Artificial neural networks and their applications to intelligent fault diagnosis of power transmission lines

Over the past thirty years, the idea of computing based on models inspired by human brains and biological neural networks emerged. Artificial neural networks play an important role in the field of machine learning and hold the key to the success of performing many intelligent tasks by machines. They are used in various applications such as pattern recognition, data classification, stock market prediction, aerospace, weather forecasting, control systems, intelligent automation, robotics, and healthcare. Their architectures generally consist of an input layer, multiple hidden layers, and one output layer. They can be implemented on software or hardware. Nowadays, various structures with various names exist for artificial neural networks, each of which has its own particular applications. Those used types in this study include feedforward neural networks, convolutional neural networks, and general regression neural networks. Increasing the number of layers in artificial neural networks as needed for large datasets, implies increased computational expenses. Therefore, besides these basic structures in deep learning, some advanced techniques are proposed to overcome the drawbacks of original structures in deep learning such as transfer learning, federated learning, and reinforcement learning. Furthermore, implementing artificial neural networks in hardware gives scientists and engineers the chance to perform high-dimensional and big data-related tasks because it removes the constraints of memory access time defined as the von Neuman bottleneck. Accordingly, analog and digital circuits are used for artificial neural network implementations without using general-purpose CPUs. In this study, the problem of fault detection, identification, and location estimation of transmission lines is studied and various deep learning approaches are implemented and designed as solutions. This research work focuses on the transmission lines’ datasets, their faults, and the importance of identification, detection, and location estimation of them. It also includes a comprehensive review of the previous studies to perform these three tasks. The application of various artificial neural networks such as feedforward neural networks, convolutional neural networks, and general regression neural networks for identification, detection, and location estimation of transmission line datasets are also discussed in this study. Some advanced methods based on artificial neural networks are taken into account in this thesis such as the transfer learning technique. These methodologies are designed and applied on transmission line datasets to enable the scientist and engineers with using fewer data points for the training purpose and wasting less time on the training step. This work also proposes a transfer learning-based technique for distinguishing faulty and non-faulty insulators in transmission line images. Besides, an effective design for an activation function of the artificial neural networks is proposed in this thesis. Using hyperbolic tangent as an activation function in artificial neural networks has several benefits including inclusiveness and high accuracy

Adolescent transport and unintentional injuries: a systematic analysis using the Global Burden of Disease Study 2019

Background: Globally, transport and unintentional injuries persist as leading preventable causes of mortality and morbidity for adolescents. We sought to report comprehensive trends in injury-related mortality and morbidity for adolescents aged 10–24 years during the past three decades. Methods: Using the Global Burden of Disease, Injuries, and Risk Factors 2019 Study, we analysed mortality and disability-adjusted life-years (DALYs) attributed to transport and unintentional injuries for adolescents in 204 countries. Burden is reported in absolute numbers and age-standardised rates per 100 000 population by sex, age group (10–14, 15–19, and 20–24 years), and sociodemographic index (SDI) with 95% uncertainty intervals (UIs). We report percentage changes in deaths and DALYs between 1990 and 2019. Findings: In 2019, 369 061 deaths (of which 214 337 [58%] were transport related) and 31·1 million DALYs (of which 16·2 million [52%] were transport related) among adolescents aged 10–24 years were caused by transport and unintentional injuries combined. If compared with other causes, transport and unintentional injuries combined accounted for 25% of deaths and 14% of DALYs in 2019, and showed little improvement from 1990 when such injuries accounted for 26% of adolescent deaths and 17% of adolescent DALYs. Throughout adolescence, transport and unintentional injury fatality rates increased by age group. The unintentional injury burden was higher among males than females for all injury types, except for injuries related to fire, heat, and hot substances, or to adverse effects of medical treatment. From 1990 to 2019, global mortality rates declined by 34·4% (from 17·5 to 11·5 per 100 000) for transport injuries, and by 47·7% (from 15·9 to 8·3 per 100 000) for unintentional injuries. However, in low-SDI nations the absolute number of deaths increased (by 80·5% to 42 774 for transport injuries and by 39·4% to 31 961 for unintentional injuries). In the high-SDI quintile in 2010–19, the rate per 100 000 of transport injury DALYs was reduced by 16·7%, from 838 in 2010 to 699 in 2019. This was a substantially slower pace of reduction compared with the 48·5% reduction between 1990 and 2010, from 1626 per 100 000 in 1990 to 838 per 100 000 in 2010. Between 2010 and 2019, the rate of unintentional injury DALYs per 100 000 also remained largely unchanged in high-SDI countries (555 in 2010 vs 554 in 2019; 0·2% reduction). The number and rate of adolescent deaths and DALYs owing to environmental heat and cold exposure increased for the high-SDI quintile during 2010–19. Interpretation: As other causes of mortality are addressed, inadequate progress in reducing transport and unintentional injury mortality as a proportion of adolescent deaths becomes apparent. The relative shift in the burden of injury from high-SDI countries to low and low–middle-SDI countries necessitates focused action, including global donor, government, and industry investment in injury prevention. The persisting burden of DALYs related to transport and unintentional injuries indicates a need to prioritise innovative measures for the primary prevention of adolescent injury. Funding: Bill & Melinda Gates Foundation

