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Showing papers in "International Journal of Advanced Research in Science, Communication and Technology in 2022"


Journal ArticleDOI
TL;DR: A brief overview of some of the most significant deep learning schemes used in computer vision problems, that is, Convolutional Neural Networks, Deep Boltzmann Machines and Deep Belief Networks, and Stacked Denoising Autoencoders are provided.
Abstract: Over the last years deep learning methods have been shown to outperform previous state-of-the-art machine learning techniques in several fields, with computer vision being one of the most prominent cases. This review paper provides a brief overview of some of the most significant deep learning schemes used in computer vision problems, that is, Convolutional Neural Networks, Deep Boltzmann Machines and Deep Belief Networks, and Stacked Denoising Autoencoders. A brief account of their history, structure, advantages, and limitations is given, followed by a description of their applications in various computer vision tasks, such as object detection, face recognition, action and activity recognition, and human pose estimation. Finally, a brief overview is given of future directions in designing deep learning schemes for computer vision problems and the challenges involved therein.

89 citations


Journal ArticleDOI
TL;DR: The objective of the project is to promote green power and to improve smartness of electric vehicle by monitoring the battery parameters such as voltage, temperature, current and charge avaibility by using IoT techniques.
Abstract: This paper describes the application of IoT Technology for monitoring different parameters of battery of electric vehicle. Electric vehicle totally depends upon the source of energy from the battery. In this project, the idea of monitoring the performance of the vehicle using IoT techniques is proposed, so that monitoring can be done easily and directly. The objective of the project is to promote green power and to improve smartness of electric vehicle by monitoring the battery parameters such as voltage, temperature, current and charge avaibility. Also, these values displayed in cloud, which brings the concept of Internet of Things (IoT). The IoT based battery monitoring system consist of two major parts i) Monitoring device and ii) User interface. Based on experimental results, the system is capable to detect battery performance.

22 citations


Journal ArticleDOI
TL;DR: A smart helmet can detect the accident's locations also save lives and makes two-wheeler driving safer from previously and is propounded in this paper.
Abstract: A motorcycle frequently called motorbike or two-wheelers, which is the most used than another form of automobiles because of its low price. But another side, this is the most unsafe automobile. The accident can happen for driving fast or drunk driving. Safety and security in vehicle traveling are a pre-eminent concern for all. With the rapid urbanization and staggering growth of transport networks like two-wheeler vehicles, safety on the roads and security on the bike has emerged as an inescapable priority for us. It has expanded the rate of accidents, which leads to several damages with loss of lives. In many circumstances, we cannot able to detect the accident's location. A helmet is a form of protecting gear worn to keep safe the head from injuries. More specifically, the helmet aids the skull in protecting the brain. A smart helmet can detect the accident's locations also save lives and makes two-wheeler driving safer from previously. This paper propounds a smart helmet system to avoid the accident. The system divides into three parts helmet circuit, automobile circuit, and mobile application. At first, the helmet circuit has IR and alcohol detection sensor. The automobile circuit has a 3-axis accelerometer, Bluetooth module, relay, and load sensor. The helmet circuit sends a signal to the automobile circuit to start if the helmet is wearied and no alcohol detects. Then the automobile circuit checks the status of the load to start. 3-axis accelerometer senses crash or hit. After detecting an accident mobile application sends the accident location automatically to police and emergency contact number via the database.

