Computer Sciences Commons^™

A Neural Network Model For Semi-Supervised Review Aspect Identification, Ying Ding, Changlong Yu, Jing Jiang

Research Collection School Of Computing and Information Systems

Aspect identification is an important problem in opinion mining. It is usually solved in an unsupervised manner, and topic models have been widely used for the task. In this work, we propose a neural network model to identify aspects from reviews by learning their distributional vectors. A key difference of our neural network model from topic models is that we do not use multinomial word distributions but instead embedding vectors to generate words. Furthermore, to leverage review sentences labeled with aspect words, a sequence labeler based on Recurrent Neural Networks (RNNs) is incorporated into our neural network. The resulting model …

Determining The Impact Regions Of Competing Options In Preference Space, Bo Tang, Kyriakos Mouratidis, Man Lung. Yiu

Research Collection School Of Computing and Information Systems

In rank-aware processing, user preferences are typically represented by a numeric weight per data attribute, collectively forming a weight vector. The score of an option (data record) is defined as the weighted sum of its individual attributes. The highest-scoring options across a set of alternatives (dataset) are shortlisted for the user as the recommended ones. In that setting, the user input is a vector (equivalently, a point) in a d-dimensional preference space, where d is the number of data attributes. In this paper we study the problem of determining in which regions of the preference space the weight vector should …

Core Determining Class And Inequality Selection, Ye Luo, Hai Wang

Research Collection School Of Computing and Information Systems

The relations between unobserved events and observed outcomes can be characterized by a bipartite graph. We propose an algorithm that explores the structure of the graph to construct the "exact Core Determining Class," i.e., the set of irredudant inequalities. We prove that in general the exact Core Determining Class does not depend on the probability measure of the outcomes but only on the structure of the graph. For more general linear inequalities selection problems, we propose a statistical procedure similar to the Dantzig Selector to select the truly informative constraints. We demonstrate performances of our procedures in Monte-Carlo experiments.

Provably Secure Attribute Based Signcryption With Delegated Computation And Efficient Key Updating, Hanshu Hong, Yunhao Xia, Zhixin Sun, Ximeng Liu

Research Collection School Of Computing and Information Systems

Equipped with the advantages of flexible access control and fine-grained authentication, attribute based signcryption is diffusely designed for security preservation in many scenarios. However, realizing efficient key evolution and reducing the calculation costs are two challenges which should be given full consideration in attribute based cryptosystem. In this paper, we present a key-policy attribute based signcryption scheme (KP-ABSC) with delegated computation and efficient key updating. In our scheme, an access structure is embedded into user’s private key, while ciphertexts corresponds a target attribute set. Only the two are matched can a user decrypt and verify the ciphertexts. When the access …

Assertion Generation Through Active Learning, Long H. Pham, Jun Sun, Jun Sun

Research Collection School Of Computing and Information Systems

Program assertions are useful for many program analysis tasks. They are however often missing in practice. In this work, we develop a novel approach for generating likely assertions automatically based on active learning. Our target is complex Java programs which cannot be symbolically executed (yet). Our key idea is to generate candidate assertions based on test cases and then apply active learning techniques to iteratively improve them. The experiments show that active learning really helps to improve the generated assertions.

Feedback-Based Debugging, Yun Lin, Jun Sun, Yinxing Xue, Yang Liu, Jin Song Dong

Research Collection School Of Computing and Information Systems

Software debugging has long been regarded as a time and effort consuming task. In the process of debugging, developers usually need to manually inspect many program steps to see whether they deviate from their intended behaviors. Given that intended behaviors usually exist nowhere but in human mind, the automation of debugging turns out to be extremely hard, if not impossible. In this work, we propose a feedback-based debugging approach, which (1) builds on light-weight human feedbacks on a buggy program and (2) regards the feedbacks as partial program specification to infer suspicious steps of the buggy execution. Given a buggy …

Search-Driven String Constraint Solving For Vulnerability Detection, Julian Thome, Lwin Khin Shar, Domenico Bianculli, Lionel Briand

Research Collection School Of Computing and Information Systems

—Constraint solving is an essential technique for detecting vulnerabilities in programs, since it can reason about input sanitization and validation operations performed on user inputs. However, real-world programs typically contain complex string operations that challenge vulnerability detection. State-ofthe-art string constraint solvers support only a limited set of string operations and fail when they encounter an unsupported one; this leads to limited effectiveness in finding vulnerabilities. In this paper we propose a search-driven constraint solving technique that complements the support for complex string operations provided by any existing string constraint solver. Our technique uses a hybrid constraint solving procedure based on …

Persona Generation From Aggregated Social Media Data, Soon-Gyo Jung, Jisun An, Haewoon Kwak, Moeed Ahmad, Lene Nielsen, Bernard J. Jansen

