Volume 11 | Issue 6

 Abstract

This research paper analyzes the role of the Reserve Bank of India (RBI) in the 2016 demonetization drive and its socio-legal implications. The paper explores the concept of demonetization and its history, the rationale behind the Indian government's decision to demonetize high-value currency notes, and the role played by the RBI in the entire process. This study sheds light on the importance of the RBI as the central bank of India and its core responsibility to maintain the stability of the country's monetary and financial system. The study evaluates the legal framework surrounding demonetization, including the laws and regulations related to the circulation, exchange, and withdrawal of currency notes. Further, the paper examines the socio- Legal impact of demonetization. The paper concludes that demonetization was a massive policy experiment with mixed results.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Demonetisation, 2016 Demonetisation, Reserve Bank of India, Currency Regulation, Legality of Demonetisation.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The development and improvement of Information and Communication Technology (ICT) is assuming indispensable part during the time spent headway of society by and large and in library and information science in particular. Quick advances in ICT in the previous twenty years have gotten progressive changes the idea, association, working and the board of library and information frameworks all through the world. This paper explains the importance and availability of ICT Infrastructure of Homoeopathy and Ayurvedic College libraries in Anand District. The development of library resources, library patronage, and staff position, conventional and non-conventional services offered and also subscribed online resources by the libraries are discussed.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Information, Communication, Technology, Library, Service, Homeopathy

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

FULL PAPER HAS BEEN SUBMITTED

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

POLITICAL SCIENCE

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Several disorders may cause cardiovascular disease, or heart disease. Heart disease has several risk factors and requires quick diagnosis for proper treatment. A symptom Data mining is a common way to analyse healthcare data. Researchers employ data mining and machine learning to analyse complex medical data for healthcare practitioners. Cardiologists predict heart disease. This study's model uses heart disease-related parameters. Supervised learning uses Naive Bayes, decision tree, K-nearest neighbour, and random forest. It uses UCI's Cleveland database of heart disease patients. The 303 instances of data include characteristics. Only 14 of the 76 traits are verified, but they're crucial to confirming the claim. Algorithm performance. This research estimates heart disease risk in a population. Patients. K- nearest neighbor has the highest accuracy, as shown in result and discussion.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Prediction, User Interaction, Artificial Intelligence, Artificial Neural Networks, Prognosis, Machine Learning

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Biological reductants continue to be studied worldwide to reduce the harmful effects of toxic chemicals used to create nanoparticles. Utilizing an aqueous leaf extract of Alternanthera sessilis, this study analyzed the effects of bio-synthesized ZnO nanoparticles(As-ZnO NPs). Zinc acetate dihydrate was employed as the precursor, and the leaf extract was used as a biological reductant to produce zinc oxide nanoparticles. The synthesis conditions, such as heat, pH, and mixing time, were optimized for the synthesis of ZnO nanoparticles. The obtained nanopowder was characterized using several analytical methods and was kept in a dry state. The As-ZnO nanoparticles were characterized using UV-Vis Spectroscopy, Scanning Electron Microscope, Energy Dispersive X-ray analysis, Powder X-ray diffraction and FT-IR Spectroscopy. The synthesized As-ZnO NPs exhibited a peak at 333 nm in the UV-Vis spectroscopy analysis. According to Scanning Electron Microscope, the structure of nanoparticles showed a hexagonal wurtzite shape. The crystalline nature of the nanoparticles was validated by Powder X-ray diffraction. The synthesized nanoparticles were tested for their antibacterial potential against the main aquatic pathogens such as Enterococcus faecalis, Staphylococcus aureus, Streptococcus pyogenes, Aeromonas hydrophilia, Klebsiella pneumonia and Pseudomonas aeruginosa. This study reported an efficient green method for synthesising zinc oxide nanoparticles with antibacterial properties against freshwater fish pathogens.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Alternanthera sessilis, zinc oxide nanoparticles, anti-bacterial, aquatic pathogens.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