11 citations


Journal ArticleDOI
TL;DR: Along with machine learning models, a deep neural network was used on the same dataset, and the deep Neural network was found to have the greatest accuracy of 99.6%.
Abstract: Chronic Kidney Disease is one of the most serious illnesses nowadays, and it is vital to have a good diagnosis as soon as possible. Machine learning has proven to be effective in medical therapy. The doctor can diagnose the ailment early with the use of machine learning classifier algorithms. This article has examined Chronic Kidney Disease prediction from this standpoint. The Chronic Kidney Disease dataset was obtained from the University of California at Irvine's repository. The artificial neural network, C5.0, Chi-square Automatic interaction detector, logistic regression, linear support vector machine with penalty L1 & with penalty L2, and random forest classifier techniques were used in this study. The dataset was also subjected to the significant feature selection technique. The results were computed for each classifier using I full features, (ii) correlation-based feature selection, (iii) Wrapper method feature selection, (iv) Least absolute shrinkage and selection operator regression, (v) synthetic minority over-sampling technique with least absolute shrinkage and selection operator regression selected features, and (vi) synthetic minority over-sampling technique with full features. The results show that in synthetic minority over-sampling technique with full features, LSVM with penalty L2 has the maximum accuracy of 98.86 percent. Along with precision, recall, F-measure, and area, accuracy, precision, recall, and area. The GINI coefficient and beneath the curve have been computed, and the results of various algorithms have been compared in the graph. After synthetic minority over-sampling technique with full features, the least absolute shrinkage and selection operator regression selected features with synthetic minority over-sampling approach produced the best results. Again, the linear support vector machine had the maximum accuracy of 98.46 percent in the synthetic minority over-sampling technique with the least absolute shrinkage and selection operator selected features. Along with machine learning models, a deep neural network was used on the same dataset, and the deep neural network was found to have the greatest accuracy of 99.6%.

9 citations


Journal ArticleDOI
TL;DR: IOT has changed the way of living of people into a high-profile way and has impact in almost various sector which has given a positive impact on world, along with various advantages it has some challenges and disadvantages too.
Abstract: Today, Internet has become the most important and a revolutionary invention which has touched almost every corner of the world and has affect human life in tremendous ways. IOT, Internet of things is simply an interaction between the physical and digital world. It is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers (UIDs). The communication taking place in today's world is basically in the form of human-human or human-machine but IOT has the ability for a great future where communication will take place in the form of machine-machine also. IOT has changed the way of living of people into a high-profile way and has impact in almost various sector which has given a positive impact on world. Also, along with various advantages it has some challenges and disadvantages too. This paper mainly focused on all the importance point related to IOT, how it works, its component, architecture, characteristics, applications, advantages-disadvantages and many more. IOT is overall a vast topic to discuss and talk about.

8 citations


Journal ArticleDOI
TL;DR: A better understanding of the cloud computing is provided and important research issues in this burgeoning area of computer science are identified.
Abstract: On demand or on pay per use of resource such as: network, storage and server these all facilities are provided by cloud computing through internet is called cloud computing. Although, cloud computing is facilitating the Information Technology industry, the research and development in this arena is yet to be satisfactory. We have contribution in this paper is an advanced survey focusing on cloud computing concept and most advanced research issues. This paper provides a better understanding of the cloud computing and identifies important research issues in this burgeoning area of computer science. Section 1 contains the introduction, in the section 2, we provide an overview of cloud computing, section 3 contains the security architecture and section 4 will focus on the research issues and security issue. We conclude the paper on section 5 along with references.

