Investigation of Compound Micro Cantilever for Imaging and Identifying Micro/Nano Particulates

Atomic Force Microscopes (AFM) are typically used to image surfaces along with small particulates that may be deposited on the surface. Surface imaging can be made down to the atomic level but usually it is conducted at the nano and micro scales. It is highly desirable to identify the constituency of particulates on the surface and if possible determine the chemical and physical identity of particulates. The objective of the research presented in this thesis is to establish the feasibility of using dual micro cantilevers to determine the physical constituency of nano particles deposited to the micro surface. The goal at this point is not to determine the physical properties of a particulate but rather to determine whether the particulate is hard or soft and categorize it. The research addresses this goal by predicting the vibration response of dual micro cantilever when the cantilever tip engages a surface and a particulate. Five different particulate models are analyzed: elastic, viscous, visco-elastic in parallel, visco-elastic in series and visco-elastic in series/parallel. Each model represents different possible physical constituencies of particles. The analysis shows that each particle model produces unique signatures and vibration responses of the dual micro cantilever. Properties that are identified in the research are signatures. Signatures can be shifts in natural frequencies, change in response amplitudes and phase angles

Power system security enhancement through direct non-disruptive load control

The transition to a competitive market structure raises significant concerns regarding reliability of the power grid. A need to build tools for security assessment that produce operating limit boundaries for both static and dynamic contingencies is recognized. Besides, an increase in overall uncertainty in operating conditions makes corrective actions at times ineffective leaving the system vulnerable to instability. The tools that are in place for stability enhancement are mostly corrective and suffer from lack of robustness to operating condition changes. They often pose serious coordination challenges. With deregulation, there have also been ownership and responsibility issues associated with stability controls. However, the changing utility business model and the developments in enabling technologies such as two-way communication, metering, and control open up several new possibilities for power system security enhancement. This research proposes preventive modulation of selected loads through direct control for power system security enhancement. Two main contributions of this research are the following: development of an analysis framework and two conceptually different analysis approaches for load modulation to enhance oscillatory stability, and the development and study of algorithms for real-time modulation of thermostatic loads.;The underlying analysis framework is based on the Structured Singular Value (SSV or mu) theory. Based on the above framework, two fundamentally different approaches towards analysis of the amount of load modulation for desired stability performance have been developed. Both the approaches have been tested on two different test systems: CIGRE Nordic test system and an equivalent of the Western Electric Coordinating Council test system.;This research also develops algorithms for real-time modulation of thermostatic loads that use the results of the analysis. In line with some recent load management programs executed by utilities, two different algorithms based on dynamic programming are proposed for air-conditioner loads, while a decision-tree based algorithm is proposed for water-heater loads. An optimization framework has been developed employing the above algorithms. Monte Carlo simulations have been performed using this framework with the objective of studying the impact of different parameters and constraints on the effectiveness as well as the effect of control.;The conclusions drawn from this research strongly advocate direct load control for stability enhancement from the perspectives of robustness and coordination, as well as economic viability and the developments towards availability of the institutional framework for load participation in providing system reliability services