E-commerce platforms facilitate customers in posting reviews for a wide range of products. Typically, a single product can accumulate numerous lengthy and repetitive reviews, making it challenging for customers to gather relevant information for informed decision-making. Therefore, the application of automatic review summarization holds immense potential in assisting customers by delivering concise and genuine summaries of online reviews on E-commerce websites. In this study, we propose a Fine-Tuning Pre-Trained Model, which produces more precise summaries closely resembling those generated by humans. Additionally, our system evaluates the overall sentiment of the generated summaries, enabling customers to quickly grasp the underlying tone of the text. For sentiment analysis, a supervised learning model using the Naive Bayes classifier has been trained on social media sentiment analysis data, achieving an accuracy exceeding 98%. The abstractive summarization model adopts a Sequence-to-Sequence approach with an attention mechanism, resulting in reasonably good review summaries.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Fine-Tuning Pre-Trained Model, abstractive summarization,seq2seq model, sentiment prediction.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Osteoporosis, a systemic progressive disease, is responsible for significant morbidity and mortality in aging postmenopausal women. It is an important public health problem because of its significant complications, namely fractures of the proximal femur (hip), vertebrae (spine), distal forearm, proximal humerus, pelvis, and other skeletal sites. Compared with other osteoporotic fractures, hip fractures incur the greatest morbidity and direct medical costs for health services. There are now a variety of treatments available for the management of osteoporosis. Inhibitors of bone resorption, including calcium, vitamin Ds, bisphosphonates, calcitonins and gonadal steroids prevent bone loss or reduce fractures. Prevention of osteoporosis with identification of risk factors, careful examination and a few simple diagnostic tests during teen and early adult years is superior to treatment of older individuals. The purpose of this article is to provide a review of osteoporosis.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

joints

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

RESEARCH ABSTRACT PROBLEM STATEMENT A STUDY TO ASSESS THE EFFECTIVENESS OF SELF LEARNING MODULE REGARDING INTERPRETATION OF HEMATOLOGICAL LAB INVESTIGATIONS AMONG FINAL YEAR NURSING STUDENTS IN SELECTED NURSING COLLEGES AT MEERUT. BACKGROUND OF THE STUDY In hospital settings every year there is an increased rate of laboratory tests as they are more evident to the patients and healthcare. Healthcare decisions are based on laboratory investigation results. They are crucial in determining the condition or status of the patient health. Thus it is very important for healthcare professionals to have clinical skills for interpreting lab investigations. Lab investigation involves testing a sample of blood urine or other substance from the body. Laboratory test can help determine a diagnosis plan treatment is working or monitor the disease over time. These clinical laboratory test results are a very parameter in providing healthcare services. Nurses being an important part of healthcare delivery system and the first level of contact to the healthcare services it is very important for nurse to be competent enough in clinical skills of interpreting the lab investigations. Nurse not only prepares the patient for testing but also evaluate the test results and report it to the doctor and physician. Lab investigation results are a very important parameter in diagnosis monitoring and screening. 70-80 % of decisions in diagnosis are based on laboratory results and more and more laboratory analyses are requested. Thus a lot of data are provided and it is therefore imperative for patient care (and safety) that the clinicians are familiar with the tests and with interpretation of the results. OBJECTIVE OF THE STUDY ? To prepare & validate self learning module on knowledge regarding interpretation of hematological lab investigations among nursing students. ? To assess pre-test and post-test knowledge score regarding interpretation of hematological lab investigation among nursing students in experimental and control group ? To find the effectiveness of self learning module on the post test knowledge score regarding interpretation of hematological lab investigations among nursing students in experimental group. ? To find out the association between post test knowledge score regarding interpretation of hematological lab investigations among nursing students with their selected demographic variables in experimental group. RESEARCH METHODOLOGY In this study quantitative research approach is used .quasi experimental non equivalent control group pre- test post-post test design was considerd to be appropriate to assess the effective of self-e learning module on regarding interpretation of hematological lab investigations among final year nursing students in selected nursing colleges at Meerut. Sample size 120 ( 60 in experimental and 60 in control group) were selected in college setting purposive sampling technique. Structured questionnaire knowledge and self -e learning module website were used to assess the knowledge regarding interpretation of hematological lab investigation among final year nursing student. Results o In this study , maximum sample 23 (38.33%), belongs to age of ( 22 years) in experimental group and 22(36.67%), of the samples belongs to the age groups of ( 21 years ) in control group. As per gender, most of the samples were females 50 (83.33%) and males were least 10(16.67%). In experimental group. Nursing course of samples show that 32 (53.33) in experimental group 28 (46.66) in control group .previous academic score of samples show that 38( 66.33%) belongs to 66 to 75%, in experimental groups. o The finding of the study revealed that the score of experimental and control is Post - Test 15.47 and 5.17 hat is t value is 27.61 with df (29) at 0.05 level of significance. In pre- test Data shows that majority samples had poor knowledge 36 (60%) and 22(36.67%) had extremely poor knowledge, 2(3.33%) had average knowledge. In post - test- majority of samples37 (65%) had good knowledge and 16 (26.66%) had excellent knowledge, 7 ( 11.6%) had average knowledge in experimental group . and In pre- test that majority of samples 33 (55%) had extremely poor knowledge, 27(45%) had poor knowledge, In post -test , majority of samples 36(60%) poor knowledge, 21(35%) extremely poor knowledge, 3(5%) had average knowledge. In control group. Significant association on knowledge on interpretation of hematological lab investigation. Conclusion The study concludes that there is a significant increase in the post test knowledge score of experimental group. So self learning module helps to improve the knowledge of the nursing students

