Automatic Food Intake Assessment Using Camera Phones

Obesity is becoming an epidemic phenomenon in most developed countries. The fundamental cause of obesity and overweight is an energy imbalance between calories consumed and calories expended. It is essential to monitor everyday food intake for obesity prevention and management. Existing dietary assessment methods usually require manually recording and recall of food types and portions. Accuracy of the results largely relies on many uncertain factors such as user's memory, food knowledge, and portion estimations. As a result, the accuracy is often compromised. Accurate and convenient dietary assessment methods are still blank and needed in both population and research societies. In this thesis, an automatic food intake assessment method using cameras, inertial measurement units (IMUs) on smart phones was developed to help people foster a healthy life style. With this method, users use their smart phones before and after a meal to capture images or videos around the meal. The smart phone will recognize food items and calculate the volume of the food consumed and provide the results to users. The technical objective is to explore the feasibility of image based food recognition and image based volume estimation. This thesis comprises five publications that address four specific goals of this work: (1) to develop a prototype system with existing methods to review the literature methods, find their drawbacks and explore the feasibility to develop novel methods; (2) based on the prototype system, to investigate new food classification methods to improve the recognition accuracy to a field application level; (3) to design indexing methods for large-scale image database to facilitate the development of new food image recognition and retrieval algorithms; (4) to develop novel convenient and accurate food volume estimation methods using only smart phones with cameras and IMUs. A prototype system was implemented to review existing methods. Image feature detector and descriptor were developed and a nearest neighbor classifier were implemented to classify food items. A reedit card marker method was introduced for metric scale 3D reconstruction and volume calculation. To increase recognition accuracy, novel multi-view food recognition algorithms were developed to recognize regular shape food items. To further increase the accuracy and make the algorithm applicable to arbitrary food items, new food features, new classifiers were designed. The efficiency of the algorithm was increased by means of developing novel image indexing method in large-scale image database. Finally, the volume calculation was enhanced through reducing the marker and introducing IMUs. Sensor fusion technique to combine measurements from cameras and IMUs were explored to infer the metric scale of the 3D model as well as reduce noises from these sensors.

Study of accelerometer assisted single key positioning user input systems

New designs of user input systems have resulted from the developing technologies and specialized user demands. Conventional keyboard and mouse input devices still dominate the input speed, but other input mechanisms are demanded in special application scenarios. Touch screen and stylus input methods have been widely adopted by PDAs and smartphones. Reduced keypads are necessary for mobile phones. A new design trend is exploring the design space in applications requiring single-handed input, even with eyes-free on small mobile devices. This requires as few keys on the input device to make it feasible to operate. But representing many characters with fewer keys can make the input ambiguous. Accelerometers embedded in mobile devices provide opportunities to combine device movements with keys for input signal disambiguation. Recent research has explored its design space for text input. In this dissertation an accelerometer assisted single key positioning input system is developed. It utilizes input device tilt directions as input signals and maps their sequences to output characters and functions. A generic positioning model is developed as guidelines for designing positioning input systems. A calculator prototype and a text input prototype on the 4+1 (5 positions) positioning input system and the 8+1 (9 positions) positioning input system are implemented using accelerometer readings on a smartphone. Users use one physical key to operate and feedbacks are audible. Controlled experiments are conducted to evaluate the feasibility, learnability, and design space of the accelerometer assisted single key positioning input system. This research can provide inspiration and innovational references for researchers and practitioners in the positioning user input designs, applications of accelerometer readings, and new development of standard machine readable sign languages.

