Comparative performance of modular with cascaded H-bridge three level inverters

The conventional two-level inverter becomes no longer has the ability to cope with the high-power requirement, so this paper discusses two very common topologies of multilevel inverter like modular multi-level converter (MMC) and cascaded H-bridge (CHB) multi-level inverter for induction motor drive applications. This work attempts to investigate the comparison between MMC and CHB. The comparison is done in aspects of the configuration, concept of operation, advantages and disadvantages, the comparison is also consider output voltage (line to line) waveform, total harmonic distortion (THD) of the output line voltage waveform and the current drawn by both inverters. The performance of the inverters under carrier-based pulse width modulation (PWM) technique and mainly in-phase disposition (IPD), level shifted pulse width modulation is viewed. The paper discusses the comparison between the two multilevel inverters (MLIs) with motor drive applications especially induction motor. The operation of the motor is studied under certain value of load torque. The simulation results for the induction motor with the two inverters (modular multi-level and Cascaded H-bride) for three numbers of levels using MATLAB/Simulink are provided). The obtained results are encouraging and promising especially in the improvement of the THD% results

Enhanced transformer long short-term memory framework for datastream prediction

In machine learning, datastream prediction is a challenging issue, particularly when dealing with enormous amounts of continuous data. The dynamic nature of data makes it difficult for traditional models to handle and sustain real-time prediction accuracy. This research uses a multi-processor long short-term memory (MPLSTM) architecture to present a unique framework for datastream regression. By employing several central processing units (CPUs) to divide the datastream into multiple parallel chunks, the MPLSTM framework illustrates the intrinsic parallelism of long short-term memory (LSTM) networks. The MPLSTM framework ensures accurate predictions by skillfully learning and adapting to changing data distributions. Extensive experimental assessments on real-world datasets have demonstrated the clear superiority of the MPLSTM architecture over previous methods. This study uses the transformer, the most recent deep learning breakthrough technology, to demonstrate how well it can handle challenging tasks and emphasizes its critical role as a cutting-edge approach to raising the bar for machine learning

A framework for utilizing unexplored game elements in designing learning systems

Gamification is defined as the use of game elements and designs in non-gaming areas and applications such as education, marketing, and healthcare. That is to facilitate and develop the engagement of users with a product or service. Researchers have found that gamified learning has the ability to improve student success, interaction, and enjoyment of courses. Recently, researchers suggested that one way to achieve that is through the personalization of students’ experiences. However, research has been focusing on a narrow group of game elements which does not ensure equal consideration when designing for different personality types. In this paper, our aim is threefold that is: to identify the unexplored game elements in the learning domain to ensure equal experiences for different personality traits; to study the utilization of the identified unexplored elements and how they can be used in relation with different personality types and learning styles to make learning tasks more desirable and enjoyable; to inform and enrich the design of gamified e-learning systems. To achieve that aim, we analyzed the literature to identify the unexplored game elements, conducted a focus group study to examine the utilization of unexplored game elements along with other contextual aspects. Then to formalize the results reached from our study and provide more systematic means for software engineers to extract useful information that can inform their designs, an ontology was implemented for that purpose. Finally, an existing gamified e-learning framework was adapted to illustrate how the formed artifacts and models interrelate to realize the research aim.</span

Indoor Radon Concentration Measurement in Selected Factories in Northern and Central Iraq

In this work, the outdoor radon concentration level and lung cancer risks have been measured in selected locations in northern and central Iraq during the summer season 2012 by using time integrated passive radon dosimeters containing LR-115 Type II plastic track detectors. These measurements were carried out in the factories for an exposure time of 60 day. The radon concentration in these factories ranges from (36.36 – 125.10) Bq.m-3 with an average of (59.93Bq.m-3), which within the acceptable radon levels (50-150) Bq.m-3 recommended by the International Commission on Radiological Protection (ICRP). The average absorption effective dose equivalent for a person living in factories for which the investigation were done was found to be (1.425mSv.y-1). It is observed that the average lung cancer per year per 106 person was found to be 25.654. Keyword: LR-115 Type II nuclear track detectors; Radon concentration; AEDE; PAEC

The Effect of Strontium Ranelate Gel on Bone Formation in Calvarial Critical Size Defects