Characterization and Classification of Faces across Age Progression

Facial aging, a new dimension that has recently been added to the problem of face recognition, poses interesting theoretical and practical challenges to the research community . How do humans perceive age ? What constitutes an age-invariant signature for faces ? How do we model facial growth across different ages ? How does facial aging effects impact recognition performance ? This thesis provides a thorough overview of the problem of facial aging and addresses the aforementioned questions. We propose a craniofacial growth model that characterizes growth related shape variations observed in human faces during formative years (0 - 18 yrs). The craniofacial growth model draws inspiration from the `revised' cardioidal strain transformation model proposed in psychophysics and further, incorporates age-based anthropometric evidences collected on facial growth during formative years. Identifying a set of fiducial features on faces, we characterize facial growth by means of growth parameters estimated on the fiducial features. We illustrate how the growth related transformations observed on facial proportions can be studied by means of linear and non-linear equations in facial growth parameters, which subsequently help in computing the growth parameters. The proposed growth model implicitly accounts for factors such as gender, ethnicity, the individual's age group etc. Predicting one's appearance across ages, performing face verification across ages etc. are some of the intended applications of the model. Next, we propose a two-fold approach towards modeling facial aging in adults. Firstly, we develop a shape transformation model that is formulated as a physically-based parametric muscle model that captures the subtle deformations facial features undergo with age. The model implicitly accounts for the physical properties and geometric orientations of the individual facial muscles. Next, we develop an image gradient based texture transformation function that characterizes facial wrinkles and other skin artifacts often observed during different ages. Facial growth statistics (both in terms of shape and texture) play a crucial role in developing the aforementioned transformation models. From a database that comprises of pairs of age separated face images of many individuals, we extract age-based facial measurements across key fiducial features and further, study textural variations across ages. We present experimental results that illustrate the applications of the proposed facial aging model in tasks such as face verification and facial appearance prediction across aging. How sensitive are face verification systems to facial aging effects ? How does age progression affect the similarity between a pair of face images of an individual ? We develop a Bayesian age difference classifier that classifies face images of individuals based on age differences and performs face verification across age progression. Further, we study the similarity of faces across age progression. Since age separated face images invariably differ in illumination and pose, we propose pre-processing methods for minimizing such variations. Experimental results using a database comprising of pairs of face images that were retrieved from the passports of 465 individuals are presented. The verification system for faces separated by as many as 9 years, attains an equal error rate of 8.5%

Construction delays causing risks on time and cost - a critical review

There is an increase in the number of construction projects experiencing extensive delays leading to exceeding initial time and cost budget.  This paper reviews 41 studies around the world which surveyed the delay factors and classified them into Groups.  The main purpose of this paper is to review literature, each of which have categorized the causes that are responsible for time delays and cost overrun in projects. The collected list has 113 causes for delays categorized in to 18 different groups.  Most of the researches have analysed the responses from the Questionnaire survey.    The collected data are used to rank the problem.  The data are further used to investigate and analyse Important Index, Frequency Index, Severity Index, Relative Important Index, Relative Importance Weight, Weighted Average, Mean, Standard Deviation and Variance.  The collective comparison has revealed that the ranking given by all the researchers is not the same.  Further each and every study has different rank ratings for the different group of the delays.  This review paper attempts to provide an updated compilation of the earlier studies on ranking of the delay causers, which are never similar and constant for universal projects.  It is concluded that a separate study is required for identifying the factors causing delay for projects operated in Sabah, East Malaysia

An fpga implementation of decision tree classification

Data mining techniques are a rapidly emerging class of applications that have widespread use in several fields. One important problem in data mining is Classification, which is the task of assigning objects to one of several predefined categories. Among the several solutions developed, Decision Tree Classification (DTC) is a popular method that yields high accuracy while handling large datasets. However, DTC is a computationally intensive algorithm, and as data sizes increase, its running time can stretch to several hours. In this paper, we propose a hardware implementation of Decision Tree Classification. We identify the computeintensive kernel (Gini Score computation) in the algorithm, and develop a highly efficient architecture, which is further optimized by reordering the computations and by using a bitmapped data structure. Our implementation on a Xilinx Virtex-II Pro FPGA platform (with 16 Gini units) provides up to 5.58 × performance improvement over an equivalent software implementation.

Comparative evaluation of PCR using IS6110 and a new target in the detection of tuberculous lymphadenitis

We evaluated TRC4 primers using polymerase chain reaction (PCR) which amplify a new target sequence from Mycobacterium tuberculosis genome to diagnose tuberculous lymphadenitis and compared the results with PCR using the widely used IS6110 primers. The PCR results were also compared with conventional methods like smear, culture and histopathology. The sensitivity of PCR using both probes is higher than the conventional methods. Out of 101 samples analysed (49 fresh and 52 fixed specimens), PCR using IS6110 and TRC4 primers was positive in 64 and 70 samples, respectively, whereas results with culture and histopathology methods were positive only in 49 and 58 samples, respectively. The problem of false negativity of IS6110 due to the absence of IS6110 copy in 4 M. tuberculosis isolates was overcome by using TRC4 primers. The results indicate that with improvement in PCR techniques, PCR using both probes, IS6110 and TRC4 can be a rapid and sensitive adjunct to conventional techniques in the diagnosis of tuberculous lymphadenitis

