Bulletin of TUIT: Management and Communication Technologies

Pre-project research is a strategic stage of the object design process, based on the results of which a decision is made on the level of competitiveness, development prospects, setting a task for the project, labor intensity and feasibilityof creating a system in general.

The existing methods of pre-project research have a high degree of generalization and are practically not formalized in any way. The disadvantage of these methods is that they consider only specific individual prototypes and are aimed at finding solutions to current problems and eliminating individual shortcomings of a particular prototype. Thus, it Is Concluded that It Is ...


A Near-Optimal Change-Detection Based Algorithm For Piecewise-Stationary Combinatorial Semi-Bandits, Huozhi ZHOU, Lingda WANG, Lav N. VARSHNEY, Ee Peng LIM 2020 Singapore Management University

A Near-Optimal Change-Detection Based Algorithm For Piecewise-Stationary Combinatorial Semi-Bandits, Huozhi Zhou, Lingda Wang, Lav N. Varshney, Ee Peng Lim

Research Collection School Of Information Systems

We investigate the piecewise-stationary combinatorial semi-bandit problem. Compared to the original combinatorial semi-bandit problem, our setting assumes the reward distributions of base arms may change in a piecewise-stationary manner at unknown time steps. We propose an algorithm, GLR-CUCB, which incorporates an efficient combinatorial semi-bandit algorithm, CUCB, with an almost parameter-free change-point detector, the Generalized Likelihood Ratio Test (GLRT). Our analysis shows that the regret of GLR-CUCB is upper bounded by O(√NKT logT), where N is the number of piecewise-stationary segments, K is the number of base arms, and T is the number of time steps. As a complement, we ...


Differential Privacy Protection Over Deep Learning: An Investigation Of Its Impacted Factors, Ying LIN, Ling-Yan BAO, Ze-Minghui LI, Shu-Sheng SI, Chao-Hsien CHU 2020 Yunnan University

Differential Privacy Protection Over Deep Learning: An Investigation Of Its Impacted Factors, Ying Lin, Ling-Yan Bao, Ze-Minghui Li, Shu-Sheng Si, Chao-Hsien Chu

Research Collection School Of Information Systems

Deep learning (DL) has been widely applied to achieve promising results in many fields, but it still exists various privacy concerns and issues. Applying differential privacy (DP) to DL models is an effective way to ensure privacy-preserving training and classification. In this paper, we revisit the DP stochastic gradient descent (DP-SGD) method, which has been used by several algorithms and systems and achieved good privacy protection. However, several factors, such as the sequence of adding noise, the models used etc., may impact its performance with various degrees. We empirically show that adding noise first and clipping second will not only ...


Interventional Few-Shot Learning, Zhongqi YUE, ZHANG Hanwang, Qianru SUN, Xian-Sheng HUA 2020 Singapore Management University

Interventional Few-Shot Learning, Zhongqi Yue, Zhang Hanwang, Qianru Sun, Xian-Sheng Hua

Research Collection School Of Information Systems

We uncover an ever-overlooked deficiency in the prevailing Few-Shot Learning (FSL) methods: the pre-trained knowledge is indeed a confounder that limits the performance. This finding is rooted from our causal assumption: a Structural Causal Model (SCM) for the causalities among the pre-trained knowledge, sample features, and labels. Thanks to it, we propose a novel FSL paradigm: Interventional Few-Shot Learning (IFSL). Specifically, we develop three effective IFSL algorithmic implementations based on the backdoor adjustment, which is essentially a causal intervention towards the SCM of many-shot learning: the upper-bound of FSL in a causal view. It is worth noting that the contribution ...


