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Articles 2731 - 2760 of 8706
Full-Text Articles in Entire DC Network
Culturally Diverse Expert Teams Have Yet To Bring Comprehensive Linguistic Diversity To Intergovernmental Ecosystem Assessments, Abigail J. Lynch, Fernández-Llamazares Álvaro, Ignacio Palomo, Pedro Jaureguiberry, Amano Tatsuya, Zeenatul Basher, Michelle Lim, Tuyeni Heita Mwampamba, Aibek Samakov, Odirilwe Selomane, Michelle Mei Ling Lim
Culturally Diverse Expert Teams Have Yet To Bring Comprehensive Linguistic Diversity To Intergovernmental Ecosystem Assessments, Abigail J. Lynch, Fernández-Llamazares Álvaro, Ignacio Palomo, Pedro Jaureguiberry, Amano Tatsuya, Zeenatul Basher, Michelle Lim, Tuyeni Heita Mwampamba, Aibek Samakov, Odirilwe Selomane, Michelle Mei Ling Lim
Research Collection Yong Pung How School Of Law
Multicultural representation is a stated goal of many global scientific assessment processes. These processes aim to mobilize a broader, more diverse knowledge base and increase legitimacy and inclusiveness of these assessment processes. Often, enhancing cultural diversity is encouraged through involvement of diverse expert teams and sources of knowledge in different languages. In this article, we examine linguistic diversity, as one representation of cultural diversity, in the eight published assessments of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES). Our results show that the IPBES assessment outputs are disproportionately filtered through English-language literature and authors from Anglophone countries. To …
Hurricane Harvey: Equal Opportunity Storm Or Disparate Disaster?, Katherine Lieberknecht, Deidre Zoll, Junfeng Jiao, Katherine Castles
Hurricane Harvey: Equal Opportunity Storm Or Disparate Disaster?, Katherine Lieberknecht, Deidre Zoll, Junfeng Jiao, Katherine Castles
Research Collection College of Integrative Studies
In the wake of Hurricane Harvey, multiple media sources claimed the event was an “equal opportunity” storm. These claims challenge existing social vulnerability research that finds marginalised groups have both unequal risk exposure and subsequent differential impacts from disasters (Cutter, Boruff, and Shirley 2003, “Assessing Current and Future Freshwater Flood Risk from North Atlantic Tropical Cyclones via Insurance Claims.” Scientific Reports 7 (February): 41609; Faber 2015, “Superstorm Sandy and the Demographics of Flood Risk in New York City.” Human Ecology 43 (3): 363–378. https://doi.org/10.1007/s10745-015-9757-x; Thomas et al. 2013, Social Vulnerability to Disasters. Boca Raton, FL: CRC Press). To understand the …
Multi-Decoder Attention Model With Embedding Glimpse For Solving Vehicle Routing Problems, Liang Xin, Wen Song, Zhiguang Cao, Jie Zhang
Multi-Decoder Attention Model With Embedding Glimpse For Solving Vehicle Routing Problems, Liang Xin, Wen Song, Zhiguang Cao, Jie Zhang
Research Collection School Of Computing and Information Systems
We present a novel deep reinforcement learning method to learn construction heuristics for vehicle routing problems. In specific, we propose a Multi-Decoder Attention Model (MDAM) to train multiple diverse policies, which effectively increases the chance of finding good solutions compared with existing methods that train only one policy. A customized beam search strategy is designed to fully exploit the diversity of MDAM. In addition, we propose an Embedding Glimpse layer in MDAM based on the recursive nature of construction, which can improve the quality of each policy by providing more informative embeddings. Extensive experiments on six different routing problems show …
Differential Training: A Generic Framework To Reduce Label Noises For Android Malware Detection, Jiayun Xu, Yingjiu Li, Robert H. Deng
Differential Training: A Generic Framework To Reduce Label Noises For Android Malware Detection, Jiayun Xu, Yingjiu Li, Robert H. Deng
Research Collection School Of Computing and Information Systems
A common problem in machine learning-based malware detection is that training data may contain noisy labels and it is challenging to make the training data noise-free at a large scale. To address this problem, we propose a generic framework to reduce the noise level of training data for the training of any machine learning-based Android malware detection. Our framework makes use of all intermediate states of two identical deep learning classification models during their training with a given noisy training dataset and generate a noise-detection feature vector for each input sample. Our framework then applies a set of outlier detection …
Evidence Aware Neural Pornographic Text Identification For Child Protection, Kaisong Song, Yangyang Kang, Wei Gao, Zhe Gao, Changlong Sun, Xiaozhong Liu
Evidence Aware Neural Pornographic Text Identification For Child Protection, Kaisong Song, Yangyang Kang, Wei Gao, Zhe Gao, Changlong Sun, Xiaozhong Liu
Research Collection School Of Computing and Information Systems
