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Full-Text Articles in Entire DC Network
New Framework Of Password-Based Authenticated Key Exchange From Only-One Lossy Encryption, Haiyang Xue, Bao Li, Jingnan He
New Framework Of Password-Based Authenticated Key Exchange From Only-One Lossy Encryption, Haiyang Xue, Bao Li, Jingnan He
Research Collection School Of Computing and Information Systems
In this paper, we introduce a new framework of password-based key exchange (PAKE). Until now, most PAKEs are based on smooth projective hash function on secure encryption. Our PAKE does not rely on smooth projective hash function, and consists of a variate lossy encryption, called only-one lossy encryption, and indistinguishable plaintext checkable secure encryption. We also give construction of only-one lossy encryption based decisional Diffie Hellman (DDH) and learning with errors (LWE) assumptions. Although the instantiation based on DDH assumption does not improve efficiency of precious works, our framework provides more easier and elegant way to construct PAKE from LWE …
Cross-Modal Recipe Retrieval With Rich Food Attributes, Jingjing Chen, Chong-Wah Ngo, Tat-Seng Chua
Cross-Modal Recipe Retrieval With Rich Food Attributes, Jingjing Chen, Chong-Wah Ngo, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Food is rich of visible (e.g., colour, shape) and procedural (e.g., cutting, cooking) attributes. Proper leveraging of these attributes, particularly the interplay among ingredients, cutting and cooking methods, for health-related applications has not been previously explored. This paper investigates cross-modal retrieval of recipes, specifically to retrieve a text-based recipe given a food picture as query. As similar ingredient composition can end up with wildly different dishes depending on the cooking and cutting procedures, the difficulty of retrieval originates from fine-grained recognition of rich attributes from pictures. With a multi-task deep learning model, this paper provides insights on the feasibility of …
Pic2dish: A Customized Cooking Assistant System, Yongsheng An, Yu Cao, Jingjing Chen, Chong-Wah Ngo, Jia Jia, Huanbo Luan, Tat-Seng Chua
Pic2dish: A Customized Cooking Assistant System, Yongsheng An, Yu Cao, Jingjing Chen, Chong-Wah Ngo, Jia Jia, Huanbo Luan, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
The art of cooking is always fascinating. Nevertheless, reproducing a delicious dish that one has never encountered before is not easy. Even if the name of dish is known and the corresponding recipe could be retrieved, the right ingredients for cooking the dish may not be available due to factors such as geography region or season. Furthermore, knowing how to cut, cook and control timing may be challenging for one whose has no cooking experience. In this paper, an all-around cooking assistant mobile app, named Pic2Dish, is developed to help users who would like to cook a dish but neither …
Jsforce: A Forced Execution Engine For Malicious Javascript Detection, Xunchao Hu, Yao Cheng, Yue Duan, Andrew Henderson, Heng Yin
Jsforce: A Forced Execution Engine For Malicious Javascript Detection, Xunchao Hu, Yao Cheng, Yue Duan, Andrew Henderson, Heng Yin
Research Collection School Of Computing and Information Systems
The drastic increase of JavaScript exploitation attacks has led to a strong interest in developing techniques to analyze malicious JavaScript. Existing analysis techniques fall into two general categories: static analysis and dynamic analysis. Static analysis tends to produce inaccurate results (both false positive and false negative) and is vulnerable to a wide series of obfuscation techniques. Thus, dynamic analysis is constantly gaining popularity for exposing the typical features of malicious JavaScript. However, existing dynamic analysis techniques possess limitations such as limited code coverage and incomplete environment setup, leaving a broad attack surface for evading the detection. To overcome these limitations, …
Visual Sentiment Analysis For Review Images With Item-Oriented And User-Oriented Cnn, Quoc Tuan Truong, Hady W. Lauw
Visual Sentiment Analysis For Review Images With Item-Oriented And User-Oriented Cnn, Quoc Tuan Truong, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Online reviews are prevalent. When recounting their experience with a product, service, or venue, in addition to textual narration, a reviewer frequently includes images as photographic record. While textual sentiment analysis has been widely studied, in this paper we are interested in visual sentiment analysis to infer whether a given image included as part of a review expresses the overall positive or negative sentiment of that review. Visual sentiment analysis can be formulated as image classification using deep learning methods such as Convolutional Neural Networks or CNN. However, we observe that the sentiment captured within an image may be affected …
Sequential Schemes For Frequentist Estimation Of Properties In Statistical Model Checking, Cyrille Jegourel, Jun Sun, Jin Song Dong
Sequential Schemes For Frequentist Estimation Of Properties In Statistical Model Checking, Cyrille Jegourel, Jun Sun, Jin Song Dong
Research Collection School Of Computing and Information Systems