Identifying indicators of sustainable development using the global sustainability quadrant approach

Advances in information technology and global data availability have opened the door for assessments of sustainable development at a truly macro scale. It is now fairly easy to conduct a study of sustainability using the entire planet as the unit of analysis; this is precisely what this work set out to accomplish. The study began by examining some of the best known composite indicator frameworks developed to measure sustainability at the country level today. Most of these were found to value human development factors and a clean local environment, but to gravely overlook consumption of (remote) resources in relation to nature’s capacity to renew them, a basic requirement for a sustainable state. Thus, a new measuring standard is proposed, based on the Global Sustainability Quadrant approach. In a two‐dimensional plot of nations’ Human Development Index (HDI) vs. their Ecological Footprint (EF) per capita, the Sustainability Quadrant is defined by the area where both dimensions satisfy the minimum conditions of sustainable development: an HDI score above 0.8 (considered ‘high’ human development), and an EF below the fair Earth‐share of 2.063 global hectares per person. After developing methods to identify those countries that are closest to the Quadrant in the present‐day and, most importantly, those that are moving towards it over time, the study tackled the question: what indicators of performance set these countries apart? To answer this, an analysis of raw data, covering a wide array of environmental, social, economic, and governance performance metrics, was undertaken. The analysis used country rank lists for each individual metric and compared them, using the Pearson Product Moment Correlation function, to the rank lists generated by the proximity/movement relative to the Quadrant measuring methods. The analysis yielded a list of metrics which are, with a high degree of statistical significance, associated with proximity to – and movement towards – the Quadrant; most notably: Favorable for sustainable development: use of contraception, high life expectancy, high literacy rate, and urbanization. Unfavorable for sustainable development: high GDP per capita, high language diversity, high energy consumption, and high meat consumption. A momentary gain, but a burden in the long‐run: high carbon footprint and debt. These results could serve as a solid stepping stone for the development of more reliable composite index frameworks for assessing countries’ sustainability.

Development of system separation strategy using synchrophasor data

In the current market system, power systems are operated at higher loads for economic reasons. Power system stability becomes a genuine concern in such operating conditions. In case of failure of any larger component, the system may become stressed. These events may start cascading failures, which may lead to blackouts. One of the main reasons of the major recorded blackout events has been the unavailability of system-wide information. Synchrophasor technology has the capability to provide system-wide real time information. Phasor Measurement Units (PMUs) are the basic building block of this technology, which provide the Global Positioning System (GPS) time-stamped voltage and current phasor values along with the frequency. It is being assumed that synchrophasor data of all the buses is available and thus the whole system is fully observable. This information can be used to initiate islanding or system separation to avoid blackouts. A system separation strategy using synchrophasor data has been developed to answer the three main aspects of system separation: (1) When to separate: One class support machines (OC-SVM) is primarily used for the anomaly detection. Here OC-SVM was used to detect wide area instability. OC-SVM has been tested on different stable and unstable cases and it is found that OC-SVM has the capability to detect the wide area instability and thus is capable to answer the question of “when the system should be separated”. (2) Where to separate: The agglomerative clustering technique was used to find the groups of coherent buses. The lines connecting different groups of coherent buses form the separation surface. The rate of change of the bus voltage phase angles has been used as the input to this technique. This technique has the potential to exactly identify the lines to be tripped for the system separation. (3) What to do after separation: Load shedding was performed approximately equal to the sum of power flows along the candidate system separation lines should be initiated before tripping these lines. Therefore it is recommended that load shedding should be initiated before tripping the lines for system separation.

Development of room temperature operating single electron transistor using FIB etching and deposition technology

