Computer Sciences Commons^™

Detektimi I Animit Politik Përmes Uebit Semantik Duke Përdorur Analizën E Sentimenteve, Dea Macula

Theses and Dissertations

Shfaqja e uebit 2.0 ka ndryshuar drastikisht mënyrën se si përdoruesit perceptojnë Internetin, duke përmirësuar shkëmbimin e informacionit, bashkëpunimin dhe ndërveprimin. Një pjesë e rëndësishme e punës sonë për mbledhjen e informacioneve ka qenë për të zbuluar se çfarë mendojnë individët tjerë me informacionet që ata i shpërndajnë. Me rritjen dhe popullaritetin e burimeve të pasura me opinione, siç janë faqet në Internet dhe blogjet personale, lindin mundësi dhe sfida të reja për njerëzit që të përdorin teknologjitë e informacionit për të kërkuar dhe kuptuar mendimet e të tjerëve. Popullariteti i papritur i aktivitetit në fushën e kërkimit të opinionit …

Klasifikimi I Imazheve Në Machine Learning Duke Përdorur Javascript, Endrit Kryeziu

Theses and Dissertations

Synimi kryesor i intelegjencës artificiale është të ndërtohet një makinë e cila mund të imitoj intelegjencën e njeriut. Për nga shkalla e vështirësisë është sikur të arrihet të eksplorohet i gjithë universi. Është e vështirë të parashikohet e ardhmja kur e dijmë se intelegjenca artificiale ekziston që nga viti 1950, por vetëm vitet e fundit ka filluar të diskutohet për të. Edhe web si platformë po bën përparim të madh, duke ju mundësuar zhvilluesve t’i përdorin këto teknologji. Ekzistojnë shumë librari dhe framework disa prej të cilave janë zhvilluar nga Google dhe Facebook. Përdorimin e tyre e gjejmë në vende …

Zhvillimi Dhe Performanca E Restful Api-Ve Në Asp.Net Core Dhe Nodejs Me Mongodb Si Nosql Bazë Të Dhënash, Endrit Shkodra

Theses and Dissertations

Zhvillimi i teknologjive në fushën e zhvillimit të aplikacioneve softuerike është shumë i shpejtë, e ndërkaq kemi shumë teknologji të cilat mund të përdoren për ofrimin e një zgjidhje. Kjo shpeshherë krijon huti te inxhinierët dhe zhvilluesit e aplikacioneve softuerike duke mos ditur se cila nga teknologjitë do të mundësonte një zgjidhje më të shpejtë, të lehtë, të sigurtë dhe gjithashtu me përformancë të mirë. Të gjitha teknologjitë e reja synim kryesorë e kanë zhvillimin e shpejtë me performancë të mirë dhe të sigurtë. Nuk është e thënë që një teknologji është e mirë në zgjidhjen e të gjitha problemeve. …

Distributed Iot Attestation Via Blockchain (Extended Version), Ira Ray Jenkins, Sean W. Smith

Computer Science Technical Reports

The growing number and nature of Internet of Things (IoT) devices makes these resource-constrained appliances particularly vulnerable and increasingly impactful in their exploitation. Current estimates for the number of connected "things" commonly reach the tens of billions. The low-cost and limited computational strength of these devices can preclude security features. Additionally, economic forces and a lack of industry expertise in security often contribute to a rush to market with minimal consideration for security implications. It is essential that users of these emerging technologies, from consumers to IT professionals, be able to establish and retain trust in the multitude of diverse …

It Seemed Like A Good Idea At The Time (Hindsight Is 2020), James Huggins, Dan Garcia, Kevin Lin, Raja Sooriamurthi, Leo Ureel Ii, Ursula Wolz

Computer Science Presentations And Conference Materials

Charles Kettering reportedly quipped: “99% of success is built on failure”. Yet, those failures rarely see the light of day, as publications naturally focus on successful innovations rather than the many failures that preceded them. The academic community is poorer as a result, as we are all left to re-create the same failures independently, rather than learning from one another. In this panel, we offer an opportunity to “celebrate failure”, by presenting four separate case studies of computing education initiatives that “seemed like a good idea at the time”, but ended up being spectacular failures. The presenters will discuss their …

Heartquake: Accurate Low-Cost Non-Invasive Ecg Monitoring Using Bed-Mounted Geophones, Jaeyeon Park, Hyeon Cho, Rajesh Krishna Balan, Jeonggil Ko

