Fuzzy Hysteresis Controller Based Unified Power Quality Conditioner for Voltage Fluctuations and Harmonic Isolation

Power quality problem makes the consumer un satisfy.  FACTS devices such as UPQC are such devices to avoid power quality problems. This paper proposed an efficient hysteresis controller and fuzzy controller for unified power quality conditioner. In this harmonics and voltage fluctuations were dealed by UPQC with hysteresis control strategy. The performance of the control strategy applied unified power quality conditioner on distribution system checked with and without UPQC. And the performances of these two controllers of UPQC are compared. This strategy makes the industries to get pure power and to avoid the disturbances from polluted distribution system. The proposed dynamic model was developed in MATLAB/SIMULINK. Keywords: power quality, voltage fluctuations, harmonics, hysteresis controller, fuzzy controller

Role of the Yeast Ste20 Protein Kinase Ortholog Map4k4 in Adipose Tissue Function: A Dissertation

Obesity has increased globally in epidemic proportions and as have the associated disorders. Insulin resistance that could further lead to type 2 diabetes is a major obesity associated dysfunction. Studies using insulin resistant mouse models and observations from human subjects exhibiting insulin resistance provide evidence for ectopic lipid deposition in organs like liver, muscle and heart as one of the major risk factors for developing insulin resistance. These observations suggest that deregulated adipose function to sequester and store excess energy as fat, could lead to insulin resistance. Furthermore, several studies have demonstrated adipose tissue dysfunction leading to inflammation and related syndromes. Interestingly, a mouse model with transgenic expression of glucose transporter in the adipose tissue exhibited improved glucose tolerance and increased insulin sensitivity despite development of obesity, upon high fat feeding. Thus mechanisms that improve adipose function could alleviate insulin resistance and associated diseases. Mitogen activated protein kinase kinase kinase kinase 4 (MAP4K4) was identified in our laboratory as a negative regulator of adipocyte function. Interestingly, siRNA mediated knockdown of MAP4K4 promoted PPARγ protein expression. Additionally, silencing of MAP4K4 increased adipocyte triglyceride content. Because MAP4K4 is a negative regulator of PPARγ expression and adipocyte function, understanding the mechanism by which MAP4K4 regulates PPARγ expression is of interest. Thus, for the first part of this thesis, I characterized the signaling pathways utilized by MAP4K4 to regulate PPARγ expression in cultured adipocytes. Here I show that MAP4K4 regulates PPARγ expression through regulation of its protein translation. siRNA mediated MAP4K4 gene silencing stimulated PPARγ protein synthesis without changing its mRNA transcription or its protein degradation. This increase in PPARγ protein translation was due to an increase in the activity of mammalian target of rapamycin (mTOR). The increase in PPARγ protein expression mediated by mTOR activation was a specific effect of the 4E-BP1 phosphorylation that leads to its inactivation and was not a general increase in mTOR activity towards all of its substrates. Finally, adenovirus mediated over expression of MAP4K4 inhibited mTOR activation, and suppressed PPARγ protein translation. For the second part of this thesis, I assessed the role of MAP4K4 in adipocytes in vivo. To accomplish this, a lentivirus mediated shRNA construct was generated to attenuate MAP4K4 expression selectively in the mouse adipose tissue. First we demonstrate that the MAP4K4 shRNA construct is able to efficiently silence the expression of MAP4K4 in vitro when co-expressed with Cre recombinase. Furthermore, we show that following modification of the lentiviral conditional vector that was introduced into a mouse embryo at one cell stage, and crossing the resulting founders with aP2-Cre mice, adipose tissue specific MAP4K4 gene silencing was achieved. Moreover, shRNA mediated gene silencing is a faster and an inexpensive means of achieving tissue specific gene knockdown relative to the available traditional gene knockout approaches. Utilizing these adipose specific MAP4K4 gene knockdown mice, I reveal that MAP4K4 silencing enhanced fat mass as well as PPARγ expression significantly. This is accompanied by improved whole body insulin sensitivity. Furthermore, when challenged with high fat diet, adipose-specific MAP4K4 silenced mice exhibit enhanced adiposity with decreased lean mass. Moreover, adipocyte cell size and triglyceride content are significantly increased. Interestingly, despite increased adiposity, hepatic insulin sensitivity is significantly improved leading to decreased glucose output. Thus MAP4K4 is an important regulator of adipocyte function that mediates whole body glucose homeostasis, through a mechanism that is yet to be identified