Global, regional, and national mortality among young people aged 10-24 years, 1950-2019: a systematic analysis for the Global Burden of Disease Study 2019

Background Documentation of patterns and long-term trends in mortality in young people, which reflect huge changes in demographic and social determinants of adolescent health, enables identification of global investment priorities for this age group. We aimed to analyse data on the number of deaths, years of life lost, and mortality rates by sex and age group in people aged 10-24 years in 204 countries and territories from 1950 to 2019 by use of estimates from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. Methods We report trends in estimated total numbers of deaths and mortality rate per 100 000 population in young people aged 10-24 years by age group (10-14 years, 15-19 years, and 20-24 years) and sex in 204 countries and territories between 1950 and 2019 for all causes, and between 1980 and 2019 by cause of death. We analyse variation in outcomes by region, age group, and sex, and compare annual rate of change in mortality in young people aged 10-24 years with that in children aged 0-9 years from 1990 to 2019. We then analyse the association between mortality in people aged 10-24 years and socioeconomic development using the GBD Socio-demographic Index (SDI), a composite measure based on average national educational attainment in people older than 15 years, total fertility rate in people younger than 25 years, and income per capita. We assess the association between SDI and all-cause mortality in 2019, and analyse the ratio of observed to expected mortality by SDI using the most recent available data release (2017). Findings In 2019 there were 1.49 million deaths (95% uncertainty interval 1.39-1.59) worldwide in people aged 10-24 years, of which 61% occurred in males. 32.7% of all adolescent deaths were due to transport injuries, unintentional injuries, or interpersonal violence and conflict; 32.1% were due to communicable, nutritional, or maternal causes; 27.0% were due to non-communicable diseases; and 8.2% were due to self-harm. Since 1950, deaths in this age group decreased by 30.0% in females and 15.3% in males, and sex-based differences in mortality rate have widened in most regions of the world. Geographical variation has also increased, particularly in people aged 10-14 years. Since 1980, communicable and maternal causes of death have decreased sharply as a proportion of total deaths in most GBD super-regions, but remain some of the most common causes in sub-Saharan Africa and south Asia, where more than half of all adolescent deaths occur. Annual percentage decrease in all-cause mortality rate since 1990 in adolescents aged 15-19 years was 1.3% in males and 1.6% in females, almost half that of males aged 1-4 years (2.4%), and around a third less than in females aged 1-4 years (2.5%). The proportion of global deaths in people aged 0-24 years that occurred in people aged 10-24 years more than doubled between 1950 and 2019, from 9.5% to 21.6%. Interpretation Variation in adolescent mortality between countries and by sex is widening, driven by poor progress in reducing deaths in males and older adolescents. Improving global adolescent mortality will require action to address the specific vulnerabilities of this age group, which are being overlooked. Furthermore, indirect effects of the COVID-19 pandemic are likely to jeopardise efforts to improve health outcomes including mortality in young people aged 10-24 years. There is an urgent need to respond to the changing global burden of adolescent mortality, address inequities where they occur, and improve the availability and quality of primary mortality data in this age group. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd

Global, regional, and national progress towards Sustainable Development Goal 3.2 for neonatal and child health: all-cause and cause-specific mortality findings from the Global Burden of Disease Study 2019

Background Sustainable Development Goal 3.2 has targeted elimination of preventable child mortality, reduction of neonatal death to less than 12 per 1000 livebirths, and reduction of death of children younger than 5 years to less than 25 per 1000 livebirths, for each country by 2030. To understand current rates, recent trends, and potential trajectories of child mortality for the next decade, we present the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 findings for all-cause mortality and cause-specific mortality in children younger than 5 years of age, with multiple scenarios for child mortality in 2030 that include the consideration of potential effects of COVID-19, and a novel framework for quantifying optimal child survival. Methods We completed all-cause mortality and cause-specific mortality analyses from 204 countries and territories for detailed age groups separately, with aggregated mortality probabilities per 1000 livebirths computed for neonatal mortality rate (NMR) and under-5 mortality rate (USMR). Scenarios for 2030 represent different potential trajectories, notably including potential effects of the COVID-19 pandemic and the potential impact of improvements preferentially targeting neonatal survival. Optimal child survival metrics were developed by age, sex, and cause of death across all GBD location-years. The first metric is a global optimum and is based on the lowest observed mortality, and the second is a survival potential frontier that is based on stochastic frontier analysis of observed mortality and Healthcare Access and Quality Index. Findings Global U5MR decreased from 71.2 deaths per 1000 livebirths (95% uncertainty interval WI] 68.3-74-0) in 2000 to 37.1 (33.2-41.7) in 2019 while global NMR correspondingly declined more slowly from 28.0 deaths per 1000 live births (26.8-29-5) in 2000 to 17.9 (16.3-19-8) in 2019. In 2019,136 (67%) of 204 countries had a USMR at or below the SDG 3.2 threshold and 133 (65%) had an NMR at or below the SDG 3.2 threshold, and the reference scenario suggests that by 2030,154 (75%) of all countries could meet the U5MR targets, and 139 (68%) could meet the NMR targets. Deaths of children younger than 5 years totalled 9.65 million (95% UI 9.05-10.30) in 2000 and 5.05 million (4.27-6.02) in 2019, with the neonatal fraction of these deaths increasing from 39% (3.76 million 95% UI 3.53-4.021) in 2000 to 48% (2.42 million; 2.06-2.86) in 2019. NMR and U5MR were generally higher in males than in females, although there was no statistically significant difference at the global level. Neonatal disorders remained the leading cause of death in children younger than 5 years in 2019, followed by lower respiratory infections, diarrhoeal diseases, congenital birth defects, and malaria. The global optimum analysis suggests NMR could be reduced to as low as 0.80 (95% UI 0.71-0.86) deaths per 1000 livebirths and U5MR to 1.44 (95% UI 1-27-1.58) deaths per 1000 livebirths, and in 2019, there were as many as 1.87 million (95% UI 1-35-2.58; 37% 95% UI 32-43]) of 5.05 million more deaths of children younger than 5 years than the survival potential frontier. Interpretation Global child mortality declined by almost half between 2000 and 2019, but progress remains slower in neonates and 65 (32%) of 204 countries, mostly in sub-Saharan Africa and south Asia, are not on track to meet either SDG 3.2 target by 2030. Focused improvements in perinatal and newborn care, continued and expanded delivery of essential interventions such as vaccination and infection prevention, an enhanced focus on equity, continued focus on poverty reduction and education, and investment in strengthening health systems across the development spectrum have the potential to substantially improve USMR. Given the widespread effects of COVID-19, considerable effort will be required to maintain and accelerate progress. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd

CMOS BASED IMPLEMENTATION OF HYPERBOLIC TANGENT ACTIVATION FUNCTION FOR ARTIFICIAL NEURAL NETWORK

FATEMEH MOHAMMADI SHAKIBA, for the Master of Science degree in MAJOR Electrical and Computer Engineering, presented on 4/11/2018, at Southern Illinois Uni- versity Carbondale. TITLE: CMOS BASED IMPLEMENTATION OF HYPERBOLIC TANGENT ACTIVA- TION FUNCTION FOR ARTIFICIAL NEURAL NETWORK MAJOR PROFESSOR: Dr.Spyros Tragoudas In this thesis, an efficient implementation for the established hyperbolic tangent acti- vation function is proposed. The efficiency of this design is considered in multiple aspects such as power consumption, simplicity of implementing, compatibility with different designs and accuracy. Considering all of these parameters, CMOS technology is chosen to be used for its implementation. This activation function is designed to resemble its mathematical definition, to reach the highest possible extent. Existing CMOS-based designs for hyperbolic tangent activation function is either power consuming for satisfying a reliable accuracy, or not compatible with both digital and ana- log circuits. Hence, we tried to implement a super fast, low power design to solve these problems. We experimented the shallow and deep neural networks with various parameters for two image processing open datasets, the MNIST and notMNIST with more than 60000 images, to present the classification accuracy of the proposed design. [5, 8] This activation function is suited for current based artificial neural networks architectures. According to symmetry feature of hyperbolic tangent function, we proposed a tricky method to have a very small circuit to simulate just half of the function, which is much faster and needs less power than existing circuits that produce a complete form of hyperbolic tangent

Decentralized Model-Predictive Control of a Coupled Wind Turbine and Diesel Engine Generator System

It is highly critical that renewable energy-based power generation units provide continuous and high-quality electricity. This requirement is even more pronounced in standalone wind–diesel systems where the wind power is not always constant or available. Moreover, it is desired that the extracted power be maximized in such a way that less fuel is consumed from the diesel engine. This paper proposes a novel method to design decentralized model-predictive controllers to control the frequency and power of a single standalone generation system, which consists of a wind turbine subsystem mechanically coupled with a diesel engine generator subsystem. Two decentralized model-predictive controllers are designed to regulate the frequency and active power, while the mechanical coupling between the two subsystems is considered, and no communication links exist between the two controllers. Simulation results show that the proposed decentralized controllers outperform the benchmark decentralized linear-quadratic Gaussian (LQG) controllers in terms of eliminating the disturbances from the wind and load power changes. Furthermore, it is demonstrated that the proposed control strategy has an acceptable robust performance against the concurrent variations in all parameters of the system as compared to the LQG controllers

Effect of dextromethorphan in the mouse forced swim and tail suspension tests: Evidence for involvement of the alpha receptors

Depression is a state of low mood that can seriously affect the quality of life of society. Therefore, finding new antidepressant agents with high efficacy is needed. Dextromethorphan (DXM) is an antitussive drug that has a potential effect on treating mood disorders, especially depression. However, because of limited data that relies on a few experimental animal studies mechanisms of action are yet not clear. The present study investigated the DXM effect in the forced swimming (FST) and tail suspension (TST) tests in mice and also the potential influence of the noradrenergic system in this effect. DXM (30 mg/kg, intraperitoneal (i.p.)) significantly decreased the immobility times in FST (P < 0.001) and TST (P < 0.01) comparable with positive controls, imipramine (IMI) 10 mg/kg and fluoxetine (20 mg/kg). Nevertheless, the number of crossings in the openfield test was not affected. The pretreatment with prazosin (1 mg/kg, i.p.; alpha 1-adrenoceptor antagonist) or yohimbine (1 mg/kg, i.p.; alpha 2-adrenoceptor antagonist) prevented the antidepressant effect of DXM (30 mg/kg, i.p). Moreover, the administration of a sub-effective dose of phenylephrine (5 mg/kg, i.p.; alpha 1-adrenoceptor agonist) or clonidine (0.06 mg/kg, i.p.; alpha 2-adrenoceptor agonist) potentiated the sub-effective dose of DXM (3 mg/kg, i.p.) in the FST and TST. The pretreatment with propranolol (5 mg/kg, i.p.; beta-adrenoceptor antagonist) did not reverse the antidepressant-like effect of DXM. Thus, the present study suggests that the antidepressant-like effect of DXM may be partially related to alpha 1/alpha 2 adrenoceptors

