Computer Engineering Commons^™

Conflict Reduction Techniques For Gpu Transactional Memory Systems, Sui Chen

LSU Doctoral Dissertations

The continued evolution of GPUs have enabled the use of irregular algorithms which involve fine-grained data sharing between threads, as well as transaction processing applications such as databases. Transactional Memory (TM) is derived from databases, which by itself is a programming construct that simplifies the programming of parallel workloads and combines the advantages of traditional approaches including fine-grained and coarse-grained locking. While hardware support for TM has started to enter mainstream commodity products, it is much farther from becoming reality on the GPU and is still being researched. In this dissertation, we study the challenges for supporting transactional workloads on …

2fly With Rpi - Evaluating The Raspberry Pi For Glass Cockpit Applications, Donald R. Morris

ASA Multidisciplinary Research Symposium

Evaluating the capabilities of Raspberry Pi computers to be used in embedded glass cockpit applications for experimental aircraft. This includes details of what is required for these applications as well as how well the Raspberry Pi 3B can perform in this role.

Strong-Dism: A First Attempt To A Dynamically Typed Assembly Language (D-Tal), Ivory Hernandez

USF Tampa Graduate Theses and Dissertations

Dynamically Typed Assembly Language (D-TAL) is not only a lightweight and effective solution to the gap generated by the drop in security produced by the translation of high-level language instructions to low-level language instructions, but it considerably eases up the burden generated by the level of complexity required to implement typed assembly languages statically. Although there are tradeoffs between the static and dynamic approaches, focusing on a dynamic approach leads to simpler, easier to reason about, and more feasible ways to understand deployment of types over monomorphically-typed or untyped intermediate languages. On this occasion, DISM, a simple but powerful and …

A Study Of Application-Awareness In Software-Defined Data Center Networks, Chui-Hui Chiu

LSU Doctoral Dissertations

A data center (DC) has been a fundamental infrastructure for academia and industry for many years. Applications in DC have diverse requirements on communication. There are huge demands on data center network (DCN) control frameworks (CFs) for coordinating communication traffic. Simultaneously satisfying all demands is difficult and inefficient using existing traditional network devices and protocols. Recently, the agile software-defined Networking (SDN) is introduced to DCN for speeding up the development of the DCNCF. Application-awareness preserves the application semantics including the collective goals of communications. Previous works have illustrated that application-aware DCNCFs can much more efficiently allocate network resources by explicitly …

Improving Large Scale Application Performance Via Data Movement Reduction, Dewan M. Ibtesham

Computer Science ETDs

The compute capacity growth in high performance computing (HPC) systems is outperforming improvements in other areas of the system for example, memory capacity, network bandwidth and I/O bandwidth. Therefore, the cost of executing a floating point operation is decreasing at a faster rate than moving that data. This increasing performance gap causes wasted CPU cycles while waiting for slower I/O operations to complete in the memory hierarchy, network, and storage. These bottlenecks decrease application time to solution performance, and increase energy consumption, resulting in system under utilization. In other words, data movement is becoming a key concern for future HPC …

Efficient Identification Of Tanimoto Nearest Neighbors; All Pairs Similarity Search Using The Extended Jaccard Coefficient, David Anastasiu, George Karypis

Faculty Publications

Tanimoto, or extended Jaccard, is an important similarity measure which has seen prominent use in fields such as data mining and chemoinformatics. Many of the existing state-of-the-art methods for market basket analysis, plagiarism and anomaly detection, compound database search, and ligand-based virtual screening rely heavily on identifying Tanimoto nearest neighbors. Given the rapidly increasing size of data that must be analyzed, new algorithms are needed that can speed up nearest neighbor search, while at the same time providing reliable results. While many search algorithms address the complexity of the task by retrieving only some of the nearest neighbors, we propose …

