Computer Sciences Commons^™

What Time Is It? Deep Learning Approaches For Circadian Rhythms, Forest Agostinelli, Nicholas Ceglia, Babak Shahbaba, Paolo Sassone-Corsi, Pierre Baldi

Faculty Publications

Motivation: Circadian rhythms date back to the origins of life, are found in virtually every species and every cell, and play fundamental roles in functions ranging from metabolism to cognition. Modern high-throughput technologies allow the measurement of concentrations of transcripts, metabolites and other species along the circadian cycle creating novel computational challenges and opportunities, including the problems of inferring whether a given species oscillate in circadian fashion or not, and inferring the time at which a set of measurements was taken.

Results: We first curate several large synthetic and biological time series datasets containing labels for both periodic and aperiodic …

A Distributed Control Algorithm For Small Swarms In Cordon And Patrol, C Kristopher Alder

Student Works

Distributed teams of air and ground robots have the potential to be very useful in a variety of application domains, and much work is being done to design distributed algorithms that produce useful behaviors. This thesis presents a set of distributed algorithms that operate under minimal human input for patrol and cordon tasks. The algorithms allow the team to surround and travel between objects of interest. Empirical analyses indicate that the surrounding behaviors are robust to variations on the shape of the object of interest, communication loss, and robot failures.

Color Image Encryption And Decryption Using Hill Cipher Associated With Arnold Transform, Rakesh Ranjan, R. K. Sharma, M. Hanmandlu

Applications and Applied Mathematics: An International Journal (AAM)

Image security over open network transmission is a big concern nowadays. This paper proposes another methodology for color image encoding and decoding using two stage Hill Cipher method which is connected with Arnold Transformation. The forgoing created a strategy for encryption and decryption of color image information and touched on just the premise of keys. In this plan, keys and the agreement of Hill Cipher (HC) are basic. Moreover, keys multiplication (pre or post) over an RGB image information framework is inevitable to know to effectively decrypt the first image information. We have given a machine simulation with a standard …

Experimental Building Demonstration Model With Viscous Fluid Dampers, Blake Thomas Reeve, Brianna Jean Kufa, Aden Malek Stepanians, Sophie Carmion Ratkovich

Architectural Engineering

The Architectural Engineering major places a heavy emphasis on structural dynamics and the role of wind and seismic loading in building analysis and design. Buildings of high importance that are critical to community function, such as hospitals, often utilize supplemental damping devices like supplemental viscous fluid dampers or base isolators to reduce the overall demands on the structural system. The design and analysis of these dampers are typically not taught at the undergraduate level, and is frequently performed by mechanical engineers, in lieu of structural engineers.

To better understand and research building behavior with supplemental damping devices, our multi-disciplinary team …

Construction Of Energy Preserving Qmf, Jian-Ao Lian, Yonghui Wang

Applications and Applied Mathematics: An International Journal (AAM)

Recently, a family of perfect reconstruction (PR) quadrature mirror filterbanks (QMF) with finite impulse response filters (FIR) from systems of biorthogonal refinable functions and wavelets were introduced and also applied to image processing. However, a detailed procedure was absent. The main objective of this paper is to present extensive examples that will provide a thorough process of construction of the new family of PR QMF with FIR filterbanks. These new filters are linearphase due to the symmetry property of their corresponding biorthogonal refinable functions and wavelets. In addition, these filters have odd lengths so that the symmetric extension can be …

Priority Queueing System With A Single Server Serving Two Queues M[X1],M[X2]/G1,G2/1 With Balking And Optional Server Vacation, G. Ayyappan, P. Thamizhselvi

Applications and Applied Mathematics: An International Journal (AAM)

In this paper we study a vacation queueing system with a single server simultaneously dealing with an M^{[x₁] _/}G₁/1 and an M^{[x₂] /}G₂/1 queues. Two classes of units, priority and non-priority, arrive at the system in two independent compound Poisson streams. Under a non-preemptive priority rule, the server provides a general service to the priority and non-priority units. We further assume that the server may take a vacation of random length just after serving the last customer in the priority unit present in the system. If the server …

Certain Operations On Bipolar Fuzzy Graph Structures, Muhammad Akram, Rabia Akmal

Applications and Applied Mathematics: An International Journal (AAM)

A graph structure is a useful tool in solving the combinatorial problems in different areas of computer science and computational intelligence systems. A bipolar fuzzy graph structure is a generalization of a bipolar fuzzy graph. In this paper, we present several different types of operations, including composition, Cartesian product, strong product, cross product, and lexicographic product on bipolar fuzzy graph structures. We also investigate some properties of operations.

