Designing of Different High Efficiency Diode Clamped Multilevel

This research work is aimed at designing of high efficiency multilevel diode clamped inverter. It would cover diode clamped multilevel inverter with particular reference to the comparison of high level and low level inverter using efficient modulation method (sinusoidal pulse width modulation). The main theme of this research is to obtain a pure sinusoidal waveform of high quality having minimum harmonics that can be utilized for both industrial purposes and to sensitive domestic loads. The proposed design besides considering high quality of the output waveform of multilevel diode clamped inverter, the problems regarding multilevel inverter design has been given more consideration high voltage stresses across switching devices. The voltage stresses issues have been resolved with DC link voltage equally distributed among capacitors in multilevel inverter. Simulation results for different level inverters both low level (5, 7, 9, level) and high levels (11, 13, 15) are used as a reference. The proposed design resulted in reduced total harmonic distortion thus eliminating the harmonics in the output waveform to a greater extent resulting in pure sine waveform output. This resulted in reduction in overall losses and elimination of voltage balancing problems in high level diode clamped inverter. Keywords: Hormonics, Clamping, Inverter, Pulse Width Modulation, Sinusoidal Pulse Width Modulation (SPWM)

Resistance patterns, prevalence, and predictors of fluoroquinolones resistance in multidrug resistant tuberculosis patients

AbstractBackgroundFluoroquinolones are the backbone of multidrug resistant tuberculosis treatment regimens. Despite the high burden of multidrug resistant tuberculosis in the country, little is known about drug resistance patterns, prevalence, and predictors of fluoroquinolones resistance among multidrug resistant tuberculosis patients from Pakistan.ObjectiveTo evaluate drug resistance patterns, prevalence, and predictors of fluoroquinolones resistance in multidrug resistant tuberculosis patients.MethodsThis was a cross-sectional study conducted at a programmatic management unit of drug resistant tuberculosis, Lady Reading Hospital Peshawar, Pakistan. Two hundred and forty-three newly diagnosed multidrug resistant tuberculosis patients consecutively enrolled for treatment at study site from January 1, 2012 to July 28, 2013 were included in the study. A standardized data collection form was used to collect patients’ socio-demographic, microbiological, and clinical data. SPSS 16 was used for data analysis.ResultsHigh degree of drug resistance (median 5 drugs, range 2–8) was observed. High proportion of patients was resistant to all five first-line anti-tuberculosis drugs (62.6%), and more than half were resistant to second line drugs (55.1%). The majority of the patients were ofloxacin resistant (52.7%). Upon multivariate analysis previous tuberculosis treatment at private (OR=1.953, p=0.034) and public private mix (OR=2.824, p=0.046) sectors were predictors of ofloxacin resistance.ConclusionThe high degree of drug resistance observed, particularly to fluoroquinolones, is alarming. We recommend the adoption of more restrictive policies to control non-prescription sale of fluoroquinolones, its rational use by physicians, and training doctors in both private and public–private mix sectors to prevent further increase in fluoroquinolones resistant Mycobacterium tuberculosis strains

Hubungan Harga Diri dan Kesepian dengan Narsisme Pada Siswa SMA Pengguna Aplikasi TikTok

The development of information technology in the modern world is currently transforming the methods of education, making them more easily accessible from anywhere. This has led to increased interaction with the internet and digital devices, accompanied by the growing use of applications on these devices, including TikTok. Excessive use of this application can have a negative impact, leading to an increase in students' narcissism, which requires control and adaptation to avoid adverse effects. This study aims to investigate the relationship between self-esteem and loneliness with narcissism among high school students who use the TikTok application.This research employs a quantitative correlational approach with the sample criteria being high school students in Salatiga, aged 15-18 years, who actively use the TikTok application. The study uses a sample size of 102 subjects selected through non-probability sampling, specifically accidental sampling. Data is collected using questionnaires in the form of self-esteem, loneliness, and narcissism scales distributed through Google Forms. The research methodology involves multiple linear regression analysis.The results of the analysis indicate a significant role of self-esteem and loneliness in narcissism, as evidenced by an F-value of 20.059 with a significance level of <0.001. Furthermore, there is a significant role of self-esteem in narcissism, supported by a t-value of -3.175 with a significance level of 0.002. Similarly, there is a significant role of loneliness in narcissism, supported by a t-value of 4.223 with a significance level of <0.001. The effective contribution of self-esteem and loneliness variables to narcissism among high school students who use the TikTok application in this study is 28.8%, with the gratitude variable contributing 11.32% and the social support variable contributing 17.53%, while 71.2% is influenced by other variables.The implication of this research is to provide recommendations for enhancing self-esteem, reducing loneliness, and mitigating narcissism among high school students who use the TikTok application

Pseudotumoral hemicerebellitis in a young male sailor with complete recovery after steroid therapy

Pseudotumoral hemicerebellitis is a rare presentation of acute cerebellitis, which involves the inflammation of a single cerebellar hemisphere and most commonly affects children. It mimics a tumor on imaging, hence given the name. In this report, we present a case of pseudotumoral hemicerebellitis in a 30-year-old male who presented to the emergency room (ER) with complaints of vertigo, vomiting, and a headache