Computer Aided Drafting Virtual Reality Interface, David M. Roach

Doctoral Dissertations and Master's Theses

Computer Aided Drafting (CAD) is pervasive in engineering fields today. It has become indispensable for planning, creating, visualizing, troubleshooting, collaborating, and communicating designs before they exist in physical form. From the beginning, CAD was created to be used by means of a mouse, keyboard, and monitor. Along the way, other, more specialized interface devices were created specifically for CAD that allowed for easier and more intuitive navigation within a 3D space, but they were at best stopgap solutions. Virtual Reality (VR) allows users to navigate and interact with digital 3D objects and environments the same way they would in the …

Fast On-Line Kernel Density Estimation For Active Object Localization, Anthony D. Rhodes, Max H. Quinn, Melanie Mitchell

Computer Science Faculty Publications and Presentations

A major goal of computer vision is to enable computers to interpret visual situations—abstract concepts (e.g., “a person walking a dog,” “a crowd waiting for a bus,” “a picnic”) whose image instantiations are linked more by their common spatial and semantic structure than by low-level visual similarity. In this paper, we propose a novel method for prior learning and active object localization for this kind of knowledge-driven search in static images. In our system, prior situation knowledge is captured by a set of flexible, kernel-based density estimations— a situation model—that represent the expected spatial structure of the given situation. These …

Intent Recognition In Smart Living Through Deep Recurrent Neural Networks, Xiang Zhang, Lina Yao, Chaoran Huang, Quan Z. Sheng, Xianzhi Wang

Research Collection School Of Computing and Information Systems

Electroencephalography (EEG) signal based intent recognition has recently attracted much attention in both academia and industries, due to helping the elderly or motor-disabled people controlling smart devices to communicate with outer world. However, the utilization of EEG signals is challenged by low accuracy, arduous and time-consuming feature extraction. This paper proposes a 7-layer deep learning model to classify raw EEG signals with the aim of recognizing subjects’ intents, to avoid the time consumed in pre-processing and feature extraction. The hyper-parameters are selected by an Orthogonal Array experiment method for efficiency. Our model is applied to an open EEG dataset provided …

Enabling Phased Array Signal Processing For Mobile Wifi Devices, Kun Qian, Chenshu Wu, Zheng Yang, Zimu Zhou, Xu Wang, Yunhao Liu

Research Collection School Of Computing and Information Systems

Modern mobile devices are equipped with multiple antennas, which brings various wireless sensing applications such as accurate localization, contactless human detection, and wireless human-device interaction. A key enabler for these applications is phased array signal processing, especially Angle of Arrival (AoA) estimation. However, accurate AoA estimation on commodity devices is non-trivial due to limited number of antennas and uncertain phase offsets. Previous works either rely on elaborate calibration or involve contrived human interactions. In this paper, we aim to enable practical AoA measurements on commodity off-the-shelf (COTS) mobile devices. The key insight is to involve users’ natural rotation to formulate …

Selective Value Coupling Learning For Detecting Outliers In High-Dimensional Categorical Data, Guansong Pang, Hongzuo Xu, Cao Longbing, Wentao Zhao

Research Collection School Of Computing and Information Systems

This paper introduces a novel framework, namely SelectVC and its instance POP, for learning selective value couplings (i.e., interactions between the full value set and a set of outlying values) to identify outliers in high-dimensional categorical data. Existing outlier detection methods work on a full data space or feature subspaces that are identified independently from subsequent outlier scoring. As a result, they are significantly challenged by overwhelming irrelevant features in high-dimensional data due to the noise brought by the irrelevant features and its huge search space. In contrast, SelectVC works on a clean and condensed data space spanned by selective …

Understanding Inactive Yet Available Assignees In Github, Jing Jiang, David Lo, Xinyu Ma, Fuli Feng, Li Zhang

Research Collection School Of Computing and Information Systems

Context In GitHub, an issue or a pull request can be assigned to a specific assignee who is responsible for working on this issue or pull request. Due to the principle of voluntary participation, available assignees may remain inactive in projects. If assignees ever participate in projects, they are active assignees; otherwise, they are inactive yet available assignees (inactive assignees for short). Objective Our objective in this paper is to provide a comprehensive analysis of inactive yet available assignees in GitHub. Method We collect 2,374,474 records of activities in 37 popular projects, and 797,756 records of activities in 687 projects …

