Volume 11 | Issue 4 |

 Abstract

This paper attempts to focus on role of project exports in equilibrium of country's favourable BOP. A balance of payment is an essential element in indicating economic and financial details of a country. BOP statement also an indicator and determines whether the currency of a country is appreciating or depreciating for a given period of time. If country has a favourable BOP that indicates a nation enjoys surplus trade balance and vice- versa. One of the measures to correct disequilibrium in BOP is to export promotion of project exports.

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 Keywords

Foreign Trade, Project Export, Balance of Payment

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Creative Commons Attribution 4.0 and The Open Definition

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The Ultrasonic Sonar System controlled by Arduino and ESP32 cam is designed to detect objects within its range. It consists of two ultra-sonic sensors, a servo motor, an ESP32 cam controller, and an IoT interface. The ultrasonic sensor is attached to the servo motor, which rotates 180 degrees on either side, covering a 360-degree field of view. The system provides a visual representation of objects' angles, positions, and distances on a software called Processing IDE, based on Java programming. The system is controlled through Arduino, which interfaces with the sensor and display device. The ESP32 cam, an IoT-based microcontroller with a built-in Camera Module, sends live streaming to a local IoT server. The system also includes an automatic laser shooting mechanism. The Ultrasonic Sonar System has applications in navigation, positioning, object identification, mapping, spying or tracking, shooting, and other fields. It is suitable for indoor applications and is a cost-effective solution for those looking to implement obstacle-detection systems. Overall, this system provides an effective solution for detecting objects within a defined range.

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 Keywords

Arduino Nano, Ultrasonic sensors, ESP32 Cam, Servo motor, Lasers, LEDs.

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 Abstract

Artificial intelligence (AI) and Machine learning (ML), and Deep Learning (DL) have been applicable practicable due to the advancements in computing facilities. Almost every application in general in Industry 4.0 is going to use these advanced mathematical tools and techniques of AI and ML and DL. SMART Healthcare is not an exception for this. In healthcare applications a lot of imaging data is generated as far as diagnostic imaging modalities like Magnetic Resonance Imaging (MRI) are concerned. MR imaging is a very popular noninvasive diagnostic imaging modality with very good soft tissue contrast. Therefore, imaging data resulting from MR imaging is used in this research. Although, there are several other medical imaging modalities. The same MRI has several clinical applications beyond routine imaging, which include functional MR Imaging (fMRI) of brain, Cardic MR imaging, MR Spectroscopy (MR) and MR Spectroscopic Imaging (MRSI), and many more. It requires that the data be processed automatically and in real time for the modern SMART healthcare diagnostic purpose. In spite of the technological developments in Magnetic Resonance Imaging, clinical applications demand accurate, reliable and real time data processing, for the purpose of making diagnostic decisions. Internet of things (IOT) has made it possible to collect the real time data and there are modern Data Analytics methods which make it possible to derive meaningful conclusions from the medical information that is available. This is then processed for providing medical diagnostic information to the medical expert, in a suitable form. In this thesis, the applicability of AI, ML and DL methods have been proposed to be investigated as applied to MR Imaging to make it suitable for providing SMART Healthcare solutions. Not only obtaining the diagnostic information but also the usability aspects of AI, ML and DL based approaches shall be attempted in this research. MR Imaging data from diagnostic centers or Hospitals, shall be used for this purpose. The results shall be compared with the standards methods in MR imaging and also verified with the experts from medical field.

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 Keywords

Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), SMART Healthcare, Magnetic Resonance Imaging (MRI), Signal and Image Processing

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Parkinson's disease (PD) is a common and disabling pathology that is characterized by both motor and non-motor symptoms and affects millions of people worldwide. The disease significantly affects quality of life of those affected. Many works in literature discuss the effects of the disease. The most promising trends involve sensor devices, which are low cost, low power, unobtrusive, and accurate in the measurements, for monitoring and managing the pathology. Objectives: This review focuses on wearable devices for PD applications and identifies five main fields: early diagnosis, tremor, body motion analysis, motor fluctuations (ON-OFF phases), and home and long-term monitoring. The concept is to obtain an overview of the pathology at each stage of development, from the beginning of the disease to consider early symptoms, during disease progression with analysis of the most common disorders, and including management of the most complicated situations. Parkinson's Disease is a nervous system disorder and is progressive in nature. It affects body movements. Symptoms begin with a hardly noticeable tremor in body parts. The disorder results in stiffness and slowing down of movements. It's a debilitating neurodegenerative disease and cannot be diagnosed through blood tests. Parkinson' s disease mostly affects the people above 60 and is one of the common diseases among war veterans. We use ML algorithm XG BOOST to diagnose Parkinson's Disease with maximum accuracy using a Sensor dataset. Machine learning algorithms XG BOOST help to generate useful content from it. To increase the lifespan of elderly people the machine learning algorithms are used to detect diseases in the early stages

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 Keywords

Internet of Things (IoT), Robot control system, Biometric sensor, Neurodegenerative disorder and Dopamine

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The prevention and solution of plant diseases is a major challenge in agriculture, with traditional methods relying on visual observation and manual recording. However, computer technologies have been increasingly implemented to aid in the prevention and solution of plant diseases. Bioinformatics, machine learning, big data analytics, and imaging technologies are some of the key technologies that have been implemented to achieve these goals. Case studies have shown the benefits of implementing computer technologies in plant pathology, with the potential to revolutionize agricultural production by improving disease management and optimizing crop management practices. As technology continues to advance, the potential for computer technologies in plant pathology will continue to grow, offering new solutions to agricultural challenges. Computer technologies have revolutionized plant pathology by providing researchers with a powerful set of tools for collecting, analyzing, and managing large volumes of data. These technologies enable researchers to study the genetic, molecular, and biochemical mechanisms underlying plant diseases and to develop new strategies for disease management. These technologies have been used to develop models for predicting disease outbreaks, to identify disease-resistant plant varieties, and to develop new chemical and biological control methods. Overall, computer technologies have greatly expanded our understanding of plant diseases and have provided new ways to manage these complex and economically important problems.