Statistical Model Checking (SMC) is an approximate verification method that overcomes the state space explosion problem for probabilistic systems by Monte Carlo simulations. Simulations might be however costly if many samples are required. It is thus necessary to implement efficient algorithms to reduce the sample size while preserving precision and accuracy. In the literature, some sequential schemes have been provided for the estimation of property occurrence based on predefined confidence and absolute or relative error. Nevertheless, these algorithms remain conservative and may result in huge sample sizes if the required precision standards are demanding. In this article, we compare some …
Nlp2code: Code Snippet Content Assist Via Natural Language Tasks, Brock A. Campbell, Christoph Treude
Nlp2code: Code Snippet Content Assist Via Natural Language Tasks, Brock A. Campbell, Christoph Treude
Research Collection School Of Computing and Information Systems
Developers increasingly take to the Internet for code snippets to integrate into their programs. To save developers the time required to switch from their development environments to a web browser in the quest for a suitable code snippet, we introduce NLP2Code, a content assist for code snippets. Unlike related tools, NLP2Code integrates directly into the source code editor and provides developers with a content assist feature to close the vocabulary gap between developers’ needs and code snippet meta data. Our preliminary evaluation of NLP2Code shows that the majority of invocations lead to code snippets rated as helpful by users and …
Loopster: Static Loop Termination Analysis, Xiaofei Xie, Bihuan Chen, Liang Zou, Shang-Wei Lin, Yang Liu, Xiaohong Li
Loopster: Static Loop Termination Analysis, Xiaofei Xie, Bihuan Chen, Liang Zou, Shang-Wei Lin, Yang Liu, Xiaohong Li
Research Collection School Of Computing and Information Systems
Loop termination is an important problem for proving the correctness of a system and ensuring that the system always reacts. Existing loop termination analysis techniques mainly depend on the synthesis of ranking functions, which is often expensive. In this paper, we present a novel approach, named Loopster, which performs an efficient static analysis to decide the termination for loops based on path termination analysis and path dependency reasoning. Loopster adopts a divide-and-conquer approach: (1) we extract individual paths from a target multi-path loop and analyze the termination of each path, (2) analyze the dependencies between each two paths, and then …
Code Coverage And Postrelease Defects: A Large-Scale Study On Open Source Projects, Pavneet Singh Kochhar, David Lo, Julia Lawall, Nachiappan Nagappan
Code Coverage And Postrelease Defects: A Large-Scale Study On Open Source Projects, Pavneet Singh Kochhar, David Lo, Julia Lawall, Nachiappan Nagappan
Research Collection School Of Computing and Information Systems
Testing is a pivotal activity in ensuring the quality of software. Code coverage is a common metric used as a yardstick to measure the efficacy and adequacy of testing. However, does higher coverage actually lead to a decline in postrelease bugs? Do files that have higher test coverage actually have fewer bug reports? The direct relationship between code coverage and actual bug reports has not yet been analyzed via a comprehensive empirical study on real bugs. Past studies only involve a few software systems or artificially injected bugs (mutants). In this empirical study, we examine these questions in the context …
Clsters: A General System For Reducing Errors Of Trajectories Under Challenging Localization Situations, Hao Wu, Weiwei Sun, Baihua Zheng, Li Yang, Wei Zhou
Clsters: A General System For Reducing Errors Of Trajectories Under Challenging Localization Situations, Hao Wu, Weiwei Sun, Baihua Zheng, Li Yang, Wei Zhou
Research Collection School Of Computing and Information Systems
Trajectory data generated by outdoor activities have great potential for location based services. However, depending on the localization technique used, certain trajectory data could contain large errors. For example, the error of trajectories generated by cellular-based localization techniques is around 100m which is ten times larger than that of GPS-based trajectories. Hence, enhancing the utility of those large-error trajectories becomes a challenge. In this paper we show how to improve the quality of trajectory data having large errors. Some existing works reduce the error through hardware which requires information such as the time of arrival (TOA), received signal strength indication …
Personality And Project Success: Insights From A Large-Scale Study With Professionals, Xin Xia, David Lo, Lingfeng Bao, Abhishek Sharma, Shanping Li
Personality And Project Success: Insights From A Large-Scale Study With Professionals, Xin Xia, David Lo, Lingfeng Bao, Abhishek Sharma, Shanping Li
Research Collection School Of Computing and Information Systems
