Volume 11 | Issue 4 |

 Abstract

The future of farming is becoming increasingly reliant on machine learning and the Internet of Things (IoT) to improve agricultural productivity and sustainability. By integrating sensors, and other smart farming technologies with machine learning algorithms, farmers can make data-driven decisions about crop management, soil health, and weather patterns. This paper explores the potential of machine learning and IoT in agriculture sector.

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Creative Commons Attribution 4.0 and The Open Definition

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Today protection of miners is a main challenge. Miner's health and lifestyles is susceptible to several critical issues, which consists of no longer only the working environment, however also the after effect of it. Mining activities release unsafe and poisonous gases in turn exposing the associated people into the chance of survival. This puts a lot of stress on the mining industry. To increase the productivity and decrease the price of mining along with consideration of the security of workers, an innovative strategy is required. Miners health is in danger on the whole because of the toxic gases which are very regularly launched in underground mines. These gases cannot be detected without problems through human senses.

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Raspberry pi pico,lorawan module,smoke sensor,light sensor,fire sensor,DHT-11 sensor

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

सिनेमा आज के समय मे जनसंचार का सशक्त माध्यम है जो समाज पर एक गहरा प्रभाव छोड़ता है। सिनेमा अच्छे समाज का निर्माण करने में निरंतर अपनी महत्वपूर्ण भूमिका निभाता आ रहा है।वर्तमान समय में सभी लोग फिल्में देखते हैं और फिल्में सभी के जीवन पर किसी न किसी तरह की प्रभाव छोड़ती है। फिल्मो को देखने के बाद दर्शकों का अपने आसपास समाज में चीजों को देखने का नजरिया प्रभावित होता है। फिल्मों में डायरेक्टर अपने तरीके से या कहें स्वयं के नजरिये से समाज को दिखाने की कोशिश करता है। जब भारतीय फिल्म उद्योग में पहला चलचित्र बनाया गया था तब किसी भी महिला ने फिल्म में कार्य नही किया था। उस समय फिल्म में महिला की भूमिका भी एक पुरूष ने अदा की थी। लेकिन धीरे-धीरे समय के बदलने के साथ महिलाओं को भी समाज में पुरुषों के बराबर समझा जाने लगा और महिलाएं हर क्षेत्र में आगे रहने लगी। भारत में महिलाओं ने उन खेलों के क्षेत्र में भी नाम कमाया जिन खेलों को पुरूष प्रधान खेल समझा जाता था उसमें भारत की महिला खिलाड़ियों ने देश के लिए गोल्ड जीता। सिनेमा ने भी इस परिवर्तन को पर्दे पर बेहतरीन ढंग से पेश किया और कुछ फिल्में भारत की महिला खिलाड़ियों के जीवन पर बनाई गई हैं, जिसमें महिलाओं के कामयाब खिलाड़ी बनने तक के उनके परिश्रम को बडी सहजता और सुन्दरता के साथ प्रदर्शित किया गया है। ऐसी फिल्में महिला सशक्तिकरण में अपना योगदान देती हैं तथा पूरे समाज में उपस्थित लोगों को महिलाओं के प्रति अपनी मानसिकता बदलने के लिए प्रेरित करती है। प्रस्तुत शोध पत्र में खेलों पर आधारित महिलाओं पर केंद्रित चर्चित हिन्दी फिल्मो का विषय-वस्तु विश्लेषणनात्मक अध्यन्न किया गया है।

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बीजक शब्दः फिल्में, खेल, महिलाएं, सिनेमा, जीवन, सशक्तिकरण।

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Creative Commons Attribution 4.0 and The Open Definition

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Jigsa padhati: prabhavshali adhgam path

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Jigsa padhati: prabhavshali adhgam path

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Creative Commons Attribution 4.0 and The Open Definition

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In brief, the prosthetic arm is a tool for persons who have paralysed body parts. The as a chic design for a natural and simple prosthesis. EEG (electroencephalography) impulses from the brain are what we employ in our endeavour. The fundamental issue with the prosthesis is the absence of a mobile, strong embedded system. We offer a concept and development of upper arm prosthetics based on electroencephalography (EEG) that can overcome numerous drawbacks of movements. In order to operate the prosthetic device, brain signals are also employed to determine force and torque. The sensor system and control system operate as necessary to provide the desired result. Our prototype will act as a foundation for a number of additional functions as well as a chic design for a natural and simple prosthetis. EEG (electroencephalography), prosthetic arm, prototype are some related terms.

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Prosthetic arm, Paralysed, EEG electrode.