Sourcevote: Fusing Multi-Valued Data Via Inter-Source Agreements, Xiu Susie Fang, Quan Z. Sheng, Xianzhi Wang, Mahmoud Barhamgi, Lina Yao, Anne H.H. Ngu

Research Collection School Of Computing and Information Systems

Data fusion is a fundamental research problem of identifyingtrue values of data items of interest from conflicting multi-sourceddata. Although considerable research efforts have been conducted on thistopic, existing approaches generally assume every data item has exactlyone true value, which fails to reflect the real world where data items withmultiple true values widely exist. In this paper, we propose a novel approach,SourceVote, to estimate value veracity for multi-valued data items.SourceVote models the endorsement relations among sources by quantifyingtheir two-sided inter-source agreements. In particular, two graphs areconstructed to model inter-source relations. Then two aspects of sourcereliability are derived from these graphs and …

An Analysis Of Rumor And Counter-Rumor Messages In Social Media, Dion Hoe-Lian Goh, Alton Y. K. Chua, Hanyu Shi, Wenju Wei, Haiyan Wang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Social media platforms are one of the fastest ways to disseminate information but they have also been used as a means to spread rumors. If left unchecked, rumors have serious consequences. Counter-rumors, messages used to refute rumors, are an important means of rumor curtailment. The objective of this paper is to examine the types of rumor and counter-rumor messages generated in Twitter in response to the falsely reported death of a politician, Lee Kuan Yew, who was Singapore’s first Prime Minister. Our content analysis of 4321Twitter tweets about Lee’s death revealed six categories of rumor messages, four categories ofcounter-rumor messages …

Sourcevote: Fusing Multi-Valued Data Via Inter-Source Agreements, Xiu Susie Fang, Quan Z. Sheng, Xianzhi Wang, Mahmoud Barhamgi, Lina Yao, Anne H.H. Ngu

Research Collection School Of Computing and Information Systems

Data fusion is a fundamental research problem of identifying true values of data items of interest from conflicting multi-sourced data. Although considerable research efforts have been conducted on this topic, existing approaches generally assume every data item has exactly one true value, which fails to reflect the real world where data items with multiple true values widely exist. In this paper, we propose a novel approach,SourceVote, to estimate value veracity for multi-valued data items. SourceVote models the endorsement relations among sources by quantifying their two-sided inter-source agreements. In particular, two graphs are constructed to model inter-source relations. Then two aspects …

Clutter Suppression Via Hankel Rank Reduction For Dfrft-Based Vibrometry Applied To Sar, Francisco Pérez, Balu Santhanam, Ranlf Dunkel, Majeed M. Hayat

Electrical and Computer Engineering Faculty Research and Publications

Hankel rank reduction (HRR) is a method that, by prearranging the data in a Hankel matrix and performing rank reduction via singular value decomposition, suppresses the noise of a time-history vector comprised of the superposition of a finite number of sinusoids. In this letter, the HRR method is studied for performing clutter suppression in synthetic aperture radar (SAR)-based vibrometry. Specifically, three different applications of the HRR method are presented. First, resembling the SAR slow-time signal model, the HRR method is utilized for separating a chirp signal immersed in a sinusoidal clutter. Second, using simulated airborne SAR data with 10 dB …

Research On System Communication By Using Unified Registry Model & Elements, Kujtim Gashi, Atdhe Buja, Fatos Idrizi

UBT International Conference

Trends of Development of Information Society in the Republic of Kosovo must fit the criteria and standards of the EU. The main objective of the paper is the identification of individual IT systems used by the Republic of Kosovo public institutions related to the trade and working out analysis and recommendations for optimizing their communication (interoperability), eventual unification in the hardware & software level and increase the efficiency of the entire economic system information. The analytical analysis outlined these points, as it follows: current technologies used by public administration of the Republic of Kosovo, risk analysis, analysis of data structures …