Research Collection School Of Computing and Information Systems

This work presents HeartQuake, a low cost, accurate, non-intrusive, geophone-based sensing system for extracting accurate electrocardiogram (ECG) patterns using heartbeat vibrations that penetrate through a bed mattress. In HeartQuake, cardiac activity-originated vibration patterns are captured on a geophone and sent to a server, where the data is filtered to remove the sensor's internal noise and passed on to a bidirectional long short term memory (Bi-LSTM) deep learning model for ECG waveform estimation. To the best of our knowledge, this is the first solution that can non-intrusively provide accurate ECG waveform characteristics instead of more basic abstract features such as the …

Quantum Transpiler Optimization: On The Development, Implementation, And Use Of A Quantum Research Testbed, Brandon K. Kamaka

Theses and Dissertations

Quantum computing research is at the cusp of a paradigm shift. As the complexity of quantum systems increases, so does the complexity of research procedures for creating and testing layers of the quantum software stack. However, the tools used to perform these tasks have not experienced the increase in capability required to effectively handle the development burdens involved. This case is made particularly clear in the context of IBM QX Transpiler optimization algorithms and functions. IBM QX systems use the Qiskit library to create, transform, and execute quantum circuits. As coherence times and hardware qubit counts increase and qubit topologies …

Artificial Agents In Corporate Boardrooms, Sergio Alberto Gramitto Ricci

Faculty Works

Thousands of years ago, Roman businessmen often ran joint businesses through commonly owned, highly intelligent slaves. Roman slaves did not have full legal capacity and were considered property of their co-owners. Now business corporations are looking to delegate decision-making to uber intelligent machines through the use of artificial intelligence in boardrooms. Artificial intelligence in boardrooms could assist, integrate, or even replace human directors. However, the concept of using artificial intelligence in boardrooms is largely unexplored and raises several issues. This Article sheds light on legal and policy challenges concerning artificial agents in boardrooms. The arguments revolve around two fundamental questions: …

Csmd: A Computational Subtraction-Based Microbiome Discovery Pipeline For Species-Level Characterization Of Clinical Metagenomic Samples, Paul W. Bible, Yu Liu, Bin Zou, Qiaoxing Liang, Cong Dong, Et Al.

Computer Science Faculty publications

Motivation

Microbiome analyses of clinical samples with low microbial biomass are challenging because of the very small quantities of microbial DNA relative to the human host, ubiquitous contaminating DNA in sequencing experiments and the large and rapidly growing microbial reference databases.

Results

We present computational subtraction-based microbiome discovery (CSMD), a bioinformatics pipeline specifically developed to generate accurate species-level microbiome profiles for clinical samples with low microbial loads. CSMD applies strategies for the maximal elimination of host sequences with minimal loss of microbial signal and effectively detects microorganisms present in the sample with minimal false positives using a stepwise convergent solution. …

Privateex: Privacy Preserving Exchange Of Crypto-Assets On Blockchain, Lei Xu, Lin Chen, Zhimin Gao, Keshav Kasichainula, Miguel Fernandez, Bogdan Carbunar, Weidong Shi

Computer Science Faculty Publications

Bitcoin introduces a new type of cryptocurrency that does not rely on a central system to maintain transactions. Inspired by the success of Bitcoin, all types of alt cryptocurrencies were invented in recent years. Some of the new cryptocurrencies focus on privacy enhancement, where transaction information such as value and sender/receiver identity can be hidden, such as Zcash and Monero. However, there are few schemes to support multiple types of cryptocurrencies/assets and offer privacy enhancement at the same time. The major challenge for a multiple asset system is that it needs to support two-way assets exchange between participants besides one-way …

A Multi-Branch Separable Convolution Neural Network For Pedestrian Attribute Recognition, Imran N. Junejo, Naveed Ahmed

All Works

© 2020 The Authors Computer science; Computer Vision; Image processing; Deep learning; Pedestrian attribute recognition

Mitigating The Impact Of Congestion Minimization On Vehicles’ Emissions In A Transportation Road Network, S. Salman, S. Alaswad

All Works

Traffic optimization normally improves flow conditions at the expense of increased vehicles’ emissions. This paper proposes a bi-objective optimization approach to address this situation. In contrast to existing literature, this study considers environmental and congestion impacts of Network Design Problems (NDPs) using the Markov chain traffic assignment approach instead of user equilibrium. The NDP model selectively reverses roads’ directions to improve network performance. The model is optimized by simultaneously minimizing maximum traffic density and total vehicles’ emissions cost using non-dominated sorting genetic algorithm. A realistic city example was used to demonstrate the approach’s efficiency. Results showed that a compromise solution …

Underwater Gesture Recognition Using Classical Computer Vision And Deep Learning Techniques, Mygel Andrei M. Martija, Jakov Ivan S. Dumbrique, Prospero C. Naval Jr.