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 Keywords

Bioinformatics, machine learning, big data analytics, and imaging technologies, agriculture, plant, diseases

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Currently, the concept of a smart city is implemented through elements such as smart farming, smart emergency services, and smart traffic analysis, among others. A smart city should also have an automated system for smart drainage since the drainage system is one of society's necessities. The sewage system in India is one of the biggest problems. Poor upkeep causes sewage water to periodically mix with drinking water and overflow onto the streets, endangering the health of nearby residents. We suggest the Smart Drainage Monitoring System model to solve this issue. The subsurface drainage system's water level, water flow rate, and gas level will all be monitored by this planned system.The measured values will be evaluated, saved in the cloud, and used to update an app that tracks the health of the drainage system. A notification addressing the problem will be delivered to our mobile when the conditions turn critical (reach threshold values). The goal is to develop a solution utilising cutting-edge IOT technologies to obtain a thorough examination of the data gathered by various IOT sensors

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 Keywords

SMART DRAINAGE MONITORING SYSTEM

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 Abstract

शोध पत्र का सार पंचायती राज व्यवस्था भारत के राष्ट्र निर्माण के गौरव में एक अमिट छाप छोड़ती है। स्थानीय स्वशासन हमारे शक्तियों के विकेंद्रीकरण और पारदर्शिता का परिणाम है। पंचायती राज संस्थानों में ग्राम ब्लाक और जिला स्तर पर परिलक्षित संगठन और उनका बुनियादी इतिहास हमारे सशक्त भारत की नींव है। विभिन्न समितियों ने समय-समय पर इसमें सुधार की रूपरेखा प्रस्तुत की है। पंचायती राज संस्था का विकास उसकी शक्तियां और कार्य और उसमें सुधार की गुंजाइश ओं का एक बेहतर लेख इस शोध पत्र के माध्यम से दिया गया है।

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 Keywords

कुंजी शब्द- स्थानीय स्वशासन, पंचायत समिति, सामाजिक क्रांति, ग्राम पंचायत, विकेंद्रीकरण

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 Abstract

Practical experimentation is an essential component of teaching process. When the course contents have to be delivered to the students in a classroom, the theoretical background of the topic has to be made clear, which time and again is provided through series of Theory sessions or lectures. To support these theory sessions and enhance the comprehensive understanding of the topic, practical experiments are designed by the Expert teachers. Students get limited time span to perform the experiment and understand as well as analyze the results. The instructors explain and demonstrate the experimental setup during the same time span which leaves very less time for actual experimentation and repetition of the experiment. As a result of this, most of the students do not understand the concept and application of the experimentation. In this research work a methodology of Flipped classroom is proposed where the Educator will make a video clip of every experiment as per the syllabus for a class. In this video session, the theoretical background will be explained at the beginning and then the demonstration related to making connections, noting down the observations, debugging the errors and concluding the experiment will be covered. These videos will be shared with the students through internet well ahead of the experimentation schedule so that students can go through them until they understand as per their grasping level and spend more practice time in performing experiments in the Laboratory.

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 Keywords

Flipped Classroom, Practical experimentation, video sessions, Comprehensive Understanding, More practice time.

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 Abstract

In India, children are recognized as both victims and offenders under the legal system. The legal framework for the protection of children in India is mainly governed by the Constitution of India , the Juvenile Justice (Care and Protection of Children) Act, 2015 , and the Protection of Children from Sexual Offences (POCSO) Act, 2012.Despite the legal framework in place, children in India continue to face numerous challenges as victims and offenders. There are various socio-economic factors that contribute to the vulnerability of children in India, such as poverty, illiteracy, and lack of access to healthcare and education. Additionally, there are often gaps in the implementation of laws and policies aimed at protecting children, leading to a lack of adequate protection and support. This paper aims at analyzing the legal framework to deal with children as offenders and victims keeping in mind the special provisions formulated like the reverse burden of prrof. It analyses the impact of these special provisions on the rights of others.

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 Keywords

Juvenile Justice, POCSO. Reverse burden of proof

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 Abstract

Indian Railways is the largest railway network in Asia and additionally world's second largest network operated underneath a single management. Due to its large size it is difficult to monitor the cracks in tracks manually. This paper deals with this problem and detects cracks in tracks with the help of ultrasonic sensor attached to moving robot. Ultrasonic sensor allows the device to moves back and forth across the track and if there is any fault, it gives information to the cloud server through which railway department is informed on time about cracks and many lives can be saved. This is the application of IoT, due to this it is cost effective system. This effective methodology of continuous observation and assessment of rail tracks might facilitate to stop accidents. This methodology endlessly monitors the rail stress, evaluate the results and provide the rail break alerts such as potential buckling conditions, bending of rails and wheel impact load detection to the concerned authorities. Here we proposed an innovative approach to detect railway track crack as this system detects crack based on image processing. Many image preprocessing steps is used to detect railway track crack. As image is prone to noise. System converts image to grayscale image and uses filtering to remove noise from image. Noise removal helps to detect crack more accurately. Image luminous level is increased and image is converted to binary image. This helps system to detect only crack and helps to remove other unwanted objects. Image once converted to binary image, holes are filled by using image processing method this helps to reject all smaller objects which are not required for crack detection. Crack is detected based on the intensity value. Intensity value is for accuracy.

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 Keywords

IoT, NodeMCU ESP32, Ultrasonic sensor, IR Sensor.

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Creative Commons Attribution 4.0 and The Open Definition