Demand of automobiles are significantly growing despite various factors, steadily increasing the average number of vehicles on the road. Increase in the number of vehicles, subsequently increases the risk of collisions, characterized by the driving behavior. Driving behavior is influenced by factors like class of vehicle, road condition and vehicle maneuvering by the driver. Rapidly growing mobile technology and use of smartphones embedded with in-built sensors, provides scope of constant development of assistance systems considering the safety of the driver by integrating with the information obtained from the vehicle on-board sensors. Our research aims at learning a vehicle system comprising of vehicle, human and road by employing driving patterns obtained from the sensor data to develop better systems of safety and alerts altogether. The thesis focusses on utilizing together various data recorded by the in-built embedded sensors in a smartphone to understand the vehicle motion and dynamics, followed by studying various impacts of collision events, types and signatures which can potentially be integrated in a prototype framework to detect variations, alert drivers and emergency responders in an event of collision.

How do the content and writing style of people who drink alcohol beverages stand out from non-drinkers? How much information can we learn about a person's alcohol consumption behavior by reading text that they have authored? This thesis attempts to extend the methods deployed in authorship attribution and authorship profiling research into the domain of automatically identifying the human action of drinking alcohol beverages. I examine how a psycholinguistics dictionary (the Linguistics Inquiry and Word Count lexicon, developed by James Pennebaker), together with Kenneth Burke's concept of words as symbols of human action, and James Wertsch's concept of mediated action provide a framework for analyzing meaningful data patterns from the content of blogs written by consumers of alcohol beverages. The contributions of this thesis to the research field are twofold. First, I show that it is possible to automatically identify blog posts that have content related to the consumption of alcohol beverages. And second, I provide a framework and tools to model human behavior through text analysis of blog data.

Hand and arm gestures are a great way of communication when you don't want to be heard, quieter and often more reliable than whispering into a radio mike. In recent years hand gesture identification became a major active area of research due its use in various applications. The objective of my work is to develop an integrated sensor system, which will enable tactical squads and SWAT teams to communicate when there is absence of a Line of Sight or in the presence of any obstacles. The gesture set involved in this work is the standardized hand signals for close range engagement operations used by military and SWAT teams. The gesture sets involved in this work are broadly divided into finger movements and arm movements. The core components of the integrated sensor system are: Surface EMG sensors, Flex sensors and accelerometers. Surface EMG is the electrical activity produced by muscle contractions and measured by sensors directly attached to the skin. Bend Sensors use a piezo resistive material to detect the bend. The sensor output is determined by both the angle between the ends of the sensor as well as the flex radius. Accelerometers sense the dynamic acceleration and inclination in 3 …

Colonoscopy is an endoscopic technique that allows a physician to inspect the mucosa of the human colon. Previous methods and software solutions to detect informative frames in a colonoscopy video (a process called informative frame filtering or IFF) have been hugely ineffective in (1) covering the proper definition of an informative frame in the broadest sense and (2) striking an optimal balance between accuracy and speed of classification in both real-time and non real-time medical procedures. In my thesis, I propose a more effective method and faster software solutions for IFF which is more effective due to the introduction of a heuristic algorithm (derived from experimental analysis of typical colon features) for classification. It contributed to a 5-10% boost in various performance metrics for IFF. The software modules are faster due to the incorporation of sophisticated parallel-processing oriented coding techniques on modern microprocessors. Two IFF modules were created, one for post-procedure and the other for real-time. Code optimizations through NVIDIA CUDA for GPU processing and/or CPU multi-threading concepts embedded in two significant microprocessor design philosophies (multi-core design and many-core design) resulted a 5-fold acceleration for the post-procedure module and a 40-fold acceleration for the real-time module. Some innovative software modules, …