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

effectiveness ,self learning ,knowledge ,interpretation

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Face recognition is one of the important issues in object recognition and computer vision. In our day-to-day activities, a few biometric applications are available, face recognizing humans such as eye recognition, fingerprint recognition.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Face Recognition, Radio Frequency System, Machine Learning, Artificial Intelligence

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Premenstrual syndrome (PMS) is the emergence of periodic one or more symptoms of symptoms before menstruation and in the first few days of menstruation. Lifestyle is one of the series of factors that affect the health of people. Activity, smoking, and food intake are factors associated with lifestyle, and evidence suggests that women and girls with PMS do not have an adequate life span. The aim of this study was to determine the factors associated with PMS in female high school students.The global incidence of premenstrual syndrome is 47.8% (95% CI: 32.6-62.9). The incidence of premenstrual syndrome varies in different countries. For instance, the incidence of premenstrual syndrome was reported as 12.2% in France and 98.2% in Iran. The lowest prevalence of PMS Premenstrual Syndrome (PMS) is a collection of physical, cognitive, affective and behavioral cyclically occurring symptoms during the luteal phase of the menstrual cycle and resolve at or within a few days after the onset of menstrual flow. Though more than 200 symptoms have been known to occur, the most frequently occurring symptoms include headache, fatigue, bloating, backache, breast tenderness, food cravings, fatigue, anxiety, irritability, social withdrawal and depression. Premenstrual syndrome for most women started at their age of menarche. Educational status shows 60 (100%) were Higher secondary. Based on family history of premenstrual syndrome 42 (73.3%) were present with PMS. According the previous knowledge about PMS 47(78.3%) were have previous knowledge about PMS. Adolescent girls 46(76.7%) had moderate risk level of factors associated with premenstrual symptoms and 14(23.3%) had high risk level of factors associated with premenstrual symptoms. Mean (14.92) and standard deviation (3.038) of adolescent girls regarding level of factors associated on prevalance rate. Association shows significant relationship with the demographic variables. Age (p=0.044) , types of family (p=0.006) and No of siblings ( p=0.001) had shown statistically significant association between the level of the factors associated with premenstrual symptoms among adolescent girls with their selected demographic variables respectively.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

premenstrual syndrome, adolescent girls, associated factors.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Breast cancer is the leading cause of cancer death among women. Screening x-ray mammography is the first and regular method currently available for the reliable early detection and treatment can be started for hopeful cure of breast cancer. Research indicates that the mortality rate could decrease by 35% if women age around 45-50years and older have regular mammograms. The detection rate can be confirmed 15-30% by providing the radiologist with results from a computer-aided diagnosis (CAD) system acting as a second opinion. However, among screening mammograms routinely interpreted by radiologists, very few (approximately 10%) cases actually have breast cancer. It would be beneficial if an accurate CAD system existed to identify normal mammograms and thus allowing the radiologist to focus on suspicious cases. This strategy could reduce the radiologist's workload and improve screening performance. Since mammography is considered as the most effective means for breast cancer diagnosis, this paper introduces two separate techniques for mass and micro-calcification segmentation in digital mammograms. There are two different segmentation techniques used for masses and microcalcifications.For masses there are three steps- background subtraction, fuzzy texture representation and entropic theresholding. Similarly micro-calcifications are also segmented in three stages - background subtraction, Laplacian of Gaussian filtering and contrast estimation followed by thresholding. GLCM texture feature extractions are known to be the most common and powerful techniques for texture analysis including histogram statistical features. Experiments have been taken for a data set of 322 images taken from MIAS of different types with the aim of improving the accuracy of Association Rule classifier by generating minimum no. of rules to cover more patterns. In this study, an incremental updating technique is applied to associative classification for constructing classification system when a new training dataset is appended to an old training dataset. The proposed algorithm, called Incremental Classification Based on Association Rules (ICBA). ICBA has 2 phases which are rule generator phase (ICBA-RG) and classifier building phase (ICBA-CB). In order to reduce the execution time, we applied the concept of Fast Update algorithm (FUP) algorithm to both phases of our algorithm. The experiment results show that the proposed algorithm has execution time better than CBA algorithm.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Breast cancer, fuzzy texture, entropy, fuzzy segmentation, Entropic thresholding, microcalcification, Laplacian of Gaussian filter. GLCM texture features, Association rule mining

