A New Scheme to Direct Torque Control of Matrix Converter-Fed Five-Phase Permanent Magnet Synchronous Motor

Multiphase machines have gained an increasing attention due to their more advantages in comparison with three-phase machines. In recent literatures, only voltage source inverters (VSIs) have been used to supply five-phase drives. Matrix converters (MCs) pose many advantages over conventional VSIs, such as lack of dc-bulk capacitors, high quality power output waveform and higher number of output voltages. Due to some special applications of multiphase machines such as ship propulsion and aerospace, the volume of these drives is an important challenging problem. As a consequence, using MCs can be a reasonable alternative. In this paper, a new direct torque control (DTC) algorithm using a three-to-five phase MC is proposed for five-phase permanent magnet synchronous motors (PMSMs). All of output voltage space vectors of three-to-five phase MC are extracted and a new switching table is proposed. Because of higher number of output voltages in MCs, there is a degree of freedom to control input power factor to keep close to unit moreover the torque and flux control. In other words, this proposed method use the advantages of both DTC method and MCs. Simulation results show the effectiveness of presented method in different operation modes

Optimum Design of a Five-phase Permanent Magnet Synchronous Motor for Underwater Vehicles by use of Particle Swarm Optimization

Permanent magnet synchronous motors are efficient motors which have widespread applications in electric industry due to their noticeable features. One of the interesting applications of such motors is in underwater vehicles. In these cases, reaching to minimum volume and high torque of the motor are the major concern. Design optimization can enhance their merits considerably, thus reduce volume and improve performance of motors. In this paper, a new method for optimum design of a five-phase surface-mounted permanent magnet synchronous motor is presented to achieve minimum loss and magnet volume with an increased torque. A multi-objective optimization is performed in search for optimum dimensions of the motor and its permanent magnets using particle swarm optimization. The design optimization results in a motor with great improvement regarding the original motor. Finally, finite element analysis is utilized to validate the accuracy of the design

A comparison between the effect of systemic and coated drug delivery in osteoporotic bone after dental implantation

The increased life expectancy has boomed the demand of dental implants in the elderly. As a consequence, considering the effect of poorer bone quality, due to aging or associated diseases such as osteoporosis, on the success of dental restoration is becoming increasingly important. Bisphosphonates are one of the most used drugs to overcome the effect of osteoporosis as they increase bone density. Bisphosphonates modify the physiological bone remodeling process by adhering to the bone surface, reducing the activity of osteoclasts. This study aims at comparing the effect on bone remodeling of two drug delivery methods of Bisphosphonates: local delivery by coating the implant surface and systemic delivery. A chemo-mechano-biological bone remodeling model validated in a previous paper was used here. The two drug delivery schemes were modeled by means of a finite element approach. In the systemic drug delivery case, the amount of drug that reaches the bone compartment was calculated using a pharmacokinetic model while in the local drug delivery system, the dose was calculated using Fickean diffusion. In particular, the effect of Zoledronate is studied here. The two drug delivery approaches are compared between them and with a control case with no drug. The results show that the use of Bisphosphonates increases the mechanical strength of bone, thus improving the implant fixation along time. Systemic drug delivery affects the entire skeleton, while local drug delivery only affects the area around the dental implant, which reduces the side effects of Bisphosphonates, such as increasing the mineral content, which may promote bone brittleness and microdamage far from the implant. These results support the conclusion that dental implants coated with Bisphosphonates can be a good solution for osteoporotic or low bone density patients without the long-term side effects of systemic drug delivery. © 202

Investigation of Interaction Hydrogen Sulfide with (5,0) and (5,5) Single-Wall Carbon Nanotubes by DFT Method

In the present study the interaction of Hydrogen Sulfide with inside and outside single-wall carbon nanotube of (5,0) and (5,5) was investigated. This study was conducted using DFT at B3LYP/6-31G* level of theory. Computational calculations were performed in the gaseous phase in Gaussian 09. The geometry of all molecules under investigation was determined by optimizing all geometrical variables without any symmetry constraints. The harmonic frequencies were computed from analytical derivatives for all species in order to define the minimum-energy structures. The adsorption energies, the thermodynamic properties, HOMO-LUMO energy gaps and partial charges of the interacting atoms were also studied during two rotation kinds of H2S molecules vertical and horizontal to the main axes of nanotube. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/3516

Micelle-Mediated Extraction and Cloud Point Pre-concentration for the Spectrophotometric Determination of Phenol in Water Samples