Debunking Rumors On Twitter With Tree Transformer, Jing MA, Wei GAO 2020 Singapore Management University

Debunking Rumors On Twitter With Tree Transformer, Jing Ma, Wei Gao

Research Collection School Of Information Systems

Rumors are manufactured with no respect for accuracy, but can circulate quickly and widely by "word-of-post" through social media conversations. Conversation tree encodes important information indicative of the credibility of rumor. Existing conversation-based techniques for rumor detection either just strictly follow tree edges or treat all the posts fully-connected during feature learning. In this paper, we propose a novel detection model based on tree transformer to better utilize user interactions in the dialogue where post-level self-attention plays the key role for aggregating the intra-/inter-subtree stances. Experimental results on the TWITTER and PHEME datasets show that the proposed approach consistently ...


A Bert-Based Dual Embedding Model For Chinese Idiom Prediction, Minghuan TAN, Jing JIANG 2020 Singapore Management University

A Bert-Based Dual Embedding Model For Chinese Idiom Prediction, Minghuan Tan, Jing Jiang

Research Collection School Of Information Systems

Chinese idioms are special fixed phrases usually derived from ancient stories, whose meanings are oftentimes highly idiomatic and non-compositional. The Chinese idiom prediction task is to select the correct idiom from a set of candidate idioms given a context with a blank. We propose a BERT-based dual embedding model to encode the contextual words as well as to learn dual embeddings of the idioms. Specifically, we first match the embedding of each candidate idiom with the hidden representation corresponding to the blank in the context. We then match the embedding of each candidate idiom with the hidden representations of all ...


Teaching Applications And Implications Of Blockchain Via Project-Based Learning: A Case Study, Kevin Mentzer, Mark Frydenberg, David J. Yates 2020 Bryant University

Teaching Applications And Implications Of Blockchain Via Project-Based Learning: A Case Study, Kevin Mentzer, Mark Frydenberg, David J. Yates

Computer Information Systems Journal Articles

This paper presents student projects analyzing or using blockchain technologies, created by students enrolled in courses dedicated to teaching blockchain, at two different universities during the 2018-2019 academic year. Students explored perceptions related to storing private healthcare information on a blockchain, managing the security of Internet of Things devices, maintaining public governmental records, and creating smart contracts. The course designs, which were centered around project-based learning, include self-regulated learning and peer feedback as ways to improve student learning. Students either wrote a research paper or worked in teams on a programming project to build and deploy a blockchain-based application using ...


Blockchain-Based Public Auditing And Secure Deduplication With Fair Arbitration, Haoran YUAN, Xiaofeng CHEN, Jianfeng WANG, Jiaming YUAN, Hongyang YAN, Willy SUSILO 2020 Singapore Management University

Blockchain-Based Public Auditing And Secure Deduplication With Fair Arbitration, Haoran Yuan, Xiaofeng Chen, Jianfeng Wang, Jiaming Yuan, Hongyang Yan, Willy Susilo

Research Collection School Of Information Systems

Data auditing enables data owners to verify the integrity of their sensitive data stored at an untrusted cloud without retrieving them. This feature has been widely adopted by commercial cloud storage. However, the existing approaches still have some drawbacks. On the one hand, the existing schemes have a defect of fair arbitration, i.e., existing auditing schemes lack an effective method to punish the malicious cloud service provider (CSP) and compensate users whose data integrity is destroyed. On the other hand, a CSP may store redundant and repetitive data. These redundant data inevitably increase management overhead and computational cost during ...


Nearest Centroid: A Bridge Between Statistics And Machine Learning, M. THULASIDAS 2020 Singapore Management University

Nearest Centroid: A Bridge Between Statistics And Machine Learning, M. Thulasidas

Research Collection School Of Information Systems

In order to guide our students of machine learning in their statistical thinking, we need conceptually simple and mathematically defensible algorithms. In this paper, we present the Nearest Centroid algorithm (NC) algorithm as a pedagogical tool, combining the key concepts behind two foundational algorithms: K-Means clustering and K Nearest Neighbors (k- NN). In NC, we use the centroid (as defined in the K-Means algorithm) of the observations belonging to each class in our training data set and its distance from a new observation (similar to k-NN) for class prediction. Using this obvious extension, we will illustrate how the concepts of ...


