Induction Motor Faults and Artificial Intelligence Based Conditioning and Monitoring Techniques

Three phase induction motors have been intensively utilized in industrial applications, mainly due to their efficiency and reliability. These motors have good properties such as increased stability, robustness, durability, large power to weight ratio, low production costs and controllability easiness. All machines realize various stresses during operational conditions. These stresses might lead to some modes of failures or faults. Condition monitoring is necessary in order to prevent faults. These faults, are necessary to be identi?ed and categorized, as soon as possible as they can end up in serious damages if not detected in due time. Different techniques of fault monitoring for induction motors are broadly classified as techniques based on model, signal processing, and soft computing. In recent years the monitoring and fault detection of electrical machines have moved from traditional techniques to Artificial Intelligence (AI). In this paper an attempt has been made to review different faults on induction motors and the applications of neural/fuzzy artificial intelligence techniques for induction motor condition monitoring. A brief description of various AI techniques highlighting the merits and demerits of each has been discussed. The futuristic trends on condition monitoring of induction motors are also indicated

Hand Gesture Recognition Using Backpropogation Algorithm Based on Neural Network

The proposed system is design for physically challenged people to communicate among common people without an intermediate human translator. The system based on hand gesture recognition using neural network. We used back propogation algorithm for the recognition of image. Some of the systems are used for the purpose of communication are costly and bulky that the common man can not afford but system we are going to used is affordable so it is possible to minimize the distance between hearing and speech impaired people with normal human being. The image is captured with the help of inbuilt camera of laptop comparing with the existing database using matlab and further it will process in neural network accordingly gives the output in the form of text along with the accuracy in percentage. Firstly the prepocessing steps are completed. The steps going to perfom are image aquisiton, image processing, feature extraction, gesture identification and finally output translated in text. We calculate the centroid of the hand image called as vectorization which will futher train our neural network and after processing we get output. DOI: 10.17762/ijritcc2321-8169.15076

Implementing UPQC based Intelligent Islanding for the Microgrid System

Increased penetration of small scale renewable energy sources in the electrical distribution network, improvement of power quality has become more critical than where the current harmonics or disturbances and level of voltage can vary widely. For this reason, Custom Power Devices (CPDs) such as the Unified Power Quality Conditioner (UPQC) can be the most appropriate solution used for improving the dynamic performance of the distribution network, where accurate prior knowledge may not be available. Therefore, the main objectives are (i) placement (ii) integration (iii) capacity enhancement and (iv) real time control of the Unified Power Quality Conditioner (UPQC) to improve the power quality of a distributed generation (DG) network connected to the grid or microgrid. A new integration method of the UPQC has been developed: helps to the DGs to deliver quality of power in the case of islanding and help to reintegrate with the grid seamlessly post fault. It perform both control operation such as Detection of Islanding and reconnection techniques, hence, it is termed UPQC?G. The DG Inverter with storage supplies the active fundamental power only and the shunt part of the UPQC compensates the reactive and harmonic power of the load during both interconnected and islanding mode

CAN Based Hotel Management System

Everyday life is getting easier with technology and automation.This paper aims at providing automation in restaurants in order to serve foods direct to customer table automatically without waiter. The customer sitting at a restaurant table can order the food using automated LCD display, making it easy for ordering foodfor both the customer and the hotel management. This paper illustrates a system which helps the customers place their orders directly to the hotel kitchen, with the help of CAN (CONTROL AREA NETWORK) protocol. The paper gives information about using a Microcontroller CAN base protocol device which uses LCD display 16x2 as an output indication and keyboard interface for customer input details. Hence it is not speaker dependent. Project comprises of three major sections Kitchen, Customer table, and Bill Desk. This 3 sections will be connected using CAN bus on network design by 3 microcontroller. The microcontroller will be used in a project is 8051 microcontroller family IC (89S51). Using this project customer is enable to order his food from sitting table without any direct contact with food serving waiter, customers order will be directly displayed to the kitchen section and the total amount of bill is calculated and automatically send it to the bill desk. This will help to reduce the manpower required to service the customers and at the same time can handle as many table requirements. The paper aims at bringing automation in hoteling industry which will change the traditional food ordering and serving method in restaurants. This change will bring more transparency and easiness in food ordering system at restaurants

