Transmission losses cost allocation in restructed electricity market environment

During these recent decades, the restructuring system of electricity market has been taken places around the whole world. Due to the restructuring (deregulation), the electrical power system has been divided into three separates categories according to the function. First stage of power system is the generation companies (GENCOs), followed by transmission companies (TRANSCOs) and distribution companies (DISCOs). The competitive environment will be handling by a non-profit entity, independent system operator (ISO) that functioning as the system securities that have to make sure that the power system continues to operate in a stable and economical manner. However, restructuring system can give effect during the energy transmission. One of the transmission issues is regarding the power losses. To overcome the losses, generators must generate more power. The issue regarding the transmission losses in deregulated system is how to allocate it to the user and charge them in fair ways as in for instance the pool trading model, it is hard to trace the power contribution and losses of each user in transmission line. In addition, the users didn’t want to pay the losses, it means that the ISO have to responsible for the losses and it will be unfair to put the responsible to ISO alone. Therefore, in this project, the allocation of transmission losses and loss cost methods which are the pro-rata and proportional sharing method will be investigated. Comparison between those methods will be done in order to identify which types of method that reflect an efficient and fair way to distribute the cost of the transmission losses to the user. These chosen methods will be tested on IEEE bus system

Kinect-based physiotherapy and assessment: a comprehensive review

In this paper, we discuss a review of the present Kinect-based physiotherapy and assessment for rehabilitation patients to provide an outline of the state of art, limitation and issues of concern as well as suggestion for future work in this approach. The paper is constructed into three main parts, each part presenting a review for a particular topic. The introduction was discussed on physiotherapy exercises and the limitation of current Kinect-based applications. Next, we also discuss on Kinect Skeleton Joint and Kinect Depth Map features that being used widely nowadays. A concise summary with significant findings of each paper had been tabulate for each feature; Skeleton Joints and Depth Map. Afterward we assemble a quite number of classification method that being implemented for activity recognition in past few years

Ambient vibration response of precast hollow core flooring system

Prestressed precast hollow core is known as a long span slab with a void along its length. The void has a big influence on the weight of the slab. In vibration theory, a lightweight slab with a long span is very sensitive to vibration. In this study, the ambient vibration response of precast hollow core is investigated using the finite element method and modal analysis. Numerical analysis is used to predict the floor vibration and modal testing is used to test the vibration performance of floors on the actual site. The prediction data is obtained by using SAP2000 to determine the vibration behaviour and compared with the modal testing result of the floor located in Kuala Lumpur. The 1st mode shape appeared for 12 natural frequencies between 8.36 Hz to 9.29Hz in the prediction analysis. For modal testing, the vibration behaviour of the actual hollow core floor is determined using an ambient test. The data was obtained using an accelerometer and analysed using Artermis software to determine natural frequencies, damping ratio and mode shape. The 1st mode of natural frequencies for floor area A and area B were 8.45Hz and 9.34Hz. The results from the analysis show that the range of natural frequency between the predicted analysis and that of the modal testing is acceptable. The limitation stated that 10Hz is the cut-off frequency to determine the class of the floor. From the analysis, it is shown that the prediction and the modal testing results are accepted where both floors are classified as low-frequency floors

Public Speaking: Teknik Berbicara di Depan Umum dalam Mengelola Vokal dan Gesture yang Tepat

Public speaking is an essential skill that supports self-confidence, effective communication, and professionalism, both in educational settings and daily life. However, many individuals, particularly students and youth, still struggle with managing their voice and gestures appropriately when speaking in public. This community service activity aimed to enhance participants’ understanding and skills in public speaking techniques, especially in vocal control and appropriate use of gestures. The target group of this program consisted of young people and students from a local community. The implementation method included interactive training, practical simulations, and evaluations through pre-test and post-test. The results showed improvements in participants’ self-confidence, understanding of public speaking concepts, and their ability to manage voice intonation and body language in a more structured manner. This activity had a positive impact on developing more effective communication potential in various public settings

A Computational and Experimental Investigation of Lignin Metabolism in Arabidopsis thaliana.