Causes of Smoking in College Students

This study was aimed at investigating smoking and causes of cigarette smoking among college students of Warsak Road Peshawar. The sample consisted of forty (N=40) students of Warsak Model School and College and Peshawar Public School and College. Average age of the students was 18.7. Among the 100 students, 40 were smokers while 60 were non-smokers. Convenient sampling technique was used for selection of the sample. Structured survey questionnaire was used for data collection. The objectives of the study were To provide an initial estimate on the frequency of cigarette smoking among students of college level on Warsak road Peshawar and explore causes of smoking in these students. Cross-sectional study design was used. The study was a small scale one due to limited financial resources and a short time frame. Students were busy in their annual exams and thus could not fully co-operate. The results revealed the main reasons for smoking were fashion and style, tension due to studies and family problems. Twenty-five (n=25) out of forty (n=40) students smoke more than 2 cigarettes per day. Out of forty (N=40) smoker students twenty-four (n=24) were introduced to smoking by their friends, 10 students by class-fellows, three (n=3) by relatives, one(n=1) by parents, two (n=2) by other people. 54 out of 60 non-smokers agreed that smoking is a bad habit. Cigarette smoking is very common among college students. Further in depth research is recommended to assess the frequency of smoking on a larger scale. Health education and awareness should be promoted in young adults in order to decrease the frequency of smoking

Comparative Analysis of State-of-the-Art Deep Learning Models for Detecting COVID-19 Lung Infection from Chest X-Ray Images

The ongoing COVID-19 pandemic has already taken millions of lives and damaged economies across the globe. Most COVID-19 deaths and economic losses are reported from densely crowded cities. It is comprehensible that the effective control and prevention of epidemic/pandemic infectious diseases is vital. According to WHO, testing and diagnosis is the best strategy to control pandemics. Scientists worldwide are attempting to develop various innovative and cost-efficient methods to speed up the testing process. This paper comprehensively evaluates the applicability of the recent top ten state-of-the-art Deep Convolutional Neural Networks (CNNs) for automatically detecting COVID-19 infection using chest X-ray images. Moreover, it provides a comparative analysis of these models in terms of accuracy. This study identifies the effective methodologies to control and prevent infectious respiratory diseases. Our trained models have demonstrated outstanding results in classifying the COVID-19 infected chest x-rays. In particular, our trained models MobileNet, EfficentNet, and InceptionV3 achieved a classification average accuracy of 95\%, 95\%, and 94\% test set for COVID-19 class classification, respectively. Thus, it can be beneficial for clinical practitioners and radiologists to speed up the testing, detection, and follow-up of COVID-19 cases

Feedback fuzzy state space modeling and optimal production planning for steam turbine of a combined cycle power generation plant

The main pwpose of a Combined Cycle (CC) power generation plant is to minimize the energyiheat losses. In this research an inverse Feedback Fuzzy State Space Model (FFSSM) for the steam turbine of the CC is modeled. The algorithm maximizes the power production with optimal input parameters. The overall turbine section consists of the high pressure intermediate pressure and the low pressure subsections. The model suggests the optimal inputs/outputs for each subsection of the steam turbine in the allowable desired ranges. The inverse modeling approach determines the optimal operating conditions keeping in view the total available throughput against the desired operating conditions. The algorithm proposes more flexible operating conditions for the three stages of the steam turbine. The primary superiority of the proposed algorithm over the more direct ones is the ability to operate on more flexible operating conditions

TARS: A Novel Mechanism for Truly Autonomous Resource Selection in LTE-V2V Mode 4

Effective communication in vehicular networks depends on the scheduling of wireless channel resources. There are two types of channel resource scheduling in Release 14 of the 3GPP, i.e., (1) controlled by eNodeB and (2) a distributed scheduling carried out by every vehicle, known as Autonomous Resource Selection (ARS). The most suitable resource scheduling for vehicle safety applications is the ARS mechanism. ARS includes (a) counter selection (i.e., specifying the number of subsequent transmissions) and (b) resource reselection (specifying the reuse of the same resource after counter expiry). ARS is a decentralized approach for resource selection. Therefore, resource collisions can occur during the initial selection, where multiple vehicles might select the same resource, hence resulting in packet loss. ARS is not adaptive towards vehicle density and employs a uniform random selection probability approach for counter selection and reselection. As a result, it can prevent some vehicles from transmitting in a congested vehicular network. To this end, the paper presents Truly Autonomous Resource Selection (TARS) for vehicular networks. TARS considers resource allocation as a problem of locally detecting the selected resources at neighbor vehicles to avoid resource collisions. The paper also models the behavior of counter selection and resource block reselection on resource collisions using the Discrete Time Markov Chain (DTMC). Observation of the model is used to propose a fair policy of counter selection and resource reselection in ARS. The simulation of the proposed TARS mechanism showed better performance in terms of resource collision probability and the packet delivery ratio when compared with the LTE Mode 4 standard and with a competing approach proposed by Jianhua He et al