A software project is typically completed as a result of a collective effort done by individuals of different personalities. Personality reflects differences among people in behaviour patterns, communication, cognition and emotion. It often impacts relationships and collaborative work, and software engineering teamwork is no exception. Some personalities are more likely to click while others to clash. A number of studies have investigated the relationship between personality and collaborative work success. However, most of them are done in a laboratory setting, do not involve professionals, or consider non software engineering tasks. Additionally, they only answer a limited set of questions, and …
Vurle: Automatic Vulnerability Detection And Repair By Learning From Examples, Ma Siqi, Ferdian Thung, David Lo, Cong Sun, Robert H. Deng
Vurle: Automatic Vulnerability Detection And Repair By Learning From Examples, Ma Siqi, Ferdian Thung, David Lo, Cong Sun, Robert H. Deng
Research Collection School Of Computing and Information Systems
Vulnerability becomes a major threat to the security of many systems. Attackers can steal private information and perform harmful actions by exploiting unpatched vulnerabilities. Vulnerabilities often remain undetected for a long time as they may not affect typical systems’ functionalities. Furthermore, it is often difficult for a developer to fix a vulnerability correctly if he/she is not a security expert. To assist developers to deal with multiple types of vulnerabilities, we propose a new tool, called VuRLE, for automatic detection and repair of vulnerabilities. VuRLE (1) learns transformative edits and their contexts (i.e., code characterizing edit locations) from examples of …
Sugarmate: Non-Intrusive Blood Glucose Monitoring With Smartphones, Weixi Gu, Yuxun Zhou, Zimu Zhou, Xi Liu, Han Zou, Pei Zhang, Costas J. Spanos, Lin Zhang
Sugarmate: Non-Intrusive Blood Glucose Monitoring With Smartphones, Weixi Gu, Yuxun Zhou, Zimu Zhou, Xi Liu, Han Zou, Pei Zhang, Costas J. Spanos, Lin Zhang
Research Collection School Of Computing and Information Systems
Inferring abnormal glucose events such as hyperglycemia and hypoglycemia is crucial for the health of both diabetic patients and non-diabetic people. However, regular blood glucose monitoring can be invasive and inconvenient in everyday life. We present SugarMate, a first smartphone-based blood glucose inference system as a temporary alternative to continuous blood glucose monitors (CGM) when they are uncomfortable or inconvenient to wear. In addition to the records of food, drug and insulin intake, it leverages smartphone sensors to measure physical activities and sleep quality automatically. Provided with the imbalanced and often limited measurements, a challenge of SugarMate is the inference …
An Efficient Privacy-Preserving Outsourced Computation Over Public Data, Ximeng Liu, Baodong Qin, Robert H. Deng, Yingjiu Li
An Efficient Privacy-Preserving Outsourced Computation Over Public Data, Ximeng Liu, Baodong Qin, Robert H. Deng, Yingjiu Li
Research Collection School Of Computing and Information Systems
In this paper, we propose a new efficient privacy preserving outsourced computation framework over public data, called EPOC. EPOC allows a user to outsource the computation of a function over multi-dimensional public data to the cloud while protecting the privacy of the function and its output. Specifically, we introduce three types of EPOC in order to tradeoff different levels of privacy protection and performance. We present a new cryptosystem called Switchable Homomorphic Encryption with Partial Decryption (SHED) as the core cryptographic primitive for EPOC.We introduce two coding techniques, called message pre-coding and message extending and coding respectively, for messages encrypted …
Vcksm: Verifiable Conjunctive Keyword Search Over Mobile E-Health Cloud In Shared Multi-Owner Settings, Yinbin Miao, Jianfeng Ma, Ximeng Liu, Qi Jiang, Junwei Zhang, Limin Shen, Zhiquan Liu
Vcksm: Verifiable Conjunctive Keyword Search Over Mobile E-Health Cloud In Shared Multi-Owner Settings, Yinbin Miao, Jianfeng Ma, Ximeng Liu, Qi Jiang, Junwei Zhang, Limin Shen, Zhiquan Liu
Research Collection School Of Computing and Information Systems
Searchable encryption (SE) is a promising technique which enables cloud users to conduct search over encrypted cloud data in a privacy-preserving way, especially for the electronic health record (EHR) system that contains plenty of medical history, diagnosis, radiology images, etc. In this paper, we focus on a more practical scenario, also named as the shared multi-owner settings, where each e-health record is co-owned by a fixed number of parties. Although the existing SE schemes under the unshared multi-owner settings can be adapted to this shared scenario, these schemes have to build multiple indexes,which definitely incur higher computational overhead. To save …
Automated Android Application Permission Recommendation, Lingfeng Bao, David Lo, Xin Xia, Shanping Li
Automated Android Application Permission Recommendation, Lingfeng Bao, David Lo, Xin Xia, Shanping Li
Research Collection School Of Computing and Information Systems