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Synthetic dyes used by the textile industry pollute a lot of water. Textile dyes are not tightly bound to the cloth and released into the streams as waste water. For this reason, a large part of the wastewater of the textile industry is discharged without treatment, causing a serious impact on the environment and human health. Therefore, environmentally friendly technology should be used for the effective treatment of wastewater in order to prevent its negative effects on the environment, human health and naturalresources. This study focuses on lowcost coagulants to remove physicochemical impurities in wastewater.Aluminum, lime and iron coagulants have been used for many years in most industries to coagulate substances in surface water and to remove turbidity from water prior to flocculation, sedimentation or filtration. Although useful, inorganic coagulants have some disadvantages, and there are concerns about the association between aluminum residues in purified water and Alzheimer's disease, and the toxicity of metal coagulants on the water supply. Therefore, the development of natural coagulants in water treatment is of great interest today. In this study, fenugreek, Cicer arientinum, neem and nirmali were used to remove physicochemical impurities such as turbidity, TDS and color in synthetic textile industrial wastes. The flocculation method will be used for this batch coagulation. This review is expected to be useful to researchers in the community who want to address the wider risk of organic pollution from the textile industry.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Textile Effluent, Coagulant, Coagulation Flocculation, Colour, Trigonella foenum-graceum, Cicer arientinum, Azadirachta indica, Strychnos potatorum

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

'Surrogacy' is a kind of assisted reproductive technology to help childless people get children. It is divided into two types: (i) altruistic surrogacy means without any monetary consideration (ii) Commercial surrogacy means where the surrogate mother takes money for letting her womb be used as a substitute womb. Eventually, commercial surrogacy gained more popularity than altruistic ones. Commercial surrogacy had changed the view about motherhood. Motherhood has always been praised by every religion, every community, and all cultures worldwide. Commercial Surrogacy is precluded by many people as they thought this is against morality. In commercial surrogacy intended parents paid good amount to surrogacy clinics, in consideration these clinics arranged the medical services plus surrogate mothers for carrying foetus in her womb. Some people termed it 'womb on rent', 'womb on labour' etc. Even some compared it with prostitution, human trafficking and organ selling. Therefore it is prohibited under The Surrogacy Regulation Act 2021, only altruistic surrogacy is allowed. The Surrogacy Regulation Act is debars single men, gay couple etc. for the sake of societal norms and avoid interest of these persons. This paper is aim to study impact of societal norms on The Surrogacy (Regulation) Act 2021. In 2018 Supreme Court protect the personal autonomy of the women in 'Joseph shine Case' and S.377 struck down in 'Navtej Singh Johar' case, impact of these moral changing judgments on Surrogacy will also examine in this paper.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

#surrogacy #surrogacylaws #surrogacyact2021

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Blood group distribution varies across different geographical regions and populations, and understanding these patterns is crucial for efficient blood transfusion services and population genetics studies. This research paper presents a comprehensive analysis of the distribution of ABO and Rh blood groups among the students of ITM Vocational University, Vadodara, Gujarat, India. The study utilized a cross-sectional design and collected data from a diverse sample of students studying in ITM Vocational University, Vadodara. A total of 778 students, comprising both males and females from various streams, were included in the study. Blood group typing was performed using standard serological methods. The results revealed that the distribution of ABO blood groups in students of ITM Vocational University, Vadodara followed the typical patterns observed globally. The most prevalent blood group was B (35.7%), followed by O (32.3%), A (22.6%), and AB (9.2%). The RhD positive (Rh+) blood group was found in 96.6% of the student strength, while the RhD negative (Rh-) blood group accounted for 3.4%. This study provides valuable insights into the distribution of ABO and Rh blood groups in the students of ITM Vocational University, Vadodara. These findings have significant implications for blood transfusion services, organ transplantation, and population genetics research in the region. The knowledge of blood group frequencies will aid in developing effective strategies for maintaining an adequate and safe blood supply, reducing transfusion-related complications, and understanding the genetic diversity of the population

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

ABO Blood Group, Rh System, Blood Transfusion Services, Healthcare Management, Blood Bank

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The removal of soft tissue or both soft tissue as well as alveolar bone for the restoration of the biologic width may be part of a surgical procedure to extend the length of the crown. Scalpel, electrosurgery, and laser methods can be used to extend the crown length. However, using lasers has a lot of benefits over other approaches. Greater precision, a generally bloodless surgical field and postsurgical course, minimum swelling and scarring, coagulation, vaporisation, cutting, minimal or no suturing, and less or no postoperative pain are some benefits of laser surgery over scalpel surgery. In this particular case, a diode laser was employed to extend the crown length and restore functionality.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Diode laser, Gingivectomy, biologic width