Five-years review of obstetric hysterectomy at tertiary care center

Background: Obstetric hysterectomy (OH) is indicated as last resort operation to save the life of the mother  and associated with high complication rates, so  requires a highly experienced and skilled medical team ,to solve any complication. Objective was to identify incidence, demographic profile, indications, risk factors, complications, maternal morbidity and mortality associated   with   obstetric hysterectomy.Methods: Retrospective   analytical study of 47 case records is done over period of last 5 years   from October 1st October 2015 to 30th September 2020 at VDGIMS, a tertiary care center, Latur. Results are expressed in frequency and percentages.Results: In our study, the rate of OH was 1.1/1000 deliveries. Most common (68%) age group was 21-30 yrs, majority (70%) were multipara, and booked (76%). Most common indication of OH was atonic PPH (65%), followed by traumatic PP, including rupture uterus (21%), and placenta acreta (10%). Most OH was performed on emergency basis (91%) and of subtotal type (95%). Major mode of delivery  was cesarean 65% and vaginal delivery in 21% cases. Most common risk factors were placental causes (55%), previous LSCS (48%) and hypertensive disorder (31%). High maternal morbidity in form of 100% blood transfusion rate, 93% ICU admission, inotropes and ventilator support in 59% cases and prolonged hospital stay in 75% cases seen. Most common complication were hemorrhagic shock 21%, DIC (29%), renal failure (12%) and septic shock (14%) with maternal death rate of 23% was noted.Conclusions: Obstetric hysterectomy is a necessary life-saving operation, but also associated with high maternal morbidity and mortality, which can be minimized with timely done procedure by experienced person

Anxiety among Adolescent Students and its Association with Socio Demographic Variables in a Rural Block of Haryana

Background: Anxiety is one of the most common psychological disorders in school-aged children and adolescents worldwide. Anxiety is associated with substantial negative effects on children’s social, emotional and academic success.Objectives: To find out the prevalence of anxiety among adolescent students and its association with sociodemographic factors in rural block Beri.Methods: It was a cross sectional study taking the sample size of 600 (300 males and 300 females) studying in class 8th to 12th. A pre-designed, pre-tested tool SCL 90 R containing 90 items was used to screen anxiety in these students. Anxiety is one of the psychiatric morbidities screened by this tool. Cut off point of estimated raw score of 1 was used to label as anxiety.Results: It was observed that nearly 18.5% adolescents suffered from anxiety. Anxiety was highest in 17-19 years age group (30.4%) followed by mid adolescence phase (13-16 years). Anxiety was maximum in 10th and 12th standard students which were 19.3% and 24% respectively. It was significantly high among females (23.7%) than males (13.7%). Anxiety was maximum in upper and lower socio-economic class of students with 24.1% and 22.3% respectively. It was more among students whose mothers were unemployed (19.5%) than those whose mothers were employed (14.6%).Conclusion: More than one – third (35%) of study subjects who were apparently healthy suffered from unnoticed anxiety. Appropriate counseling through school-based screening programme is the urgent need of the hour

Addisonian Hyperpigmentation as Oral Manifestation in Primary Adrenal Insufficiency – A Case Report

Primary adrenal insufficiency is an endocrine disorder which is characterized by aldosterone and cortisol deficiency due to destruction of the adrenal cortex. The purpose of this case report is to present a rare case of 10-year-old child patient who reported with a chief complaint of pain in the upper left back tooth region of the jaw since a week and was diagnosed as Addison disease with hyperpigmentation of dorsal surface of the tongue, perioral structures and skin folds, nails and overall skin of the body. Oral manifestations along with endocrine issues play a crucial role in diagnosis & treatment planning of this disease. Dental infection can be a cause of adrenal crisis in patients with long term adrenal insufficiency, so paediatric dentists should be aware and a multidisciplinary approach is mandatory to ensure adequate medical and dental treatment in children. Limited number of case reports in literature suggest that adrenal crisis is a rare emergency condition in dentistry, and diagnosis is mandatory to rule out any condition before a dental surgical procedur

MiRNA and associated inflammatory changes from baseline to hypoglycemia in type 2 diabetes

