Digital Commons Network^™

Differential Privacy Protection Over Deep Learning: An Investigation Of Its Impacted Factors, Ying Lin, Ling-Yan Bao, Ze-Minghui Li, Shu-Sheng Si, Chao-Hsien Chu

Research Collection School Of Computing and Information Systems

Deep learning (DL) has been widely applied to achieve promising results in many fields, but it still exists various privacy concerns and issues. Applying differential privacy (DP) to DL models is an effective way to ensure privacy-preserving training and classification. In this paper, we revisit the DP stochastic gradient descent (DP-SGD) method, which has been used by several algorithms and systems and achieved good privacy protection. However, several factors, such as the sequence of adding noise, the models used etc., may impact its performance with various degrees. We empirically show that adding noise first and clipping second will not only …

Lightning-Fast And Privacy-Preserving Outsourced Computation In The Cloud, Ximeng Liu, Robert H. Deng, Pengfei Wu, Yang Yang

Research Collection School Of Computing and Information Systems

In this paper, we propose a framework for lightning-fast privacy-preserving outsourced computation framework in the cloud, which we refer to as LightCom. Using LightCom, a user can securely achieve the outsource data storage and fast, secure data processing in a single cloud server different from the existing multi-server outsourced computation model. Specifically, we first present a general secure computation framework for LightCom under the cloud server equipped with multiple Trusted Processing Units (TPUs), which face the side-channel attack. Under the LightCom, we design two specified fast processing toolkits, which allow the user to achieve the commonly-used secure integer computation and …

Nearest Centroid: A Bridge Between Statistics And Machine Learning, Manoj Thulasidas

Research Collection School Of Computing and Information Systems

In order to guide our students of machine learning in their statistical thinking, we need conceptually simple and mathematically defensible algorithms. In this paper, we present the Nearest Centroid algorithm (NC) algorithm as a pedagogical tool, combining the key concepts behind two foundational algorithms: K-Means clustering and K Nearest Neighbors (k- NN). In NC, we use the centroid (as defined in the K-Means algorithm) of the observations belonging to each class in our training data set and its distance from a new observation (similar to k-NN) for class prediction. Using this obvious extension, we will illustrate how the concepts of …

Causal Intervention For Weakly-Supervised Semantic Segmentation, Zhang Dong, Hanwang Zhang, Jinhui Tang, Xian-Sheng Hua, Qianru Sun

Research Collection School Of Computing and Information Systems

We present a causal inference framework to improve Weakly-Supervised Semantic Segmentation (WSSS). Specifically, we aim to generate better pixel-level pseudo-masks by using only image-level labels --- the most crucial step in WSSS. We attribute the cause of the ambiguous boundaries of pseudo-masks to the confounding context, e.g., the correct image-level classification of "horse'' and "person'' may be not only due to the recognition of each instance, but also their co-occurrence context, making the model inspection (e.g., CAM) hard to distinguish between the boundaries. Inspired by this, we propose a structural causal model to analyze the causalities among images, contexts, and …

Debunking Rumors On Twitter With Tree Transformer, Jing Ma, Wei Gao

Research Collection School Of Computing and Information Systems

Rumors are manufactured with no respect for accuracy, but can circulate quickly and widely by "word-of-post" through social media conversations. Conversation tree encodes important information indicative of the credibility of rumor. Existing conversation-based techniques for rumor detection either just strictly follow tree edges or treat all the posts fully-connected during feature learning. In this paper, we propose a novel detection model based on tree transformer to better utilize user interactions in the dialogue where post-level self-attention plays the key role for aggregating the intra-/inter-subtree stances. Experimental results on the TWITTER and PHEME datasets show that the proposed approach consistently improves …

Smartfuzz: An Automated Smart Fuzzing Approach For Testing Smartthings Apps, Lwin Khin Shar, Nguyen Binh Duong Ta, Lingxiao Jiang, David Lo, Wei Minn, Kiah Yong Glenn Yeo, Eugene Kim

Research Collection School Of Computing and Information Systems

As IoT ecosystem has been fast-growing recently, there have been various security concerns of this new computing paradigm. Malicious IoT apps gaining access to IoT devices and capabilities to execute sensitive operations (sinks), e.g., controlling door locks and switches, may cause serious security and safety issues. Unlike traditional mobile/web apps, IoT apps highly interact with a wide variety of physical IoT devices and respond to environmental events, in addition to user inputs. It is therefore important to conduct comprehensive testing of IoT apps to identify possible anomalous behaviours. On the other hand, it is also important to optimize the number …

