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Articles 13321 - 13350 of 25611

Full-Text Articles in Computer Engineering

Resource Estimation For Large Scale, Real-Time Image Analysis On Live Video Cameras Worldwide, Caleb Tung, Yung-Hsiang Lu, Anup Mohan Aug 2017

Resource Estimation For Large Scale, Real-Time Image Analysis On Live Video Cameras Worldwide, Caleb Tung, Yung-Hsiang Lu, Anup Mohan

The Summer Undergraduate Research Fellowship (SURF) Symposium

Thousands of public cameras live-stream an abundance of data to the Internet every day. If analyzed in real-time by computer programs, these cameras could provide unprecedented utility as a global sensory tool. For example, if cameras capture the scene of a fire, a system running image analysis software on their footage in real-time could be programmed to react appropriately (perhaps call firefighters). No such technology has been deployed at large scale because the sheer computing resources needed have yet to be determined. In order to help us build computer systems powerful enough to achieve such lifesaving feats, we developed a …

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Optimal Placement Of Intrusion Detection Systems To Identify Multi-Stage Attacks In Software Defined Networks, Rebecca S. Salo, Subramaniyam Kannan, Paul C. Wood Aug 2017

Optimal Placement Of Intrusion Detection Systems To Identify Multi-Stage Attacks In Software Defined Networks, Rebecca S. Salo, Subramaniyam Kannan, Paul C. Wood

The Summer Undergraduate Research Fellowship (SURF) Symposium

A major threat to network security is the multi-stage attack, where an attacker compromises an outer edge server from which he penetrates an inner server, and so on, until he gains access to protected information deep in the network. Intrusion detection systems (IDS) can detect such attacks, but limited resources constrain the number of IDS deployed. Software defined networking (SDN) provides network flexibility, and combined with network function virtualization (NFV), it enables IDS placement optimizations that can relieve cost constraint pressures. In this work, we develop a novel algorithm for placing IDS to maximize network protection benefits and minimize costs. …

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Web-Based Interactive Social Media Visual Analytics, Diego Rodríguez-Baquero, Jiawei Zhang, David S. Ebert, Sorin A. Matei Aug 2017

Web-Based Interactive Social Media Visual Analytics, Diego Rodríguez-Baquero, Jiawei Zhang, David S. Ebert, Sorin A. Matei

The Summer Undergraduate Research Fellowship (SURF) Symposium

Real-time social media platforms enable quick information broadcasting and response during disasters and emergencies. Analyzing the massive amount of generated data to understand the human behavior requires data collection and acquisition, parsing, filtering, augmentation, processing, and representation. Visual analytics approaches allow decision makers to observe trends and abnormalities, correlate them with other variables and gain invaluable insight into these situations. In this paper, we propose a set of visual analytic tools for analyzing and understanding real-time social media data in times of crisis and emergency situations. First, we model the degree of risk of individuals’ movement based on evacuation zones …

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Development Of A Water Quality Status And Trend Detection Tool*, Ruchir Aggarwal, Valeria Mijares, Margaret W. Gitau Aug 2017

Development Of A Water Quality Status And Trend Detection Tool*, Ruchir Aggarwal, Valeria Mijares, Margaret W. Gitau

The Summer Undergraduate Research Fellowship (SURF) Symposium

Water Quality Index (WQI) models have been developed since the early 1970s. They present a means by which water quality status and trends can be compared across time and space on the basis of a composite value computed using existing water quality data. There is a need for a tool that can bring the different water quality parameters together and calculate the WQIs so as to facilitate data use in predictive modeling and water quality management. We are developing a software tool that can be used by water quality managers and others with different technical backgrounds to calculate WQI of …

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Compiler And Runtime Optimization Techniques For Implementation Scalable Parallel Applications, Zahra Khatami Aug 2017

Compiler And Runtime Optimization Techniques For Implementation Scalable Parallel Applications, Zahra Khatami