One-year prevalence and the association between SARS-CoV-2 cycle threshold, comorbidity and outcomes in population of Babol, North of Iran (2020-2021).

Background: The present study aimed to investigate the one-year prevalence of SARS-CoV-2, common comorbidities and demographic information among negative- and positive rRT-PCR in health care workers (HCW), hospitalized and outpatients. Also, the association between SARS-CoV-2 cycle threshold (Ct) and the outcomes of patients were analyzed in Babol, northern Iran. Methods: This large&#160;retrospective cross-sectional study was performed between March 2020 and March 2021. The records of 19232 hospitalized, outpatients and HCW suspected to COVID-19 were collected from teaching hospitals in the North of Iran. Results: Out of the 19232 suspected to COVID-19 patients, 7251 (37.7) had a positive rRT-PCR result; 652 (9), 4599 (63.4) and 2000 (27.6) of those were categorized as HCW, hospitalized and outpatients, respectively. Moreover, between the hospitalized and the outpatient group, 10.2 and 0.8 cases died, whereas no death cases were reported in the HCW. Furthermore, it seems that death rate was significantly different between the three groups of Ct value, the highest mortality in those with Ct between 21 and 30 (group B=7.6) and the lowest in the group with the highest Ct (between 31 and 40 = 5.5) (p&#60;0.001). Conclusion: In summary, 37.7 of cases were positive for SARS-CoV-2; of which, 63.4, 27.6 and 9 were hospitalized, outpatients and HCW, respectively. With regard to the mortality rate in hospitalized patients and the significant association with Ct under 20 and 30, it seems that the early detection and the initial quantification of SARS-CoV-2 in the first week of the conflict and therapeutic considerations to reduce the relative load can reduce the mortality rate

Prevalence of elimination disorders and comorbid psychiatric disorders in Iranian children and adolescents

PURPOSE: Currently, there is a paucity of studies on the prevalence of Elimination Disorders among Iranian children and adolescents. Due to the ongoing need to monitor the health status of these children and adolescents, the present study aims to investigate the prevalence of Elimination Disorders and comorbid disorders in Iranian children and adolescents. METHODS: In this cross-sectional study, 29,781 children and adolescents age 6 to 18 years old were selected and studied from all the provinces in Iran. The sampling was carried out by employing a multistage cluster sampling method, and several clinical psychologists using semi-structured interviews collected the data. Furthermore, clinical psychologists collected demographic information (including information about gender, age, place of residence, education level, and parental education level). The collected data were analyzed using SPSS version 20. RESULTS: Generally, the prevalence of Elimination Disorders was found to be 5.4% covering both enuresis (p = 5.4, 95% CI = 5.1-5.7) and encopresis (p = 0.13, 95% CI = 0.09-0.2). The total prevalence of comorbid disorders was 38%, and among the comorbid disorders, Attention Deficit Hyperactivity Disorder (ADHD) (p = 11, 95% CI = 9.5-12.7) and Separation Anxiety (p = 10.6, 95% CI = 9.1-12.2) were the most prevalent. CONCLUSION: The prevalence of Elimination Disorders in Iranian children and adolescents is moderate compared to similar studies elsewhere. As for comorbid disorders, ADHD and Separation Anxiety were found to be the most prevalent disorders. Since Elimination Disorders coexist with psychiatric disorders in children, further studies of these comorbidities may give better insight into the treatment and prognosis of Elimination Disorders