Renewal Of An Information Systems Curriculum To Support Career Based Tracks: A Case Study, Swapna Gottipati, Venky Shankararaman, Kyong Jin Shim

Research Collection School Of Computing and Information Systems

The pace at which technology redefines traditional job functions is picking up rapidly. This trend is triggered particularly by advances in analytics, security, cloud computing, Artificial Intelligence and big data. The purpose of this paper is to present a case study on our approach to renewing an undergraduate IS Major curriculum to align with the needs of the industry. We adopt a survey based approach to study Information Systems (IS) graduate skills requirements and re-design the curriculum framework for the IS program at our school. The paper describes in detail the process, the redesigned IS curriculum, the impact of the …

A Social Network Analysis Of Jobs And Skills, Derrick Ming Yang Lee, Dion Wei Xuan Ang, Grace Mei Ching Pua, Lee Ning Ng, Sharon Purbowo, Eugene Wen Jia Choy, Kyong Jin Shim

Research Collection School Of Computing and Information Systems

In this study, we analyzed job roles and skills across industries in Singapore. Using social network analysis, we identified job roles with similar required skills, and we also identified relationships between job skills. Our analysis visualizes such relationships in an intuitive way. Insights derived from our analyses are expected to assist job seekers, employers as well as recruitment agencies wanting to understand trending and required job roles and skills in today’s fast changing world.

A Hybrid Approach For Detecting Prerequisite Relations In Multi-Modal Food Recipes, Liangming Pan, Jingjing Chen, Shaoteng Liu, Chong-Wah Ngo, Min-Yen Kan, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Modeling the structure of culinary recipes is the core of recipe representation learning. Current approaches mostly focus on extracting the workflow graph from recipes based on text descriptions. Process images, which constitute an important part of cooking recipes, has rarely been investigated in recipe structure modeling. We study this recipe structure problem from a multi-modal learning perspective, by proposing a prerequisite tree to represent recipes with cooking images at a step-level granularity. We propose a simple-yet-effective two-stage framework to automatically construct the prerequisite tree for a recipe by (1) utilizing a trained classifier to detect pairwise prerequisite relations that fuses …

Jointly Optimizing Sensing Pipelines For Multimodal Mixed Reality Interaction, Ramesh Darshana Rathnayake Kanatta Gamage, Ashen De Silva, Dasun Puwakdandawa, Lakmal Meegahapola, Archan Misra, Indika Perera

Research Collection School Of Computing and Information Systems

Natural human interactions for Mixed Reality Applications are overwhelmingly multimodal: humans communicate intent and instructions via a combination of visual, aural and gestural cues. However, supporting low-latency and accurate comprehension of such multimodal instructions (MMI), on resource-constrained wearable devices, remains an open challenge, especially as the state-of-the-art comprehension techniques for each individual modality increasingly utilize complex Deep Neural Network models. We demonstrate the possibility of overcoming the core limitation of latency–vs.–accuracy tradeoff by exploiting cross-modal dependencies–i.e., by compensating for the inferior performance of one model with an increased accuracy of more complex model of a different modality. We present a …

Sadt: Syntax-Aware Differential Testing Of Certificate Validation In Ssl/Tls Implementations, Lili Quan, Qianyu Guo, Hongxu Chen, Xiaofei Xie, Xiaohong Li, Yang Liu, Jing Hu

Research Collection School Of Computing and Information Systems

The security assurance of SSL/TLS critically depends on the correct validation of X.509 certificates. Therefore, it is important to check whether a certificate is correctly validated by the SSL/TLS implementations. Although differential testing has been proven to be effective in finding semantic bugs, it still suffers from the following limitations: (1) The syntax of test cases cannot be correctly guaranteed. (2) Current test cases are not diverse enough to cover more implementation behaviours. This paper tackles these problems by introducing SADT, a novel syntax-aware differential testing framework for evaluating the certificate validation process in SSL/TLS implementations. We first propose a …