LSU Doctoral Dissertations

The compiler is able to detect the data dependencies in an application and is able to analyze the specific sections of code for parallelization potential. However, all of these techniques provided by a compiler are usually applied at compile time, so they rely on static analysis, which is insufficient for achieving maximum parallelism and desired application scalability. These compiler techniques should consider both the static information gathered at compile time and dynamic analysis captured at runtime about the system to generate a safe parallel application. On the other hand, runtime information is often speculative. Solely relying on it doesn't guarantee …

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A Feature-Based Structural Measure: An Image Similarity Measure For Face Recognition, Noor A. Shnain, Zahir Hussain, Song F. Lu Aug 2017

A Feature-Based Structural Measure: An Image Similarity Measure For Face Recognition, Noor A. Shnain, Zahir Hussain, Song F. Lu

Research outputs 2014 to 2021

Facial recognition is one of the most challenging and interesting problems within the field of computer vision and pattern recognition. During the last few years, it has gained special attention due to its importance in relation to current issues such as security, surveillance systems and forensics analysis. Despite this high level of attention to facial recognition, the success is still limited by certain conditions; there is no method which gives reliable results in all situations. In this paper, we propose an efficient similarity index that resolves the shortcomings of the existing measures of feature and structural similarity. This measure, called …

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Spectroscopic Contrast Of Diarylethene Molecules On Octanethiol Monolayer, Arramel Arramel, Tibor Kudernac, Nathalie Katsonis, Bernard Lucas Feringa, Bart Jan Van Wees Aug 2017

Spectroscopic Contrast Of Diarylethene Molecules On Octanethiol Monolayer, Arramel Arramel, Tibor Kudernac, Nathalie Katsonis, Bernard Lucas Feringa, Bart Jan Van Wees

Makara Journal of Technology

We present a systematic scanning tunneling microscopy (STM) study of bias-dependent imaging of disulfur diarylethene (2S-DE) molecules on octanethiol (C8) monolayer at room temperature. In a rigid confinement of the C8 matrix, we did not observe any significant variation in the appearance of the 2S-DE. On the contrary, a reversal in the apparent height of the 2S-DE was present when the molecule was situated on a gold vacancy island. We attributed this finding to the presence of a new electronic state that became accessible for a tunneling event. In addition, the C8 surface structure underwent a reversible phase transformation from …

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Residual Stress Measurements On The Tig Weld Joint Of 57fe15cr25ni Austenitic Steel For Structural Material Applications By Means X-Ray Diffraction Techniques, Parikin Parikin, Agus Hadi Ismoyo, Riza Iskandar, Arbi Dimyati Aug 2017

Residual Stress Measurements On The Tig Weld Joint Of 57fe15cr25ni Austenitic Steel For Structural Material Applications By Means X-Ray Diffraction Techniques, Parikin Parikin, Agus Hadi Ismoyo, Riza Iskandar, Arbi Dimyati

Makara Journal of Technology

Measurements of residual stress on the 57Fe25Cr15Ni steel plate with no-filler TIG-welding process were carried out. This work was conducted to determine the nature of weld ability in synthesized steel. The bulks were formed in a dimension of 30x20x7 mm3 to ease data retrieval. Results show that the largest residual stress occurred in the weld metal area, amounting to 82.40 MPa with lattice stretching of 0.18%. Conversely, the values decreased to 65.92 MPa and a stretch of 0.14% in the HAZ area. This residual stress is a tensile stress that can reduce the mechanical strength of the material since it …

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An Efficient Palladium-Thiourea Catalysed Heck Cross-Coupling Reaction For Molecular Electronic Interest, Wan M. Khairul, Mohd Shahrul Shahmi Md Shariff, Rafizah Rahamathullah, Adibah Izzati Daud, Mustaffa Shamsuddin, Siti Kamilah Che Soh Aug 2017

An Efficient Palladium-Thiourea Catalysed Heck Cross-Coupling Reaction For Molecular Electronic Interest, Wan M. Khairul, Mohd Shahrul Shahmi Md Shariff, Rafizah Rahamathullah, Adibah Izzati Daud, Mustaffa Shamsuddin, Siti Kamilah Che Soh

