Databases and Information Systems Commons^™

Knowledge Base Question Answering With A Matching-Aggregation Model And Question-Specific Contextual Relations, Yunshi Lan, Shuohang Wang, Jing Jiang

Research Collection School Of Computing and Information Systems

Making use of knowledge bases to answer questions (KBQA) is a key direction in question answering systems. Researchers have developed a diverse range of methods to address this problem, but there are still some limitations with the existing methods. Specifically, the existing neural network-based methods for KBQA have not taken advantage of the recent “matching-aggregation” framework for the sequence matching, and when representing a candidate answer entity, they may not choose the most useful context of the candidate for matching. In this paper, we explore the use of a “matching-aggregation” framework to match candidate answers with questions. We further make …

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 …

Why Reinventing The Wheels? An Empirical Study On Library Reuse And Re-Implementation, Bowen Xu, Le An, Ferdian Thung, Foutse Khomh, David Lo

Research Collection School Of Computing and Information Systems

Nowadays, with the rapid growth of open source software (OSS), library reuse becomes more and more popular since a large amount of third- party libraries are available to download and reuse. A deeper understanding on why developers reuse a library (i.e., replacing self-implemented code with an external library) or re-implement a library (i.e., replacing an imported external library with self-implemented code) could help researchers better understand the factors that developers are concerned with when reusing code. This understanding can then be used to improve existing libraries and API recommendation tools for researchers and practitioners by using the developers concerns identified …

Predicting The Hardness Of Turf Surfaces From A Soil Moisture Sensor Using Iot Technologies, Ann Marie Mckeon

Other

In horseracing, “the going” is a term to describe the racetrack ground conditions. In Ireland presently, a groundskeeper or course clerk walks the racecourse poking it with a blackthorn stick, assesses conditions, and declares the going – it is a subjective measurement.

This thesis will propose using remote low-cost soil moisture sensors to gather high frequency data about the soil water content in the ground and to enable informed decisions to be made. This will remove the subjective element from the ground hardness, and look at the data in an objective way.

The soil moisture sensor will systematically collect high …

Amazon Alexa + Linked Open Data: Theorizing Concerning Relationships Between (Surveillant) Smart-Home Voice Assistants And Linked Open Data, Michelle Nitto

Publications and Research

No abstract provided.

Lightweight Fine-Grained Search Over Encrypted Data In Fog Computing, Yinbin Miao, Jianfeng Ma, Ximeng Liu, Jian Weng, Hongwei Li, Hui Li

Research Collection School Of Computing and Information Systems

Fog computing, as an extension of cloud computing, outsources the encrypted sensitive data to multiple fog nodes on the edge of Internet of Things (IoT) to decrease latency and network congestion. However, the existing ciphertext retrieval schemes rarely focus on the fog computing environment and most of them still impose high computational and storage overhead on resource-limited end users. In this paper, we first present a Lightweight Fine-Grained ciphertexts Search (LFGS) system in fog computing by extending Ciphertext-Policy Attribute-Based Encryption (CP-ABE) and Searchable Encryption (SE) technologies, which can achieve fine-grained access control and keyword search simultaneously. The LFGS can shift …

Directional Co-Clustering, Aghiles Salah, Mohamed Nadif

Research Collection School Of Computing and Information Systems

Co-clustering addresses the problem of simultaneous clustering of both dimensions of a data matrix. When dealing with high dimensional sparse data, co-clustering turns out to be more beneficial than one-sided clustering even if one is interested in clustering along one dimension only. Aside from being high dimensional and sparse, some datasets, such as document-term matrices, exhibit directional characteristics, and the L2 normalization of such data, so that it lies on the surface of a unit hypersphere, is useful. Popular co-clustering assumptions such as Gaussian or Multinomial are inadequate for this type of data. In this paper, we extend the scope …

Confusion And Information Triggered By Photos In Persona Profiles, Joni Salminen, Soon-Gyo Jung, Jisun An, Haewoon Kwak, Lene Nielsen, Bernard J. Jansen