Testing Multiple Hypotheses With Skewed Alternatives, Naveen K. Bansal, Gholamhossein G. Hamedani, Mehdi Maadooliat

Mathematics, Statistics and Computer Science Faculty Research and Publications

In many practical cases of multiple hypothesis problems, it can be expected that the alternatives are not symmetrically distributed. If it is known a priori that the distributions of the alternatives are skewed, we show that this information yields high power procedures as compared to the procedures based on symmetric alternatives when testing multiple hypotheses. We propose a Bayesian decision theoretic rule for multiple directional hypothesis testing, when the alternatives are distributed as skewed, under a constraint on a mixed directional false discovery rate. We compare the proposed rule with a frequentist's rule of Benjamini and Yekutieli (2005) using simulations. …

The Asynchronous T-Step Approximation For Scheduling Batch Flow Systems, David R. Grimsman

Theses and Dissertations

Heap models in the max-plus algebra are interesting dynamical systems that can be used to model a variety of tetris-like systems, such as batch flow shops for manufacturing models. Each heap in the model can be identified with a single product to manufacture. The objective is to manufacture a group of products in such an order so as to minimize the total manufacturing time. Because this scheduling problem reduces to a variation of the Traveling Salesman Problem (known to be NP-complete), the optimal solution is computationally infeasible for many real-world systems. Thus, a feasible approximation method is needed. This work …

Hci Testing In Laboratory Or Field Settings, Chuan-Hoo Tan, Austin Silva, Rich Lee, Kanliang Wang, Fiona Fui-Hoon Nah

Research Collection School Of Computing and Information Systems

This paper presents perspectives from both academia and practice on how an HCI testing is to be conducted and the deliberations that go into the testing. HCI testing can be conducted in closed-door laboratory or in a field setting. While there is an increased interest in field testing of an HCI artifact, there is always an enduring concern over how to administer a field testing given that the testers will have less control over the course of testing. In this paper, we cover HCI testing deliberation as well as the operational issues of field testing, and conclude the paper with …

Supervised Learning For Multi-Domain Text Classification, Siva Charan Reddy Gangireddy

Master's Projects

Digital information available on the Internet is increasing day by day. As a result of this, the demand for tools that help people in finding and analyzing all these resources are also growing in number. Text Classification, in particular, has been very useful in managing the information. Text Classification is the process of assigning natural language text to one or more categories based on the content. It has many important applications in the real world. For example, finding the sentiment of the reviews, posted by people on restaurants, movies and other such things are all applications of Text classification. In …

Privacy And Security In Mobile Health – A Research Agenda, David Kotz, Carl A. Gunter, Santosh Kumar, Jonathan P. Weiner

Dartmouth Scholarship

Mobile health technology has great potential to increase healthcare quality, expand access to services, reduce costs, and improve personal wellness and public health. However, mHealth also raises significant privacy and security challenges.

Link Prediction In A Weighted Network Using Support Vector Machine, Jan Miles Co, Proceso L. Fernandez Jr

Department of Information Systems & Computer Science Faculty Publications

Link prediction is a field under network analysis that deals with the existence or emergence of links. In this study, we investigate the effect of using weighted networks for two link prediction techniques, which are the Vector Auto Regression (VAR) technique and our proposed modified VAR that uses Support Vector Machine (SVM). Using a co-authorship network from DBLP as the dataset and the Area Under the Receiver Operating Curve (AUC-ROC) as the fitness metric, the results show that the performance of both VAR and SVM are surprisingly lower in the weighted network than in the unweighted network. In an attempt …

Mobipot: Understanding Mobile Telephony Threats With Honeycards, Marco Balduzzi, Payas Gupta, Lion Gu, Debin Gao, Mustaque Ahamad

Research Collection School Of Computing and Information Systems

Over the past decade, the number of mobile phones has increased dramatically, overtaking the world population in October 2014. In developing countries like India and China, mobile subscribers outnumber traditional landline users and account for over 90% of the active population. At the same time, convergence of telephony with the Internet with technologies like VoIP makes it possible to reach a large number of telephone users at a low or no cost via voice calls or SMS (short message service) messages. As a consequence, cybercriminals are abusing the telephony channel to launch attacks, e.g., scams that offer fraudulent services and …

Fusing Wifi And Video Sensing For Accurate Group Detection In Indoor Spaces, Kasthuri Jayarajah, Zaman Lantra, Archan Misra

Research Collection School Of Computing and Information Systems

Understanding one's group context in indoor spaces is useful for many reasons - e.g., at a shopping mall, knowing a customer's group context can help in offering context-specific incentives, or estimating taxi demand for customers exiting the mall. Group detection and monitoring using WiFi-based indoor location traces fails when users are invisible (either because they don't carry smartphones, or because their WiFi is turned OFF) or when location tracking is inaccurate. In this paper, we propose a multi-modal group detection system that fuses two independent modes: video and WiFi, for detecting groups with low latency and high accuracy. We present …

