Computer Sciences Commons^™

Evaluation Of Sigfox Lpwan For Sensor-Enabled Homes To Identify At Risk Community Dwelling Seniors, Crys Tan, Hwee-Pink Tan

Research Collection School Of Computing and Information Systems

It is projected that Singapore will become superaged (where 20% of its population will comprise seniors) by 2025. Although various community programs are available to promote active ageing among seniors who are well, provide befriending services for seniors at risk of isolation and care and support for frail and vulnerable seniors, it is not easy to differentiate between `well' seniors and `at risk' seniors. While privacy-preserving z-wave based sensor-enabled homes have been piloted in 100 homes of seniors living alone and have been successful in the timely detection of at-risk seniors, they have limited scalability due to high costs, reliability …

Supporting Software Architecture Maintenance By Providing Task-Specific Recommendations, Matthias Galster, Christoph Treude, Kelly Blincoe

Research Collection School Of Computing and Information Systems

During software maintenance, developers have different information needs (e.g., to understand what type of maintenance activity to perform, the impact of a maintenance activity and its effort). However, information to support developers may be distributed across various sources. Furthermore, information captured in formal architecture documentation may be outdated. In this paper, we put forward a late breaking idea and outline a solution to improve the productivity of developers by providing task-specific recommendations based on concrete information needs that arise during software maintenance.

Tracy: A Business-Driven Technical Debt Prioritization Framework, Rodrigo Rebouças De Almeida, Christoph Treude, Uirá Kulesza

Research Collection School Of Computing and Information Systems

Technical debt is a pervasive problem in software development. Software development teams have to prioritize debt items and determine whether they should address debt or develop new features at any point in time. This paper presents "Tracy", a framework for the prioritization of technical debt using a business-driven approach built on top of business processes. The current stage of the proposed framework is at the beginning of the third phase of Design Science Research, which is usually divided into the phases of exploration, engineering, and evaluation. The exploration and engineering phases involved the participation of 49 professionals from 12 different …

Tighter Security Proofs For Post-Quantum Key Encapsulation Mechanism In The Multi-Challenge Setting, Zhengyu Zhang, Puwen Wei, Haiyang Xue

Research Collection School Of Computing and Information Systems

Due to the threat posed by quantum computers, a series of works investigate the security of cryptographic schemes in the quantum-accessible random oracle model (QROM) where the adversary can query the random oracle in superposition. In this paper, we present tighter security proofs of a generic transformations for key encapsulation mechanism (KEM) in the QROM in the multi-challenge setting, where the reduction loss is independent of the number of challenge ciphertexts. In particular, we introduce the notion of multi-challenge OW-CPA (mOW-CPA) security, which captures the one-wayness of the underlying public key encryption (PKE) under chosen plaintext attack in the multi-challenge …

Multi-Label Thoracic Disease Image Classification With Cross-Attention Networks, Congbo Ma, Hu Wang, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

Automated disease classification of radiology images has been emerging as a promising technique to support clinical diagnosis and treatment planning. Unlike generic image classification tasks, a real-world radiology image classification task is significantly more challenging as it is far more expensive to collect the training data where the labeled data is in nature multi-label; and more seriously samples from easy classes often dominate; training data is highly class-imbalanced problem exists in practice as well. To overcome these challenges, in this paper, we propose a novel scheme of Cross-Attention Networks (CAN) for automated thoracic disease classification from chest x-ray images, which …

Semi-Supervised Deep Quantization For Cross-Modal Search, Xin Wang, Wenwu Zhu, Chenghao Liu

Research Collection School Of Computing and Information Systems

The problem of cross-modal similarity search, which aims at making efficient and accurate queries across multiple domains, has become a significant and important research topic. Composite quantization, a compact coding solution superior to hashing techniques, has shown its effectiveness for similarity search. However, most existing works utilizing composite quantization to search multi-domain content only consider either pairwise similarity information or class label information across different domains, which fails to tackle the semi-supervised problem in composite quantization. In this paper, we address the semi-supervised quantization problem by considering: (i) pairwise similarity information (without class label information) across different domains, which captures …

Duplicate Pull Request Detection: When Time Matters, Qingye Wang, Bowen Xu, Xin Xia, Ting Wang, Shanping Li

