Volume 11 | Issue 5

 Abstract

Smart Breath Analyzers were developed as sensing terminals of a telemedicine architecture devoted to remote monitoring of patients suffering from Asthma, Chronic Obstructive Pulmonary Disease (COPD) and home-assisted by non-invasive mechanical ventilation via respiratory face mask. The devices based on different sensors (Gas, Smoke Sensor and Volatile Organic Compounds (VOCs), relative humidity and temperature (R.H. & T) and Heart rate, respiration sensors) monitor the breath air exhaled. The system uses multiple sensors, including a heart rate sensor, temperature sensor, respiration sensor, gas sensor, sound sensor, humidity sensor, and smoke sensor, to collect real-time data on the user's respiratory health status. This data is then transmitted to an IoT cloud server, such as the Cayenne cloud server, for remote monitoring and management. The sensor raw signals are transmitted to National Health Service units / Doctor by TCP/IP communication through a cloud remote platform using IoT module. The work is a proof-of-concept of a sensors-based IoT system with the perspective to check continuously the effectiveness of monitoring and/or any state of exacerbation of the disease requiring healthcare. By a gas-mixing bench towards gas, smoke in environment and acetone concentrations in exhaled breath collected in a sampling bag were carried out to test the realized prototypes. This system uses analyze the data and detect early warning signs of Asthma and COPD attacks before they occur.

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 Keywords

COPD, Spirometry, lung inflammation and capnography.

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A mic preamp is a type of amplifier with the purpose of bringing mic level signals up to line level for use with professional equipment. Microphones output mic level signals and need preamps if they are to be used with mixing consoles, recording devices or digital audio workstations. There's a lot to know about microphone preamplifiers and their role with microphones. In this article, we'll discuss mic preamps in great detail to better your understanding of these largely necessary audio devices. A microphone preamplifier is an active electronic device designed primarily to supply gain to a mic signal and output the signal at line level. Mic level is the typically nominal level outputted by microphones. It ranges greatly between -60 dBV and -20 dBV. Line level is the professional standard for recording/mixing audio with a nominal level of +4dBu (1.78 dBV). A microphone preamplifier is designed to take a microphone signal at its input; apply an appropriate amount of gain (typically adjustable), and output a line-level signal. With the levels mentioned above, a good microphone preamplifier should be able to apply at least 60 dB of gain to bring low-level mic signals (typically from dynamic or ribbon mics) up to line level. Ribbon microphones, which notoriously output very low-level signals, sometimes require their own specialty preamplifiers. These preamps are able to provide a great amount of clean gain so that the ribbon mics can be used effectively.

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 Keywords

Noise contribution, Dynamic and Ribbon mics, low-level signals and Microphone

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Today, exploiting sentiment analysis has become popular in designing recommender systems in various fields, including the restaurant and food area. The analysis of users' opinions and the extraction of their food preferences lead to the provision of personalized recommendations. The semantic approach is used to cluster the name of foods extracted from users' comments and analyze their sentiments about them. Finally, nearby open restaurants are recommended based on their similarity to user preferences. Restaurant Recommendation System is an online system to search for restaurants. The system allows visitors to browse information about the restaurants, including searching for restaurants, viewing/giving recommendations, and viewing/rating restaurants. Visitors can only view recommendations and view rating results. If the user would like to give recommendations or rate restaurants, he or she has to login or sign up. Additionally, the user can check the history of previous recommendations. In addition to customer functions, the system also provides functions to the administrator that allows to manage the contents of the site, including editing customer info, restaurants, recommendations and ratings, etc.

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 Keywords

Machine Learning, Recommendation system, Clustering, Sentiment Analysis.

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Peeple leaves are used as medicinal plants. They are used as traditionally from ancient times in various herbal medicines such Ayurveda, siddha, and homeopathic. Peeple leaves contain flavonoids, alkaloids, and other chemical constituents which are used for various medicinal uses. The peeple plant leaves are used for heart attack treatment, menstrual cycle treatment, and reducing the level of cholesterol. Secondary metabolites present in plants have multiple roles to be treated as therapeutic. The present research emphasizes on traditional uses and clinical potential of peeple leaves is a large evergreen tree found throughout the world as the wild plant or cultivated .It has great mythological, religious, medical importance and considered as the oldest tree in Indian history.