Makara Journal of Technology

The synthesis and utilization of C-C bonds formation are concerned about the key steps for the building of several conducting molecular electronics involving many asymmetric catalysts approached, which is an essential task that most researchers would ignore in preparing these materials to enhance the production yield of cross-coupling materials. Despite the enormous progress, there still remains a great demand for economic and practicable cross-coupling processes involving ultra-low catalyst loadings with high turnover numbers due to the employment of conventional metal catalyst. Thus, there has been an excessive interest to cultivate non-phosphine palladium catalysts for excellent achievement of activity, stability, and …

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A Study On Dielectric Properties Of The Cellulose Derivative-Nh4br-Glycerol- Based The Solid Polymer Electrolyte System, Nur Muhitul Jalilah Rasali, Saifful Kamaluddin Muzakir, Ahmad Salihin Samsudin Aug 2017

A Study On Dielectric Properties Of The Cellulose Derivative-Nh4br-Glycerol- Based The Solid Polymer Electrolyte System, Nur Muhitul Jalilah Rasali, Saifful Kamaluddin Muzakir, Ahmad Salihin Samsudin

Makara Journal of Technology

The characterization of biopolymer-based solid polymer electrolytes (SPEs) has been carried out in this present work. Cellulose derivative was chosen due to its superior physical attributes. In this work, NH4Br-doped glycerol plasticized carboxyl methylcellulose-based SPEs were successfully prepared via the solution casting method. The conductivity and dielectric properties of the prepared films were investigated using the impedance analysis which presented ~1.91×10-3 Scm-1 (with addition of 6 wt% of glycerol). In addition, the studied SPE system shows a non-Debye behaviour without a single relaxation time. The findings of the research indicate that the complexes of NH4Br and glycerol in the cellulose …

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Urban Drainage Management And Flood Control Improvement Using The Duflow Case Study: Aur Sub Catchment, Palembang, South Sumatra, Indonesia, Charlotte De Fraiture, Robiyanto Hendro Susanto, F.X. Suryadi, Harrini Mutiara Hapsari Wahyu Aug 2017

Urban Drainage Management And Flood Control Improvement Using The Duflow Case Study: Aur Sub Catchment, Palembang, South Sumatra, Indonesia, Charlotte De Fraiture, Robiyanto Hendro Susanto, F.X. Suryadi, Harrini Mutiara Hapsari Wahyu

Makara Journal of Technology

Urban flooding often times staggers the livelihood in an urban area, which most likely happens in the lowland urban area. Therefore, the existing urban drainage system should be improved in order to tackle the upcoming urban flooding events, which are more than likely to be more devastating than those in the previous years. The research location is in Palembang, Sumatra, Indonesia, where 30% of its urban part is a lowland area. The selected Aur Sub Catchment is located in Silaberanti. The main objective of this research is to improve the current drainage system in order to achieve the optimal design …

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Ethanol Purification Using Activated Natural Zeolite, Chandra Wahyu Purnomo, Nelliza Putri, Indra Perdana, Hirofumi Hinode Aug 2017

Ethanol Purification Using Activated Natural Zeolite, Chandra Wahyu Purnomo, Nelliza Putri, Indra Perdana, Hirofumi Hinode

Makara Journal of Technology

Bio ethanol is one of the potential fuels in the future. However, ethanol in water mixture has an azeotropic concentration of 95.6 wt. %, which makes it difficult to purify further. The common method of purification is by using an azeotropic distillation column, which requires an intensive energy and an addition of specific solvent. In this study, ethanol purification is done using an adsorption column packed with zeolite Raschig rings. The natural zeolite ring was modified beforehand using the NaOH solution to enhance the material’s water adsorption performance. The ethanol purity can reach more than 99% with the modified zeolite …