Identifying pornographic text online is practically useful to protect children from access to such adult content. However, some authors may intentionally avoid using sensitive words in their pornographic texts to take advantage of the lack of human audits. Without prior knowledge guidance, real semantics of such pornographic text is difficult to understand by existing methods due to its high context-sensitivity and heavy usage of figurative language, which brings huge challenges to the porn detection systems used in social media platforms. In this paper, we approach to the problem as a document-level porn identification task by locating and integrating sentence-level evidence …
Terrace-Based Food Counting And Segmentation, Huu-Thanh Nguyen, Chong-Wah Ngo
Terrace-Based Food Counting And Segmentation, Huu-Thanh Nguyen, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
This paper represents object instance as a terrace, where the height of terrace corresponds to object attention while the evolution of layers from peak to sea level represents the complexity in drawing the finer boundary of an object. A multitask neural network is presented to learn the terrace representation. The attention of terrace is leveraged for instance counting, and the layers provide prior for easy-to-hard pathway of progressive instance segmentation. We study the model for counting and segmentation for a variety of food instances, ranging from Chinese, Japanese to Western food. This paper presents how the terrace model deals with …
Qlens: Visual Analytics Of Multi-Step Problem-Solving Behaviors For Improving Question Design, Meng Xia, Reshika P. Velumani, Yong Wang, Huamin Qu, Xiaojuan Ma
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 Computing and 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 from …
Contingency Theory Of Strategic Conflict Management: Explicating A “Grand” Theory Of Public Relations, Pang, A., Yan Jin, Glen T. Cameron
Contingency Theory Of Strategic Conflict Management: Explicating A “Grand” Theory Of Public Relations, Pang, A., Yan Jin, Glen T. Cameron
Research Collection Lee Kong Chian School Of Business
Since the 1990s, the contingency theory of strategic conflict management has evolved into its own, and emerged as an empirically tested perspective. Coombs (2010) has described the contingency theory as a “grand theory of public relations” (p.41). A “grand theory” is one which “seeks to explain how public relations as a whole operates”; grand theories seek to explain an entire discipline and “can be adapted to specific areas of the discipline” (Coombs 2010: 41). Today, it is one of the top six theories applied in crisis communication research (An and Cheng 2010). The purpose of this chapter is threefold: First, …
Fireeye: Cybersecurity In Action, Singapore Management University
Fireeye: Cybersecurity In Action, Singapore Management University
Perspectives@SMU
FireEye built its success on its ‘Human + AI’ philosophy. But can a cybersecurity firm get ahead of the attackers and predict an attack…on itself?
Smu’S Computing School Heralds A Fresh Chapter With New Name, Singapore Management University
Smu’S Computing School Heralds A Fresh Chapter With New Name, Singapore Management University
SMU Press Releases and News
The Singapore Management University (SMU) today announced that its School of Information Systems (SIS) has been renamed School of Computing and Information Systems (SCIS) to project the expanded aspirations and role of the School beyond Information Systems to include computing which encompasses Computer Science, Computer Engineering and Software Engineering.
Situational Judgment Tests: From Low-Fidelity Simulations To Alternative Measures Of Personality And The Person-Situation Interplay, Filip Lievens, Philipp Schäpers, Christoph N. Herde
Situational Judgment Tests: From Low-Fidelity Simulations To Alternative Measures Of Personality And The Person-Situation Interplay, Filip Lievens, Philipp Schäpers, Christoph N. Herde
Research Collection Lee Kong Chian School Of Business
In employment and education settings, Situational Judgment Tests (SJTs) have made strong inroads. So far, however, they are still underutilized in personality research. The objective of this chapter is to outline how SJTs might be adapted to measure personality traits, shed light onto the person-situation interplay, and stimulate research on it. We start by discussing the traditional simulation-based view on SJTs, including information on their development and research results. Next, we show how more recent versions have started to assess people’s knowledge of relevant behavior related to personality traits. Finally, we specify various strategies as to how SJTs might be …
Pay For Performance: When Does It Fail?, Nirmalya Kumar, Madan Pillutla
Pay For Performance: When Does It Fail?, Nirmalya Kumar, Madan Pillutla
Research Collection Lee Kong Chian School Of Business
The consensus in social psychology is that monetary incentives for performance have a detrimental impact on individual performance. Yes, under certain specific and limited conditions, rewards can reduce performance. Yet pay for performance schemes are ubiquitous. How can we resolve this divergence between theoretical recommendations and observed practices? Nirmalya Kumar and Madan Pillutla recommend solving the problem by designing smarter incentives that avoid these detrimental effects.