Secure Answer Book And Automatic Grading, M. THULASIDAS 2020 Singapore Management University

Secure Answer Book And Automatic Grading, M. Thulasidas

Research Collection School Of Information Systems

In response to the growing need to perform assess- ments online, we have developed a secure answer book, as well as a tool for automatically grading it for our course on spread- sheet modeling. We applied these techniques to a cohort of about 160 students who took the course last term. In this paper, we describe the design, implementation and the techniques em- ployed to enhance both the security of the answer book and the ease, accuracy and consistency of grading. In addition, we sum- marize the experience and takeaways, both from the instructor and the student perspectives. Although the ...


Causal Intervention For Weakly-Supervised Semantic Segmentation, ZHANG Dong, Hanwang ZHANG, Jinhui TANG, Xian-Sheng HUA, Qianru SUN 2020 Singapore Management University

Causal Intervention For Weakly-Supervised Semantic Segmentation, Zhang Dong, Hanwang Zhang, Jinhui Tang, Xian-Sheng Hua, Qianru Sun

Research Collection School Of Information Systems

We present a causal inference framework to improve Weakly-Supervised Semantic Segmentation (WSSS). Specifically, we aim to generate better pixel-level pseudo-masks by using only image-level labels --- the most crucial step in WSSS. We attribute the cause of the ambiguous boundaries of pseudo-masks to the confounding context, e.g., the correct image-level classification of "horse'' and "person'' may be not only due to the recognition of each instance, but also their co-occurrence context, making the model inspection (e.g., CAM) hard to distinguish between the boundaries. Inspired by this, we propose a structural causal model to analyze the causalities among images, contexts ...


Renewal Of An Information Systems Curriculum To Support Career Based Tracks: A Case Study, GOTTIPATI Swapna, SHANKARARAMAN, Venky, Kyong Jin SHIM 2020 Singapore Management University

Renewal Of An Information Systems Curriculum To Support Career Based Tracks: A Case Study, Gottipati Swapna, Shankararaman, Venky, Kyong Jin Shim

Research Collection School Of Information Systems

The pace at which technology redefines traditional job functions is picking up rapidly. This trend is triggered particularly by advances in analytics, security, cloud computing, Artificial Intelligence and big data. The purpose of this paper is to present a case study on our approach to renewing an undergraduate IS Major curriculum to align with the needs of the industry. We adopt a survey based approach to study Information Systems (IS) graduate skills requirements and re-design the curriculum framework for the IS program at our school. The paper describes in detail the process, the redesigned IS curriculum, the impact of the ...


An Analysis Of Technological Components In Relation To Privacy In A Smart City, Kayla Rutherford, Ben Lands, A. J. Stiles 2020 James Madison University

An Analysis Of Technological Components In Relation To Privacy In A Smart City, Kayla Rutherford, Ben Lands, A. J. Stiles

James Madison Undergraduate Research Journal (JMURJ)

A smart city is an interconnection of technological components that store, process, and wirelessly transmit information to enhance the efficiency of applications and the individuals who use those applications. Over the course of the 21st century, it is expected that an overwhelming majority of the world’s population will live in urban areas and that the number of wireless devices will increase. The resulting increase in wireless data transmission means that the privacy of data will be increasingly at risk. This paper uses a holistic problem-solving approach to evaluate the security challenges posed by the technological components that make up ...


A Framework For Identifying Host-Based Artifacts In Dark Web Investigations, Arica Kulm 2020 Dakota State University

A Framework For Identifying Host-Based Artifacts In Dark Web Investigations, Arica Kulm

Masters Theses & Doctoral Dissertations

The dark web is the hidden part of the internet that is not indexed by search engines and is only accessible with a specific browser like The Onion Router (Tor). Tor was originally developed as a means of secure communications and is still used worldwide for individuals seeking privacy or those wanting to circumvent restrictive regimes. The dark web has become synonymous with nefarious and illicit content which manifests itself in underground marketplaces containing illegal goods such as drugs, stolen credit cards, stolen user credentials, child pornography, and more (Kohen, 2017). Dark web marketplaces contribute both to illegal drug usage ...


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