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Physical And Mechanical Properties Of Palm Kernel Oil-Based Polyester Polyurethane/Multi-Walled Carbon Nanotube Composites, Khairul Anuar Mat Amin, Muhammad Alif Zailani, Nurul Nabilah Zulkifli, Khairiah Haji Badri Aug 2017

Physical And Mechanical Properties Of Palm Kernel Oil-Based Polyester Polyurethane/Multi-Walled Carbon Nanotube Composites, Khairul Anuar Mat Amin, Muhammad Alif Zailani, Nurul Nabilah Zulkifli, Khairiah Haji Badri

Makara Journal of Technology

In this study, polyurethane (PU) films from palm kernel oil-based polyester (PKO-p) incorporated multi-walled carbon nanotubes (MWNTs) are prepared via a evaporative casting method. Nanoparticle fluid dispersions containing 0.02%, 0.03%, and 0.05% wt. of MWNTs are added into PKO-p based resin and mixed by digital probe sonicator for 30 min followed by mixing with isocyanate to produce PU-MWNTs composite films. The mechanical properties, swelling, water vapour transmission rate (WVTR) and conductivity of the PU-MWNTs composite films are examined. Results show that the toughness (T) or flexibility, the tensile strength (TS), and Young’s modulus (YM) values of PU-MWNTs composite films increase …

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Personality Trait Based Intervention For Workplace Accident Prevention, Yassierli Yassierli, Nurhayati Nurhayati, Marisa Anatasia, Shamsul Bahri Aug 2017

Personality Trait Based Intervention For Workplace Accident Prevention, Yassierli Yassierli, Nurhayati Nurhayati, Marisa Anatasia, Shamsul Bahri

Makara Journal of Technology

Previous research has suggested that some traits may be useful as the predictors of risk behaviours behaviors. Therefore, personality traits seem to play a role in accident involvement. The purpose of this study is was to explore the relationship between the personality traits based on the Big Five Inventory (BFI) and worker accident experiences in order to elaborate personality traits based intervention for workplace accident prevention. A cross cross-sectional study was conducted among 173 workers in a cement company using a set of questionnaires consisting of respondents’ characteristics, BFI, and self-reported accident experience. The correlations were computed using Goodman Kruskal’s …

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Breaking Into The Vault: Privacy, Security And Forensic Analysis Of Android Vault Applications, Xiaolu Zhang, Ibrahim Baggili, Frank Breitinger Aug 2017

Breaking Into The Vault: Privacy, Security And Forensic Analysis Of Android Vault Applications, Xiaolu Zhang, Ibrahim Baggili, Frank Breitinger

Electrical & Computer Engineering and Computer Science Faculty Publications

In this work we share the first account for the forensic analysis, security and privacy of Android vault applications. Vaults are designed to be privacy enhancing as they allow users to hide personal data but may also be misused to hide incriminating files. Our work has already helped law enforcement in the state of Connecticut to reconstruct 66 incriminating images and 18 videos in a single criminal case. We present case studies and results from analyzing 18 Android vault applications (accounting for nearly 220 million downloads from the Google Play store) by reverse engineering them and examining the forensic artifacts …

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Robust Classification Of City Roadway Objects For Traffic Related Applications, Niveditha Bhandary, Charles Mackay, Alex Richards, Ji Tong, David Anastasiu Aug 2017

Robust Classification Of City Roadway Objects For Traffic Related Applications, Niveditha Bhandary, Charles Mackay, Alex Richards, Ji Tong, David Anastasiu

Faculty Publications

The increasing prevalence of video data, particularly from traffic and surveillance cameras, is accompanied by a growing need for improved object detection, tracking, and classification techniques. In order to encourage development in this area, the AI City Challenge, sponsored by IEEE Smart World and NVIDIA, cultivated a competitive environment in which teams from all over the world sought to demonstrate the effectiveness of their models after training and testing on a common dataset of 114,766 unique traffic camera keyframes. Models were constructed for two distinct purposes; track 1 designs addressed object detection, localization and classification, while track 2 designs aimed …