Prompt-Specificity In Scenario-Based Assessments: Associations With Personality Versus Knowledge And Effects On Predictive Validity, Thomas Rockstuhl, Filip Lievens
Prompt-Specificity In Scenario-Based Assessments: Associations With Personality Versus Knowledge And Effects On Predictive Validity, Thomas Rockstuhl, Filip Lievens
Research Collection Lee Kong Chian School Of Business
Many scenario-based assessments (e.g., interviews, assessment center exercises, work samples, simulations, and situational judgment tests) use prompts (i.e., cues provided to respondents to increase the likelihood that the information received from them is clear, sufficient, and job-related). However, a dilemma for practitioners and researchers is how general or specific one should prompt people's answers. We posit that such differences in prompt-specificity (i.e., extent to which prompts cue performance criteria) have important implications for the predictive validity of scenario-based assessment scores. Drawing on the interplay of situation construal and situational strength theory, we propose that prompt-specificity leads to differential relationships between …
Crowdfunding Digital Platforms: Backer Networks And Their Impact On Project Outcomes, Yee Heng Tan, Srinivas K. Reddy
Crowdfunding Digital Platforms: Backer Networks And Their Impact On Project Outcomes, Yee Heng Tan, Srinivas K. Reddy
Research Collection Lee Kong Chian School Of Business
Crowdfunding platforms serve to connect project creators and backers. Previous research has explored several project and platform determinants that impact crowdfunding outcomes. However, there has been limited research on these determinants at an individual level. Our paper addresses how backers may influence the outcomes of projects in crowdfunding platforms. We explore several methods commonly used in the industry to identify influence and show that centrality measures through a backer affiliation network best exemplifies influence. Using data from Kickstarter, we construct a weighted backer network based on 52,678 common projects backed by 11,134 backers. Controlling for digital media mentions and project …
Adversarial Specification Mining, Hong Jin Kang, David Lo
Adversarial Specification Mining, Hong Jin Kang, David Lo
Research Collection School Of Computing and Information Systems
There have been numerous studies on mining temporal specifications from execution traces. These approaches learn finite-state automata (FSA) from execution traces when running tests. To learn accurate specifications of a software system, many tests are required. Existing approaches generalize from a limited number of traces or use simple test generation strategies. Unfortunately, these strategies may not exercise uncommon usage patterns of a software system. To address this problem, we propose a new approach, adversarial specification mining, and develop a prototype, DICE (Diversity through Counter-Examples). DICE has two components: DICE-Tester and DICE-Miner. After mining Linear Temporal Logic specifications from an input …
A Data-Driven Method For Online Monitoring Tube Wall Thinning Process In Dynamic Noisy Environment, Chen Zhang, Jun Long Lim, Ouyang Liu, Aayush Madan, Yongwei Zhu, Shili Xiang, Kai Wu, Rebecca Yen-Ni Wong, Jiliang Eugene Phua, Karan M. Sabnani, Keng Boon Siah, Wenyu Jiang, Yixin Wang, Emily Jianzhong Hao, Hoi, Steven C. H.
A Data-Driven Method For Online Monitoring Tube Wall Thinning Process In Dynamic Noisy Environment, Chen Zhang, Jun Long Lim, Ouyang Liu, Aayush Madan, Yongwei Zhu, Shili Xiang, Kai Wu, Rebecca Yen-Ni Wong, Jiliang Eugene Phua, Karan M. Sabnani, Keng Boon Siah, Wenyu Jiang, Yixin Wang, Emily Jianzhong Hao, Hoi, Steven C. H.