Research Collection School Of Computing and Information Systems

In open source communities (e.g., GitHub), developers frequently submit pull requests to fix bugs or add new features during development process. Since the process of pull request is uncoordinated and distributed, it causes massive duplication. Usually, only the first pull request qualified by reviewers can be merged to the main branch of the repository, and the others are regarded as duplication by maintainers. Since the duplication largely aggravates workloads of project reviewers and maintainers, the evolutionary process of open source repositories is delayed. To identify the duplicate pull requests automatically, Ren et al. proposed a state-of-the-art approach that models a …

Identifying Relationships Of Interest In Complex Environments By Using Channel Theory, Andreas Bildstein, Junkang Feng

Communications of the IIMA

Complex environments show a high degree of dynamics caused by vital interactions between objects within those environments and alterations through which the set of objects and their characteristics within those environments go over time. Within this work, we show that we can tame the level of complexity in dynamic environments by identifying ‘relationships of interest’ between objects in such environments. To this end, we apply the theory of Information Flow, also known as Channel Theory, to the application area of smart manufacturing. We enhance the way how the Channel Theory has been applied so far by using an …

Similarity-Based Chained Transfer Learning For Energy Forecasting With Big Data, Yifang Tian, Ljubisa Sehovac, Katarina Grolinger

Electrical and Computer Engineering Publications

Smart meter popularity has resulted in the ability to collect big energy data and has created opportunities for large-scale energy forecasting. Machine Learning (ML) techniques commonly used for forecasting, such as neural networks, involve computationally intensive training typically with data from a single building or a single aggregated load to predict future consumption for that same building or aggregated load. With hundreds of thousands of meters, it becomes impractical or even infeasible to individually train a model for each meter. Consequently, this paper proposes Similarity-Based Chained Transfer Learning (SBCTL), an approach for building neural network-based models for many meters by …

Machine Learning-Based Models For Assessing Impacts Before, During And After Hurricane Events, Julie L. Harvey

Electronic Theses and Dissertations

Social media provides an abundant amount of real-time information that can be used before, during, and after extreme weather events. Government officials, emergency managers, and other decision makers can use social media data for decision-making, preparation, and assistance. Machine learning-based models can be used to analyze data collected from social media. Social media data and cloud cover temperature as physical sensor data was analyzed in this study using machine learning techniques. Data was collected from Twitter regarding Hurricane Florence from September 11, 2018 through September 20, 2018 and Hurricane Michael from October 1, 2018 through October 18, 2018. Natural language …

Huawei, Bis, And The Ieee: It's Déjà Vu All Over Again, Hal Berghel

Computer Science Faculty Research

No abstract provided.

Blockchain In Internet Of Things (Iot), Debrath Banerjee

Student Theses and Dissertations

Nowadays, Blockchain is not an enigmatic technical term rather a technology that holds promise as a way not only to record financial transactions but also to decentralize infrastructure and build a trust layer for business logic. Currently blockchain development is undoubtedly empowering many financial sectors. However non-financial application areas have incredibly grown complex due to the involvement of IoT. So, although they intend to reshape the model, still lots of uncertainty exist in terms of effectiveness. In convergence of blockchain and IoT, there is no definite design model. We have developed a blockchain based IoT platform to replace the traditional …

Phishing: Message Appraisal And The Exploration Of Fear And Self-Confidence, Deanna House, M. K. Raja

Information Systems and Quantitative Analysis Faculty Publications

Phishing attacks have threatened the security of both home users and organizations in recent years. Phishing uses social engineering to fraudulently obtain information that is confidential or sensitive. Individuals are targeted to take action by clicking on a link and providing information. This research explores fear arousal and self-confidence in subjects confronted by phishing attacks. The study collected data from multiple sources (including an attempted phishing attack). The survey results indicated that when individuals had a high level of fear arousal related to providing login credentials they had a decreased intention to respond to a phishing attack. Self-confidence did not …

Why Does This Entity Matter? Support Passage Retrieval For Entity Retrieval, Shubham Chatterjee, Laura Dietz

Computer Science Faculty Research & Creative Works

Our goal is to complement an entity ranking with human-readable explanations of how those retrieved entities are connected to the information need. While related to the problem of support passage retrieval, in this paper, we explore two underutilized indicators of relevance: contextual entities and entity salience. The effectiveness of the indicators is studied within a supervised learning-to-rank framework on a dataset from TREC Complex Answer Retrieval. We find that salience is a useful indicator, but it is often not applicable. In contrast, although performance improvements are obtained by using contextual entities, using contextual words still outperforms contextual entities.