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The Nvidia Ai City Challenge, Milind Naphade, David Anastasiu, Anuj Sharma, Vamsi Jagrlamudi, Hyeran Jeon, Kaikai Liu, Ming-Ching Chang, Siwei Lyu, Zeyu Gao Aug 2017

The Nvidia Ai City Challenge, Milind Naphade, David Anastasiu, Anuj Sharma, Vamsi Jagrlamudi, Hyeran Jeon, Kaikai Liu, Ming-Ching Chang, Siwei Lyu, Zeyu Gao

Faculty Publications

Web image analysis has witnessed an AI renaissance. The ILSVRC benchmark has been instrumental in providing a corpus and standardized evaluation. The NVIDIA AI City Challenge is envisioned to provide similar impetus to the analysis of image and video data that helps make cities smarter and safer. In its first year, this Challenge has focused on traffic video data. While millions of traffic video cameras around the world capture data, albeit low-quality, very little automated analysis and value creation results. Lack of labeled data, and trained models that can be deployed at the edge of the city fabric, ensure that …

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On-Chip Training Of Memristor Crossbar Based Multi-Layer Neural Networks, Raqibul Hasan, Tarek M. Taha, Christopher Yakopcic Aug 2017

On-Chip Training Of Memristor Crossbar Based Multi-Layer Neural Networks, Raqibul Hasan, Tarek M. Taha, Christopher Yakopcic

Electrical and Computer Engineering Faculty Publications

Memristor crossbar arrays carry out multiply-add operations in parallel in the analog domain, and so can enable neuromorphic systems with high throughput at low energy and area consumption. On-chip training of these systems have the significant advantage of being able to get around device variability and faults. This paper presents on-chip training circuits for multi-layer neural networks implemented using a single crossbar per layer and two memristors per synapse. Using two memristors per synapse provides double the synaptic weight precision when compared to a design that uses only one memristor per synapse. Proposed on-chip training system utilizes the back propagation …

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Deep Learning And Transfer Learning In The Classification Of Eeg Signals, Jacob M. Williams Aug 2017

Deep Learning And Transfer Learning In The Classification Of Eeg Signals, Jacob M. Williams

School of Computing: Dissertations, Theses, and Student Research

Deep learning is seldom used in the classification of electroencephalography (EEG) signals, despite achieving state of the art classification accuracies in other spatial and time series data. Instead, most research has continued to use manual feature extraction followed by a traditional classifier, such as SVMs or logistic regression. This is largely due to the low number of samples per experiment, high-dimensional nature of the data, and the difficulty in finding appropriate deep learning architectures for classification of EEG signals. In this thesis, several deep learning architectures are compared to traditional techniques for the classification of visually evoked EEG signals. We …

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Exploring The Telecommunications Properties Of The Human Nervous System: Analytical Modeling And Experimental Validation Of Information Flow Through The Somatosensory System, Natalie Hanisch Aug 2017

Exploring The Telecommunications Properties Of The Human Nervous System: Analytical Modeling And Experimental Validation Of Information Flow Through The Somatosensory System, Natalie Hanisch

School of Computing: Dissertations, Theses, and Student Research

The growing field of Body Area Networks (BANs) is providing solutions to the wireless connectivity of wearable and implantable devices with applications in medicine, entertainment, fitness, and military, amongst others. While electromagnetic wave propagation has been the main BANs' enabling technology, the increasingly pervasive nature of these devices encourages novel solutions with added bio-compatibility and sustainability. In this thesis, a novel communication system is proposed for BANs based on the natural propagation of tactile stimuli through the nervous system. This system is composed of a tactile stimulator coupled to an ElectroEncephaloGraphy (EEG) system, and realizes the propagation of somatosensory signals …

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Energy And Performance Balancing Architecture For Asynchronous Data Processing Platforms, Chien-Wei Lo Aug 2017

Energy And Performance Balancing Architecture For Asynchronous Data Processing Platforms, Chien-Wei Lo