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In the modern world, there is an increased need for language translations owing to the fact that language is an effective medium of communication. The demand for translation has become more in recent years due to increase in the exchange of information between various regions using different regional languages. Accessibility to web document in other languages, for instance, has been a concern for information Professionals. Machine translation (MT), a subfield under Artificial Intelligence, is the application of computers to the task of translating texts from one natural (human) language to another. Many approaches have been used in the recent times to develop an MT system. Each of these approaches has its own advantages and challenges. This paper takes a look at these approaches with the few of identifying their individual features, challenges and the best domain they are best suited to.

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Machine Translation, Rule-based Approach, Corpus-based Approach, Statistical Approach, Transfer-Based Approach

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Creative Commons Attribution 4.0 and The Open Definition

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Klippel-Trenaunay Syndrome(KTS) is a congenital disorder with a rare incidence to affect at least 3-5 in 100,000 people worldwide. Alternative names given for Klippel-Trenaunay Syndrome are Klippel-Trenaunay-Weber syndrome. It is a rare sporadic disease characterized by clinical triad of capillary malformation; soft tissue and bony hypertrophy; and atypical varicosity. Symptoms of Klippel-Trenaunay Syndrome (KTS) include pain, swelling, lymphedema, bleeding, superficial thrombophlebitis, and deep vein thrombosis. This type of syndrome was first described more than hundred years ago, exact incidence has not been estimated yet. We report a case of a 21-year-old Male who presented to us with the symptoms of varicose plaques over left lower limbs & was diagnosed as a case of KTS. CT-Angiography IV contrast Vascular Doppler Ultrasound, skeletal X-ray, and magnetic resonance imaging of the Limb indicated a Klippel-Trenaunay disease.

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Klippel-Trenaunay Syndrome, Varicose veins, Capillary Malformations, compression stockings.

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Creative Commons Attribution 4.0 and The Open Definition

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Identifying message sources in social networks plays a critical role in limiting the damage caused by them through the timely quarantine of the sources. However, the temporal variation in the topology of social networks and the ongoing dynamic processes challenge our traditional source identification techniques that are considered in static networks. In this paper, we borrow an idea from criminology and propose a novel method to overcome the challenges. First, we reduce the time-varying networks to a series of static networks by introducing a time-integrating window. Second, instead of inspecting every individual in traditional techniques, we adopt a reverse dissemination strategy to specify a set of suspects of the real message source. This process addresses the scalability issue of source identification problems, and therefore dramatically promotes the efficiency of message source identification. Third, to determine the real source from the suspects, we employ a novel microscopic message spreading model to calculate the maximum likelihood (ML) for each suspect. The one who can provide the largest ML estimate is considered as the real source. The evaluations are carried out on real social networks with time- varying topology. The experiment results show that our method can reduce 60% - 90% of the source seeking area in various time-varying social networks. The results further indicate that our method can accurately identify the real source, or an individual who is very close to the real source. To the best of our knowledge, the proposed method is the first that can be used to identify message sources in time-varying social network

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Networking

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The process of Reproduction is natural and bearing a child is essential for any creature in this world to claim their existence. Generally every couple wants to give birth of their child but sometimes they are failure due to several causes like the problem of infertility, critical health issues, and some time it's biologically impossible. Nowadays infertility becomes a great problem that women have to face and in our Indian society a woman who has not a child is considered as an incomplete and inauspicious for any good social ritual. She has to tolerate undeserved comments and sometimes received worst behavior from society and even from her family members. Sometimes men have to face the same problem and in this way they are emotionally tortured by the society. So here it can be said that surrogacy is a new hope for these couples. Surrogacy is a contract between a fertile women and infertile couple or intended parent(s), where a fertile woman ready to give birth child on the behalf of intended parent(s). Generally on the basis of contract we found two types of surrogacy Altruistic surrogacy and Commercial surrogacy. Among this especially Commercial surrogacy is badly involved many ethical and legal issues. But here on this article I am going to discuss another ethical perspective from need based point of view. It helps us to rethinking about the ethical issues of surrogacy.

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surrogacy, surrogate mother, intended parent(s), commissioning parents, commercial surrogacy, altruistic surrogacy.

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Creative Commons Attribution 4.0 and The Open Definition

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In the current study, a framework is presented that makes use of a dataset of housing prices from various areas of Mumbai as well as important variables like the property's location, size, and existence of a swimming pool, among others. The information came from Kaggle Inc. Based on the aforementioned parameters, the technique is intended to predict the resale price of a property. An ensemble learning technique was used to improve prediction accuracy by mixing numerous machine learning algorithms rather of relying just on one. In order to provide a more accurate prediction result than utilising only one method, the ensemble model used in the study integrates Decision Tree, Linear Regression, and K-Nearest Neighbour algorithms. The system achieves the lowest predicting error with the use of this ensemble model, with the trained model showing a Mean Absolute Percentage Error (MAPE) of 16.09%.

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House Price Prediction, Linear Regression, Decision Tree, KNN, Ensemble Learning

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Creative Commons Attribution 4.0 and The Open Definition