Design Of A Two-Echelon Freight Distribution System In An Urban Area Considering Third-Party Logistics And Loading-Unloading Zones, Vincent F. Yu, Winarno, Shih-Wei Lin, Aldy Gunawan

Research Collection School Of Computing and Information Systems

This research examines the problem of designing a two-echelon freight distribution system in a dense urban area that considers third-party logistics (TPL) and loading–unloading zones (LUZs). The proposed system takes advantage of outsourcing the last mile deliveries to a TPL provider and utilizing LUZs as temporary intermediate facilities instead of using permanent intermediate facilities to consolidate freight. A mathematical model and a simulated annealing (SA) algorithm are developed to solve the problem. The efficiency and effectiveness of the proposed SA heuristic are verified by testing it on existing benchmark instances. Computational results show that the performance of the proposed SA …

Understanding Continuance Intention Toward Crowdsourcing Games: A Longitudinal Investigation, Xiaohui Wang, Dion Hoe-Lian Goh, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Given the increasing popularity of gamified crowdsourcing, the study reported here involved examining determinants of users' continuance intention toward crowdsourcing games, both with longitudinal data and reference to a revised unified theory of acceptance and use of technology (UTAUT). At three time points, data were collected from an online survey about playing crowdsourcing games. Time-lagged regression, cross-temporal correlation, and structural equation modeling were performed to examine determinants of the acceptance of crowdsourcing games. Results indicate that the revised UTAUT2 is applicable to explaining the acceptance of crowdsourcing games. Not only did effort expectancy, hedonic motivation, and social influence directly affect …

Security Analysis Of Permission Re-Delegation Vulnerabilities In Android Apps, Biniam Fisseha Demissie, Mariano Ceccato, Lwin Khin Shar

Research Collection School Of Computing and Information Systems

The Android platform facilitates reuse of app functionalities by allowing an app to request an action from another app through inter-process communication mechanism. This feature is one of the reasons for the popularity of Android, but it also poses security risks to the end users because malicious, unprivileged apps could exploit this feature to make privileged apps perform privileged actions on behalf of them. In this paper, we investigate the hybrid use of program analysis, genetic algorithm based test generation, natural language processing, machine learning techniques for precise detection of permission re-delegation vulnerabilities in Android apps. Our approach first groups …

Sharper Generalisation Bounds For Pairwise Learning, Yunwen Lei, Antoine Ledent, Marius Kloft

Research Collection School Of Computing and Information Systems

Pairwise learning refers to learning tasks with loss functions depending on a pair of training examples, which includes ranking and metric learning as specific examples. Recently, there has been an increasing amount of attention on the generalization analysis of pairwise learning to understand its practical behavior. However, the existing stability analysis provides suboptimal high-probability generalization bounds. In this paper, we provide a refined stability analysis by developing generalization bounds which can be √nn-times faster than the existing results, where nn is the sample size. This implies excess risk bounds of the order O(n−1/2) (up to a logarithmic factor) for both …

Environmental Hygiene For Covid-19: It's All About The Mask, Daniel B. Oerther, Mona Shattell

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

No abstract provided.

Partial Sums Of Some Fractional Operators Of Bounded Turning, Zainab E. Abdulnaby

Baghdad Science Journal

In this paper, several conditions are put in order to compose the sequence of partial sums , and of the fractional operators of analytic univalent functions , and of bounded turning which are bounded turning too.

The Fractional Local Metricdimension Of Combproduct Graphs, S. Aisyah, Mohammad Imam Utoyo, Liliek Susilowati

Baghdad Science Journal

For the connected graph G with vertex set V(G)and edge set E(G), the localresolvingneighborhood R1{u,v}of two adjacent vertices u,v isdefined by R1{u,v}={ x ꞓ v(G):d(x,u)≠��d(x,v)}. A local resolving0function f1of G is a real valued function f1:V(G)→[0,1]such0 that f1(R1{u,v})≥1 for every two adjacent u,v vertices u,v ꞓ (x,v).Thefractional local metric dimension of graph G denoted dim f1(G), is defined by dim f1(G)=min⁡{| f1|:f1}.One of the operation in graph is the comb product graphs. The comb product graphs of G and H is denoted by ��G ⊳ H⊳��.The purpose of this research is to determine the fractionallocal metric dimension of G ⊳ …