Research Collection School Of Computing and Information Systems

We develop a methodology for persona generation using real time social media data for the distribution of products via online platforms. From a large social media account containing more than 30 million interactions from users from 181 countries engaging with more than 4,200 digital products produced by a global media corporation, we demonstrate that our methodology can first identify both distinct and impactful user segments and then create persona descriptions by automatically adding pertinent features, such as names, photos, and personal attributes. We validate our approach by implementing the methodology into an actual working system that leverages large scale online …

Implementation And Analysis Of Communication Protocols In Internet Of Things, Priyanka Thota

UNLV Theses, Dissertations, Professional Papers, and Capstones

Internet of Things (IoT) is the future of all the present-day devices around the globe. Giving them internet connectivity makes IoT the next frontier of technology. Possibilities are limitless as the devices communicate and interact with each other which make it even more interesting for the global markets. For example, Rolls-Royce announced that it would use the Microsoft Azure IoT suite and also the Intelligence suite of Cortana to keep track of the fuel usage, for performance analysis, to optimize the fly routes etc. which improves the airline efficiency. The devices must communicate with each other, the data from these …

Survey And Analysis Of Android Authentication Using App Locker, Akshitha Reddy Chintalaphani

UNLV Theses, Dissertations, Professional Papers, and Capstones

Android Smart phones have gained immense popularity over the years and is undoubtedly more popular than other operating system phones. Following the similar lines android wear was introduced. Steadily android wear is making its way into our daily lives. It helps keep track of the sleep you have, helps you reach fitness goals, keeps track of phone and helps users have easy authentication. Due to the usage of smart lock which enables phone to be unlocked as long as connected to the android wear, this leads to almost no security on both the ends as android wear before Android 5.0 …

Non-Blocking Priority Queue Based On Skiplists With Relaxed Semantics, Ashok Adhikari

UNLV Theses, Dissertations, Professional Papers, and Capstones

Priority queues are data structures that store information in an orderly fashion. They are of tremendous importance because they are an integral part of many applications, like Dijkstra’s shortest path algorithm, MST algorithms, priority schedulers, and so on.

Since priority queues by nature have high contention on the delete_min operation, the design of an efficient priority queue should involve an intelligent choice of the data structure as well as relaxation bounds on the data structure. Lock-free data structures provide higher scalability as well as progress guarantee than a lock-based data structure. That is another factor to be considered in the …

Finding Top-K Dominance On Incomplete Big Data Using Map-Reduce Framework, Payam Ezatpoor

UNLV Theses, Dissertations, Professional Papers, and Capstones

Incomplete data is one major kind of multi-dimensional dataset that has random-distributed missing nodes in its dimensions. It is very difficult to retrieve information from this type of dataset when it becomes huge. Finding top-k dominant values in this type of dataset is a challenging procedure. Some algorithms are present to enhance this process but are mostly efficient only when dealing with a small-size incomplete data. One of the algorithms that make the application of TKD query possible is the Bitmap Index Guided (BIG) algorithm. This algorithm strongly improves the performance for incomplete data, but it is not originally capable …

Scalability Analysis Of Blockchains Through Blockchain Simulation, Sneha Goswami

UNLV Theses, Dissertations, Professional Papers, and Capstones

The past decade has witnessed a surge of cryptocurrencies such as bitcoins, litecoin, dogecoin, peercoin, bitcoin being the most popular amongst them. Enthusiasts and skeptics have debated and come up with disparate opinions to contest both the success and failures of such currencies. However, the veracity of such opinions can only be derived after true analysis of the technological breakthroughs that have occurred in this domain. Blockchains being the backbone of such currencies is a broad subject that encompasses economics, law, cryptography and software engineering. Most of these technologies are decentralized and are open source algorithms. Blockchains popularity is largely …

Degree Constrained Triangulation Of Annular Regions And Point Sites, Bhaikaji Gurung

UNLV Theses, Dissertations, Professional Papers, and Capstones

Generating constrained triangulations of point sites distributed in the plane is a significant problem in computational geometry. We present theoretical and experimental investigation results for generating triangulations for polygons and point sites that address node degree constraints. We characterize point sites that have almost all vertices of odd degree. We present experimental results on the node degree distribution of Delaunay triangulations of point sites generated randomly. Additionally, we present a heuristic algorithm for triangulating a given normal annular region with an increment of even degree nodes.