Researchers have speculated that global software teams have activity patterns that are dictated by work-place schedules or a client's need. Similar patterns have been suggested for individuals enrolled in distant learning projects that require students to post feedback in response to questions or assignments. Researchers tend to accept the notion that students' temporal patterns adjust to academic or social calendars and are a result of choices made within these constraints. Although there is some evidence that culture do have an impact on communication activity behavior, there is not a clear how each of these factors may relate to work done in online groups. This particular study represents a new approach to studying student-group communication activities and also pursues an alternative approach by using activity data from students participating in a global software development project to generate a variety of complex measures that capture patterns about when students work. Students work habits are also often determined by where they live and what they are working on. Moreover, students tend to work on group projects in cycles, which correspond to a start, middle, and end time period. Knowledge obtained from this study should provide insight into current empirical research on global software …

Smart phones today have become increasingly popular with the general public for its diverse abilities like navigation, social networking, and multimedia facilities to name a few. These phones are equipped with high end processors, high resolution cameras, built-in sensors like accelerometer, orientation-sensor, light-sensor, and much more. According to comScore survey, 25.3% of US adults use smart phones in their daily lives. Motivated by the capability of smart phones and their extensive usage, I focused on utilizing them for bio-medical applications. In this thesis, I present a new application for a smart phone to quantify the vital signs such as heart rate, respiratory rate and blood pressure with the help of its built-in sensors. Using the camera and a microphone, I have shown how the blood pressure and heart rate can be determined for a subject. People sometimes encounter minor situations like fainting or fatal accidents like car crash at unexpected times and places. It would be useful to have a device which can measure all vital signs in such an event. The second part of this thesis demonstrates a new mode of communication for next generation 9-1-1 calls. In this new architecture, the call-taker will be able to control the …

Wireless sensor networks are composed of sensor nodes, which can monitor an environment and observe events of interest. These networks are applied in various fields including but not limited to environmental, industrial and habitat monitoring. In many applications, the exact location of the sensor nodes is unknown after deployment. Localization is a process used to find sensor node's positional coordinates, which is vital information. The localization is generally assisted by anchor nodes that are also sensor nodes but with known locations. Anchor nodes generally are expensive and need to be optimally placed for effective localization. Passive localization is one of the localization techniques where the sensor nodes silently listen to the global events like thunder sounds, seismic waves, lighting, etc. According to previous studies, the ideal location to place anchor nodes was on the perimeter of the sensor network. This may not be the case in passive localization, since the function of anchor nodes here is different than the anchor nodes used in other localization systems. I do extensive studies on positioning anchor nodes for effective localization. Several simulations are run in dense and sparse networks for proper positioning of anchor nodes. I show that, for effective passive localization, the …

Mobile phone advancements and ubiquitous internet connectivity are resulting in ever expanding possibilities in the application of smart phones. Users of mobile phones are now capable of hosting server applications from their personal devices. Whether providing services individually or in an ad hoc network setting the devices are currently not configured for defending against distributed denial of service (DDoS) attacks. These attacks, often launched from a botnet, have existed in the space of personal computing for decades but recently have begun showing up on mobile devices. Research is done first into the required steps to develop a potential botnet on the Android platform. This includes testing for the amount of malicious traffic an Android phone would be capable of generating for a DDoS attack. On the other end of the spectrum is the need of mobile devices running networked applications to develop security against DDoS attacks. For this mobile, phones are setup, with web servers running Apache to simulate users running internet connected applications for either local ad hoc networks or serving to the internet. Testing is done for the viability of using commonly available modules developed for Apache and intended for servers as well as finding baseline capabilities of …

Service-oriented architecture enables web services to operate in a loosely-coupled setting and provides an environment for dynamic discovery and use of services over a network using standards such as WSDL, SOAP, and UDDI. Web service has both functional and non-functional characteristics. This thesis work proposes to add QoS descriptions (non-functional properties) to WSDL and compose various services to form a business process. This composition of web services also considers QoS properties along with functional properties and the composed services can again be published as a new Web Service and can be part of any other composition using Composed WSDL.