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Peeple leaves, Kadha or Decoction, Reduce Cholesterol levels, Method and material, Pharmacological activity.

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Ayurved as Adravya Chikitsa, where no internal medicine as such is used to treat a disease but presence of some kind of things given or in simple way only Shita dhara or Shit parishek are used. This type of chikitsa can called in Ayurveda as adarvya chikitsa. There are two types of Chikitsa in Ayurveda such as Shita & Ushna. So in the treatment of disorders, both shit and ushna therapy plays a very important role. Shit treatment is essential in various disorders as a emergency treatment. So shita chikitsa plays as important role in chikitsa.

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Shita Chikitsa

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In distributed environment, load balancing is necessary for effective functioning. Load balancing for the cloud has developed into a very fascinating and significant study subject as a result of the rapid growth of cloud computing and the clients' increase need for more services and better outcomes. To create effective processes and algorithms for allocating the client's requests to accessible Cloud nodes, numerous techniques have been proposed. These methods seek to improve the Cloud's general performance while giving users better, more effective services. In this article, we examine the various strategies put out to address the load balancing and work scheduling issues in cloud computing. In order to give a comprehensive review of the most recent methods in the field, we discuss about and contrast various algorithms, particularly hybrid algorithms.

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Cloud Computing, Load Balancing, Task Scheduling, Cloud Storage, Replications.

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 Abstract

: A study was conducted by using the descriptive designs with 80 B.Sc. nursing students were selected by probability convenience sampling technique. They were assessed for the level of knowledge regarding organ donation by structured questionnaire and level of attitude regarding donation by 5 point likert scale. In majority of students 56.3% (45) are having moderate level of knowledge, 28.7% (23) were having adequate level of knowledge and 15 % (12) were having inadequate level of knowledge regarding organ donation. And also majority 86.25% (69) were having moderate favourable level of attitude about organ donation, 12.5% (10) were having favourable level of attitude and 1.25% (1) was having unfavourable level of attitude towards organ donation

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Knowledge, Attitude, organ donation

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 Abstract

Tax planning helps in the reduction of tax amount and helps in utilizing the various reliefs, deductions, exemptions and rebates as per the IT Act, 1961. Tax-saving is an important part of financial planning. Tax planning is the process of analyzing a financial plan or a situation from a tax perspective. With the help of tax planning, one can ensure that all elements of a financial plan can function together with maximum tax-efficiency. Tax Saving Instrument involves selection of the right kind of instruments / schemes with an aim of maximizing returns. The decision regarding the type of instrument depends upon the risk taking capabilities of individuals. Although there are various tax-saving instrument plans available in the market. People often get confused about which plan best suits them. In order to make you choose the best instrument plan for you depending on your risk appetite and preferences. The purpose of the study was to know the awareness level and perception on the Tax saving instruments and to determine the tax-saving instrument options which are preferred to save tax reason for preference of Instrument. This study also aims to know the most suitable and popular tax saving instrument used by salaried Individuals. Descriptive statistics used to analyze the data collected randomly through the 110 respondents from Bengaluru City. Both Primary and Secondary Data Used in this study. Data Collected were analyzed by using frequency and percentages and findings are interpreted accordingly.

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Income Tax, Tax saving instrument, Awareness and Perception, Tax Planning.

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 Abstract

The goal of this study is to streamline the identification and diagnosis of Haemoprotozoan diseases in cattle using machine learning algorithms to develop a model from a dataset of images and diagnoses gathered from local laboratories. The research is centered around three major Haemoprotozoan diseases, which are widespread and dangerous to cattle throughout India: Anaplasmosis, Babesiosis, and Theileriosis. The resulting model has been designed to operate on a hosted client-server web application, with a picture of the bloodstream sample transmitted to the server, which returns two parameters indicating whether the diagnosis is positive or negative and the type of disease. This has the potential to lower mortality rates by making the process quicker and more cost-effective. The model has been thoroughly tested and evaluated during the training and testing phases, with an emphasis on accuracy, speed, and cost-effectiveness. The ultimate model will be hosted on the client-server web application online, so that it can be used anywhere.