Predominantly localized in plant secondary cell walls, lignin is a highly crosslinked, aromatic polymer that imparts structural support to plant vasculature, and renders biomass recalcitrant to pretreatment techniques impeding the economical production of biofuels. Lignin is synthesized via the phenylpropanoid pathway where the primary precursor phenylalanine (Phe) undergoes a series of functional modifications catalyzed by 11 enzyme families to produce p-coumaryl, coniferyl, and sinapyl alcohol, which undergo random polymerization into lignin. Several metabolic engineering efforts have aimed to alter lignin content and composition, and make biofuel feedstock more amenable to pretreatment techniques. Despite significant advances, several questions pertaining to carbon flux distribution in the phenylpropanoid network remain unanswered. Furthermore, complexity of the metabolic pathway and a lack of sensitive analytical tools add to the challenges of mechanistically understanding lignin synthesis. In this work, I describe improvements in analytical techniques used to characterize phenylpropanoid metabolism that have been applied to obtain a comprehensive quantitative mass balance of the phenylpropanoid pathway. Finally, machine learning and artificial intelligence were utilized to make predictions about optimal lignin amount and composition for improving saccharification. In summary, the overarching goal of this thesis was to further the understanding of lignin metabolism in the model system, Arabidopis thaliana, employing a combination of experimental and computational strategies. First, we developed comprehensive and sensitive analytical methods based on liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) to quantify intermediates of the phenylpropanoid pathway. Compared to existing targeted profiling techniques, the methods were capable of quantifying a wider range of phenylpropanoid intermediates, at lower concentrations, with minimal sample preparation. The technique was used to generate flux maps for wild type and mutant Arabidopsis stems that were fed exogenously 13C6-Phe. Flux maps computed in this work; (i) suggest the presence of a hitherto uncharacterized alternative route to caffeic acid and lignin synthesis, (ii) shed light on flux splits at key branch points of the network, and (iii) indicate presence of inactive pools for a number of metabolites. Finally, we present a machine learning based model that captures the non-linear relationship between lignin content and composition, and saccharification efficiency. A support vector machine (SVM) based regression technique was developed to predict saccharification efficiency and biomass yields as a function of lignin content, and composition of monomers that make up lignin, namely p-coumaryl (H), coniferyl (G), and sinapyl (S) alcohol derived lignin. The model was trained on data obtained from the literature and validated on Arabidopsis mutants that were excluded from the training data set. Functional forms obtained from SVM regression were further optimized using genetic algorithms (GA) to maximize total sugar yields. Our efforts resulted in two optimal solutions with lower lignin content and interestingly varying H:G:S composition that were conducive to saccharide extractability

Methods for functional characterization of transcription factor binding sites in bacteria

Thesis (Ph.D.)--Boston UniversityUnderstanding gene regulation is necessary to gain insight into and model important cellular processes including disease. Current inability to combat many diseases is partly because of incomplete understanding of gene circuitry. Regulation mechanisms of Mycobacterium tuberculosis, the causative agent of Tuberculosis are not properly understood. Transcriptional regulatory network (TRN) is a network comprising transcription factors (TF) and their targeted genes that provide a powerful framework to analyze the complete regulatory system. Chromatin immunoprecipitation followed by next generation sequencing (ChiP-Seq) is becoming the method of choice to identify genome wide TFBS . Therefore, we use ChiP-Seq on known transcription factors to reconstruct the TRN of Mycobacterium tuberculosis (Mtb) and other bacteria. ChiP-Seq reveals various transcription factor binding sites (TFBS) but doesn't provide any information on the mechanism of regulation of the genes by their corresponding TF's. Techniques to gain more insight into the mechanisms include microarray, knock out studies and qPCR. But, these techniques provide a static view of network. Also, they provide information at RNA level and mask the regulation happening at protein level. Therefore, in order to understand both the mechanism of regulation at protein level as well as to capture the network dynamics, we built a synthetic gene circuit in Mycobacterium smegmatis and defined input-output relationships between key TFs and their targeted promoters. We validated this system on kstR, a TF which is a known repressor. KstR regulates genes involved in cholesterol degradation and is shown to de- repress itself and its regulon genes in the presence of cholesterol as well as in hypoxia, where there are no exogenous lipids4- . We explored the possibility of other by-products that may be responsible for the de-repression of kstR and its regulon. The data suggests that propionyl-coA, a by-product from degradation of cholesterol, odd numbered fatty acids as well as branched chain amino-acids is causing the de-repression of kstR and its regulon. ChiP-Seq data on transcription factors in MTb as well as E.coli shows that many TFBS are located immediately upstream of open reading frame start sites, consistent with our understanding ofprokaryotic gene regulation. However, the data also suggests that many TFBS are located inside and also downstream of open reading frames6. One of our hypotheses is that these novel TFBS might be indirect binding sites that mediate chromatin looping . Therefore, we developed a method 3C (Chromosome Conformation Capture) to understand the regulation in the third dimension by analyzing the chromosomal interactions. We optimized the protocol in E.coli and validated using a known interaction mediated by a repressor GalR . We then identified two regions, 20 kbp apart, containing TFBS of StpA, a nucleoid associated protein, which are not directly involved in gene regulation of their downstream genes. The data from a 3C experiment on an E.coli strain with inducible StpA suggests that these two regions interact by an unknown mechanism. However, the interaction was not lost when a similar experiment is done in StpA knock out strain suggesting that StpA may not be a sole TF responsible for this interaction. Lastly, we developed Hi-C method on E.coli genomic DNA to identify long range interactions in a genome wide and unbiased manner