Research Collection School Of Computing and Information Systems

We investigate whether additional photos beyond a single headshot makes a persona profile more informative without confusing the end user. We conduct an eye-tracking experiment and qualitative interviews with digital content creators after varying the persona in photos via a single headshot, a headshot and photo of the persona in different contexts, and a headshot with photos of different people with key persona attributes the gender and age. Findings show that contextual photos provide significantly more persona information to end users; however, showing photos of multiple people engenders confusion and lowers informativeness. Also, as anticipated, viewing additional photos requires more …

Applied Deep Learning In Intelligent Transportation Systems And Embedding Exploration, Xiaoyuan Liang

Dissertations

Deep learning techniques have achieved tremendous success in many real applications in recent years and show their great potential in many areas including transportation. Even though transportation becomes increasingly indispensable in people’s daily life, its related problems, such as traffic congestion and energy waste, have not been completely solved, yet some problems have become even more critical. This dissertation focuses on solving the following fundamental problems: (1) passenger demand prediction, (2) transportation mode detection, (3) traffic light control, in the transportation field using deep learning. The dissertation also extends the application of deep learning to an embedding system for visualization …

Cooperation In Maritime Search And Rescue Between Democratic People’S Republic Of Korea, The People’S Republic Of China And The Russian Federation, Kwangmyong Ri

Maritime Safety & Environment Management Dissertations (Dalian)

No abstract provided.

Model Of The State Of Threats To The Access Control System, ‪Durdona Irgasheva

Bulletin of TUIT: Management and Communication Technologies

This article is devoted to the presentation of the threat state model of access control, which allows calculating the probabilities of the impact of threats on the access control system and the probability of opening this system based on taking into account the generalized algorithm for the implementation of external threats, and determines the need to develop additional components of the access control system designed to identify and classify attacks.

Foodai: Food Image Recognition Via Deep Learning For Smart Food Logging, Doyen Sahoo, Hao Wang, Ke Shu, Xiongwei Wu, Hung Le, Palakorn Achananuparp, Ee-Peng Lim, Hoi, Steven C. H.

Research Collection School Of Computing and Information Systems

An important aspect of health monitoring is effective logging of food consumption. This can help management of diet-related diseases like obesity, diabetes, and even cardiovascular diseases. Moreover, food logging can help fitness enthusiasts, and people who wanting to achieve a target weight. However, food-logging is cumbersome, and requires not only taking additional effort to note down the food item consumed regularly, but also sufficient knowledge of the food item consumed (which is difficult due to the availability of a wide variety of cuisines). With increasing reliance on smart devices, we exploit the convenience offered through the use of smart phones …

Social Inclusion In The Digital Era: Rethinking Debates And Narratives In The World Bank Report., Calisto Kondowe, Wallace Chigona

African Conference on Information Systems and Technology

The 2019 (5th) proceedings of ACIST focuses on how African societies are leveraging and can leverage the smart capabilities in digital technologies to address organizational and societal challenges. Technology-enabled solutions offer solutions to many of these challenges. Digital technologies are increasingly becoming integral to and interdependent with the African society.

An Electronic Framework To Shepherd The Pastoral Livestock (Resolve Conflicts In Pastoral Communities), Frezewd Lemma, Anteneh Alemu, Desta Zerihun, Endale Aregu

African Conference on Information Systems and Technology

This paper proposes a tracking framework based on GPS enabled location sensors, the GSM/WCDMA wireless network, and algorithms running in an edge clouds to resolve deadly conflicts that arise in the Africans pastorals community. The paper also proposes an automatic digital identification mechanism that helps resolve conflicts during animals mixup. This algorithmic based solution would totally relief the community from using the traditional identification mechanisms such as hot branding which are known to be cruel to animals. To communicate with the pastorals, the framework takes into consideration the low level literacy of the community as well as their use of …

Sentence-Level Evidence Embedding For Claim Verification With Hierarchical Attention Networks, Jing Ma, Wei Gao, Shafiq Joty, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