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 Keywords

Neural Networks, Image preprocessing, Keras, Softmax, Streamlit, Convolution.

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The Virtual Museum Android App is a mobile application designed to provide an immersive museum experience to users. Users can explore the virtual museum by navigating through different galleries and exhibits, interacting with objects, and learning about their history and significance. The app also includes audio and visual guides, as well as educational resources, to enhance the user's learning experience. The app would use graphical modelling and augmented reality technology to create a realistic and interactive environment for users to explore.

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virtual museum, museum, books, educational purpose, audio guidelines

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Creative Commons Attribution 4.0 and The Open Definition

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Abstract: -- The Main Objective of this research paper is to find out the early stage of lung cancer and explore the accuracy levels of various machine learning algorithms. After a systematic literature study, we found out that some classifiers have low accuracy and some are higher accuracy but difficult to reached nearer of 100%. Low accuracy and high implementation cost due to improper dealing with DICOM images. For medical image processing many different types of images are used but Computer Tomography (CT) scans are generally preferred because of less noise. Deep learning is proven to be the best method for medical image processing, lung nodule detection and classification, feature extraction and lung cancer stage prediction. In the first stage of this system used image processing techniques to extract lung regions. The segmentation is done using K Means. The features are extracted from the segmented images and the classification are done using various machine learning algorithm. The performances of the proposed approaches are evaluated based on their accuracy, sensitivity, specificity and classification time.

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Structural Co-occurrence Matrix (SCM), Classifier, Data Set, ROC curve, Malignant nodule, Benign nodule.

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 Abstract

Malware detection is a very important factor in security of internet oriented machines. The combination of different features is used for dynamic malware analysis. The different combinations are generated from APIs, Summary Information, DLL and Registry Keys Changed. Cuckoo sandbox is used for dynamic malware analysis, which is customizable, and provides good accuracy. More than 2300 features are extracted from dynamic analysis of malware and 92 features are extracted statically from binary malware using PEFILE. We used machine learning to discover different types of windows malwares. The dataset used to train the model has static and dynamic analysis of different programs. According to the data every one program was labeled as humanely or malware. There are 6 types of malwares in total: Backdoor, Trojan, Trojan Downloader, Trojan Dropper, Virus, and Worm. Static features are extracting from 39000 hateful binaries and 10000 benign files. Dynamically 800 humanely files and 2200 malware files are analyzed in Cuckoo Sandbox and 2300 features are extracted. The precision of dynamic malware analysis is 94.64% while static analysis precision is 99.36%. The dynamic malware analysis is not effective due to tricky and intelligent behaviors of malwares. The dynamic analysis has some restrictions due to controlled network behavior and it cannot be analyzed completely due to limited access of network.

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API, DLL, Registry Key, Static and Dynamic analysis

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ABSTRACT: The primary objective of this project is to design and implement a device to aid visually impaired individuals in navigating their surroundings with enhanced confidence and ease. The proposed device aims to alleviate some of the common challenges that visually impaired individuals face while walking. The project intends to mitigate the significant travel-related difficulties faced by visually impaired individuals, which arise due to their restricted ability to gather and interpret visual information. This lack of awareness about their surroundings makes it challenging to navigate both indoor and outdoor environments and increases their risk of accidents and injuries. "There are approximately 37 million people across the globe who are blind according the (WHO) World Health Organization [1]." And if talking about numbers of blind people in India, then "one out of every three blind people in world is Indian i.e., estimated 15 million blind people love in India [2]." Thus, the project aims to develop an All-In-One device that would provide as a guidance to the blind people. The paper focusses on constructing a device for visually impaired (or blind) people that would support them to travel independently. The Technology introduced in the paper serves as a solution for visual impaired people that alerts them over obstacles coming between their ways, alerting for any fluid or moisture in the path and even tracking and sending the location of user and also other functionalities that make it fully smart.