Smia: Improving Kosovo's Education Management System, Lazar Adjijgogov, Dejan Stamenov, Edmond Jajaga

UBT International Conference

Successful management of today’s education systems requires effective policy-making and system monitoring through data and information. To this end, countries around the world have invested significant resources into collecting, processing, and managing more and better data through education management information systems (EMIS). SMIA is a modern EMIS, which offers easier management of educational process in Kosovo. It facilitates decision-making, resource planning, strategy building, monitoring and evaluation of educational system through a rich set of analytical and statistical tools. For over six years of activity, the system has efficiently tracked and thus helped the development of the educational process for every …

Study Of The Power Consumption Of Pseudo Random Bit Generator Circuits Implemented On Fpga, Galia Marinova

UBT International Conference

Pseudo Random Bit and Number Generator (PRB/NG) circuits being very widely used for security, compressive sensing and diverse other applications in telecommunications are studies in different aspects in the laboratory of Computer-aided Design in Telecommunications in Technical University-Sofia. Some results of this study are published in [1] where tests for randomness from the National Institute of Standards and Technology (NIST) suit are applied on commonly used PRB/NGs. Other aspects of the PRB/NG circuits study is their power consumption in the aim of green communications as noticed in [2,3] and the concern about low power consuming devices for Internet of Things’ …

Computer Science: Application Of Technology/Iot In Hydropower Dams, Orjola Jaupi

UBT International Conference

As time passes by, we barely see how much time it costs people to stay at work, fixing problems that happen every day. As people we should do more about humanity and technology is the door that opens opportunities for us to do this. Technology today is transforming every human daily life routine and it’s only the beginning of what technology can bring. By 2020 we know that technology will connect the unconnected by introducing the real idea of Internet of Things. Every little, tiny thing all over the world will be connected, but also big and important projects like …

Review Of Artificial Intelligence Development, Its Impact And Its Challenges, Litvane Spahija, Festim Halili

UBT International Conference

The field of Artificial Intelligence, which started roughly half a century ago, has a turbulent history. In the 1980s there has been a major paradigm shift towards embodiment. While embodied artificial intelligence is still highly diverse, changing, and far from “theoretically stable”, a certain consensus about the important issues and methods has been achieved or is rapidly emerging. In this paper we briefly characterize the field, summarize its achievements, and identify important issues for future research.

With the popularization of the Internet, permeation of sensor networks, emergence of big data, increase in size of the information community, and interlinking and …

Characteristics And Temporal Behavior Of Internet Backbone Traffic, Artan Salihu, Muharrem Shefkiu, Arianit Maraj

UBT International Conference

With the rapid increase demand for data usage, Internet has become complex and harder to analyze. Characterizing the Internet traffic might reveal information that are important for Network Operators to formulate policy decisions, develop techniques to detect network anomalies, help better provision network resources (capacity, buffers) and use workload characteristics for simulations (typical packet sizes, flow durations, common protocols).

In this paper, using passive monitoring and measurements, we show collected data traffic at Internet backbone routers. First, we reveal main observations on patterns and characteristics of this dataset including packet sizes, traffic volume for inter and intra domain and protocol …

Permission-Based Privacy Analysis For Android Applications, Erza Gashi, Zhilbert Tafa

UBT International Conference

While Information and Communication Technology (ICT) trends are moving towards the Internet of Things (IoT), mobile applications are becoming more and more popular. Mostly due to their pervasiveness and the level of interaction with the users, along with the great number of advantages, the mobile applications bring up a great number of privacy related issues as well. These platforms can gather our very sensitive private data by only granting them a list of permissions during the installation process. Additionally, most of the users can find it difficult, or even useless, to analyze system permissions. Thus, their guess of app’s safety …

A Critical Overview Of Data Mining For Business Applications, George Telonis, Peter P. Groumpos

UBT International Conference

Everybody looks to a world that does not remain the same. Furthermore no one can deny that the world is changing, and changing very fast.