Mathematics Faculty Publications

Underwater Gesture Recognition is a challenging task since conditions which are normally not an issue in gesture recognition on land must be considered. Such issues include low visibility, low contrast, and unequal spectral propagation. In this work, we explore the underwater gesture recognition problem by taking on the recently released Cognitive Autonomous Diving Buddy Underwater Gestures dataset. The contributions of this paper are as follows: (1) Use traditional computer vision techniques along with classical machine learning to perform gesture recognition on the CADDY dataset; (2) Apply deep learning using a convolutional neural network to solve the same problem; (3) Perform …

Approximation And Computational Complexity Of Some Hammock Variations Of The Poset Cover Problem, Ivy Ordanel, Proceso L. Fernandez Jr, Richelle Ann B. Juayong, Henry N. Adorna

Department of Information Systems & Computer Science Faculty Publications

The Hammock(⏟𝟐, 𝟐 , … , 𝟐 / 𝒌 )-Poset Cover Problem is a variation of the Poset Cover Problem with the same input – set {𝑳_𝟏, 𝑳_𝟐, … , 𝑳_𝒎} of linear orders over the set {𝟏, 𝟐, … ,𝒏}, but the solution is restricted to a set of simple hammock(𝟐⏟, 𝟐 , … , 𝟐 / 𝒌 ) posets. The problem is NP-Hard when 𝒌 ≥ 𝟑 but is in 𝑷 when 𝒌 = 𝟏. The computational complexity of the problem when 𝒌 = 𝟐 is not yet known. In this paper, …

Using Knowledge Bases For Question Answering, Yunshi Lan

Dissertations and Theses Collection (Open Access)

A knowledge base (KB) is a well-structured database, which contains many of entities and their relations. With the fast development of large-scale knowledge bases such as Freebase, DBpedia and YAGO, knowledge bases have become an important resource, which can serve many applications, such as dialogue system, textual entailment, question answering and so on. These applications play significant roles in real-world industry.

In this dissertation, we try to explore the entailment information and more general entity-relation information from the KBs. Recognizing textual entailment (RTE) is a task to infer the entailment relations between sentences. We need to decide whether a hypothesis …

An Empirical Study On Correlation Between Coverage And Robustness For Deep Neural Networks, Yizhen Dong, Peixin Zhang, Jingyi Wang, Shuang Liu, Jun Sun, Jianye Hao, Xinyu Wang, Li Wang, Jinsong Dong, Ting Dai

Research Collection School Of Computing and Information Systems

Deep neural networks (DNN) are increasingly applied in safety-critical systems, e.g., for face recognition, autonomous car control and malware detection. It is also shown that DNNs are subject to attacks such as adversarial perturbation and thus must be properly tested. Many coverage criteria for DNN since have been proposed, inspired by the success of code coverage criteria for software programs. The expectation is that if a DNN is well tested (and retrained) according to such coverage criteria, it is more likely to be robust. In this work, we conduct an empirical study to evaluate the relationship between coverage, robustness and …

Learning Fault Models Of Cyber Physical Systems, Teck Ping Khoo, Jun Sun, Sudipta Chattopadhyay

Research Collection School Of Computing and Information Systems

Cyber Physical Systems (CPSs) comprise sensors and actuators which interact with the physical environment over a computer network to achieve some control objective. Bugs in CPSs can have severe consequences as CPSs are increasingly deployed in safety-critical applications. Debugging CPSs is therefore an important real world problem. Traces from a CPS can be lengthy and are usually linked to different parts of the system, making debugging CPSs a complex and time-consuming undertaking. It is challenging to isolate a component without running the whole CPS. In this work, we propose a model-based approach to debugging a CPS. For each CPS property, …

Using Reinforcement Learning To Minimize The Probability Of Delay Occurrence In Transportation, Zhiguang Cao, Hongliang Guo, Wen Song, Kaizhou Gao, Zhengghua Chen, Le Zhang, Xuexi Zhang