Robotic Competitions: Motivation for Engineering Programmes

e-Health is referred to in literature as the usage of information and communication technologies (ICT’s) in the health domain, to administer treatment of patients, research, health education and the monitoring of public health. South Africa is in the process of re-engineering its public healthcare to improve healthcare for all South African citizens. E- health forms part of the re-engineering process. The purpose of this paper is therefore to explore benefits and challenges of e-health as experienced in other countries. A list of both e-health benefits and e- health challenges are provided and could provide guidance in the implementation of e-health in South Africa. To realise the purpose of the paper, an inductive content analysis methodology was followed. The main results were that although the challenges outweighs the benefits in the provided lists, there is still hope that through proper ICT solutions the benefits of e-health can grow more rapidly. This can lead to improved e-health service delivery and citizens in countries can all benefit from this

Modeling Study of Beach Placer Minerals using Artificial Neural Network: A Case Study

In recent years, artificial neural network (ANNs) have been found to be an attractive tool for steady-state /dynamic process modeling, and model based control in situations where the development of phenomenological or the empirical models just given either becomes impracti-cal or cumbersome. ANN technology is well suited to solve problems in the mineral industry, and is expected to have a significant impact in many technological areas. Beneficiation plants for beach sand minerals are often very complex in nature with a number of alternative flow sheets are possible for the same mineral sand deposits

Using robot operating system (ROS) and single board computer to control bioloid robot motion

This paper presents a research study on the adaptation of a novel technique for placing a programmable component over the structural component of a Robotis Bioloid humanoid robot. Assimilating intelligence plays an important role in the field of robotics that enables a computer to model or replicate some of the intelligent behaviors of human beings but with minimal human intervention. As a part of this effort, this paper revises the Bioloid robot structure so as to be able to control the robotic movement via a single board computer Beaglebone Black (BBB) and Robot operating system (ROS). ROS as the development frame work in conjunction with the main BBB controller that integrates robotic functions is an important aspect of this research, and is a first of its kind approach. A full ROS computation has been developed by which an API that will be usable by high level software using ROS services has also been developed. The human like body structure of the Bioloid robot and BeagleBone Black running ROS along with the intellectual components are used to make the robot walk efficiently

Expert System for Signature Analysis

Vibrating Machinery Noise, - airborne, structureborne or waterborne - has a signature characteristic of the combination of machinery, its mounting, load coupling, and the structure. FFT and RTA are standard techniques for obtaining power spectral density(PSD) of the noise from the source. In this paper a technique of extraction of features from the PSD, and classification of the sources is presented. An expert system is reported which classifies if the same source has appeared second time. It also gives the degree of confidence to which the classification is made to the operator

Research journal articles as document genres: exploring their role in knowledge organization

Deep learning is one of the most promising machine learning techniques that revolutionalized the artificial intelligence field. The known traditional and con- volutional neural networks (CNNs) have been utilized in medical pattern rec- ognition applications that depend on deep learning concepts. This is attributed to the importance of anomaly detection (AD) in automatic diagnosis systems. In this paper, the AD is performed on medical electroencephalography (EEG) signal spectrograms and medical corneal images for Internet of medical things (IoMT) systems. Deep learning based on the CNN models is employed for this task with training and testing phases. Each input image passes through a series of convolution layers with different kernel filters. For the classification task, pooling and fully-connected layers are utilized. Computer simulation experi- ments reveal the success and superiority of the proposed models for automated medical diagnosis in IoMT systems

Control and Automation Engineering Education: combining physical, remote and virtual labs

Although a large volume of literature is available on mobile commerce (m-commerce), the topic is still under development and offers potential opportunities for further research and applications. Since the subject is at the stage of development, a review of the literature on m-commerce with the objective of bringing to the fore the state-of-art in m-commerce research and applications will initiate further research on the growth of m-commerce technologies. This paper reviews the literature on m- commerce and applications using a suitable classification scheme to identify the gap between theory and practice and future research directions. The 149 m-commerce articles are classified and the results of these are presented based on a scheme that consists of five distinct categories: m-commerce theory and research, wireless network infrastructure, mobile middleware, wireless user infrastructure, and m-commerce applications and cases. A comprehensive list of references is presented. We hope that the findings of this research will provide useful insights into the anatomy of m-commerce literature and be a good source for anyone who is interested in m-commerce. The paper also provides some future directions for research. &nbsp