The single-electron transistor (SET) is one of the best candidates for future nano electronic circuits because of its ultralow power consumption, small size and unique functionality. SET devices operate on the principle of Coulomb blockade, which is more prominent at dimensions of a few nano meters. Typically, the SET device consists of two capacitively coupled ultra-small tunnel junctions with a nano island between them. In order to observe the Coulomb blockade effects in a SET device the charging energy of the device has to be greater that the thermal energy. This condition limits the operation of most of the existing SET devices to cryogenic temperatures. Room temperature operation of SET devices requires sub-10nm nano-islands due to the inverse dependence of charging energy on the radius of the conducting nano-island. Fabrication of sub-10nm structures using lithography processes is still a technological challenge. In the present investigation, Focused Ion Beam based etch and deposition technology is used to fabricate single electron transistors devices operating at room temperature. The SET device incorporates an array of tungsten nano-islands with an average diameter of 8nm. The fabricated devices are characterized at room temperature and clear Coulomb blockade and Coulomb oscillations are observed. An improvement in the resolution limitation of the FIB etching process is demonstrated by optimizing the thickness of the active layer. SET devices with structural and topological variation are developed to explore their impact on the behavior of the device. The threshold voltage of the device was minimized to ~500mV by minimizing the source-drain gap of the device to 17nm. Vertical source and drain terminals are fabricated to realize single-dot based SET device. A unique process flow is developed to fabricate Si dot based SET devices for better gate controllability in the device characteristic. The device vi parameters of the fabricated devices are extracted by using a conductance model. Finally, characteristic of these devices are validated with the simulated data from theoretical modeling.

EXTRACTION OF PICTORIAL ENERGY INFORMATION FROM CAMPUS UNMETERED BUILDINGS USING IMAGE PROCESSING TECHNIQUES

In recent years, advanced metering infrastructure (AMI) has been the main research focus due to the traditional power grid has been restricted to meet development requirements. There has been an ongoing effort to increase the number of AMI devices that provide real-time data readings to improve system observability. Deployed AMI across distribution secondary networks provides load and consumption information for individual households which can improve grid management. Significant upgrade costs associated with retrofitting existing meters with network-capable sensing can be made more economical by using image processing methods to extract usage information from images of the existing meters. This thesis presents a new solution that uses online data exchange of power consumption information to a cloud server without modifying the existing electromechanical analog meters. In this framework, application of a systematic approach to extract energy data from images replaces the manual reading process. One case study illustrates the digital imaging approach is compared to the averages determined by visual readings over a one-month period.

Development of a 1-D Catalyzed Diesel Particulate Filter Model for Simulation of the Performance and the Oxidation of Particulate Matter and Nitrogen Oxides Using Passive Oxidation and Active Regeneration Engine Experimental Data

Back-pressure on a diesel engine equipped with an aftertreatment system is a function of the pressure drop across the individual components of the aftertreatment system, typically, a diesel oxidation catalyst (DOC), catalyzed particulate filter (CPF) and selective catalytic reduction (SCR) catalyst. Pressure drop across the CPF is a function of the mass flow rate and the temperature of the exhaust flowing through it as well as the mass of particulate matter (PM) retained in the substrate wall and the cake layer that forms on the substrate wall. Therefore, in order to control the back-pressure on the engine at low levels and to minimize the fuel consumption, it is important to control the PM mass retained in the CPF. Chemical reactions involving the oxidation of PM under passive oxidation and active regeneration conditions can be utilized with computer numerical models in the engine control unit (ECU) to control the pressure drop across the CPF. Hence, understanding and predicting the filtration and oxidation of PM in the CPF and the effect of these processes on the pressure drop across the CPF are necessary for developing control strategies for the aftertreatment system to reduce back-pressure on the engine and in turn fuel consumption particularly from active regeneration. Numerical modeling of CPF's has been proven to reduce development time and the cost of aftertreatment systems used in production as well as to facilitate understanding of the internal processes occurring during different operating conditions that the particulate filter is subjected to. A numerical model of the CPF was developed in this research work which was calibrated to data from passive oxidation and active regeneration experiments in order to determine the kinetic parameters for oxidation of PM and nitrogen oxides along with the model filtration parameters. The research results include the comparison between the model and the experimental data for pressure drop, PM mass retained, filtration efficiencies, CPF outlet gas temperatures and species (NO2) concentrations out of the CPF. Comparisons of PM oxidation reaction rates obtained from the model calibration to the data from the experiments for ULSD, 10 and 20% biodiesel-blended fuels are presented.