Deployment Strategies For A Fleet Of Unmanned Aerial Vehicles Providing Cellular And Data Services, Nima Mohseni

UNLV Theses, Dissertations, Professional Papers, and Capstones

Wireless voice and data communications have become an essential part of our day to day lives. In order to provide these services to as many people as possible, a great infrastructure has been put in place over the last two decades throughout the world. The current infrastructure is mainly consists of cellular towers with gateways to the telecommunication backbone. The wireless infrastructure is doing an adequate job of providing voice and data services, getting more powerful and efficient every day. However, because wireless infrastructure is mainly based on fixed cell towers, it lacks the flexibility and dynamism that may be …

Deep Learning Implementation For Comparison Of User Reviews And Ratings, Nishit Shrestha

UNLV Theses, Dissertations, Professional Papers, and Capstones

Sentiment Analysis is the task of identifying and classifying the sentiment expressed in a piece of text as of positive or negative sentiment and has wide application in E-Commerce. In present time, most e-commerce websites have product review sections, which can be used to identify customer satisfaction/dissatisfaction for their product. In E-COMMERCE websites such as Amazon.com, E-bay.com etc, consumers can submit their reviews along with a specific polarity rating (e.g. 1 to 5 stars at Amazon.com). There is a possibility of mismatch between review submitted and polarity of rating. For Amazon.com, a customer can submit a strongly positive review but …

High Utility Itemsets Identification In Big Data, Ashish Tamrakar

UNLV Theses, Dissertations, Professional Papers, and Capstones

High utility itemset mining is an important data mining problem which considers profit factors besides quantity from the transactional database. It helps find the most valuable products/items that are difficult to track using only the frequent data mining set. An item that has a high-profit value might be rare in the transactional database despite its tremendous importance. While there are many existing algorithms which generate comparatively large candidate sets while finding high utility itemsets, the major focus is to reduce the computational time significantly with the introduction of pruning strategies. Another aspect of high utility itemset mining is to compute …

Effects Of Virtualization In Database Benchmarking, Jigarkumar Jayantibhai Rathod

Theses and Dissertations

Many applications are being deployed on the cloud because virtualization provides inexpensive virtual machines which are easy to create and use. To perform benchmark in scale, one has to rely on virtualization. Virtualization itself, however affects the performance of the database systems. In this thesis, we investigate the unanticipated effects of the virtualization on the database systems by running experiments on virtual machines. The results of our experiments indicate that the performance of a virtual machine is highly influenced by the host machine.

Hexarray: A Novel Self-Reconfigurable Hardware System, Fady Hussein

Boise State University Theses and Dissertations

Evolvable hardware (EHW) is a powerful autonomous system for adapting and finding solutions within a changing environment. EHW consists of two main components: a reconfigurable hardware core and an evolutionary algorithm. The majority of prior research focuses on improving either the reconfigurable hardware or the evolutionary algorithm in place, but not both. Thus, current implementations suffer from being application oriented and having slow reconfiguration times, low efficiencies, and less routing flexibility. In this work, a novel evolvable hardware platform is proposed that combines a novel reconfigurable hardware core and a novel evolutionary algorithm.

The proposed reconfigurable hardware core is a …

Hand Gesture Recognition For Sign Language Transcription, Iker Vazquez Lopez

Boise State University Theses and Dissertations

Sign Language is a language which allows mute people to communicate with other mute or non-mute people. The benefits provided by this language, however, disappear when one of the members of a group does not know Sign Language and a conversation starts using that language. In this document, I present a system that takes advantage of Convolutional Neural Networks to recognize hand letter and number gestures from American Sign Language based on depth images captured by the Kinect camera. In addition, as a byproduct of these research efforts, I collected a new dataset of depth images of American Sign Language …

Towards Automatic Repair Of Xacml Policies, Shuai Peng

Boise State University Theses and Dissertations

In a complex information system, controlling the access to resources is challenging. As a new generation of access control techniques, Attribute-Based Access Control (ABAC) can provide more flexible and fine-grained access control than Role-Based-Access Control (RBAC). XACML (eXtensible Access Control Markup Language) is an industrial standard for specifying ABAC policies. XACML policies tend to be complex because of the great variety of attribute types for fine-grained access control. This means that XACML policies are prone to errors and difficult to debug. This paper presents a first attempt at automating the debugging process of XACML policies. Two techniques are used for …

A Green Form-Based Information Extraction System For Historical Documents, Tae Woo Kim

Theses and Dissertations

Many historical documents are rich in genealogical facts. Extracting these facts by hand is tedious and almost impossible considering the hundreds of thousands of genealogically rich family-history books currently scanned and online. As one approach for helping to make the extraction feasible, we propose GreenFIE—a "Green" Form-based Information-Extraction tool which is "green" in the sense that it improves with use toward the goal of minimizing the cost of human labor while maintaining high extraction accuracy. Given a page in a historical document, the user's task is to fill out given forms with all facts on a page in a document …