Objective: Hypoglycemia in type 2 diabetes (T2D) increases morbidity and mortality but the underlying physiological response is still not fully understood, though physiological changes are still apparent 24 hours after the event. Small noncoding microRNA (miRNA) have multiple downstream biological effects that may respond rapidly to stress. We hypothesized that hypoglycemia would induce rapid miRNA changes; therefore, this pilot exploratory study was undertaken.Methods: A pilot prospective, parallel study in T2D (n=23) and controls (n=23). Insulin-induced hypoglycemia (2mmol/l: 36mg/dl) was induced and blood sampling performed at baseline and hypoglycemia. Initial profiling of miRNA was undertaken on pooled samples identified 96 miRNA that were differentially regulated, followed by validation on a custom designed 112 miRNA panel.Results: Nine miRNAs differed from baseline to hypoglycemia in control subjects; eight were upregulated: miR-1303, miR-let-7e-5p, miR-1267, miR-30a-5p, miR-571, miR-661, miR-770-5p, miR-892b and one was downregulated: miR-652-3p. None of the miRNAs differed from baseline in T2D subjects.Conclusion: A rapid miRNA response reflecting protective pathways was seen in control subjects that appeared to be lost in T2D, suggesting that mitigating responses to hypoglycemia with blunting of the counter-regulatory response in T2D occurs even in patients with short duration of disease

An appraisal of peer-reviewed published literature on Influenza, 2000–2021 from countries in South-East Asia Region

BackgroundInfluenza poses a major public health challenge in South-East Asia Region (SEAR). To address the challenge, there is a need to generate contextual evidence that could inform policy makers and program managers for response preparedness and impact mitigation. The World Health Organization has identified priority areas across five streams for research evidence generation at a global level (WHO Public Health Research Agenda). Stream 1 focuses on research for reducing the risk of emergence, Stream 2 on limiting the spread, Stream 3 on minimizing the impact, Stream 4 on optimizing the treatment and Stream 5 on promoting public health tools and technologies for Influenza. However, evidence generation from SEAR has been arguably low and needs a relook for alignment with priorities. This study aimed to undertake a bibliometric analysis of medical literature on Influenza over the past 21 years to identify gaps in research evidence and for identifying major areas for focusing with a view to provide recommendations to member states and SEAR office for prioritizing avenues for future research.MethodsWe searched Scopus, PubMed, Embase, and Cochrane databases in August 2021. We identified studies on influenza published from the 11 countries in WHO SEAR in the date range of 1 January 2000–31 December 2021. Data was retrieved, tagged and analyzed based on the WHO priority streams for Influenza, member states, study design and type of research. Bibliometric analysis was done on Vosviewer.FindingsWe included a total of 1,641 articles (Stream 1: n = 307; Stream 2: n = 516; Stream 3: n = 470; Stream 4: n = 309; Stream 5: n = 227). Maximum number of publications were seen in Stream 2, i.e., limiting the spread of pandemic, zoonotic, and seasonal epidemic influenza which majorly included transmission, spread of virus at global and local levels and public health measures to limit the transmission. The highest number of publications was from India (n = 524) followed by Thailand (n = 407), Indonesia (n = 214) and Bangladesh (n = 158). Bhutan (n = 10), Maldives (n = 1), Democratic People’s Republic of Korea (n = 1), and Timor-Leste (n = 3) had the least contribution in Influenza research. The top-most journal was PloS One which had the maximum number of influenza articles (n = 94) published from SEAR countries. Research that generated actionable evidence, i.e., implementation and intervention related topics were less common. Similarly, research on pharmaceutical interventions and on innovations was low. SEAR member states had inconsistent output across the five priority research streams, and there was a much higher scope and need for collaborative research. Basic science research showed declining trends and needed reprioritization.InterpretationWhile a priority research agenda has been set for influenza at the global level through the WHO Global Influenza Program since 2009, and subsequently revisited in 2011 and again in 2016–2017, a structured contextualized approach to guide actionable evidence generation activities in SEAR has been lacking. In the backset of the Global Influenza Strategy 2019–2030 and the COVID-19 pandemic, attuning research endeavors in SEAR could help in improved pandemic influenza preparedness planning. There is a need to prioritize contextually relevant research themes within priority streams. Member states must inculcate a culture of within and inter-country collaboration to produce evidence that has regional as well as global value