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Keywords-- Visually impaired, Smart shoes, Sensors, Guidance device, Obstacle detection, Fluid or water detection, Location tracking, Smart device, Assistive technology, Arduino, Blind Navigation system, wireless.

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 Abstract

Objectives: To find effectiveness of proprioceptive training exercises in upper extremity on reaction time in batsmen by using ruler drop test after 3 weeks Methods:An experimental study was performed from Oct22 to April 23 A convenient sampling technique was applied to select 38 samples Results: Paired t test was done The result obtained for upper extremity proprioceptive training exercises on reaction time in batsmen by Rular drop test suggests significnce as P value obtained was (<0.0001) Conclusion: According to results it can be concluded that proprioceptive exercise training for upper extremity shows significantly beneficial in improving reaction time in batsmen.

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Batsmen, Reaction time, proprioceptive exercises, ruler drop test

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Tridosha theory is the foundation of Ayurvedic science. One of the three doshas, called Pitta, is very important for digestion and metabolism. There are five different varieties of pitta dosha: Pachaka, Ranjaka, Alochaka, Bhrajaka, and Sadhaka. Food digestion, Sara and Kitta's Vibhajan, and feeding the Agneya component of Pitta, which is distributed throughout the body, are all tasks carried out by the Pachaka Pitta. It also goes by the name Jatharagni. After aiding in food digestion, this Agni form Pitta divides the Sara and Kitta Bhaga. Due to its position, it nourishes and gives Pitta power to relax. It is amply demonstrated in our book that Pachaka Pitta is accountable for Aahar Pachan. On the other hand, modern science has established via numerous research that several digestive fluids are responsible for food digestion. All digestive enzymes, such as amylolytic, proteolytic, and lipolytic enzymes, can be compared to pachaka pitta, as suggested by the functions of this substance. The goals of digestive enzymes, gastrointestinal hormones, and local hormones can be linked to the actions of Pachaka Pitta.

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Pachaka, Pitta, Shareera, Kriya, Digestive Enzymes.

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 Abstract

Water bodies have a huge aquatic ecosystem within them. Any high concentration of suspended solids can cause numerous issues for aquatic life by blocking light from reaching submerged vegetation. Hence, there is a need for a solution to remove this trash from the water bodies. The Water cleaning boat Project is an endeavour to clean water bodies with an ambitious mission: to achieve cleaner water-bodies that are free from suspended solids; to reduce human intervention and human labour. This project gives a solution of automated river cleaning with the help of a tread mill arrangement. The RF transmitter and receiver are used to control the cleaning machine. The battery energizes the conveyer belt to clean suspended solids in the river, then is stored in the boat itself to aside. A camera affixed to the boat helps in monitoring the movement of the boat in the necessary directions. The Water-boat Project not only concentrates on technology but also believes that using Science, Technology and Community it is possible to build a sustainable environment.

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river water cleaning boat, pollution free water bodies, dust collecting boat-

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 Abstract

This project is a song recommendation system, which maps facial expressions to detect the current mood of the user and recommends the songs based on the analysis. This project uses various modules like Mediapipe and Keras for emotional analysis, OpenCV and Streamlit for making the web app and the Streamlit-WebRTC to access user's web camera for mapping facial expressions in real time. The system provides a personalized music experience which in result enhances the user's music listening experience. By analyzing the user's facial expressions, the application can identify the user's current emotional state and recommend songs that match their mood. The web app provides a simple yet user-friendly interface which allows users to easily interact with the system and listen to songs.