Perspectives of Teachers at Medical Colleges Across India regarding the Competency based Medical Education Curriculum – A Qualitative, Manual, Theoretical Thematic Content Analysis

Background: Competency-based medical education (CBME) curriculum has been implemented in India since 2019 with a goal to create an “Indian Medical Graduate” (IMG) possessing requisite knowledge, skills, attitudes, values, and responsiveness. Objectives: To explore teachers’ perceptions across India at medical colleges on the newly implemented competency-based medical education curriculum. Methods: This was a qualitative cross?sectional study conducted among teachers working at medical colleges across India, between February and April 2022 (n = 192). The data collection was done using Google forms online survey platform on teachers’ perception regarding CBME, its specific components, and perceived bottlenecks. We analyzed this qualitative data using manual, theoretical thematic content analysis following the steps endorsed in Braun and Clarke’s six-phase framework. Results: The majority of the teachers (64.1%) have positively responded to the CBME curriculum’s implementation. However, it came with a caution that the curriculum should continuously evolve and adapt to regional demands. The foundation course, early clinical exposure, and the family adoption program were the specific components of CBME curriculum over which the teachers raised concerns. The need for additional teachers in each department (department-specific teacher or faculty per hundred students ratio to be worked out) and the need for enabling faculty preparedness through adequate training was highlighted. Concerns were also raised regarding implementing CBME with teachers without a medical background (especially in preclinical departments). Conclusion: It is the need of the hour for the curriculum to incorporate a systematic feedback mechanism built into the system, though which such critical appraisals can be meaning collated and acted upon, to ultimately evolve, thereby creating an “Indian Medical Graduate” for the needs of todays’ society

Evaluation of an Intermittent Six-month Regimen in New Pulmonary Tuberculosis Patients with Diabetes Mellitus

Background: The treatment of tuberculosis (TB) with category I regimen of the Revised National Tuberculosis Control Programme (RNTCP) for patients with diabetes mellitus (DM) needs evaluation. Objective: To assess the cure and relapse rates in 3 years, among the new smear-positive TB patients with Type-2 DM (DMTB) treated with CAT-I regimen (2E3H3R3Z3/4R3H3) of RNTCP. Methodology: TB suspects attending the diabetology units and the TB research centre (TRC) Chennai, were investigated. Eligible DMTB cases were enrolled. Baseline estimation of cardiac, renal, liver function tests and glycosylated-HBA1c were undertaken. All patients received 2E3H3R3Z3/4R3H3 under supervision at TRC. Clinical and sputum (smear and culture) examinations and monitoring of diabetic status were undertaken every month up to 24 months, then once in 3 months up to 36 months. Results: Of 100 patients admitted, 7 were excluded for various reasons from analysis. Of 93 patients, 87 (94%) had a favourable response at the end of treatment. Pre and post treatment mean glycosylated-HBA1c were 9.7% and 8.4 %.(>7% poor control). During follow-up period, 6 died and one lost to follow-up. Of the remaining, four relapsed. Conclusion: Category-I regimen, recommended for all the new smear-positive patients in the Indian TB programme, is effective in the treatment of DMTB patients, despite poor control of diabetes

Habituation based synaptic plasticity and organismic learning in a quantum perovskite

A central characteristic of living beings is the ability to learn from and respond to their environment leading to habit formation and decision making. This behavior, known as habituation, is universal among all forms of life with a central nervous system, and is also observed in single-cell organisms that do not possess a brain. Here, we report the discovery of habituation-based plasticity utilizing a perovskite quantum system by dynamical modulation of electron localization. Microscopic mechanisms and pathways that enable this organismic collective charge-lattice interaction are elucidated by first-principles theory, synchrotron investigations, ab initio molecular dynamics simulations, and in situ environmental breathing studies. We implement a learning algorithm inspired by the conductance relaxation behavior of perovskites that naturally incorporates habituation, and demonstrate learning to forget: A key feature of animal and human brains. Incorporating this elementary skill in learning boosts the capability of neural computing in a sequential, dynamic environment.United States. Army Research Office (Grant W911NF-16-1-0289)United States. Air Force Office of Scientific Research (Grant FA9550-16-1-0159)United States. Army Research Office (Grant W911NF-16-1-0042