Research Collection School Of Computing and Information Systems
Tube internal erosion, which corresponds to its wall thinning process, is one of the major safety concerns for tubes. Many sensing technologies have been developed to detect a tube wall thinning process. Among them, fiber Bragg grating (FBG) sensors are the most popular ones due to their precise measurement properties. Most of the current works focus on how to design different types of FBG sensors according to certain physical laws and only test their sensors in controlled laboratory conditions. However, in practice, an industrial system usually suffers from harsh and dynamic environmental conditions, and FBG signals are affected by many …
Smart Scribbles For Image Matting, Yang Xin, Yu Qiao, Shaozhe Chen, Shengfeng He, Baocai Yin, Qiang Zhang, Xiaopeng Wei, Rynson W. H. Lau
Smart Scribbles For Image Matting, Yang Xin, Yu Qiao, Shaozhe Chen, Shengfeng He, Baocai Yin, Qiang Zhang, Xiaopeng Wei, Rynson W. H. Lau
Research Collection School Of Computing and Information Systems
Image matting is an ill-posed problem that usually requires additional user input, such as trimaps or scribbles. Drawing a fine trimap requires a large amount of user effort, while using scribbles can hardly obtain satisfactory alpha mattes for non-professional users. Some recent deep learning-based matting networks rely on large-scale composite datasets for training to improve performance, resulting in the occasional appearance of obvious artifacts when processing natural images. In this article, we explore the intrinsic relationship between user input and alpha mattes and strike a balance between user effort and the quality of alpha mattes. In particular, we propose an …
Performance-Based Iadl Evaluation Of Older Adults With Cognitive Impairment Within A Smart Home: A Feasibility Study, Iris Rawtaer, Khalid Abdul Jabbar, Xiao Liu, Thit Thit Htat Ying, Anh Thuy Giang, Philip Lin Kiat Yap, Rachel Chin Yee Cheong, Hwee-Pink Tan, Pius Lee Wei Qi, Shiou Liang Wee, Tze Pin Ng
Performance-Based Iadl Evaluation Of Older Adults With Cognitive Impairment Within A Smart Home: A Feasibility Study, Iris Rawtaer, Khalid Abdul Jabbar, Xiao Liu, Thit Thit Htat Ying, Anh Thuy Giang, Philip Lin Kiat Yap, Rachel Chin Yee Cheong, Hwee-Pink Tan, Pius Lee Wei Qi, Shiou Liang Wee, Tze Pin Ng
Research Collection School Of Computing and Information Systems
Introduction Mild cognitive impairment (MCI) is characterized by subtle deficits that functional assessment via informant-report measures may not detect. Sensors can potentially detect deficits in everyday functioning in MCI. This study aims to establish feasibility and acceptability of using sensors in a smart home for performance-based assessments of two instrumental activities of daily living (IADLs). Methods Thirty-five older adults (>65 years) performed two IADL tasks in a smart home laboratory equipped with sensors and a web camera. Participants' cognitive states were determined using published criteria including measures of global cognition and comprehensive neuropsychological test batteries. Selected subtasks of the …
Partial Adversarial Behavior Deception In Security Games, Thanh H. Nguyen, Arunesh Sinha, He He
Partial Adversarial Behavior Deception In Security Games, Thanh H. Nguyen, Arunesh Sinha, He He
Research Collection School Of Computing and Information Systems
Learning attacker behavior is an important research topic in security games as security agencies are often uncertain about attackers’ decision making. Previous work has focused on developing various behavioral models of attackers based on historical attack data. However, a clever attacker can manipulate its attacks to fail such attack-driven learning, leading to ineffective defense strategies. We study attacker behavior deception with three main contributions. First, we propose a new model, named partial behavior deception model, in which there is a deceptive attacker (among multiple attackers) who controls a portion of attacks. Our model captures real-world security scenarios such as wildlife …
Coherence And Identity Learning For Arbitrary-Length Face Video Generation, Shuquan Ye, Chu Han, Jiaying Lin, Guoqiang Han, Shengfeng He
Coherence And Identity Learning For Arbitrary-Length Face Video Generation, Shuquan Ye, Chu Han, Jiaying Lin, Guoqiang Han, Shengfeng He
Research Collection School Of Computing and Information Systems
Face synthesis is an interesting yet challenging task in computer vision. It is even much harder to generate a portrait video than a single image. In this paper, we propose a novel video generation framework for synthesizing arbitrary-length face videos without any face exemplar or landmark. To overcome the synthesis ambiguity of face video, we propose a divide-and-conquer strategy to separately address the video face synthesis problem from two aspects, face identity synthesis and rearrangement. To this end, we design a cascaded network which contains three components, Identity-aware GAN (IA-GAN), Face Coherence Network, and Interpolation Network. IA-GAN is proposed to …