Claim verification is generally a task of verifying the veracity of a given claim, which is critical to many downstream applications. It is cumbersome and inefficient for human fact-checkers to find consistent pieces of evidence, from which solid verdict could be inferred against the claim. In this paper, we propose a novel end-to-end hierarchical attention network focusing on learning to represent coherent evidence as well as their semantic relatedness with the claim. Our model consists of three main components: 1) A coherence-based attention layer embeds coherent evidence considering the claim and sentences from relevant articles; 2) An entailment-based attention layer …

Factors Influencing Customers’ Attitude For Using M-Birr Adoption In Ethiopia, Gebremedhin Gebreyohans, Abdurehman Ali

African Conference on Information Systems and Technology

Diffusion of Innovations (DOI) is a theory to explain how and over time new philosophies and then technology diffuse into different contexts. This research tested the attributes of DOI and other variables empirically,usingM-Birr system as the goal of the innovation. The research was conducted among customers of M-Birr service in Addis Ababa, Ethiopia. The data collection instrument was a closed-ended questionnaire administered to 360 respondents of which 211 were returned giving 58.6% return rate. The demographic make-up of the respondents showed that most of them were between the age of 30 to 50 and degree holders. From the factor analysis …

Exploring Delay Dispersal In Us Airport Network, Brandon Sripimonwan, Arun Sathanur

STAR Program Research Presentations

The modeling of delay diffusion in airport networks can potentially help develop strategies to prevent the spread of such delays and disruptions. With this goal, we used the publicly-available historical United States Federal Aviation Administration (FAA) flight data to model the spread of delays in the US airport network. For the major (ASPM-77) airports for January 2017, using a threshold on the volume of flights, we sparsify the network in order to better recognize patterns and cluster structure of the network. We developed a diffusion simulator and greedy optimizer to find the top influential airport nodes that propagate the most …

The Effect Of Conversational Agent Skill On User Behavior During Deception, Ryan M. Schuetzler, G. Mark Grimes, Justin Scott Giboney

Information Systems and Quantitative Analysis Faculty Publications

Conversational agents (CAs) are an integral component of many personal and business interactions. Many recent advancements in CA technology have attempted to make these interactions more natural and human-like. However, it is currently unclear how human-like traits in a CA impact the way users respond to questions from the CA. In some applications where CAs may be used, detecting deception is important. Design elements that make CA interactions more human-like may induce undesired strategic behaviors from human deceivers to mask their deception. To better understand this interaction, this research investigates the effect of conversational skill—that is, the ability of the …

Deep Anomaly Detection With Deviation Networks, Guansong Pang, Chunhua Shen, Anton Van Den Hengel

Research Collection School Of Computing and Information Systems

Although deep learning has been applied to successfully address many data mining problems, relatively limited work has been done on deep learning for anomaly detection. Existing deep anomaly detection methods, which focus on learning new feature representations to enable downstream anomaly detection methods, perform indirect optimization of anomaly scores, leading to data-inefficient learning and suboptimal anomaly scoring. Also, they are typically designed as unsupervised learning due to the lack of large-scale labeled anomaly data. As a result, they are difficult to leverage prior knowledge (e.g., a few labeled anomalies) when such information is available as in many real-world anomaly detection …

Creating Top Ranking Options In The Continuous Option And Preference Space, Bo Tang, Kyriakos Mouratidis, Man Lung Yiu, Zhenyu Chen

Research Collection School Of Computing and Information Systems

Top-k queries are extensively used to retrieve the k most relevantoptions (e.g., products, services, accommodation alternatives, etc)based on a weighted scoring function that captures user preferences. In this paper, we take the viewpoint of a business owner whoplans to introduce a new option to the market, with a certain type ofclientele in mind. Given a target region in the consumer spectrum,we determine what attribute values the new option should have,so that it ranks among the top-k for any user in that region. Ourmethodology can also be used to improve an existing option, at theminimum modification cost, so that it ranks …