The number of Android applications has increased rapidly as Android is becoming the dominant platform in the smartphone market. Security and privacy are key factors for an Android application to be successful. Android provides a permission mechanism to ensure security and privacy. This permission mechanism requires that developers declare the sensitive resources required by their applications. On installation or during runtime, users are required to agree with the permission request. However, in practice, there are numerous popular permission misuses, despite Android introducing official documents stating how to use these permissions properly. Some data mining techniques (e.g., association rule mining) have …
Genomic Security (Lest We Forget), Tatiana Bradley, Xuhua Ding, Gene Tsudik
Genomic Security (Lest We Forget), Tatiana Bradley, Xuhua Ding, Gene Tsudik
Research Collection School Of Computing and Information Systems
Genomic privacy has attracted much attention from the research community, because its risks are unique and breaches can lead to terrifying leakage of sensitive information. The less-explored topic of genomic security must address threats of digitized genomes being altered, which can have dire consequences in medical or legal settings.
Parallel Personalized Pagerank On Dynamic Graphs, Wentian Guo, Yuchen Li, Yuchen Li, Kian-Lee Tan
Parallel Personalized Pagerank On Dynamic Graphs, Wentian Guo, Yuchen Li, Yuchen Li, Kian-Lee Tan
Research Collection School Of Computing and Information Systems
Personalized PageRank (PPR) is a well-known proximitymeasure in graphs. To meet the need for dynamic PPRmaintenance, recent works have proposed a local updatescheme to support incremental computation. Nevertheless,sequential execution of the scheme is still too slow for highspeedstream processing. Therefore, we are motivated todesign a parallel approach for dynamic PPR computation.First, as updates always come in batches, we devise a batchprocessing method to reduce synchronization cost among everysingle update and enable more parallelism for iterativeparallel execution. Our theoretical analysis shows that theparallel approach has the same asymptotic complexity asthe sequential approach. Second, we devise novel optimizationtechniques to e↵ectively reduce runtime …
S3: Syntax- And Semantic-Guided Repair Synthesis Via Programming By Examples, Xuan-Bach D. Le, Duc-Hiep Chu, David Lo, Claire Le Goues, Willem Visser
S3: Syntax- And Semantic-Guided Repair Synthesis Via Programming By Examples, Xuan-Bach D. Le, Duc-Hiep Chu, David Lo, Claire Le Goues, Willem Visser
Research Collection School Of Computing and Information Systems
A notable class of techniques for automatic program repair is known as semantics-based. Such techniques, e.g., Angelix, infer semantic specifications via symbolic execution, and then use program synthesis to construct new code that satisfies those inferred specifications. However, the obtained specifications are naturally incomplete, leaving the synthesis engine with a difficult task of synthesizing a general solution from a sparse space of many possible solutions that are consistent with the provided specifications but that do not necessarily generalize. We present S3, a new repair synthesis engine that leverages programming-by-examples methodology to synthesize high-quality bug repairs. The novelty in S3 that …
On-Demand Time Blurring To Support Side-Channel Defense, Weijie Liu, Debin Gao, Michael K. Reiter
On-Demand Time Blurring To Support Side-Channel Defense, Weijie Liu, Debin Gao, Michael K. Reiter
Research Collection School Of Computing and Information Systems
Side-channel attacks are a serious threat to multi-tenant public clouds. Past work showed how secret information in one virtual machine (VM) can be leaked to another, co-resident VM using timing side channels. Recent defenses against timing side channels focus on reducing the degree of resource sharing. However, such defenses necessarily limit the flexibility with which resources are shared. In this paper, we propose a technique that dynamically adjusts the granularity of platform time sources, to interfere with timing side-channel attacks. Our proposed technique supposes an interface by which a VM can request the temporary coarsening of platform time sources as …
On-Demand Developer Documentation, Martin P. Robillard, Andrian Marcus, Christoph Treude, Gabriele Bavota, Oscar Chaparro, Neil Ernst, Marco Aurélio Gerosa, Michael Godfrey, Michele Lanza, Mario Linares-Vasquez, Gail C. Murphy, Laura Moreno, David Shepherd, Edmund Wong
On-Demand Developer Documentation, Martin P. Robillard, Andrian Marcus, Christoph Treude, Gabriele Bavota, Oscar Chaparro, Neil Ernst, Marco Aurélio Gerosa, Michael Godfrey, Michele Lanza, Mario Linares-Vasquez, Gail C. Murphy, Laura Moreno, David Shepherd, Edmund Wong
Research Collection School Of Computing and Information Systems
We advocate for a paradigm shift in supporting the information needs of developers, centered around the concept of automated on-demand developer documentation. Currently, developer information needs are fulfilled by asking experts or consulting documentation. Unfortunately, traditional documentation practices are inefficient because of, among others, the manual nature of its creation and the gap between the creators and consumers. We discuss the major challenges we face in realizing such a paradigm shift, highlight existing research that can be leveraged to this end, and promote opportunities for increased convergence in research on software documentation.