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Open CV, Keras, Mediapipe, Streamlit, Streamlit-WebRTC

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Existing techniques in user-individualized recommendation scenarios have faced significant challenges due to the vast amount of music data and the wide variety of listening habits. Many prior music recommendation algorithms only considered temporal links between records of sequential listening, ignoring the use of other data like the artist and album. A person's mood can be controlled, and profound emotional experiences can be evoked through music. The study of music recommendation services has advanced significantly since the introduction of online streaming services. The importance of information retrieved from lyrics and acoustic content has been disregarded by contemporary methods that leverage users' listening histories to inform session-based song suggestions. We approach song prediction using a variety of modalities, such as tags, lyrics, and acoustic content. We suggest a novel approach to ensemble learning for acoustic characteristics in this study. By combining poetic and acoustic data, our model outperforms current state-of-the-art models in terms of performance. Additionally, we conduct research to determine how users' psychological well-being affects the effectiveness of our models. Particularly, a piece of music frequently originates from and is part of an album by a particular musician. Singer and album information, which is regarded as music metadata, can be used as crucial supplementary information between various music pieces and may greatly affect the user's musical preferences. In this paper, we concentrate on the sequential recommendation task for music while considering additional information, and we propose a novel Graph based Attentive Sequential model with Metadata (GASM) that uses metadata to enhance music representations and efficiently mine user listening behaviour patterns. To be more specific, we first model the relationships between various types of nodes (user, music, singer, album) using a directed listening graph, and then we utilise graph neural networks to learn their latent representation vectors. The user's musical preference is then divided into long- term, short-term, and dynamic components using customised attention networks. Finally, GASM combines three different sorts of preferences to anticipate the upcoming (new) song in line with the user's musical interests. Three real-world datasets have been the subject of extensive testing, and the findings indicate that the suggested method, GASM, performs better than baselines. From a long list of available songs, choosing one that matches a user's preferences can be challenging. The primary problem with music software recommendations is that they correspond to song recommendations. Although this might not seem to be a problem at first, any typical music recommendation engine will undoubtedly notice a pattern and provide a monotonous selection of music, disappointing the user and making them lose interest. To keep the recommendations exciting and appealing to the user's tastes, our programme overcomes this problem by mixing in fresh music from different genres that matches the user's interests. Using machine learning and KNN, we present a customised music recommendation system in this work. We suggest a collaborative filtering and content filtering recommendation algorithm for the personalised music recommendation system that combines the output of the network with the log files to recommend music to the user. User data from the log file is used by the suggested technique to generate song recommendations for each recommendation. While collaborative approaches forecast potential preferences using a matrix with scores on various songs, content-based approaches make recommendations based on the similarities between the contents or attributes of two songs.

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Keywords:- KNN, Machine learning, Collaborative filtering, GASM

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 Abstract

Information and communication technology have a significant role in building the new global economy and causing fast societal changes. New ICT technologies have significantly transformed people's lives during the last decade. The current era is the age of technology, and technology plays an important part in our everyday life. The present study tries to investigate the effect of technological use in the teaching-learning process on the pupil-teachers' of B. Ed institutions. The investigation carried out to find the signifcance difference among urban and rural B.Ed pupil-teachers; male and female B.Ed pupil-teachers' and science education and social sciences B.Ed pupil-teachers'.

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Effect, Technology, Use, B.Ed pupil-teachers'

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Our Aims to provide effective and active rehabilitation for patients suffering from upper limb paresis, using gaming based a therapy technique. By disguising the tasks into further amusing, patients are motivated to train for longer and more constantly. The advantage of this system can be a tone- managed, at- home remedy system; reducing fatigue for physical therapists, and the time needed for therapist- case sessions. The system incorporates a virtual reality (VR) terrain displaying both the games and a mortal model as feedback of the patients' conduct whilst playing the games. The game was developed, each targeting enhancement of muscle strength, control, delicacy, and speed. The difficulty of the games can be varied to suit several impairments and patient progress is covered. The games are played using a band. The successful advancements with lower costs associated with this system, are pronounced advancements for patients suffering from such an enervating condition.

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 Keywords

Paralysis, Rehabilitation, Stroke, Upper extremity, Video games, Virtual reality.

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Creative Commons Attribution 4.0 and The Open Definition