Loneliness, Sense Of Control, And Risk Of Dementia In Healthy Older Adults: A Moderated Mediation Analysis, Hwajin Yang, Germaine Tng, Wee Qin Ng, Sujin Yang
Loneliness, Sense Of Control, And Risk Of Dementia In Healthy Older Adults: A Moderated Mediation Analysis, Hwajin Yang, Germaine Tng, Wee Qin Ng, Sujin Yang
Research Collection School of Social Sciences
Objectives: Despite the rising prevalence of dementia, little research has been conducted to identify modifiable psychological factors that alleviate the risk of dementia in older adults and the underlying mechanisms. Given that loneliness is, in part, concomitant with a weakened sense of control, we examined whether sense of control would mediate the relation between loneliness and dementia risk. Further, considering that working -memory capacity is a critical cognitive resource that serves as a buffer against age-related cognitive decline, we examined a second-order moderated mediational model whereby working-memory capacity moderates the relation between control beliefs and dementia risk in older adults. …
Scalable Online Vetting Of Android Apps For Measuring Declared Sdk Versions And Their Consistency With Api Calls, Daoyuan Wu, Debin Gao, David Lo
Scalable Online Vetting Of Android Apps For Measuring Declared Sdk Versions And Their Consistency With Api Calls, Daoyuan Wu, Debin Gao, David Lo
Research Collection School Of Computing and Information Systems
Android has been the most popular smartphone system with multiple platform versions active in the market. To manage the application’s compatibility with one or more platform versions, Android allows apps to declare the supported platform SDK versions in their manifest files. In this paper, we conduct a systematic study of this modern software mechanism. Our objective is to measure the current practice of declared SDK versions (which we term as DSDK versions afterwards) in real apps, and the (in)consistency between DSDK versions and their host apps’ API calls. To successfully analyze a modern dataset of 22,687 popular apps (with an …
Understanding The Inter-Domain Presence Of Research Topics In The Computing Discipline, Subhajit Datta, Rumana Lakdawala, Santonu Sarkar
Understanding The Inter-Domain Presence Of Research Topics In The Computing Discipline, Subhajit Datta, Rumana Lakdawala, Santonu Sarkar
Research Collection School Of Computing and Information Systems
The very nature of scientific inquiry encourages the flow of ideas across research domains in a discipline. Research topics with higher inter-domain presence tend to attract higher attention at individual and organizational levels. This is more pronounced in a discipline like computing, with its deeply intertwined ideas and strong connections with technology. In this paper, we study corpora of research publications across four domains of the computing discipline – covering more than 150,000 papers, involving more than 200,000 authors over 55 years and 175 publication venues – to examine the influences on inter-domain presence of research topics. We find statistically …
Smart Contracts: Will Fintech Be The Catalyst For The Next Global Financial Crisis?, Randall Duran, Paul Griffin
Smart Contracts: Will Fintech Be The Catalyst For The Next Global Financial Crisis?, Randall Duran, Paul Griffin
Research Collection School Of Computing and Information Systems
Purpose: This paper aims to examine the risks associated with smart contracts, a disruptive financial technology (FinTech) innovation, and assesses how in the future they could threaten the integrity of the global financial system. Design/methodology/approach: A qualitative approach is used to identify risk factors related to the use of new financial innovations, by examining how over-the-counter (OTC) derivatives contributed to the Global Financial Crisis (GFC) which occurred during 2007 and 2008. Based on this analysis, the potential for similar concerns with smart contracts are evaluated, drawing on the failure of The DAO on the Ethereum blockchain, which involved the loss …
A Continual Deepfake Detection Benchmark: Dataset, Methods, And Essentials, Chuqiao Li, Zhiwu Huang, Danda Pani Paudel, Yabin Wang, Mohamad Shahbazi, Xiaopeng Hong, Van Gool Luc
A Continual Deepfake Detection Benchmark: Dataset, Methods, And Essentials, Chuqiao Li, Zhiwu Huang, Danda Pani Paudel, Yabin Wang, Mohamad Shahbazi, Xiaopeng Hong, Van Gool Luc
Research Collection School Of Computing and Information Systems
There have been emerging a number of benchmarks and techniques for the detection of deepfakes. However, very few works study the detection of incrementally appearing deepfakes in the real-world scenarios. To simulate the wild scenes, this paper suggests a continual deepfake detection benchmark (CDDB) over a new collection of deepfakes from both known and unknown generative models. The suggested CDDB designs multiple evaluations on the detection over easy, hard, and long sequence of deepfake tasks, with a set of appropriate measures. In addition, we exploit multiple approaches to adapt multiclass incremental learning methods, commonly used in the continual visual recognition, …