Understanding Stack Overflow Code Fragments, Christoph Treude, Martin P. Robillard
Understanding Stack Overflow Code Fragments, Christoph Treude, Martin P. Robillard
Research Collection School Of Computing and Information Systems
Code fragments posted in answers on Q&A forums can form an important source of developer knowledge. However, effective reuse of code fragments found online often requires information other than the code fragment alone. We report on the results of a survey-based study to investigate to what extent developers perceive Stack Overflow code fragments to be self-explanatory. As part of the study, we also investigated the types of information missing from fragments that were not self-explanatory. We find that less than half of the Stack Overflow code fragments in our sample are considered to be self-explanatory by the 321 participants who …
Ind-Pca Secure Kem Is Enough For Password-Based Authenticated Key Exchange (Short Paper), Haiyang Xue, Bao Li, Xianhui Lu
Ind-Pca Secure Kem Is Enough For Password-Based Authenticated Key Exchange (Short Paper), Haiyang Xue, Bao Li, Xianhui Lu
Research Collection School Of Computing and Information Systems
There are several frameworks for password-based authenticated key exchange (PAKE) protocols with common reference string following the work of Katz, Ostrovsky and Yung (Eurocrypt’01), and it seems that the IND-CCA secure encryption is inevitable when constructing PAKE in standard model.In this paper, we show that IND-PCA secure key encapsulation mechanism (KEM) is enough for PAKE, which is weaker and easier to be constructed than IND-CCA secure encryption. Our refined PAKE consists of a smooth projective hash function on IND-CPA secure encryption and an IND-PCA secure KEM. Based on DDH assumption, the total communication of PAKE consists of 6 group elements …
From Retweet To Believability: Utilizing Trust To Identify Rumor Spreaders On Twitter, Bhavtosh Rath, Wei Gao, Jing Ma, Jaideep Srivastava
From Retweet To Believability: Utilizing Trust To Identify Rumor Spreaders On Twitter, Bhavtosh Rath, Wei Gao, Jing Ma, Jaideep Srivastava
Research Collection School Of Computing and Information Systems
Ubiquitous use of social media such as microblogging platforms brings about ample opportunities for the false information to diffuse online. It is very important not just to determine the veracity of information but also the authenticity of the users who spread the information, especially in time-critical situations like real-world emergencies, where urgent measures have to be taken for stopping the spread of fake information. In this work, we propose a novel machine learning based approach for automatic identification of the users spreading rumorous information by leveraging the concept of believability, i.e., the extent to which the propagated information is likely …
Semantic Visualization For Short Texts With Word Embeddings, Van Minh Tuan Le, Hady W. Lauw
Semantic Visualization For Short Texts With Word Embeddings, Van Minh Tuan Le, Hady W. Lauw
Research Collection School Of Computing and Information Systems
Semantic visualization integrates topic modeling and visualization, such that every document is associated with a topic distribution as well as visualization coordinates on a low-dimensional Euclidean space. We address the problem of semantic visualization for short texts. Such documents are increasingly common, including tweets, search snippets, news headlines, or status updates. Due to their short lengths, it is difficult to model semantics as the word co-occurrences in such a corpus are very sparse. Our approach is to incorporate auxiliary information, such as word embeddings from a larger corpus, to supplement the lack of co-occurrences. This requires the development of a …
Secure Encrypted Data Deduplication With Ownership Proof And User Revocation, Wenxiu Ding, Zheng Yan, Robert H. Deng
Secure Encrypted Data Deduplication With Ownership Proof And User Revocation, Wenxiu Ding, Zheng Yan, Robert H. Deng
Research Collection School Of Computing and Information Systems
