Direct Torque Control of VSI Fed Induction Motor with Fuzzy Controller

The Direct Torque Control (DTC) methods for AC machines are commonly utilized in many variable speed drives, especially in case the torque control is more desired than speed control. Two major problems that are usually related with DTC drives are: 1) switching frequency that varies with operating conditions and 2) high torque ripple. To solve these problems and at the same time intermit the simple control structure of DTC, a constant switching frequency torque controller is proposed to replace the conventional hysteresis-based controller. The major advantages of the Voltage Source Inverter (VSI) are combines with those of the DTC technique, producing the appropriate voltage vectors under 0.9 input power factor operations. The results prove the high quality and robustness in the system dynamic response and minimize in the both steady-state and transient motor ripple torque. The proposed switching scheme for VSI based DTC of IM drive select the necessary switching vectors for control of torque with small variations of the stator flux within the hysteresis band. This paper presents a novel control scheme based on Fuzzy Logic Controller (FLC). This paper reviews the research and development in direct torque control of VSI fed IM.Such a review helps the highly effective control strategies for AC machine to provide a very fast torque and flux control. In this technical context an overview of VSI fed induction motor has been carried out based on the reports from the literature present in past two recent decades

THE IMPORTANCE OF ANTIBIOTICS IN A VARIOUS UNIQUE METASTASIS ALONG WITH CYTOTOXIC THERAPY AT TERTIARY CARE HOSPITAL: A PROSPECTIVE COHORT STUDY

Objective: Rare cancers are creating a massive challenge to the world. It has associated with genetic mutations or socio-environmental factors, which includes genes, smoking, alcohol, ionizing radiation exposure, organic-inorganic chemicals, air and water pollution, viruses, and bacteria. When 15 cases per 1,00,000 people per year, we can consider it as a rare case as per the National Cancer Institute This study aim is the importance of antibiotics in various unique metastasis along with cytotoxic therapy at tertiary care hospital. Methods: The inclusion criteria of our study include a person who is suffering from rare metastasis at an early stage. We excluded the data that are those who are suffering from the typical type of cancers, multiple co-morbid conditions. This study was carried out the Prospective Cohort Study conducted between June 2018 to March 2020. Results: Number of 20 rare cancers we consider for final analysis, the overall antibiotics use in this study 18 antibiotics they prescribed in overall cases, prescribed cytotoxic drugs are 23. the chi-square test value is P=0.001, the confidence interval(CI) is 95%, the likelihood ratio is 54.4, odd’s ratio is 2.0(CI 95%, P=0.711), Male patients more than the female patients. Conclusion: Cancer is a complex disorder, which is occurred through gene proliferation and socio-environmental factors. Rare metastasis is challenging to physicians and patients, however as per our observation, cytotoxic therapy with antibiotics can reduce the risk of rare metastasis and as well improved therapeutic adhesion, and we need clear supporting evidence on it through clinical trials

A Few-Shot Approach to Dysarthric Speech Intelligibility Level Classification Using Transformers

Dysarthria is a speech disorder that hinders communication due to difficulties in articulating words. Detection of dysarthria is important for several reasons as it can be used to develop a treatment plan and help improve a person's quality of life and ability to communicate effectively. Much of the literature focused on improving ASR systems for dysarthric speech. The objective of the current work is to develop models that can accurately classify the presence of dysarthria and also give information about the intelligibility level using limited data by employing a few-shot approach using a transformer model. This work also aims to tackle the data leakage that is present in previous studies. Our whisper-large-v2 transformer model trained on a subset of the UASpeech dataset containing medium intelligibility level patients achieved an accuracy of 85%, precision of 0.92, recall of 0.8 F1-score of 0.85, and specificity of 0.91. Experimental results also demonstrate that the model trained using the 'words' dataset performed better compared to the model trained on the 'letters' and 'digits' dataset. Moreover, the multiclass model achieved an accuracy of 67%.Comment: Paper has been presented at ICCCNT 2023 and the final version will be published in IEEE Digital Library Xplor

Effects of positional coracohumeral ligament stretching on the size of calcium deposits in adhesive capsulitis

Adhesive capsulitis is a painful condition of unknown etiology with restriction of active and passive movements of the glenohumeral joint. The condition is a result of inflammation, adherence, and swelling in the lining of the shoulder joint capsule and its associated ligaments, causing resultant contracture of the capsule. We describe a patient with calcified and thickened coracohumeral ligament with adhesive capsulitis and diabetes mellitus