The Numerical Technique Based On Shifted Jacobi-Gauss-Lobatto Polynomials For Solving Two Dimensional Multi-Space Fractional Bioheat Equations, Hameeda Oda Al-Humedi, Firas Amer Al-Saadawi

Baghdad Science Journal

This article deals with the approximate algorithm for two dimensional multi-space fractional bioheat equations (M-SFBHE). The application of the collection method will be expanding for presenting a numerical technique for solving M-SFBHE based on “shifted Jacobi-Gauss-Labatto polynomials” (SJ-GL-Ps) in the matrix form. The Caputo formula has been utilized to approximate the fractional derivative and to demonstrate its usefulness and accuracy, the proposed methodology was applied in two examples. The numerical results revealed that the used approach is very effective and gives high accuracy and good convergence.

Optimization Of Voltammetric Determination Of Dysprosium (Iii) Using Plackett-Burman And Rsm-Ccd Experimental Designs, Santhy Wyantuti, Zulida Setyorini, Safri Ishmayana, Yeni Wahyuni Hartati, M Lutfi Firdaus

Baghdad Science Journal

This study was aimed to develop an optimized Dy determination method using differential pulse voltammetry (DPV). The Plackett-Burman (PB) experimental design was used to select significant factors that affect the electrical current response, which were further optimized using the response surface method-central composite design (RSM-CCD). The type of electrolyte solution and amplitude modulation were found as two most significant factors, among the nine factors tested, which enhance the current response based on PB design. Further optimization using RSM-CCD shows that the optimum values for the two factors were 0.1046 M and 0.1082 V respectively. When the optimum conditions were applied …

A Generalization Of T-Practical Numbers, Saad A. Baddai

Baghdad Science Journal

This paper generalizes and improves the results of Margenstren, by proving that the number of t-practical numbers��n,n≤x,(t≥1) which is defined by N(x) has a lower bound in terms of . This bound is more sharper than Mangenstern bound when Further general results are given for the existence of -practical numbers, by proving that the interval (x.x +2(x/t)^½, t≥1 contains a t-practical for all x≥t/3

Designing A Microstrip Patch Antenna In Part Of Ultra-Wideband Applications, Wa'il A. Godaymi Al-Tumah, Raed M. Shaaban, Zeki A. Ahmed

Baghdad Science Journal

In this work, a simulated study was carried out for designing a novel spiral rectangular patch of microstrip antenna that is used in ultra-wideband applications by using a high frequency structure simulator software (HFSS). A substrate with dielectric constant of 4.4 and height 2.10 mm (commercial substrate height available is about 0.8-1.575 mm) has been used for the design of the proposed antenna. The design basis for enhancing bandwidth in the frequency range 6.63 - 10.93 GHz is based on increasing the edge areas that positively affect the antenna's efficiency. This design makes the designed antenna cost less by reducing …

A Near-Optimal Change-Detection Based Algorithm For Piecewise-Stationary Combinatorial Semi-Bandits, Huozhi Zhou, Lingda Wang, Lav N. Varshney, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

We investigate the piecewise-stationary combinatorial semi-bandit problem. Compared to the original combinatorial semi-bandit problem, our setting assumes the reward distributions of base arms may change in a piecewise-stationary manner at unknown time steps. We propose an algorithm, GLR-CUCB, which incorporates an efficient combinatorial semi-bandit algorithm, CUCB, with an almost parameter-free change-point detector, the Generalized Likelihood Ratio Test (GLRT). Our analysis shows that the regret of GLR-CUCB is upper bounded by O(√NKT logT), where N is the number of piecewise-stationary segments, K is the number of base arms, and T is the number of time steps. As a complement, we also …

Nerve Response To Superelastic Shape Memory Polyurethane Aerogels, Martina Rodriguez Sala, Omar Skalli, Nicholas Leventis, Firouzeh Sabri

Chemistry Faculty Research & Creative Works

We have previously shown the suitability of aerogels as scaffolds for neuronal cells. Here, we report on the use of super elastic shape memory polyurethane aerogels (SSMPA). SSMPA have a distinctly different stiffness than previously reported aerogels. The soft and deformable nature of SSMPA allowed for radial compression of the aerogel induced by a custom designed apparatus. This radial compression changed the pore diameter and surface roughness (Sa) of SSMPA, while maintaining similar stiffness. Two varieties of SSMPA were used, Mix-14 and Mix-18, with distinctly different pore diameters and Sa. Radial compression led to a decreased pore diameter, which, in …