Research Collection School Of Computing and Information Systems

Reducing traffic delay is of crucial importance for the development of sustainable transportation systems, which is a challenging task in the studies of stochastic shortest path (SSP) problem. Existing methods based on the probability tail model to solve the SSP problem, seek for the path that minimizes the probability of delay occurrence, which is equal to maximizing the probability of reaching the destination before a deadline (i.e., arriving on time). However, they suffer from low accuracy or high computational cost. Therefore, we design a novel and practical Q-learning approach where the converged Q-values have the practical meaning as the actual …

Capacitor-Based Activity Sensing For Kinetic-Powered Wearable Iots, Guohao Lan, Dong Ma, Weitao Xu, Mahbub Hassan, Wen Hu

Research Collection School Of Computing and Information Systems

We propose the use of the conventional energy storage component, i.e., capacitor, in the kinetic-powered wearable IoTs as the sensor to detect human activities. Since activities accumulate energy in the capacitor at different rates, the charging rate of the capacitor can be used to detect the activities. The key advantage of the proposed capacitor-based activity sensing mechanism, called CapSense, is that it obviates the need for sampling the motion signal at a high rate, and thus, significantly reduces power consumption of the wearable device. The challenge we face is that capacitors are inherently non-linear energy accumulators, which leads to significant …

Detecting Fake News In Social Media: An Asia-Pacific Perspective, Meeyoung Cha, Wei Gao, Cheng-Te Li

Research Collection School Of Computing and Information Systems

In March 2011, the catastrophic accident known as "The Fukushima Daiichi nuclear disaster" took place, initiated by the Tohoku earthquake and tsunami in Japan. The only nuclear accident to receive a Level-7 classification on the International Nuclear Event Scale since the Chernobyl nuclear power plant disaster in 1986, the Fukushima event triggered global concerns and rumors regarding radiation leaks. Among the false rumors was an image, which had been described as a map of radioactive discharge emanating into the Pacific Ocean, as illustrated in the accompanying figure. In fact, this figure, depicting the wave height of the tsunami that followed, …

Automated Synthesis Of Local Time Requirement For Service Composition, Étienne André, Tian Huat Tan, Manman Chen, Shuang Liu, Jun Sun, Yang Liu, Jin Song Dong

Research Collection School Of Computing and Information Systems

Service composition aims at achieving a business goal by composing existing service-based applications or components. The response time of a service is crucial, especially in time-critical business environments, which is often stated as a clause in service-level agreements between service providers and service users. To meet the guaranteed response time requirement of a composite service, it is important to select a feasible set of component services such that their response time will collectively satisfy the response time requirement of the composite service. In this work, we use the BPEL modeling language that aims at specifying Web services. We extend it …

The Spatial Optimization And Evaluation Of The Economic, Ecological, And Social Value Of Urban Green Space In Shenzhen, Yuhan Yu, Wenting Zhang, Peihong Fu, Wei Huang, Keke Li, Kai Cao

Research Collection School Of Computing and Information Systems

Urban green space (UGS) is important in urban systems, as it benefits economic development, ecological conservation, and living conditions. Many studies have evaluated the economic, ecological, and social value of UGS worldwide, and spatial optimization for UGS has been carried out to maximize its value. However, few studies have simultaneously examined these three values of UGS in one optimization system. To fill this gap, this study evaluated the economic value of UGS in terms of promoting housing prices, its ecological value through the relief of high land surface temperature (LST), and its social value through the provision of recreation spaces …

S2n2: An Interpretive Semantic Structure Attention Neural Network For Trajectory Classification, Canghong Jin, Ting Tao, Xianzhe Luo, Zemin Liu, Minghui Wu

Research Collection School Of Computing and Information Systems

We have witnessed a rapid growth over past decades in sensor data mining (SDM), which aims at extracting valuable information automatically from large repositories of moving activity data. One of the significant SDM tasks is identifying humans through their transit modes using a variety of user-tracking systems. However, to the best of our knowledge, distinguishing traces of users and understanding their behaviors are difficult tasks in most real-life cases for the following reasons: 1) activity data containing both temporal and spatial contexts are of high order and sparse; 2) living patterns are not as regular as expected, and the route …

Global Gradient-Based Phase Unwrapping Algorithm For Increased Performance In Wavefront Sensing, Bryan R. Bartelt

Theses and Dissertations

As the reliance on satellite data for military and commercial use increases, more effort must be exerted to protect our space-based assets. In order to help increase our space domain awareness (SDA), new approaches to ground-based space surveillance via wavefront sensing must be adopted. Improving phase-unwrapping algorithms in order to assist in phase retrieval methods is one way of increasing the performance in current adaptive optics (AO) systems. This thesis proposes a new phase-unwrapping algorithm that uses a global, gradient-based technique to more rapidly identify and correct for areas of phase wrapping during particular phase retrieval methods. This is beneficial …

