Computer Sciences Commons^™

Coupled Hierarchical Transformer For Stance-Aware Rumor Verification In Social Media Conversations, Jianfei Yu, Jing Jiang, Ling Min Serena Khoo, Hai Leong Chieu, Rui Xia

Research Collection School Of Computing and Information Systems

The prevalent use of social media enables rapid spread of rumors on a massive scale, which leads to the emerging need of automatic rumor verification (RV). A number of previous studies focus on leveraging stance classification to enhance RV with multi-task learning (MTL) methods. However, most of these methods failed to employ pre-trained contextualized embeddings such as BERT, and did not exploit inter-task dependencies by using predicted stance labels to improve the RV task. Therefore, in this paper, to extend BERT to obtain thread representations, we first propose a Hierarchical Transformer1 , which divides each long thread into shorter subthreads, …

Enhancing Developer Interactions With Programming Screencasts Through Accurate Code Extraction, Lingfeng Bao, Shengyi Pan, Zhenchang Xing, Xin Xia, David Lo, Xiaohu Yang

Research Collection School Of Computing and Information Systems

Programming screencasts have become a pervasive resource on the Internet, which is favoured by many developers for learning new programming skills. For developers, the source code in screencasts is valuable and important. However, the streaming nature of screencasts limits the choice that they have for interacting with the code. Many studies apply the Optical Character Recognition (OCR) technique to convert screen images into text, which can be easily searched and indexed. However, we observe that the noise in the screen images significantly affects the quality of OCRed code.In this paper, we develop a tool named psc2code, which has two components, …

Leveraging Profanity For Insincere Content Detection: A Neural Network Approach, Swapna Gottipati, Annabel Tan, David Jing Shan Chow, Joel Wee Kiat Lim

Research Collection School Of Computing and Information Systems

Community driven social media sites are rich sources of knowledge and entertainment and at the same vulnerable to the flames or toxic content that can be dangerous to various users of these platforms as well as to the society. Therefore, it is crucial to identify and remove such content to have a better and safe online experience. Manually eliminating flames is tedious and hence many research works focus on machine learning or deep learning models for automated methods. In this paper, we primarily focus on detecting the insincere content using neural network-based learning methods. We also integrated the profanity features …

Security Analysis Of Permission Re-Delegation Vulnerabilities In Android Apps, Biniam Fisseha Demissie, Mariano Ceccato, Lwin Khin Shar

Research Collection School Of Computing and Information Systems

The Android platform facilitates reuse of app func- tionalities by allowing an app to request an action from another app through inter-process communication mechanism. This fea- ture is one of the reasons for the popularity of Android, but it also poses security risks to end users because malicious, unprivileged apps could exploit this feature to make privileged apps perform privileged actions on behalf of them.

In our journal paper [4], we investigate the hybrid use of program analysis, genetic algorithm based test generation, natu- ral language processing, machine learning techniques for precise detection of permission re-delegation vulnerabilities in Android apps. …

Base-Package Recommendation Framework Based On Consumer Behaviours In Iptv Platform, Kuruparan Shanmugalingam, Ruwinda Ranganayanke, Chanka Gunawardhaha, Rajitha Navarathna

Research Collection School Of Computing and Information Systems

Internet Protocol TeleVision (IPTV) provides many services such as live television streaming, time-shifted media, and Video On Demand (VOD). However, many customers do not engage properly with their subscribed packages due to a lack of knowledge and poor guidance. Many customers fail to identify the proper IPTV service package based on their needs and to utilise their current package to the maximum. In this paper, we propose a base-package recommendation model with a novel customer scoring-meter based on customers behaviour. Initially, our paper describes an algorithm to measure customers engagement score, which illustrates a novel approach to track customer engagement …

Learning Personal Conscientiousness From Footprints In E-Learning Systems, Lo Pang-Yun Ting, Shan Yun Teng, Kun Ta Chuang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Personality inference has received widespread attention for its potential to infer psychological well being, job satisfaction, romantic relationship success, and professional performance. In this research, we focus on Conscientiousness, one of the well studied Big Five personality traits, which determines if a person is self-disciplined, organized, and hard-working. Research has shown that Conscientiousness is related to a person's academic and workplace success. For an expert to evaluate a person's Conscientiousness, long-term observation of the person's behavior at work place or at home is usually required. To reduce this evaluation effort as well as to cope with the increasing trend of …