Computer security attacks take place due to the presence of vulnerabilities and bugs in software applications. Bugs and vulnerabilities are the result of weak software architecture and lack of standard software development practices. Despite the fact that software companies are investing millions of dollars in the research and development of software designs security risks are still at large. In some cases software applications are found to carry vulnerabilities for many years before being identified. A recent such example is the popular Heart Bleed Bug in the Open SSL/TSL. In today’s world, where new software application are continuously being developed for a varied community of users; it’s highly unlikely to have software applications running without flaws. Attackers on computer system securities exploit these vulnerabilities and bugs and cause threat to privacy without leaving any trace. The most critical vulnerabilities are those which are related to the integrity of the software applications. Because integrity is directly linked to the credibility of software application and data it contains. Here I am giving solution of maintaining web applications integrity running on RADIUM by using daikon. Daikon generates invariants, these invariants are used to maintain the integrity of the web application and also check the …

Electrical energy is used at approximately the rate of 15 Terawatts world-wide. Generating this much energy has become a primary concern for all nations. There are many ways of generating energy among which the most commonly used are non-renewable and will extinct much sooner than expected. Very active research is going on both to increase the use of renewable energy sources and to use the available energy with more efficiency. Among these sources, solar energy is being considered as the most abundant and has received high attention. The mobile phone has become one of the basic needs of modern life, with almost every human being having one.Individually a mobile phone consumes little power but collectively this becomes very large. This consideration motivated the research undertaken in this masters thesis. The objective of this thesis is to design a model for solar power based charging circuits for mobile phone using Simulink(R). This thesis explains a design procedure of solar power based mobile charger circuit using Simulink(R) which includes the models for the photo-voltaic array, maximum power point tracker, pulse width modulator, DC-DC converter and a battery. The first part of the thesis concentrates on electron level behavior of a solar cell, …

Students often use the web as a source of help for problems that they encounter on programming assignments.In this work, we seek to understand how students use the web to search for help on their assignments.We used a mixed methods approach with 344 students who complete a survey and 41 students who participate in a focus group meetings and helped in recording data about their search habits.The survey reveals data about student reported search habits while the focus group uses a web browser plug-in to record actual search patterns.We examine the results collectively and as broken down by class year.Survey results show that at least 2/3 of the students from each class year rely on search engines to locate resources for help with their programming bugs in at least half of their assignments;search habits vary by class year;and the value of different types of resources such as tutorials and forums varies by class year.Focus group results exposes the high frequency web sites used by the students in solving their programming assignments.

The design of VLSI electronic circuits can be achieved at many different abstraction levels starting from system behavior to the most detailed, physical layout level. As the number of transistors in VLSI circuits is increasing, the complexity of the design is also increasing, and it is now beyond human ability to manage. Hence CAD (Computer Aided design) or EDA (Electronic Design Automation) tools are involved in the design. EDA or CAD tools automate the design, verification and testing of these VLSI circuits. In today’s market, there are many EDA tools available. However, they are very expensive and require high-performance platforms. One of the key challenges today is to select appropriate CAD or EDA tools which are open-source for academic purposes. This thesis provides a detailed examination of an open-source EDA tool called Electric VLSI Design system. An excellent and efficient CAD tool useful for students and teachers to implement ideas by modifying the source code, Electric fulfills these requirements. This thesis' primary objective is to explain the Electric software features and architecture and to provide various digital and analog designs that are implemented by this software for educational purposes. Since the choice of an EDA tool is based on the …

The objective of this thesis is to design a model for a multi global navigation satellite system using Simulink. It explains a design procedure which includes the models for transmitter and receiver for two different navigation systems. To overcome the problem, where less number of satellites are visible to determine location degrades the performance of any positioning system significantly, this research has done to make use of multi GNSS satellite signals in one navigation receiver.