AIM: The current study was designed to investigate the effectiveness of locally applied Strontium ranelate to induce bone formation.MATERIALS AND METHODS: Forty-eight female rats were divided into six groups (eight rats in each group): The three test groups included Strontium (SR) 2.5 mg, 5 mg and 10 mg that was dissolved in methylcellulose gel. The control groups included methylcellulose, simvastatin 5 mg and a negative control where the defect was left to heal without any intervention. At 44 days the groups were sacrificed, and the bone defects were assessed histomorphometically to assess bone formation. The data was statistically analysed.RESULTS: There was a statistically significant difference in the amount of new bone formation between all groups, where the 2.5 mg SR group showed the highest median bone percentage, is 41.95 %, followed by the 5, and 10 mg SR demonstrating a median bone are a percentage of 39.89%, and 30.19% respectively. Simvastatin showed a median bone percentage of 36.07 %, while the methylcellulose and the negative control groups demonstrated the lowest median area percentage of 23.12 and 20.70 % respectively.CONCLUSIONS: The study showed that the local application of an SR could up-regulate the bone formation and may prove to be a cost-effective method of bone regeneration

Local Revenue Development in Egypt / الإيرادات المحلية في مصر

Local administration in Egypt faces several challenges that hinder fulfilling its responsibilities towards citizens sufficiently. The main challenges are the lack of financial resources due to over-regulation as well as the non-enforcement of laws and regulations that allow the local administration to collect its own tax share, the local administration staff’s lack of skills to manage and develop revenue sources, and lack of accountability mechanisms. This policy paper seeks to propose policies to aid the local administration in increasing its financial resources. In this paper, the authors depended on desk research as well as interviews held with officials from the Ministry of Finance and the Ministry of Local Development. Based on the information gathered, the authors proposed three policy options. Finally, they selected the “Local Non-Tax Revenue Mobilization” policy option based on the evaluation criteria and provided recommendations for this policy’s successful implementation

Micro-structural Auditory Pathway Changes in Patients with Sensorineural Hearing Loss with or without Tinnitus, could diffusion tensor imaging be valuable?

Background: Advanced magnetic resonance imaging (MRI) technique called diffusion tensor imaging (DTI) can assess tissue microstructure. It's challenging to identify sensorineural hearing loss (SNHL) cause suing CT or MRI without significant gross disruption. Objectives: to assess microstructural integrity of auditory neural pathway SNHL patients with or without tinnitus by DTI. Patients and methods: This prospective, case-control study included 55 subjects in three groups: 30 healthy volunteers in control group (GI), 12 patients in bilateral SNHL without tinnitus group (GII), and 13 patients in bilateral SNHL with tinnitus group (GIII) were MRI-assessed using 1.5 Tesla GE machine. Ordinary one-way ANOVA test was used to compare groups with normal distributions, Kroskal Wallis test: compares groups with abnormally distributed data; post-hoc test: determines significance between pairs. Results: ANOVA test revealed statistically significant difference at Lateral lemniscus(LL), Inferior colliculus(IC), medial geniculate body (MGB), auditory radiation(AR), Superior temporal gyrus(STG), Hippocampus, amygdala, Superior longitudinal fasciculus(SLF), genu and splenium of corpus callosum (CC) with P value ≤0.05. Post-hoc test: group II had lower FA comparing to group I at LL, MGB, IC, AR, STG, genu and splenium of CC. In group III the forementioned regions were affected besides hippocampus and amygdala. Group III had statistically significant lower FA values compared to group II at LL, IC, MGB, hippocampus, amygdala, SLF, genu and splenium of CC. Conclusion: Using DTI to assess microstructural integrity of auditory pathway, SNHL is associated with white matter microstructure affection as proved by the current study, and presence of tinnitus is associated with limbic system affection

Drone deep reinforcement learning: A review

Unmanned Aerial Vehicles (UAVs) are increasingly being used in many challenging and diversified applications. These applications belong to the civilian and the military fields. To name a few; infrastructure inspection, traffic patrolling, remote sensing, mapping, surveillance, rescuing humans and animals, environment monitoring, and Intelligence, Surveillance, Target Acquisition, and Reconnaissance (ISTAR) operations. However, the use of UAVs in these applications needs a substantial level of autonomy. In other words, UAVs should have the ability to accomplish planned missions in unexpected situations without requiring human intervention. To ensure this level of autonomy, many artificial intelligence algorithms were designed. These algorithms targeted the guidance, navigation, and control (GNC) of UAVs. In this paper, we described the state of the art of one subset of these algorithms: the deep reinforcement learning (DRL) techniques. We made a detailed description of them, and we deduced the current limitations in this area. We noted that most of these DRL methods were designed to ensure stable and smooth UAV navigation by training computer-simulated environments. We realized that further research efforts are needed to address the challenges that restrain their deployment in real-life scenarios

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London