Technology, education, science, environment, health, communicating habits, entertainment, eating habits, dress - there is hardly anything in life that is not changing. Some changes we like, while others create fear and anxiety around us. Everywhere there is a feeling of insecurity.

What will happen to us tomorrow, or what will happen to our children, are questions we keep frequently asking. One thing, however, is clear.

It is no more possible to live in the way …

Decision Making Based On Data Analyses Using Data Warehouses, Valdrin Haxhiu

UBT International Conference

Data warehouses are a collection of several databases, whose goal is to help different companies and corporations make important decisions about their activities. These decisions are taken from the analyses that are made to the data within the data warehouse. These data are taken from data that companies and corporations collect on daily basis from their branches that may be located in different cities, regions, states and continents. Data that are entered to data warehouses are historical data and they represent that part of data that is important for making decisions. These data go under a transformation process in order …

Mobile Cloud Computing: A New Way Of Cloud Computing, Festim Halili, Verda Misimi, Rilinda Iseini, Mirije Salihi

UBT International Conference

Cloud Computing seems to be the most promising technology of the century we are living. It provides a new manner of sharing distributed resources and services that may be part of different organizations, geographically located in different places and different time zones. Mobile Cloud Computing offers partially the same functionality, with the only additional requirement that, at least, some of the devices are mobile. In this paper, we will try to provide a detailed explanation of Mobile Cloud Computing concept by providing different examples, figures and charts showing usage, accessibility, pros and cons and comparison of different cloud platforms.

A Need For An Integrative Security Model For Semantic Stream Reasoning Systems, Admirim Aliti, Edmond Jajaga, Kozeta Sevrani

UBT International Conference

State-of-the-art security frameworks have been extensively addressing security issues for web resources, agents and services in the Semantic Web. The provision of Stream Reasoning as a new area spanning Semantic Web and Data Stream Management Systems has eventually opened up new challenges. Namely, their decentralized nature, the metadata descriptions, the number of users, agents, and services, make securing Stream Reasoning systems difficult to handle. Thus, there is an inherent need of developing new security models which will handle security and automate security mechanisms to a more autonomous system that supports complex and dynamic relationships between data, clients and service providers. …

Analysis Of Central Banks Platforms On Social Networks, Goran Bjelobaba, Ana Savic, Hana Stefanovic

UBT International Conference

The paper describes the advantages of using technical and technological achievements through the social networks and their implementation in Central Banks communication. A study of some Central Banks on their use of social media and some of the most popular social networks are given, showing that social media is becoming an important medium of communication for Central Banks around the world. The study shows that a majority of Central Banks use Twitter to send alerts for information already disseminated through the website, even as they are not very active in responding to public tweets, and also shows an increasing number …

Development And Improvement Of The Quality Of The Mobile Services At The Mobile Market In Macedonia, Arsov Boris, Trajkovski Vasko, Sherifi Vergim

UBT International Conference

To determine the strategic direction for the development of electronic communications market in the part of mobile telecommunication services in Republic of Macedonia, the Agency for electronic communication has made an assessment of the regulatory progress and that has been made in recent years. The needs are in order to obtain a clear strategy for the development of the mobile telecommunication market in Macedonia, and primarily will create a clear picture in the: technical, financial, operational and competitive segments. Republic of Macedonia at this moment has 2 mobile operators with own network and the third mobile virtual operator. They are …

Development Trends In Robotics, Peter Kopacek

UBT International Conference

Robots are always a frequently used as an example for Mechatronic Systems. Currently the field of robotics is very fast growing. Therefore the overview is definitely not actual and have to be improved. The main goal of this contribution is to make some additional remarks to the existing kinds of robots and introduce some new with special emphasis to Mechatronic Systems like manufacturing automation by Production 4.0.