Extracting information from a stack of data is a tedious task and the scenario is no different in proteomics. Volumes of research papers are published about study of various proteins in several species, their interactions with other proteins and identification of protein(s) as possible biomarker in causing diseases. It is a challenging task for biologists to keep track of these developments manually by reading through the literatures. Several tools have been developed by computer linguists to assist identification, extraction and hypotheses generation of proteins and protein-protein interactions from biomedical publications and protein databases. However, they are confronted with the challenges of term variation, term ambiguity, access only to abstracts and inconsistencies in time-consuming manual curation of protein and protein-protein interaction repositories. This work attempts to attenuate the challenges by extracting protein-protein interactions in humans and elicit possible interactions using associative rule mining on full text, abstracts and captions from figures available from publicly available biomedical literature databases. Two such databases are used in our study: Directory of Open Access Journals (DOAJ) and PubMed Central (PMC). A corpus is built using articles based on search terms. A dataset of more than 38,000 protein-protein interactions from the Human Protein Reference Database (HPRD) …

In modern society, computers are primarily interacted with via keyboards, touch screens, voice recognition, video analysis, and many others. For certain applications, these methods may be the most efficient interface. However, there are applications that we can conceive where a more natural interface could be convenient and connect humans and computers in a more intuitive and natural way. These applications are gesture recognition systems and range from the interpretation of sign language by a computer to virtual reality control. This Thesis proposes a gesture recognition system that primarily uses accelerometers to capture gestures from a tactical communications application. A segmentation algorithm is developed based on the accelerometer energy to segment these gestures from an input sequence. Using signal processing and machine learning techniques, the segments are reduced to mathematical features and classified with support vector machines. Experimental results show that the system achieves an overall gesture recognition accuracy of 98.9%. Additional methods, such as non-gesture recognition/suppression, are also proposed and tested.

Optical character recognition (OCR) software has advanced greatly in recent years. Machine-printed text can be scanned and converted to searchable text with word accuracy rates around 98%. Reasonably neat hand-printed text can be recognized with about 85% word accuracy. However, cursive handwriting still remains a challenge, with state-of-the-art performance still around 75%. Algorithms based on hidden Markov models have been only moderately successful, while recurrent neural networks have delivered the best results to date. This thesis explored the feasibility of using a special type of feedforward neural network to convert freeform cursive handwriting to searchable text. The hidden nodes in this network were grouped into clusters, with each cluster being trained to recognize a unique character bigram. The network was trained on writing samples that were pre-segmented and annotated. Post-processing was facilitated in part by using the network to identify overlapping bigrams that were then linked together to form words and sentences. With dictionary assisted post-processing, the network achieved word accuracy of 66.5% on a small, proprietary corpus. The contributions in this thesis are threefold: 1) the novel clustered architecture of the feed-forward neural network, 2) the development of an expanded set of observers combining image masks, modifiers, and feature …

Shadows in indoor scenarios are usually characterized with multiple light sources that produce complex shadow patterns of a single object. Without removing shadow, the foreground object tends to be erroneously segmented. The inconsistent hue and intensity of shadows make automatic removal a challenging task. In this thesis, a dynamic thresholding and transfer learning-based method for removing shadows is proposed. The method suppresses light shadows with a dynamically computed threshold and removes dark shadows using an online learning strategy that is built upon a base classifier trained with manually annotated examples and refined with the automatically identified examples in the new videos. Experimental results demonstrate that despite variation of lighting conditions in videos our proposed method is able to adapt to the videos and remove shadows effectively. The sensitivity of shadow detection changes slightly with different confidence levels used in example selection for classifier retraining and high confidence level usually yields better performance with less retraining iterations.

In recent years, the collection of genomic data has skyrocketed and databases of genomic data are growing at a faster rate than ever before. Although many computational methods have been developed to interpret these data, they tend to struggle to process the ever increasing file sizes that are being produced and fail to take advantage of the advances in multi-core processors by using parallel processing. In some instances, loss of accuracy has been a necessary trade off to allow faster computation of the data. This thesis discusses one such algorithm that has been developed and how changes were made to allow larger input file sizes and reduce the time required to achieve a result without sacrificing accuracy. An information entropy based algorithm was used as a basis to demonstrate these techniques. The algorithm dissects the distinctive patterns underlying genomic data efficiently requiring no a priori knowledge, and thus is applicable in a variety of biological research applications. This research describes how parallel processing and object-oriented programming techniques were used to process larger files in less time and achieve a more accurate result from the algorithm. Through object oriented techniques, the maximum allowable input file size was significantly increased from 200 …