Finding The Shortest Path In Stochastic Vehicle Routing: A Cardinality Minimization Approach, Zhiguang Cao, Hongliang Guo, Jie Zhang, Dusit Niyato, Ulrich Fastenrath Fastenrath

Research Collection School Of Computing and Information Systems

This paper aims at solving the stochastic shortest path problem in vehicle routing, the objective of which is to determine an optimal path that maximizes the probability of arriving at the destination before a given deadline. To solve this problem, we propose a data-driven approach, which directly explores the big data generated in traffic. Specifically, we first reformulate the original shortest path problem as a cardinality minimization problem directly based on samples of travel time on each road link, which can be obtained from the GPS trajectory of vehicles. Then, we apply an l(1)-norm minimization technique and its variants to …

User Behavior Mining In Microblogging, Tuan Anh Hoang

Dissertations and Theses Collection (Open Access)

This dissertation addresses the modeling of factors concerning microblogging users' content and behavior. We focus on two sets of factors. The first set includes behavioral factors of users and content items driving content propagation in microblogging. The second set consists of latent topics and communities of users as the users are engaged in content generation and behavior adoptions. These two sets of factors are extremely important in many applications, e.g., network monitoring and recommender systems. In the first part of this dissertation, we identify user virality, user susceptibility, and content virality as three behavioral factors that affect users' behaviors in …

Learning Natural Language Inference With Lstm, Shuohang Wang, Jing Jiang

Research Collection School Of Computing and Information Systems

Natural language inference (NLI) is a fundamentally important task in natural language processing that has many applications. The recently released Stanford Natural Language Inference (SNLI) corpus has made it possible to develop and evaluate learning-centered methods such as deep neural networks for natural language inference (NLI). In this paper, we propose a special long short-term memory (LSTM) architecture for NLI. Our model builds on top of a recently proposed neural attention model for NLI but is based on a significantly different idea. Instead of deriving sentence embeddings for the premise and the hypothesis to be used for classification, our solution …

Application Of Computer Modeling And Simulation Techniques For Optimization Of Factory Floor Operations In Small To Medium- Sized Businesses, Brian P. Romano

Theses and Dissertations

The rationale and motive for this thesis was to prove that no matter the size of a company and its particular value stream, the application of applied computer science principles with a reliance on computer modeling and simulation onto the factory floor process improves efficiencies and throughput through the reduction of downtime and/or process waiting. This thesis research specifically emphasized small businesses of between $2 and $20 million and was purposely limited to factory floor production processes and utilized standardized applied computer science techniques including simulation and modeling, microprocessor based factory floor intelligence devices. The results of this applied technology …

Analysis Tools And Defense Mechanisms For Dos Hash Attacks, Pratick Henry Bakhtiani

Theses and Dissertations

This thesis focuses on creating tools for the gathering and management of data for analyzing Denial of Service attacks on the advertisement-based synchronization mechanism used in the DirectDemocracyP2P application. In this report we present two tools that were developed as part of this eort: AttackerClient and Decoding and Distribution. These tools are used to perform the attack and analyze the captured network packets of the attack data, storing them in a database. The Decoding and Distribution tool can distinguish between dierent types of messages. It can also assemble fragmented messages from UDP chunks. The created tools help to manage a …

Rapid Android Parser For Investigating Dex Files (Rapid), Xiaolu Zhang, Frank Breitinger, Ibrahim Baggili

Electrical & Computer Engineering and Computer Science Faculty Publications

Android malware is a well-known challenging problem and many researchers/vendors/practitioners have tried to address this issue through application analysis techniques. In order to analyze Android applications, tools decompress APK files and extract relevant data from the Dalvik EXecutable (DEX) files. To acquire the data, investigators either use decompiled intermediate code generated by existing tools, e.g., Baksmali or Dex2jar or write their own parsers/dissemblers. Thus, they either need additional time because of decompiling the application into an intermediate representation and then parsing text files, or they reinvent the wheel by implementing their own parsers. In this article, we present Rapid Android …

The Elder Scrolls V: Skyrim Stamina Combat Overhaul, Richard Rattner

Liberal Arts and Engineering Studies

No abstract provided.

Visual Code: Breaking The Binary, Jacob Johannesen, Andrew Adriance

Liberal Arts and Engineering Studies

This project seeks to create an accessible programming language that is more visually based. Although some solutions exist, namely MIT’s Scratch, nothing has caught up to the mobile age. This proj- ect aims to reframe creating a game or app into the context of tell- ing a story, putting character creation first. By researching sto- ry-telling and how people learn, and by applying technical and user interface design knowledge, this project intends to deliver a soft- ware solution that opens introductory coding education to more people.