Why My Code Summarization Model Does Not Work: Code Comment Improvement With Category Prediction, Qiuyuan Chen, Xin Xia, Han Hu, David Lo, Shanping Li
Why My Code Summarization Model Does Not Work: Code Comment Improvement With Category Prediction, Qiuyuan Chen, Xin Xia, Han Hu, David Lo, Shanping Li
Research Collection School Of Computing and Information Systems
Code summarization aims at generating a code comment given a block of source code and it is normally performed by training machine learning algorithms on existing code block-comment pairs. Code comments in practice have different intentions. For example, some code comments might explain how the methods work, while others explain why some methods are written. Previous works have shown that a relationship exists between a code block and the category of a comment associated with it. In this article, we aim to investigate to which extent we can exploit this relationship to improve code summarization performance. We first classify comments …
Technical Q8a Site Answer Recommendation Via Question Boosting, Zhipeng Gao, Xin Xia, David Lo, John Grundy
Technical Q8a Site Answer Recommendation Via Question Boosting, Zhipeng Gao, Xin Xia, David Lo, John Grundy
Research Collection School Of Computing and Information Systems
Software developers have heavily used online question and answer platforms to seek help to solve their technical problems. However, a major problem with these technical Q&A sites is "answer hungriness" i.e., a large number of questions remain unanswered or unresolved, and users have to wait for a long time or painstakingly go through the provided answers with various levels of quality. To alleviate this time-consuming problem, we propose a novel DeepAns neural network-based approach to identify the most relevant answer among a set of answer candidates. Our approach follows a three-stage process: question boosting, label establishment, and answer recommendation. Given …
Context-Aware Retrieval-Based Deep Commit Message Generation, Haoye Wang, Xin Xia, David Lo, Qiang He, Xinyu Wang, John Grundy
Context-Aware Retrieval-Based Deep Commit Message Generation, Haoye Wang, Xin Xia, David Lo, Qiang He, Xinyu Wang, John Grundy
Research Collection School Of Computing and Information Systems
Commit messages recorded in version control systems contain valuable information for software development, maintenance, and comprehension. Unfortunately, developers often commit code with empty or poor quality commit messages. To address this issue, several studies have proposed approaches to generate commit messages from commit diffs. Recent studies make use of neural machine translation algorithms to try and translate git diffs into commit messages and have achieved some promising results. However, these learning-based methods tend to generate high-frequency words but ignore low-frequency ones. In addition, they suffer from exposure bias issues, which leads to a gap between training phase and testing phase. …
Do Blockchain And Iot Architecture Create Informedness To Support Provenance Tracking In The Product Lifecycle?, Somnath Mazumdar, Thomas Jensen, Raghava Rao Mukkamala, Robert John Kauffman, Jan Damsgaard
Do Blockchain And Iot Architecture Create Informedness To Support Provenance Tracking In The Product Lifecycle?, Somnath Mazumdar, Thomas Jensen, Raghava Rao Mukkamala, Robert John Kauffman, Jan Damsgaard
Research Collection School Of Computing and Information Systems
Consumers often lack information about the origin and provenance of the products they buy. They may ask: Is a food product truly organic? Or, what is the origin of the gemstone in the ring I purchased? They also may have sustainability concerns about the footprint of a product at the end of its life. Producers and sellers, meanwhile, wish to know how longitudinal tracking of the provenance of products and their components can boost their sales prices and after-market value, and re- veal new business opportunities. We focus on how the product lifecycle (PLC) can be leveraged to track information …
Can We Trust Your Explanations? Sanity Checks For Interpreters In Android Malware Analysis, Min Fan, Wenying Wei, Xiaofei Xie, Yang Liu, Xiaohong Guan, Ting Liu
Can We Trust Your Explanations? Sanity Checks For Interpreters In Android Malware Analysis, Min Fan, Wenying Wei, Xiaofei Xie, Yang Liu, Xiaohong Guan, Ting Liu
Research Collection School Of Computing and Information Systems
With the rapid growth of Android malware, many machine learning-based malware analysis approaches are proposed to mitigate the severe phenomenon. However, such classifiers are opaque, non-intuitive, and difficult for analysts to understand the inner decision reason. For this reason, a variety of explanation approaches are proposed to interpret predictions by providing important features. Unfortunately, the explanation results obtained in the malware analysis domain cannot achieve a consensus in general, which makes the analysts confused about whether they can trust such results. In this work, we propose principled guidelines to assess the quality of five explanation approaches by designing three critical …