Reducing Estimation Bias Via Triplet-Average Deep Deterministic Policy Gradient, Dongming Wu, Xingping Dong, Jianbing Shen, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

The overestimation caused by function approximation is a well-known property in Q-learning algorithms, especially in single-critic models, which leads to poor performance in practical tasks. However, the opposite property, underestimation, which often occurs in Q-learning methods with double critics, has been largely left untouched. In this article, we investigate the underestimation phenomenon in the recent twin delay deep deterministic actor-critic algorithm and theoretically demonstrate its existence. We also observe that this underestimation bias does indeed hurt performance in various experiments. Considering the opposite properties of single-critic and double-critic methods, we propose a novel triplet-average deep deterministic policy gradient algorithm that …

Boosting Privately: Federated Extreme Gradient Boosting For Mobile Crowdsensing, Yang Liu, Zhuo Ma, Ximeng Liu, Siqi Ma, Surya Nepal, Robert H. Deng, Kui Ren

Research Collection School Of Computing and Information Systems

Recently, Google and other 24 institutions proposed a series of open challenges towards federated learning (FL), which include application expansion and homomorphic encryption (HE). The former aims to expand the applicable machine learning models of FL. The latter focuses on who holds the secret key when applying HE to FL. For the naive HE scheme, the server is set to master the secret key. Such a setting causes a serious problem that if the server does not conduct aggregation before decryption, a chance is left for the server to access the user’s update. Inspired by the two challenges, we propose …

An Empirical Study Of Release Note Production And Usage In Practice, Tingting Bi, Xin Xia, David Lo, John Grundy, Thomas Zimmermann

Research Collection School Of Computing and Information Systems

The release note is one of the most important software artifacts that serves as a bridge for communication among stakeholders. Release notes contain a set of crucial information, such as descriptions of enhancements, improvements, potential issues, development, evolution, testing, and maintenance of projects throughout the whole development lifestyle. A comprehensive understanding of what makes a good release note and how to write one for different stakeholders would be highly beneficial. However, in practice, the release note is often neglected by stakeholders and has not to date been systematically investigated by researchers. In this paper, we conduct a mixed methods study …

Using Data Analytics To Predict Students Score, Nang Laik Ma, Gim Hong Chua

Research Collection School Of Computing and Information Systems

Education is very important to Singapore, and the government has continued to invest heavily in our education system to become one of the world-class systems today. A strong foundation of Science, Technology, Engineering, and Mathematics (STEM) was what underpinned Singapore's development over the past 50 years. PISA is a triennial international survey that evaluates education systems worldwide by testing the skills and knowledge of 15-year-old students who are nearing the end of compulsory education. In this paper, the authors used the PISA data from 2012 and 2015 and developed machine learning techniques to predictive the students' scores and understand the …

How Should We Understand The Digital Economy In Asia? Critical Assessment And Research Agenda, Kai Li, Dan J. Kim, Karl R. Lang, Robert J. Kauffman, Maurizio Naldi

Research Collection School Of Computing and Information Systems

By Asian digital economy, we refer to high-tech developments, business and social transformations, and information-driven changes in the region's growth. We discuss its background and foundations, significance in Asia and contribution to removal of historical barriers in traditional business. We assess how new value chains are transforming country-level involvement in worldwide manufacturing and note "smiling curve theory" predictions about the global value chain in Asia for high-tech firms and their economies. The takeaway is that the digital economy in Asian nations involves revamping business processes through technology innovation, government policies for growth, and digital entrepreneurship. We analyze the "digital economy …

Empowering Singapore’S Smes: Fintech P2p Lending — A Lifeline For Smes’ Survival?, Grace Lee, Alan Megargel