In this paper, a cloud point extraction method for the determination of trace amounts of phenol by spectrophotometry is described. The method is based on the colour reaction of phenol with diazotized p-nitroanilinean alkaline media and the cloud point extraction of azo dye product using of nonionic surfactant Triton X-114. The effects of reaction and extraction parameters were studied and optimum parameters were established. The calibration graph was linear in the range of 2.0–400 ng mL–1 of phenol. Detection limit based on three times the standard deviation of the blank (3Sb) was 1.0 ng mL–1 and the relative standard deviation (RSD) for 50 ng mL–1 of phenol was 1.73 % (n=10). The proposed method was applied for the determination of phenolin water samples.Keywords: Pre-concentration, cloud point extraction, phenol, spectrophotometry, water sample

A Link-Level Communication Analysis for Real-Time NoCs

This thesis presents a link-level latency analysis for real-time network-on-chip interconnects that use priority-based wormhole switching. This analysis incorporates both direct and indirect interferences from other traffic flows, and it leverages pipelining and parallel transmission of data across the links. The resulting link-level analysis provides a tighter worst-case upper-bound than existing techniques, which we verify with our analysis and simulation experiments. Our experiments show that on average, link-level analysis reduces the worst-case latency by 28.8%, and improves the number of flows that are schedulable by 13.2% when compared to previous work

The Frequency of Urinary Tract Infection among Children with Febrile Convulsion

ObjectiveThis study was conducted to determine the frequency of urinary tract infection(UTI) among children with febrile convulsion (FC).Materials & MethodsWe analyzed the hospital records of 137 children who had been admitted to thepediatric ward from March 2004 to February 2007 because of FC. Informationsuch as age, sex, developmental status, type of FC, family history of seizure,urine sampling method, and the results of antibiograms were recorded.ResultsThe age distribution of 137 patients (82 boys, 55 girls) was as follows: 1-6 monthsof age, 1 infant (0.7%); 6-12 months, 21 infants (15.3%); 1-3 years, 75 (54.8%);3-5 years, 30 (21.9%); and more than 5 years, 10 (7.3%). Three out of the 82boys and 6 out of the 55 girls had UTI (3.7% vs. 10.9%, total, 6.6%). The agedistribution of these 9 patients was as follows: 1-6 months, 1 patient (11.1%);7-12 months, 5 (55.6%); and 1-3 years, 3 (33.3%). The relative incidence of UTIwas 6.6%. The most common organisms causing infections were Escherichiacoli in 8 and Proteus spp., in 1 patient (88.8% vs. 11.1%). Simple FC was seenin all 9 patients with UTI.ConclusionIn this study, the relative frequency of UTI among children with FC was 6.6%and this frequency was higher that the incidence of UTI in girls and boys(3-5% and 1%, respectively). Therefore, we recommend that UTI should beconsidered as an important cause of FC in children.Keywords: Febrile convulsion; urinary tract infection; children  

Logging Statements Analysis and Automation in Software Systems with Data Mining and Machine Learning Techniques

Log files are widely used to record runtime information of software systems, such as the timestamp of an event, the name or ID of the component that generated the log, and parts of the state of a task execution. The rich information of logs enables system developers (and operators) to monitor the runtime behavior of their systems and further track down system problems in development and production settings. With the ever-increasing scale and complexity of modern computing systems, the volume of logs is rapidly growing. For example, eBay reported that the rate of log generation on their servers is in the order of several petabytes per day in 2018 [17]. Therefore, the traditional way of log analysis that largely relies on manual inspection (e.g., searching for error/warning keywords or grep) has become an inefficient, a labor intensive, error-prone, and outdated task. The growth of the logs has initiated the emergence of automated tools and approaches for log mining and analysis. In parallel, the embedding of logging statements in the source code is a manual and error-prone task, and developers often might forget to add a logging statement in the software's source code. To address the logging challenge, many e orts have aimed to automate logging statements in the source code, and in addition, many tools have been proposed to perform large-scale log le analysis by use of machine learning and data mining techniques. However, the current logging process is yet mostly manual, and thus, proper placement and content of logging statements remain as challenges. To overcome these challenges, methods that aim to automate log placement and content prediction, i.e., `where and what to log', are of high interest. In addition, approaches that can automatically mine and extract insight from large-scale logs are also well sought after. Thus, in this research, we focus on predicting the log statements, and for this purpose, we perform an experimental study on open-source Java projects. We introduce a log-aware code-clone detection method to predict the location and description of logging statements. Additionally, we incorporate natural language processing (NLP) and deep learning methods to further enhance the performance of the log statements' description prediction. We also introduce deep learning based approaches for automated analysis of software logs. In particular, we analyze execution logs and extract natural language characteristics of logs to enable the application of natural language models for automated log le analysis. Then, we propose automated tools for analyzing log files and measuring the information gain from logs for different log analysis tasks such as anomaly detection. We then continue our NLP-enabled approach by leveraging the state-of-the-art language models, i.e., Transformers, to perform automated log parsing