Management of adhesive capsulitis of shoulder joint with arthroscopic release vs. manipulation under anaesthesia: a comparative study

Background: Shoulder stiffness is a manifestation of various pathologies or clinical scenarios variously described as scapula humeral periarthritis, frozen shoulder and adhesive capsulitis. Frozen shoulder is characterized by significant restriction of active and passive motion of the shoulder that occurs due to unknown factors. Adhesive capsulitis causes contracted, thickened joint capsule that seemed to be drawn tightly around the humeral head with a relative absence of synovial fluid and chronic inflammatory changes within the subsynovial layer of the capsule. In this study we did a comparison of 30 patients treated with arthroscopic release and manipulation under anesthesia. Methods: There were 30 patients in this study with 15 patients in each group of different age groups. All the patients were studied for a period of one year between July 2021 to July 2022. The functional outcomes were assessed using dash scoring system. Results: in this study of 30 patients with different age groups followed for 12 months and assessed by DASH scoring system. We had excellent results in arthroscopic group with postop dash score standard deviation is 5.87. Conclusions: The arthroscopic capsular release of shoulder joint in adhesive capsulitis was found to have a better functional outcome as compared to the manipulation of shoulder joint under anaesthesia. Currently no treatment protocols are universally effective which needs more and more research and developments for proper treatment strategies. Morbidity with this condition has caused significant loss both economically and psychologically

Smart Multi-Model Emotion Recognition System with Deep learning

Emotion recognition is added a new dimension to the sentiment analysis. This paper presents a multi-modal human emotion recognition web application by considering of three traits includes speech, text, facial expressions, to extract and analyze emotions of people who are giving interviews. Now a days there is a rapid development of Machine Learning, Artificial Intelligence and deep learning, this emotion recognition is getting more attention from researchers. These machines are said to be intelligent only if they are able to do human recognition or sentiment analysis. Emotion recognition helps in spam call detection, blackmailing calls, customer services, lie detectors, audience engagement, suspicious behavior. In this paper focus on facial expression analysis is carried out by using deep learning approaches with speech signals and input text

Implementation of Pattern Matching Algorithm for Multimedia Files in Mail Function Detection

Now a days internet and mail based file transfer has increased enormously due to this server space required will be highly and also occurs largely. In existing system if we upload the same file which is present in the server also get uploaded and duplication occurs. We used a pattern matching algorithm it eliminate duplication and also to avoid time wastage in uploading the same file present in the server. During file upload pattern will be matched. If pattern matched file won't be uploaded again it will simply matched the existing file it avoids uploading the file again. If pattern doesn't match it allow uploading the file. From this we save the memory space in the server and duplication doesn't occur

Estimation of Channel Performance of Satellite Communication and Frequency Reader

ABSTRACT: National Remote Sensing Center (NRSC) receives data from different remote satellites like IRS-P6, IRS-P5, Cartosat-2, Cartosat-2a, etc., and processes it depending on the user requirements. The satellite data received in X band is in a particular data format. This data has to be frame synchronized using a special hardware. The receiver hardware setup must be ready at any time to make it ready it"s performance is to be tested continuously.The frequency with which satellite data is coming is also continuously tested . In the proposed project VHDL code has been developed for BER reader with differential encoding and decoding and frequency reader. The external frequency and number of errors in satellite data will be displayed on HP display devices. This project has been implemented and tested using the ALTERA EPLDs. This needs crystal oscillators, thumb wheel switches,7 segment display etc., must be programmed as per the requirement. The hardware required for this has been implemented on the wire-warp board

PHARMACOGNOSTIC STUDY OF MANSOA ALLIACEA LEAF

Mansoa alliacea Lam. (Family: Bignoniaceae) is a native plant from Amazonian basin in South America. Plant derivatives are used as anti-inflammatory, antioxidant, antiseptic and antibacterial agents. The study was aimed to determine the pharmacognostic and phytochemicals present in Mansoa alliacea. Micro and organoleptic characteristics of fresh and dried leaf samples had been examined. Physicochemical variables had been done by using WHO suggested variables; preliminary phytochemical of leaf sample had been performed to identify the presence of alkaloids, flavonoids, tannins and phenols, and quinones using the ethanolic extract of the leaves of M. alliacea