Research Collection School Of Computing and Information Systems

The COVID-19 pandemic has sent shock waves throughout the world, pushed countries into lockdown, and wreaked havoc on the world’s people and the global economy. The damage to economies around the world caused by the COVID-19 pandemic has far exceeded that of the global financial crisis. While all businesses suffered hugely, it would be of grave consequence if the small and medium-sized enterprises (SMEs), an important segment of every country’s economy, are unable to withstand the shock wave and sustain themselves beyond this pandemic. The COVID-19 pandemic has highlighted the importance of cash flow or working capital for the viability …

Bist: Bi-Directional Spatio-Temporal Reasoning For Video-Grounded Dialogues, Hung Le, Doyen Sahoo, Nancy F. Chen, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Video-grounded dialogues are very challenging due to (i) the complexity of videos which contain both spatial and temporal variations, and (ii) the complexity of user utterances which query different segments and/or different objects in videos over multiple dialogue turns. However, existing approaches to video-grounded dialogues often focus on superficial temporal-level visual cues, but neglect more fine-grained spatial signals from videos. To address this drawback, we propose Bi-directional Spatio-Temporal Learning (BiST), a vision-language neural framework for high-resolution queries in videos based on textual cues. Specifically, our approach not only exploits both spatial and temporal-level information, but also learns dynamic information diffusion …

Global Context Aware Convolutions For 3d Point Cloud Understanding, Zhiyuan Zhang, Binh-Son Hua, Wei Chen, Yibin Tian, Sai-Kit Yeung

Research Collection School Of Computing and Information Systems

Recent advances in deep learning for 3D point clouds have shown great promises in scene understanding tasks thanks to the introduction of convolution operators to consume 3D point clouds directly in a neural network. Point cloud data, however, could have arbitrary rotations, especially those acquired from 3D scanning. Recent works show that it is possible to design point cloud convolutions with rotation invariance property, but such methods generally do not perform as well as translation-invariant only convolution. We found that a key reason is that compared to point coordinates, rotation-invariant features consumed by point cloud convolution are not as distinctive. …

Tangi: Tangible Proxies For Embodied Object Exploration And Manipulation In Virtual Reality, Martin Feick, Scott Bateman, Anthony Tang, Anthony Tang

Research Collection School Of Computing and Information Systems

Exploring and manipulating complex virtual objects is challenging due to limitations of conventional controllers and free-hand interaction techniques. We present the TanGi toolkit which enables novices to rapidly build physical proxy objects using Composable Shape Primitives. TanGi also provides Manipulators allowing users to build objects including movable parts, making them suitable for rich object exploration and manipulation in VR. With a set of different use cases and applications we show the capabilities of the TanGi toolkit and evaluate its use. In a study with 16 participants, we demonstrate that novices can quickly build physical proxy objects using the Composable Shape …

Highly Efficient And Scalable Multi-Hop Ride-Sharing, Yixin Xu, Lars Kulik, Renata Borovica‐Gajic, Abdullah Aldwyish, Jianzhong Qi

Research Collection School Of Computing and Information Systems

On-demand ride-sharing services such as Uber and Lyft have gained tremendous popularity over the past decade, largely driven by the omnipresence of mobile devices. Ride-sharing services can provide economic and environmental benefits such as reducing traffic congestion and vehicle emissions. Multi-hop ride-sharing enables passengers to transfer between vehicles within a single trip, which significantly extends the benefits of ride-sharing and provides ride opportunities that are not possible otherwise. Despite its advantages, offering real-time multi-hop ride-sharing services at large scale is a challenging computational task due to the large combination of vehicles and passenger transfer points. To address these challenges, we …

Selecting Third-Party Libraries: The Practitioners' Perspective, Enrique Larios Vargas, Maurício Aniche, Christoph Treude, Magiel Bruntink, Georgios Gousios

Research Collection School Of Computing and Information Systems

The selection of third-party libraries is an essential element of virtually any software development project. However, deciding which libraries to choose is a challenging practical problem. Selecting the wrong library can severely impact a software project in terms of cost, time, and development effort, with the severity of the impact depending on the role of the library in the software architecture, among others. Despite the importance of following a careful library selection process, in practice, the selection of third-party libraries is still conducted in an ad-hoc manner, where dozens of factors play an influential role in the decision. In this …