Trusted Computing capability has become ubiquitous these days, and it is being widely deployed into consumer devices as well as enterprise platforms. As the number of threats is increasing at an exponential rate, it is becoming a daunting task to secure the systems against them. In this context, the software integrity measurement at runtime with the support of trusted platforms can be a better security strategy. Trusted Computing devices like TPM secure the evidence of a breach or an attack. These devices remain tamper proof if the hardware platform is physically secured. This type of trusted security is crucial for forensic analysis in the aftermath of a breach. The advantages of trusted platforms can be further leveraged if they can be used wisely. RADIUM (Race-free on-demand Integrity Measurement Architecture) is one such architecture, which is built on the strength of TPM. RADIUM provides an asynchronous root of trust to overcome the TOC condition of DRTM. Even though the underlying architecture is trusted, attacks can still compromise applications during runtime by exploiting their vulnerabilities. I propose an application-level integrity measurement solution that fits into RADIUM, to expand the trusted computing capability to the application layer. This is based on the concept …

The basis of today’s security systems is the trust and confidence that the system will behave as expected and are in a known good trusted state. The trust is built from hardware and software elements that generates a chain of trust that originates from a trusted known entity. Leveraging hardware, software and a mandatory access control policy technology is needed to create a trusted measurement environment. Employing a control layer (hypervisor or microkernel) with the ability to enforce a fine grained access control policy with hyper call granularity across multiple guest virtual domains can ensure that any malicious environment to be contained. In my research, I propose the use of radium's Asynchronous Root of Trust Measurement (ARTM) capability incorporated with a secure mandatory access control policy engine that would mitigate the limitations of the current hardware TPM solutions. By employing ARTM we can leverage asynchronous use of boot, launch, and use with the hypervisor proving its state and the integrity of the secure policy. My solution is using Radium (Race free on demand integrity architecture) architecture that will allow a more detailed measurement of applications at run time with greater semantic knowledge of the measured environments. Radium incorporation of a …

Email connects 85% of the world. This paper explores the pattern of information overload encountered by majority of email users and examine what steps key email providers are taking to combat the problem. Besides fighting spam, popular email providers offer very limited tools to reduce the amount of unwanted incoming email. Rather, there has been a trend to expand storage space and aid the organization of email. Storing email is very costly and harmful to the environment. Additionally, information overload can be detrimental to productivity. We propose a simple solution that results in drastic reduction of unwanted mail, also known as graymail.

One of the challenges fairly common in motivational interviewing is patient resistance to health behavior change. Hence, automated dialog systems aimed at counseling patients need to be capable of detecting resistance and appropriately altering dialog. This thesis focusses primarily on the development of such a system for automatic identification of patient resistance to behavioral change. This enables the dialogue system to direct the discourse towards a more agreeable ground and helping the patient overcome the obstacles in his or her way to change. This thesis also proposes a dialogue system framework for health behavior change via natural language analysis and generation. The proposed framework facilitates automated motivational interviewing from clinical psychology and involves three broad stages: rapport building and health topic identification, assessment of the patient’s opinion about making a change, and developing a plan. Using this framework patients can be encouraged to reflect on the options available and choose the best for a healthier life.

Free and fair elections are the basis for democracy, but conducting elections is not an easy task. Different groups of people are trying to influence the outcome of the election in their favor using the range of methods, from campaigning for a particular candidate to well-financed lobbying. Often the stakes are too high, and the methods are illegal. Two main properties of any voting scheme are the privacy of a voter’s choice and the integrity of the tally. Unfortunately, they are mutually exclusive. Integrity requires making elections transparent and auditable, but at the same time, we must preserve a voter’s privacy. It is always a trade-off between these two requirements. Current voting schemes favor privacy over auditability, and thus, they are vulnerable to voting fraud. I propose two novel voting systems that can achieve both privacy and verifiability. The first protocol is based on cryptographical primitives to ensure the integrity of the final tally and privacy of the voter. The second protocol is a simple paper-based voting scheme that achieves almost the same level of security without usage of cryptography.