Event Detection With Zero Example: Select The Right And Suppress The Wrong Concepts, Yi-Jie Lu, Hao Zhang, Maaike De Boer, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Complex video event detection without visual examples is a very challenging issue in multimedia retrieval. We present a state-of-the-art framework for event search without any need of exemplar videos and textual metadata in search corpus. To perform event search given only query words, the core of our framework is a large, pre-built bank of concept detectors which can understand the content of a video in the perspective of object, scene, action and activity concepts. Leveraging such knowledge can effectively narrow the semantic gap between textual query and the visual content of videos. Besides the large concept bank, this paper focuses …

Demo: Drumming Application Using Commodity Wearable Devices, Bharat Dwivedi, Archan Misra, Youngki Lee

Research Collection School Of Computing and Information Systems

We aim to develop a drumming application in which individual can play drums using multiple wearable and mobile devices. Our vision is to tap out different rythms in the air using smart watches as a virtual drum stick and smart phone would act as a drum kit. Same user interface can be visualized in smart glasses. Here, our prime target is to use multiple commodity wearable devices (non-commodity i.e. Myo arm band) and smart phones for recognizing new (or same type of here) types of multi limb gestural context and building an adaptive application interface and allow such gesture recognition …

Iccdetector: Icc-Based Malware Detection On Android, Xu Ke, Yingjiu Li, Robert H. Deng

Research Collection School Of Computing and Information Systems

Most existing mobile malware detection methods (e.g., Kirin and DroidMat) are designed based on the resources required by malwares (e.g., permissions, application programming interface (API) calls, and system calls). These methods capture the interactions between mobile apps and Android system, but ignore the communications among components within or cross application boundaries. As a consequence, the majority of the existing methods are less effective in identifying many typical malwares, which require a few or no suspicious resources, but leverage on inter-component communication (ICC) mechanism when launching stealthy attacks. To address this challenge, we propose a new malware detection method, named ICCDetector. …

Livelabs: Building In-Situ Mobile Sensing And Behavioural Experimentation Testbeds, Kasthuri Jayarajah, Rajesh Krishna Balan, Meera Radhakrishnan, Archan Misra, Youngki Lee

Research Collection School Of Computing and Information Systems

In this paper, we present LiveLabs, a first-of-its-kind testbed that isdeployed across a university campus, convention centre, and resortisland and collects real-time attributes such as location, group contextetc., from hundreds of opt-in participants. These venues, data,and participants are then made available for running rich humancentricbehavioural experiments that could test new mobile sensinginfrastructure, applications, analytics, or more social-sciencetype hypotheses that influence and then observe actual user behaviour.We share case studies of how researchers from aroundthe world have and are using LiveLabs, and our experiences andlessons learned from building, maintaining, and expanding LiveLabsover the last three years.

Deduplication On Encrypted Big Data In Cloud, Zheng Yan, Wenxiu Ding, Xixun Yu, Haiqi Zhu, Deng, Robert H.

Research Collection School Of Computing and Information Systems

Cloud computing offers a new way of service provision by re-arranging various resources over the Internet. The most important and popular cloud service is data storage. In order to preserve the privacy of data holders, data are often stored in cloud in an encrypted form. However, encrypted data introduce new challenges for cloud data deduplication, which becomes crucial for big data storage and processing in cloud. Traditional deduplication schemes cannot work on encrypted data. Existing solutions of encrypted data deduplication suffer from security weakness. They cannot flexibly support data access control and revocation. Therefore, few of them can be readily …

Smart Living For Elderly: Design And Human-Computer Interaction Considerations, Ranjana Sharma, Fiona Fui-Hoon Nah, Kavya Sharma, Teja S. Katta, Natalie Pang, Alvin Yong

Research Collection School Of Computing and Information Systems

To address aging challenges, we examine the concept of smart living and its applications for the elderly. Smart living refers to improving quality of life by transforming environments to become more intelligent and adaptable to users. In this paper, we discuss how smart living applications can help to address the needs of the elderly, as well as the design and human-computer interaction considerations for such applications.

Self-Organizing Neural Network For Adaptive Operator Selection In Evolutionary Search, Teck Hou Teng, Stephanus Daniel Handoko, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Evolutionary Algorithm is a well-known meta-heuristics paradigm capable of providing high-quality solutions to computationally hard problems. As with the other meta-heuristics, its performance is often attributed to appropriate design choices such as the choice of crossover operators and some other parameters. In this chapter, we propose a continuous state Markov Decision Process model to select crossover operators based on the states during evolutionary search. We propose to find the operator selection policy efficiently using a self-organizing neural network, which is trained offline using randomly selected training samples. The trained neural network is then verified on test instances not used for …