Multi-Hop Inference For Question-Driven Summarization, Yang Deng, Wenxuan Zhang, Wai Lam

Research Collection School Of Computing and Information Systems

Question-driven summarization has been recently studied as an effective approach to summarizing the source document to produce concise but informative answers for non-factoid questions. In this work, we propose a novel question-driven abstractive summarization method, Multi-hop Selective Generator (MSG), to incorporate multi-hop reasoning into question-driven summarization and, meanwhile, provide justifications for the generated summaries. Specifically, we jointly model the relevance to the question and the interrelation among different sentences via a human-like multi-hop inference module, which captures important sentences for justifying the summarized answer. A gated selective pointer generator network with a multi-view coverage mechanism is designed to integrate diverse …

Covid-19 Pandemic – Online Education In The New Normal And The Next Normal, X. Xie, Keng Siau, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

The development and advancement of information technology provide a technical platform for education reform and opportunities for innovation in education. The global COVID-19 pandemic has created a new normal that further springboards such opportunities to large scale implementation of online education. Because online education has the advantages of flexibility, information accessibility, global reach, equity, innovation, and efficiency, a growing number of educational institutions are offering degree-granting distance and hybrid education programs. However, online education also has its shortcomings, which include technological constraints, the lack of a sense of belonging and connectedness, the presence of distractions, and a lack of engagement. …

Attribute-Based Keyword Search Over Hierarchical Data In Cloud Computing, Yinbin Miao, Jianfeng Ma, Ximeng Liu, Xinghua Li, Qi Jiang, Junwei Zhang

Research Collection School Of Computing and Information Systems

Searchable encryption (SE) has been a promising technology which allows users to perform search queries over encrypted data. However, the most of existing SE schemes cannot deal with the shared records that have hierarchical structures. In this paper, we devise a basic cryptographic primitive called as attribute-based keyword search over hierarchical data (ABKS-HD) scheme by using the ciphertext-policy attribute-based encryption (CP-ABE) technique, but this basic scheme cannot satisfy all the desirable requirements of cloud systems. The facts that the single keyword search will yield many irrelevant search results and the revoked users can access the unauthorized data with the old …

Usage Of The Symbols And Dionis Square In The Cryptosystem Of Dionis, Dionis Shabani

UBT International Conference

The rapid developments of technology which have brought with them a host of benefits to humanity have also left behind a host of spaces which have mostly aided cyber piracy who exploit the many benefits of the internet for purposes that are in their favor,but these actions which negatively affect the privacy of all internet users. In this project I will present some modifications which are enabled through the 16x16 square of Dionis with 256 elements based in the Masonic Cipher method, with the help of which based on the rules I have created and developed it is different from …

Proposal Of A Legal Framework Through The Development Of New Domain Specific Languages (Dsl) In Compliance With Gdpr, Tea Tavanxhiu, Andrea Alberici, Kozeta Sevrani

UBT International Conference

The adaptation of company processes to the EU Regulation represents a major opportunity to review, update and improve the internal processes and management tools used. The loss of data, in most cases, causes serious damage to the image and very often the total closure of the company. The legislation therefore represents an opportunity and a stimulus to verify the management methods applied, to define an organizational model and a code of conduct (policies, processes, rules / provisions and controls) capable of improving internal processes, defining and achieving desired objectives, ensure data and systems protection with proper risk management and assessment. …

Suggestions And Recommendations For Fulfillment And Implementation Of The Project For Broadband Internet In Macedonia, Zoran Aleksov, Boris Arsov, Vergim Sherifi, Nenad Popovic

UBT International Conference

Nowadays, broadband is defined on the basis of a number of parameters that can be offered through existing electronic communications networks (fixed or mobile networks) and the construction of some next generation of advanced electronic communications networks. This is extremely important for the quality of the received service, because with the existence of a quality electronic communication network, you will distribute a quality and fast data transfer to the end users, some of whom actually want it. Optical cable, among other types of cables, using the Operator and the access method known as " fiber to the home ", has …