Performance Evaluation Of Modbus Tcp In Normal Operation And Under A Distributed Denial Of Service Attack, Eric Gamess, Brody Smith, Guillermo Francia Iii

Research, Publications & Creative Work

Modbus is the de facto standard communication protocol for the industrial world. It was initially designed to be used in serial communications (Modbus RTU/ASCII). However, not long ago, it was adapted to TCP due to the increasing popularity of the TCP/IP stack. Since it was originally designed for controlled serial lines, Modbus does not have any security features. In this paper, we wrote several benchmarks to evaluate the performance of networking devices that run Modbus TCP. Parameters reported by our benchmarks include: (1) response time for Modbus requests, (2) maximum number of requests successfully handled by Modbus devices in a …

Understanding Wikipedia As A Resource For Opportunistic Learning Of Computing Concepts, Martin P. Robillard, Christoph Treude

Research Collection School Of Computing and Information Systems

Posts on on-line forums where programmers look for information often include links to Wikipedia when it can be assumed the reader will not be familiar with the linked terms. A Wikipedia article will thus often be the first exposure to a new computing concept for a novice programmer. We conducted an exploratory study with 18 novice programmers by asking them to read a Wikipedia article on a common computing concept that was new to them, while using the think-aloud protocol. We performed a qualitative analysis of the session transcripts to better understand the experience of the novice programmer learning a …

W8-Scope: Fine-Grained, Practical Monitoring Of Weight Stack-Based Exercises, Meeralakshmi Radhakrishnan, Archan Misra, Rajesh Krishna Balan

Research Collection School Of Computing and Information Systems

Fine-grained, unobtrusive monitoring of gym exercises can help users track their own exercise routines and also provide corrective feedback. We propose W8-Scope, a system that uses a simple magnetic-cum-accelerometer sensor, mounted on the weight stack of gym exercise machines, to infer various attributes of gym exercise behavior. More specifically, using multiple machine learning models, W8-Scope helps identify who is exercising, what exercise she is doing, how much weight she is lifting, and whether she is committing any common mistakes. Real world studies, conducted with 50 subjects performing 14 different exercises over 103 distinct sessions in two gyms, show that W8-Scope …

Space Efficient Revocable Ibe For Mobile Devices In Cloud Computing, Baodong Qin, Ximeng Liu, Zhuo Wei, Dong Zheng

Research Collection School Of Computing and Information Systems

Revocation capacity is one of the main properties for an identity-based encryption (IBE), as in practice users’ private keys are possibly leaked or expired. However, existing revocable IBE schemes usually lack of short keys. Recently, Lin et al. proposed a method to design space efficient revocable IBE scheme from non-monotonic key-policy attribute-based encryption scheme. But, it requires too many pairings (linear to the number of revoked users) to decrypt an IBE ciphertext. In this study, we overcome this problem by adopting the technique of server-aided revocation, recently proposed by Qin et al. in ESORICS 2015. The main contribution is a …

How Secure Having Iot Devices In Our Homes?, Debora Estrada, Lo'ai A. Tawalbeh, Robert Vinaja

Computer Science Faculty Publications (Archived)

Nowadays, technology has evolved to be in our daily lives to assist in making our lives easier. We now have technology helping us in our lives at home. Devices used to create our “smart home” have done a great deal in making our lives at home less burdensome, but sadly, these devices have secured our personal lives to be more accessible to outsiders. In this paper, the security of home smart devices and their communication will be researched by using other academic articles to support facts found. The operation of the devices will be discussed along with security risks and …

Algorithm Selection Framework For Cyber Attack Detection, Marc W. Chalé, Nathaniel D. Bastian, Jeffery D. Weir

Faculty Publications

The number of cyber threats against both wired and wireless computer systems and other components of the Internet of Things continues to increase annually. In this work, an algorithm selection framework is employed on the NSL-KDD data set and a novel paradigm of machine learning taxonomy is presented. The framework uses a combination of user input and meta-features to select the best algorithm to detect cyber attacks on a network. Performance is compared between a rule-of-thumb strategy and a meta-learning strategy. The framework removes the conjecture of the common trial-and-error algorithm selection method. The framework recommends five algorithms from the …