Cloud storage as one of the most important cloud services enables cloud users to save more data without enlarging its own storage. In order to eliminate repeated data and improve the utilization of storage, deduplication is employed to cloud storage. Due to the concern about data security and user privacy, encryption is introduced, but incurs new challenge to cloud data deduplication. Existing work cannot achieve flexible access control and user revocation. Moreover, few of them can support efficient ownership proof, especially public verifiability of ownership. In this paper, we propose a secure encrypted data deduplication scheme with effective ownership proof …
Smartphone Sensing Meets Transport Data: A Collaborative Framework For Transportation Service Analytics, Yu Lu, Archan Misra, Wen Sun, Huayu Wu
Smartphone Sensing Meets Transport Data: A Collaborative Framework For Transportation Service Analytics, Yu Lu, Archan Misra, Wen Sun, Huayu Wu
Research Collection School Of Computing and Information Systems
We advocate for and introduce TRANSense, a framework for urban transportation service analytics that combines participatory smartphone sensing data with city-scale transportation-related transactional data (taxis, trains etc.). Our work is driven by the observed limitations of using each data type in isolation: (a) commonly-used anonymous city-scale datasets (such as taxi bookings and GPS trajectories) provide insights into the aggregate behavior of transport infrastructure, but fail to reveal individual-specific transport experiences (e.g., wait times in taxi queues); while (b) mobile sensing data can capture individual-specific commuting-related activities, but suffers from accuracy and energy overhead challenges due to usage artefacts and lack …
Large-Scale Online Feature Selection For Ultra-High Dimensional Sparse Data, Yue Wu, Steven C. H. Hoi, Tao Mei, Nenghai Yu
Large-Scale Online Feature Selection For Ultra-High Dimensional Sparse Data, Yue Wu, Steven C. H. Hoi, Tao Mei, Nenghai Yu
Research Collection School Of Computing and Information Systems
Feature selection (FS) is an important technique in machine learning and data mining, especially for large scale high-dimensional data. Most existing studies have been restricted to batch learning, which is often inefficient and poorly scalable when handling big data in real world. As real data may arrive sequentially and continuously, batch learning has to retrain the model for the new coming data, which is very computationally intensive. Online feature selection (OFS) is a promising new paradigm that is more efficient and scalable than batch learning algorithms. However, existing online algorithms usually fall short in their inferior efficacy. In this article, …
Fair Deposits Against Double-Spending For Bitcoin Transactions, Xingjie Yu, Shiwen M. Thang, Yingjiu Li, Robert H. Deng
Fair Deposits Against Double-Spending For Bitcoin Transactions, Xingjie Yu, Shiwen M. Thang, Yingjiu Li, Robert H. Deng
Research Collection School Of Computing and Information Systems
In Bitcoin network, the distributed storage of multiple copies of the blockchain opens up possibilities for double spending, i.e., a payer issues two separate transactions to two different payees transferring the same coins. To detect the doublespending and penalize the malicious payer, decentralized non-equivocation contracts have been proposed. The basic idea of these contracts is that the payer locks some coins in a deposit when he initiates a transaction with the payee. If the payer double spends, a cryptographic primitive called accountable assertions can be used to reveal his Bitcoin credentials for the deposit. Thus, the malicious payer could be …
An Experimental Comparison Of Two Machine Learning Approaches For Emotion Classification, Wangchuchu Zhao, Keng Siau
An Experimental Comparison Of Two Machine Learning Approaches For Emotion Classification, Wangchuchu Zhao, Keng Siau
Research Collection School Of Computing and Information Systems
Correctly identifying an emotion has always been challenging for humans, not to mention machines! In this research, we use machine learning to classify human emotion. Emotional differences between genders are well documented in fields like psychology. We hypothesize that genders will impact the accuracy of classifying emotion with machine learning. Two different machine learning approaches were tested in an experimental study. In one approach, emotions from both genders were used to train the machine. In another approach, the genders were separated and two separate machines were used to learn the emotions of the two genders. Our preliminary results show that …