Global, regional, and national progress towards Sustainable Development Goal 3.2 for neonatal and child health : all-cause and cause-specific mortality findings from the Global Burden of Disease Study 2019

Background Sustainable Development Goal 3.2 has targeted elimination of preventable child mortality, reduction of neonatal death to less than 12 per 1000 livebirths, and reduction of death of children younger than 5 years to less than 25 per 1000 livebirths, for each country by 2030. To understand current rates, recent trends, and potential trajectories of child mortality for the next decade, we present the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 findings for all-cause mortality and cause-specific mortality in children younger than 5 years of age, with multiple scenarios for child mortality in 2030 that include the consideration of potential effects of COVID-19, and a novel framework for quantifying optimal child survival. Methods We completed all-cause mortality and cause-specific mortality analyses from 204 countries and territories for detailed age groups separately, with aggregated mortality probabilities per 1000 livebirths computed for neonatal mortality rate (NMR) and under-5 mortality rate (USMR). Scenarios for 2030 represent different potential trajectories, notably including potential effects of the COVID-19 pandemic and the potential impact of improvements preferentially targeting neonatal survival. Optimal child survival metrics were developed by age, sex, and cause of death across all GBD location-years. The first metric is a global optimum and is based on the lowest observed mortality, and the second is a survival potential frontier that is based on stochastic frontier analysis of observed mortality and Healthcare Access and Quality Index. Findings Global U5MR decreased from 71.2 deaths per 1000 livebirths (95% uncertainty interval WI] 68.3-74-0) in 2000 to 37.1 (33.2-41.7) in 2019 while global NMR correspondingly declined more slowly from 28.0 deaths per 1000 live births (26.8-29-5) in 2000 to 17.9 (16.3-19-8) in 2019. In 2019,136 (67%) of 204 countries had a USMR at or below the SDG 3.2 threshold and 133 (65%) had an NMR at or below the SDG 3.2 threshold, and the reference scenario suggests that by 2030,154 (75%) of all countries could meet the U5MR targets, and 139 (68%) could meet the NMR targets. Deaths of children younger than 5 years totalled 9.65 million (95% UI 9.05-10.30) in 2000 and 5.05 million (4.27-6.02) in 2019, with the neonatal fraction of these deaths increasing from 39% (3.76 million [95% UI 3.53-4.021) in 2000 to 48% (2.42 million; 2.06-2.86) in 2019. NMR and U5MR were generally higher in males than in females, although there was no statistically significant difference at the global level. Neonatal disorders remained the leading cause of death in children younger than 5 years in 2019, followed by lower respiratory infections, diarrhoeal diseases, congenital birth defects, and malaria. The global optimum analysis suggests NMR could be reduced to as low as 0.80 (95% UI 0.71-0.86) deaths per 1000 livebirths and U5MR to 1.44 (95% UI 1-27-1.58) deaths per 1000 livebirths, and in 2019, there were as many as 1.87 million (95% UI 1-35-2.58; 37% [95% UI 32-43]) of 5.05 million more deaths of children younger than 5 years than the survival potential frontier. Interpretation Global child mortality declined by almost half between 2000 and 2019, but progress remains slower in neonates and 65 (32%) of 204 countries, mostly in sub-Saharan Africa and south Asia, are not on track to meet either SDG 3.2 target by 2030. Focused improvements in perinatal and newborn care, continued and expanded delivery of essential interventions such as vaccination and infection prevention, an enhanced focus on equity, continued focus on poverty reduction and education, and investment in strengthening health systems across the development spectrum have the potential to substantially improve USMR. Given the widespread effects of COVID-19, considerable effort will be required to maintain and accelerate progress. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.Peer reviewe