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Chemotherapy is a common cancer treatment. It may be paired with other cancer treatments such as radiation therapy and surgery. Chemotherapy affects cell division, tumors with high growth rates.One of the most important roles for cancer chemotherapy is an adjuvant to local treatment modalities. Chemotherapeutic agents can be used to increase both the length and quality of the lives of patients with a wide variety of neoplastic diseases.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Chemotherapy, Tumors, Neoplastic Diseases, Radiation therapy

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In today's automobile industry, leaf springs are commonly use in heavy-duty vehicles. A leaf spring is a simple form of spring commonly used as a suspension in wheeled vehicles. Fatigue is responsible for 90% of the failures that occur in an industry. Fatigue testing equipment is used to determine the fatigue life or fatigue strength of a material. Mechanical Engineering students are having a hard time visualizing on how manufacturers determine the fatigue strength of a leaf spring. This is because the professors only teach the concepts and theories about leaf spring, and there is no actual representation on how the testing of leaf spring really works. So are tried to develop prototype leaf spring fatigue testing machine using pneumatic cylinder and microcontroller. With the help of this machine, we can measure fatigue life cycle of testing leaf spring.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Leaf Spring, Arduino UNO, Aeroflex Pneumatic Valve, HC-SR04

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Partition of India in 1947 and the drawing of the administrative lines of control: Radcliffe Lines which gave birth of two independent nationalities: the Republic of India and the Republic of Pakistan had its grim aftermath too especially in the border line localities of both the countries. This appeared massively in Indian literature written in English as well as in other languages like Bengali, Gujarati, Hindi, Punjabi, Marathi and others, but a cinematic representation of the Partition has its special attraction for the viewers. And among all the Indian films based on the Partition of 1947, Srijit Mukherji's Rajkahini (2015) is an exceptional filmic representation not because he has depicted the bleak and bloody history of the Partition, but because he has singularly represented the Partition and politics of the Radcliffe Lines on the backdrop of a whorehouse and the miserable lives of its eleven women inmates most of whom are in the flesh trade. The present paper proposes to find out some of these politics.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

: Partition, Radcliffe Lines, Politics, Rajkahini.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This paper is evaluating performance of three supervised machine learning algorithms such as SVM (Support Vector Machine), Random Forest and Decision Tree. Machine learning algorithms will be used to detect whether request data contains normal or attack (anomaly) signatures. Now-a-days all services are available on internet and malicious users can attack client or server machines through this internet and to avoid such attack request IDS (Network Intrusion Detection System) will be used, IDS will monitor request data and then check if it contains normal or attack signatures, if contains attack signatures then request will be dropped. IDS will be trained with all possible attacks signatures with machine learning algorithms and then generate train model, whenever new request signatures arrived then this model applied on new request to determine whether it contains normal or attack signatures. In this paper we are evaluating performance of three machine learning algorithms such as SVM , Random Forest and Decision Tree .To avoid all attacks IDS systems has developed which process each incoming request to detect such attacks and if request is coming from genuine users then only it will forward to server for processing, if request contains attack signatures then IDS will drop that request and log such request data into dataset for future detection purpose.To detect such attacks IDS will be prior train with all possible attacks signatures coming from malicious user's request and then generate a training model. Upon receiving new request IDS will apply that request on that train model to predict it class whether request belongs to normal class or attack class. To train such models and prediction various data mining classification or prediction algorithms will be used.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

IDS,Random Forest,Decision Tree,SVM,anomaly,machine learning.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The goal of the current study was to find out how practicing yoga poses affected the flexibility of Drug Addicts. To accomplish the study's goal, thirty Drug Addicts were chosen from Drug Rehabilitation Shimla, Himachal Pradesh. The subject's age ranges from 20-30 years. The individuals that were chosen were randomly assigned to one of two groups: the experimental group or the control group, both of which were composed of 15 persons each. The experimental group participated in a six-week yoga asana practice program. Throughout the trial, there was no training provided to the control group. In this study, flexibility acted as a criteria variable. Flexibility of the chosen participants was evaluated using the sit-and-reach test. The pre-test was administered prior to the training period, and the post-test was administered right afterward following the six week training session. Methodology of Statistics, The means of both the experimental and control groups were compared before and after the intervention using the t-test. When compared to the control group, the experimental group experienced greater increases in flexibility as a result of the Yogasana practice that was given to them.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Yogasana, flexibility, Meditation, Drug Abuse, Narcotics.

  License

Creative Commons Attribution 4.0 and The Open Definition