Graduate Theses and Dissertations

The semiconductor industry has been increasingly focused on the energy consumption and heat generation in CMOS-based integrated circuits (ICs) for its dominating impact on the system performance and reliability. Without clock-related timing constraints, asynchronous circuits have demonstrated unique flexibility in performance-energy tradeoffs compared to synchronous designs. This dissertation work presents the architecture capable of balancing energy and performance for asynchronous digital signal processing circuits using the Multi-Threshold NULL Convention Logic (MTNCL). Architecture implementing user-configurable adaptive dynamic voltage scaling (DVS) and data processing core disabling based on the detection and parameterization of system throughput are developed for MTNCL parallel homogeneous and …

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Operating System Identification By Ipv6 Communication Using Machine Learning Ensembles, Adrian Ordorica Aug 2017

Operating System Identification By Ipv6 Communication Using Machine Learning Ensembles, Adrian Ordorica

Graduate Theses and Dissertations

Operating system (OS) identification tools, sometimes called fingerprinting tools, are essential for the reconnaissance phase of penetration testing. While OS identification is traditionally performed by passive or active tools that use fingerprint databases, very little work has focused on using machine learning techniques. Moreover, significantly more work has focused on IPv4 than IPv6. We introduce a collaborative neural network ensemble that uses a unique voting system and a random forest ensemble to deliver accurate predictions. This approach uses IPv6 features as well as packet metadata features for OS identification. Our experiment shows that our approach is valid and we achieve …

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An Ameliorated Prediction Of Drug–Target Interactions Based On Multi-Scale Discrete Wavelet Transform And Network Features, Cong Shen, Yijie Ding, Jijun Tang, Xinying Xu, Fei Guo Aug 2017

An Ameliorated Prediction Of Drug–Target Interactions Based On Multi-Scale Discrete Wavelet Transform And Network Features, Cong Shen, Yijie Ding, Jijun Tang, Xinying Xu, Fei Guo

Faculty Publications

The prediction of drug–target interactions (DTIs) via computational technology plays a crucial role in reducing the experimental cost. A variety of state-of-the-art methods have been proposed to improve the accuracy of DTI predictions. In this paper, we propose a kind of drug–target interactions predictor adopting multi-scale discrete wavelet transform and network features (named as DAWN) in order to solve the DTIs prediction problem. We encode the drug molecule by a substructure fingerprint with a dictionary of substructure patterns. Simultaneously, we apply the discrete wavelet transform (DWT) to extract features from target sequences. Then, we concatenate and normalize the target, drug, …

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Study Of Comparison Of Ocs And Hybrid Switching In Fso Data Centers, Suraj Yadav Aug 2017

Study Of Comparison Of Ocs And Hybrid Switching In Fso Data Centers, Suraj Yadav

School of Computing: Dissertations, Theses, and Student Research

With the increase in big data applications, it has become the need of the hour to handle data efficiently to handle the growing traffic in the data centers. The popular mechanism is parallel processing using commodity hardware hence it is becoming an interesting research topic to explore new architectures which have high performance, but with an increase in data sizes the architecture has to expand which increases the cabling complexity. Hence the study of Free Space Optical (FSO) communication for the data centers is gaining more importance now than ever. We proposed square OWCELL topology which is a new free …

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Dynamic Adversarial Mining - Effectively Applying Machine Learning In Adversarial Non-Stationary Environments., Tegjyot Singh Sethi Aug 2017

Dynamic Adversarial Mining - Effectively Applying Machine Learning In Adversarial Non-Stationary Environments., Tegjyot Singh Sethi

Electronic Theses and Dissertations

While understanding of machine learning and data mining is still in its budding stages, the engineering applications of the same has found immense acceptance and success. Cybersecurity applications such as intrusion detection systems, spam filtering, and CAPTCHA authentication, have all begun adopting machine learning as a viable technique to deal with large scale adversarial activity. However, the naive usage of machine learning in an adversarial setting is prone to reverse engineering and evasion attacks, as most of these techniques were designed primarily for a static setting. The security domain is a dynamic landscape, with an ongoing never ending arms race …