Derivation Of Direct Explicit Integrators Of Rk Type For Solving Class Of Seventh-Order Ordinary Differential Equations, Mohammed S. Mechee, Jawad K. Mshachal

Karbala International Journal of Modern Science

The main contribution of this work is the development of direct explicit methods of Runge-Kutta (RK) type for solving class of seventh-order ordinary differential equations (ODEs) to improve computational efficiency. For this purpose, we have generalized RK, RKN, RKD, RKT, RKFD and RKM methods for solving class of first-, second-, third-, fourth-, and fifth-order ODEs. Using Taylor expansion approach, we have derived the algebraic equations of the order conditions for the proposed RKM integrators up to the tenth-order. Based on these order conditions, two RKM methods of fifth- and sixth-order with four- and five-stage are derived. The zero stability of …

Age-Invariant Face Recognition Using Trigonometric Central Features, Ahmad Malek Bilal, Mohamad-Bassam Kurdy Ph.D

Karbala International Journal of Modern Science

Many facial recognition systems must fail because of many influences such as lighting, changes in composition, expression and aging in the face. But the effects of facial aging are the main problem that many algorithms face with precision. Accordingly, this work provides a model based on the extraction of a number of trigonometric features. The proposed model includes three areas connecting and surrounding the main facial features. In addition, aging is recognized by calculating the trigonometric zones extracted. The system compares the query face with the database. Then, the query image is extracted from the original face image. Next, the …

Properties Of Concrete Modified With Ultra-Fine Slag, Panga Narasimha Reddy, Javed Ahmed Naqash

Karbala International Journal of Modern Science

The supplementary cementitious materials (SCM) can be used as a replacement of cement in the construction industry to minimize the drawbacks of normal concrete such as the emission of carbon dioxide so as to be eco-friendly. This paper presents the effect of ultra-fine slag (i.e. 25% of alccofine) as a replacement of cement for different water to binder ratios (i.e. 0.38, 0.4 and 0.45). The effect of alccofine on the concrete strength properties were studied at 7 and 28 days wherein considerable strength enhancement was observed compared to normal concrete. Thermogravimetric analysis was also carried out in which mass loss …

Analytical Approach To Investigation Of Free Vibration Of Thin Rectangular Plate Immersed In Fluid, Resting On Winkler And Pasternak Foundations, Obanishola Sadiq, Gbeminiyi Sobamowo, Saheed Salawu

Karbala International Journal of Modern Science

Dynamic behaviour of free vibration of rectangular plate is investigated. This study considered an analytical approach to investigation of free vibration of thin rectangular plate immersed in fluid, resting on Winkler and Pasternak foundations.The governing nonlinear partial differential equation is analyzed using two-dimensional differential transform method. The accuracy of the analytical solutions obtained is verified with existing results in literature and confirmed in excellent agreement. Thereafter, the analytical solutions are used for investigation of effect of elastic foundation, fluid and aspect ratio on vibrating plate.From the result, it is observed that, increase elastic foundation parameters increases natural frequency, increase aspect …

Editorial Board

Karbala International Journal of Modern Science

No abstract provided.

Overview Of The System Integration Lab And Its Role In The Space Launch System, Matthew Pickard, David Rose

Von Braun Symposium Student Posters

No abstract provided.

9th Annual Postdoctoral Science Symposium, University Of Texas Md Anderson Cancer Center Postdoctoral Association

Annual Postdoctoral Science Symposium Abstracts

The mission of the Annual Postdoctoral Science Symposium (APSS) is to provide a platform for talented postdoctoral fellows throughout the Texas Medical Center to present their work to a wider audience. The MD Anderson Postdoctoral Association convened its inaugural Annual Postdoctoral Science Symposium (APSS) on August 4, 2011.

The APSS provides a professional venue for postdoctoral scientists to develop, clarify, and refine their research as a result of formal reviews and critiques of faculty and other postdoctoral scientists. Additionally, attendees discuss current research on a broad range of subjects while promoting academic interactions and enrichment and developing new collaborations.

Image Labeler: Label Earth Science Images For Machine Learning, Ashish Acharya, Iksha Gurung, Brian Freitag, Manil Maskey, Rahul Ramachandran

Von Braun Symposium Student Posters

No abstract provided.

Radio Frequency Based Multi-Source Positioning In Indoor Environments, Vishal Perekadan, Tathagata Mukherjee

Von Braun Symposium Student Posters

No abstract provided.