Constructing Hadamard Matrices Using Binary Codes, Hizer Leka, Faton Kabashi

UBT International Conference

In this paper is presented a very efficient method for constructing Hadamard matrices, using binary code products. We will construct such matrices using the scalar production of two vectors and the tensor production of Hadamard matrices. This method is based on the representation of the natural number as a binary code which takes only two values 0 or 1. Such a method of generating Hadamard matrices can be used in practice to generate different codes, in telecommunication systems, to correct blocked codes, but also in science as for example in Boolean algebra.

An Alternative Probabilistic Protocol For Relaying Wireless Networks, Faton Maliqi

UBT International Conference

In this paper we propose an alternative probabilistic protocol for relaying wireless network. Usually, the communication protocols are designed to be deterministic when it comes to the order of retransmission from the communication nodes. In contrast, we propose an alternative probabilistic protocol where the retransmitting nodes are chosen probabilistically, and which allows easier performance optimization. Using Monte Carlo simulations, we will show at which location of the Relay do we get the best performance. Due to energy consuming concern and due to lower complexity advantage, as required in technologies such as Internet of Things (IoT), we will consider the case …

Fraud Detection Using Data-Driven Approach, Arianit Mehana, Krenare Pireva Nuci

UBT International Conference

The extensive use of internet is continuously drifting businesses to incorporate their services in the online environment. One of the first spectrums to embrace this evolution was the banking sector. In fact, the first known online banking service came in 1980. It was deployed from a community bank located in Knoxville, called the United American Bank. Since then, internet banking has been offering ease and efficiency to costumers in completing their daily banking tasks. The ever increasing use of internet banking and the large number of online transactions, increased fraudulent behaviour also. As if fraud increase wasn’t enough, the massive …

Big Data Analytics On Cloud: Challenges, Techniques And Technologies, Aleksander Biberaj, Olimpion Shurdi, Bledar Kazia, Renalda Kushe, Alban Rakipi

UBT International Conference

These days it is known that Big Data Analytics is taking a huge attention from researchers and also from business. We all are witness of the data growth that every institution, company or even individuals store in order to use them in the future. There is a big potential to extract useful data from this Big Data that is stored usually in Cloud because sometimes there is not enough local space to store big amounts of data. There is a huge number of sectors where Big Data can be helpful including economic and business activities, public administration, national security, scientific …

Multithreaded Approach For Using Blockchain As An Automated Versioning Tool, Arber Kadriu, Dijar Kadriu, Donjet Salihi, Edmond Jajaga

UBT International Conference

Blockchain is a new and growing technology with a bright future ahead. It can be implemented in many different ways and different industries like banking, cryptocurrencies, health information systems etc. Its powerfulness in security and systematic tracking of different items makes it one of its kind and attractive to work with. This technology is also a suitable environment for multithreaded programming to be adopted in, while using blocks and items to be tracked by single threads. This paper presents an innovative approach of using blockchain as a versioning control tool for personal or commercial usage.

Performance Evaluation Of Non-Relational Data On Big Data Environments, Edmond Jajaga, Edi Hasaj

UBT International Conference

Big data management is a real challenge for traditional systems. The experimental evaluation is performed on measurement of performance of five different databases with an open non-relational dataset. It was structured and tested separately in each store, giving some advantages and limitations to them from a practical point of view. The results are drawn based on the throughput per number of users executed respectively. It was loaded and executed more than a million of records in each and every database. Following its semi-persistent model, Redis performed better than other databases.

Peer To Peer Audio And Video Communication, Kushtrim Pacaj, Kujtim Hyseni, Donika Sfishta

UBT International Conference

In this paper we introduce a simple way on how you can build your own “end-to- end” audio and video chat. You can expect to learn how to add new features on it, as well as building your own signaling server, your mobile UI and mobile calls logic implemented in a perfect coexistence between NodeJS, Java and Kotlin. What makes this application special is the possibility to express yourself with different annotations while you’re on a video chat.