Impact Of Disadvantaged Business Enterprises Participation And Mobilization Cost On Highway Project Performance, Shristy Maharjan

UNLV Theses, Dissertations, Professional Papers, and Capstones

Construction practitioners have their goals to complete projects within time without exceeding the allocated budget. However, studies have shown many projects overrun their allocated budget and face delays due to numerous reasons. Some of the main reasons are lack of efficient construction and financial resource management, lack of proper planning, and unavailability of new construction technologies, as well as ineffective supervision and communication, design changes, and unskilled workers. In some studies, mobilization costs, along with the participation of Disadvantaged Business Enterprises (DBEs) in projects were identified as factors affecting the cost and schedule performance of construction projects. However, no statistical …

Fighter Aircraft Guidance And Control, Kaushik Raj

UNLV Theses, Dissertations, Professional Papers, and Capstones

Aircraft technology has undergone momentous improvements over the decades due to the growing demand and competition among industries. The performance requirement and stability of fighter aircraft is a major factor due to the ever-increasing flight envelope. Advanced fighter aircraft are expected to be highly maneuverable. To achieve extreme maneuverability a very good aircraft design with multiple redundant control actuators having static instabilities in certain modes, near accurate nonlinear aircraft mathematical model, and suitable nonlinear control design technique is required. Conventionally, training aircrafts such as Cessna and Piper aircraft are built for static and dynamic stability, making them easy to trim …

Bayesian Variable Selection Methods For Genome-Wide Association Studies With Categorical Phenotypes, Benazir Rowe

UNLV Theses, Dissertations, Professional Papers, and Capstones

Genome-wide association studies (GWAS) attempt to find the associations between genetic markers and studied traits (phenotypes). The problem of GWAS is complex and various methods have been developed to approach it. One of such methods is Bayesian variable selection (BVS). We describe the BVS methods in detail and demonstrate the ability of BVS method Posterior Inference via Model Averaging and Subset Selection (piMASS) to improve the power of detecting phenotype-associated genetic loci, potentially leading to new discoveries from existing data without increasing the sample size.

We present several ways to improve and extend the applicability of piMASS for GWAS. The …

Unsupervised Structural Graph Node Representation Learning, Mikel Joaristi

Boise State University Theses and Dissertations

Unsupervised Graph Representation Learning methods learn a numerical representation of the nodes in a graph. The generated representations encode meaningful information about the nodes' properties, making them a powerful tool for tasks in many areas of study, such as social sciences, biology or communication networks. These methods are particularly interesting because they facilitate the direct use of standard Machine Learning models on graphs. Graph representation learning methods can be divided into two main categories depending on the information they encode, methods preserving the nodes connectivity information, and methods preserving nodes' structural information. Connectivity-based methods focus on encoding relationships between nodes, …

Constitutive Modeling Of Force-Controlled Fatigue Testing In Human Meniscus Tissue, Bradley Scott Henderson

Boise State University Theses and Dissertations

The meniscus is a wedge-shaped fibrocartilaginous tissue located between the femur and tibia that helps stabilize the knee and protect the underlying cartilage. There are 2.5 million reported knee injuries each year, making it the most injured joint in the human body. Nearly twenty percent of these injuries are due to a torn meniscus, leading to over half a million meniscus surgeries performed in the United States annually. Therefore, it is critical to understand the failure modes of meniscus tissue to prevent these debilitating injuries. A failure mode that accounts for one-third of all meniscus injuries is repeated exposure to …

A Resilience Metric For Modern Power Distribution Systems, Tyler Bennett Phillips

Boise State University Theses and Dissertations

Modern society has become increasingly reliant on the functioning of critical infrastructure. It is considered so vital that its incapacitation or destruction would have debilitating effects on the global economy, national security, and public health and safety. The electrical power system is uniquely positioned, as it is essential for all other sectors of critical infrastructure to operate as intended. However, it is constantly at risk due to factors such as natural disasters, climate change, aging infrastructure, and cyber threats. Thus, ensuring the efficient and continuous supply of electricity is of utmost importance and the topic of this dissertation.

The work …