Identifying Irrigated Agriculture Land Using Remote Sensing And Machine Learning, Ryann Firestine, Cameron Handyside, Tamseel Syed, Leiqiu Hu

Von Braun Symposium Student Posters

No abstract provided.

Capturing Dialogue State Variable Dependencies With An Energy-Based Neural Dialogue State Tracker, Anh Duong Trinh, Robert J. Ross, John D. Kelleher

Conference papers

Dialogue state tracking requires the population and maintenance of a multi-slot frame representation of the dialogue state. Frequently, dialogue state tracking systems assume independence between slot values within a frame. In this paper we argue that treating the prediction of each slot value as an independent prediction task may ignore important associations between the slot values, and, consequently, we argue that treating dialogue state tracking as a structured prediction problem can help to improve dialogue state tracking performance. To support this argument, the research presented in this paper is structured into three stages: (i) analyzing variable dependencies in dialogue data; …

Correct-By-Construction Typechecking With Scope Graphs, Katherine Imhoff Casamento

Dissertations and Theses

Dependently-typed languages are well-known for the ability to enforce program invariants through type signatures, and previous work establishes the effectiveness of this style of program verification in the implementation of type-safe interpreters for a wide class of languages with a variety of interesting scoping semantics, offering an account of dynamic semantics. This thesis covers the complementary topic of static semantics, in the form of a pattern for constructing verified typechecking procedures in a dependently-typed setting. Implementations are given for simply-typed lambda calculus and a small procedural language as well as a module system with unrestricted cyclic module dependency semantics that …

On Video Analysis Of Omnidirectional Bee Traffic: Counting Bee Motions With Motion Detection And Image Classification, Vladmir Kulyukin, Sarbajit Mukherjee

Computer Science Faculty and Staff Publications

Omnidirectional bee traffic is the number of bees moving in arbitrary directions in close proximity to the landing pad of a given hive over a given period of time. Video bee traffic analysis has the potential to automate the assessment of omnidirectional bee traffic levels, which, in turn, may lead to a complete or partial automation of honeybee colony health assessment. In this investigation, we proposed, implemented, and partially evaluated a two-tier method for counting bee motions to estimate levels of omnidirectional bee traffic in bee traffic videos. Our method couples motion detection with image classification so that motion detection …

The Future Of Cybercrime Prevention Strategies: Human Factors And A Holistic Approach To Cyber Intelligence, Sinchul Back, Jennifer Laprade

International Journal of Cybersecurity Intelligence & Cybercrime

New technology is rapidly emerging to fight increasing cybercrime threats, however, there is one important component of a cybercrime that technology cannot always impact and that is human behavior. Unfortunately, humans can be vulnerable and easily deceived making technological advances alone inadequate in the cybercrime fight. Instead, we must take a more holistic approach by using technology and better understanding the human factors that make cybercrime possible. In this issue of the International Journal of Cybersecurity Intelligence and Cybercrime, three studies contribute to our knowledge of human factors and emerging cybercrime technology so that more effective comprehensive cybercrime prevention strategies …

A Test Of Structural Model For Fear Of Crime In Social Networking Sites, Seong-Sik Lee, Kyung-Shick Choi, Sinyong Choi, Elizabeth Englander

International Journal of Cybersecurity Intelligence & Cybercrime

This study constructed a structural model which consists of social demographic factors, experience of victimization, opportunity factors, and social context factors to explain the public’s fear of crime on social networking sites (SNS). The model is based on the risk interpretation model, which predicts that these factors influence users’ fear of crime victimization. Using data from 486 university students in South Korea, an empirically-tested model suggests that sex and age have direct and significant effects on fear of victimization, supporting the vulnerability hypothesis. Among opportunity factors, the level of personal information and the number of offending peers have significant effects …

An Exploratory Perception Analysis Of Consensual And Nonconsensual Image Sharing, Jin Ree Lee, Steven Downing

International Journal of Cybersecurity Intelligence & Cybercrime

Limited research has considered individual perceptions of moral distinctions between consensual and nonconsensual intimate image sharing, as well as decision making parameters around why others might engage in such behavior. The current study conducted a perception analysis using mixed-methods online surveys administered to 63 participants, inquiring into their perceptions of why individuals engage in certain behaviors surrounding the sending of intimate images from friends and partners. The study found that respondents favored the concepts of (1) sharing images with romantic partners over peers; (2) sharing non-intimate images over intimate images; and (3) sharing images with consent rather than without it. …