Advanced Applications Of Big Data Analytics, Sai Phani Krishna Parsa

UNLV Theses, Dissertations, Professional Papers, and Capstones

Human life is progressing with advancements in technology such as laptops, smart phones, high speed communication networks etc., which helps us by reducing load in doing our daily activities. For instance, one can chat, talk, make video calls with his/her friends instantly using social networking platforms such as Facebook, Twitter, Google+, WhatsApp etc. LinkedIn, Indeed, etc., connects employees with potential employers. The number of people using these applications are increasing day-by-day, and so is the amount of data generated from these applications. Processing such vast amounts of data, may require new techniques for gaining valuable insights. Network theory concepts form …

A Parallel Genetic Algorithm For Optimizing Multicellular Models Applied To Biofilm Wrinkling, Christopher Douglas Johnson

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Multiscale computational models integrating sub-cellular, cellular, and multicellular levels can be powerful tools that help researchers replicate, understand, and predict multicellular biological phenomena. To leverage their potential, these models need correct parameter values, which specify cellular physiology and affect multicellular outcomes. This work presents a robust parameter optimization method, utilizing a parallel and distributed genetic-algorithm software package. A genetic algorithm was chosen because of its superiority in fitting complex functions for which mathematical techniques are less suited. Searching for optimal parameters proceeds by comparing the multicellular behavior of a simulated system to that of a real biological system on the …

Wearable Computing: Accelerometer-Based Human Activity Classification Using Decision Tree, Chong Li

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

In this study, we designed a system that recognizes a person’s physical activity by analyzing data read from a device that he or she wears. In order to reduce the system’s demands on the device’s computational capacity and memory space, we designed a series of strategies such as making accurate analysis based on only a small amount of data in the memory, extracting only the most useful features from the data, cutting unnecessary branches of the classification system, etc. We also implemented a strategy to correct certain types of misclassifications, in order to improve the performance of the system.

We …

Modeling De Novo Granulation Of Anaerobic Sludge, Honey Varghese

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

The global market for biological waste water treatment is large and growing. Bioengineered reactor setups employ microorganisms to degrade waste and produce useful/less harmful components. Scientists are interested in studies that reveal the biological mechanisms involved in the process of these microbial actions in order to improve the reactor performance. The process of granulation in aerobic sludge is one such interesting process which is less explained.

The primary goal of the thesis is to design a computational model that simulates the process of granulation in anaerobic sludge and that addresses the role physiochemical and biological processes play in granule formation. …

Detecting Malicious Campaigns In Crowdsourcing Platforms, Hongkyu Choi

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Crowdsourcing sites such as Mechanical Turk and Crowdflower provide a marketplace where requesters create tasks and recruit workers, who may perform certain tasks in order to get financial compensation. Anyone in the world can be a requester and/or a worker as long as he/she has the Internet connection. Crowdsourcing creates a new way to solve various tasks by using “human computation power”. However, crowdsourcing has been misused by malicious requesters and unethical workers for account generation, search engine optimization, content and link generation, ad posting and spam mailing, and social network linking. It creates new threats to the Web system. …

Power Analysis Of Continuous Data Capture In Beepi, A Solar- Powered Multi-Sensor Electronic Beehive Monitoring System For Langstroth Beehives, Keval Shah

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Honey bee (Apis mellifera) is one of the most important pollinating species in agriculture. The decline in the bee population worldwide is a sign of something going amiss in the environment. This decrease in the population is attributed to the Colony Collapse Disorder (CCD). In this thesis, a power analysis is presented of a solar-powered, multi-sensor electronic beehive monitoring (EBM) system. EBM may contribute to our understanding of the major factors affecting the health of honeybee colonies without disturbing the colonies' daily behavioral patterns or putting extra burdens on beekeepers. The EBM system analyzed in this thesis runs …

Modelling And Verification Of A Cluster-Tree Formation Protocol Implementation For The Ieee 802.15.4 Tsch Mac Operation Mode, Mahmoud Talebi, Jan Friso Groote, Conrad Dandelski

NIMBUS Articles

Correct and efficient initialization of wireless sensor networks can be challenging in the face of many uncertainties present in ad hoc wireless networks. In this paper we examine an implementation for the formation of a cluster-tree topology in a network which operates on top of the TSCH MAC operation mode of the IEEE 802.15.4 standard, and investigate it using formal methods. We show how both the mCRL2 language and toolset help us in identifying scenarios where the implementation does not form a proper topology. More importantly, our analysis leads to the conclusion that the cluster-tree formation algorithm has a super …

Tango: A Spanish-Based Programming Language, Ashley M. Zegiestowsky

Butler Journal of Undergraduate Research

The first part of this article deals with the creation of my own Spanish-based programming language, Tango, using Spanish key words (instead of English key words). The second part relates to the design and implementation of a compiler that follows the grammar rules outlined in the Tango language in order to successfully lexically analyze, parse, semantically analyze, and generate code for Tango. This article begins with a description of the specific goals achieved in the Tango language, an explanation and brief examples of the Tango Grammar, a high-level overview of the compiler design and data structures used, and concludes with …