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An Interactive Interface For Nursing Robots., Ankita Sahu Aug 2017

An Interactive Interface For Nursing Robots., Ankita Sahu

Electronic Theses and Dissertations

Physical Human-Robot Interaction (pHRI) is inevitable for a human user while working with assistive robots. There are various aspects of pHRI, such as choosing the interface, type of control schemes implemented and the modes of interaction. The research work presented in this thesis concentrates on a health-care assistive robot called Adaptive Robot Nursing Assistant (ARNA). An assistive robot in a health-care environment has to be able to perform routine tasks and be aware of the surrounding environment at the same time. In order to operate the robot, a teleoperation based interaction would be tedious for some patients as it would …

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A Data Science Pipeline For Educational Data : A Case Study Using Learning Catalytics In The Active Learning Classroom., Asuman Cagla Acun Sener Aug 2017

A Data Science Pipeline For Educational Data : A Case Study Using Learning Catalytics In The Active Learning Classroom., Asuman Cagla Acun Sener

Electronic Theses and Dissertations

This thesis presents an applied data science methodology on a set of University of Louisville, Speed School of Engineering student data. We used data mining and classic statistical techniques to help educational researchers quickly see the data trends and peculiarities. Our data includes scores and information about two Engineering Fundamental Class. The format of these classes is called an inverted classroom model or flipped class. The purpose of this study is to analyze the data in order to uncover potentially hidden information, tell interesting stories about the data, examine student learning behavior and learning performance in an active learning environment, …

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Pivot-Based Metric Indexing, Lu Chen, Yunjun Gao, Baihua Zheng, Christian S. Jensen, Hanyu Yang, Keyu Yang Aug 2017

Pivot-Based Metric Indexing, Lu Chen, Yunjun Gao, Baihua Zheng, Christian S. Jensen, Hanyu Yang, Keyu Yang

Research Collection School Of Computing and Information Systems

The general notion of a metric space encompasses a diverse range of data types and accompanying similarity measures. Hence, metric search plays an important role in a wide range of settings, including multimedia retrieval, data mining, and data integration. With the aim of accelerating metric search, a collection of pivot-based indexing techniques for metric data has been proposed, which reduces the number of potentially expensive similarity comparisons by exploiting the triangle inequality for pruning and validation. However, no comprehensive empirical study of those techniques exists. Existing studies each offers only a narrower coverage, and they use different pivot selection strategies …

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Geometric Approaches For Top-K Queries [Tutorial], Kyriakos Mouratidis Aug 2017

Geometric Approaches For Top-K Queries [Tutorial], Kyriakos Mouratidis

Research Collection School Of Computing and Information Systems

Top-k processing is a well-studied problem with numerous applications that is becoming increasingly relevant with the growing availability of recommendation systems and decision-making software. The objective of this tutorial is twofold. First, we will delve into the geometric aspects of top-k processing. Second, we will cover complementary features to top-k queries, with strong practical relevance and important applications, that have a computational geometric nature. The tutorial will close with insights in the effect of dimensionality on the meaningfulness of top-k queries, and interesting similarities to nearest neighbor search.

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Mechanism Design For Strategic Project Scheduling, Pradeep Varakantham, Na Fu Aug 2017

Mechanism Design For Strategic Project Scheduling, Pradeep Varakantham, Na Fu

Research Collection School Of Computing and Information Systems

Organizing large scale projects (e.g., Conferences, IT Shows, F1 race) requires precise scheduling of multiple dependent tasks on common resources where multiple selfish entities are competing to execute the individual tasks. In this paper, we consider a well studied and rich scheduling model referred to as RCPSP (Resource Constrained Project Scheduling Problem). The key change to this model that we consider in this paper is the presence of selfish entities competing to perform individual tasks with the aim of maximizing their own utility. Due to the selfish entities in play, the goal of the scheduling problem is no longer only …

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