5 citations


Journal ArticleDOI
TL;DR: The size, shape, and material qualities of nanoparticles can be used to classify them into several categories as mentioned in this paper , such as hard, such as silica particles and fullerenes, or soft, like nanodroplets.
Abstract: The size, shape, and material qualities of nanoparticles can be used to classify them into several categories. Some classifications distinguish between organic and inorganic nanoparticles; nevertheless, the classification of nanoparticles is often determined by their applications or may be connected to how they were formed. Nanoparticles can be found in nature and are also produced as a result of human activity. Nanoparticles have unique material properties due to their sub-microscopic size, and they may find practical uses in a range of fields. A nanoparticle is a distinct nano-object with all three Cartesian dimensions smaller than 100 nm, according to the International Organization for Standardization (ISO). Two-dimensional nano-objects and one-dimensional nano-objects are both described in the ISO standard. However, the definition is later changed. Nanoparticles can also be classed as hard, such as silica particles and fullerenes, or soft, such as nanodroplets. For millennia, nanometreshave been used to study biological systems and to develop a variety of materials such as colloidal dispersions, metallic quantum dots, and catalysts. For example, more than a thousand years ago, the Chinese used Au nanoparticles as an inorganic dye to provide red colour to their ceramic porcelains. Although a complete study on the creation and properties of colloidal gold was only published in the middle of the nineteenth century, its use has a long history. Colloidal Faraday's gold dispersion, was created in 1857. Nanotechnology is a technology for designing, fabricating, and applying nanostructures and nanomaterials in general. Fundamental knowledge of the physical properties and phenomena of nanomaterials and nanostructures is also required for nanotechnology. Nanoscience is the study of basic links between physical characteristics and events in nanoscale scale materials. Nanotechnology is described in the United States as materials and systems with nanoscale structures and components that display innovative and considerably improved physical, chemical, and biological properties, phenomena, and processes. Here are some of the techniques for making nanomaterials.

4 citations


Journal ArticleDOI
TL;DR: This paper presents a comprehensive review of the state-of-the- art in the area of diabetes opinion and vaticination using data mining and gives a comprehensive bracket and comparison of the ways that have been constantly used for opinion andvaticination of diabetes grounded on important crucial criteria.
Abstract: Diabetes is one of the most fleetly growing habitual conditions, which has affected millions of people around the globe. Its opinion, vaticination, proper cure, and operation are pivotal. Data booby-trapping grounded soothsaying ways for data analysis of diabetes can help in the early discovery and vaticination of the complaint and the affiliated critical events similar as hypo/ hyperglycemia. Multitudinous ways have been developed in this sphere for diabetes discovery, vaticination and bracket. In this paper, we present a comprehensive review of the state-of-the- art in the area of diabetes opinion and vaticination using data mining. The end of this paper is twofold; originally, we explore and probe the data mining grounded opinion and vaticination result in the field of glycemic control for diabetes. Secondly, in the light of this disquisition, we give a comprehensive bracket and comparison of the ways that have been constantly used for opinion and vaticination of diabetes grounded on important crucial criteria. Also, we punctuate the challenges and unborn exploration directions in this area that can be considered in order to develop optimized results for diabetes discovery and vaticination.

4 citations


Journal ArticleDOI
TL;DR: Recent developments in IoT technology are described and future application and research challenges are addressed and the IoT opens the way to a new dimension in research.
Abstract: As the Internet of Things (IoT) develops as the next phase in the Internet's growth, it's critical to identify the numerous potential domains of IoT applications and the research agenda connected with these applications. Become. The Internet of Things is predicted to transform everything from smart cities to smart agriculture, logistics, retail, smart homes, and smart ecosystem permeate almost every aspect of everyday life. Today's IoT technology has improved significantly over the last few years, but there are still many issues that need attention. As the concept of IoT emerges from heterogeneous technologies, many research challenges inevitably arise. The fact that the IoT is so widespread that it affects almost every area of our lives has become a significant research topic for research in various related areas such as information technology and computer science. Therefore, the IoT opens the way to a new dimension in research. This white paper describes recent developments in IoT technology and addresses future application and research challenges.

4 citations


Journal ArticleDOI
TL;DR: The System deals with better production and cancelling out all factors leading to crop failure and will give best results based on the necessity of the crops, which will help to deal with the requirement and crisis faced during crop productivity.
Abstract: With the increase of world population, the availability of food to all inhabitants on globe is one of the significant challenges. These challenges need to be addressed by adopting innovative options to improve the soil capacity and the safety of environmental resources. The availability of real-time vital parameters related to farming such as moisture, temperature, weather, and water management as well as predictive actions against the changes in parameters can provide great help to deal with these challenges. Internet of Things (IoT) is an evolving technology, has great potential to play and prevail its miraculous role in almost every field. IoT is a network of things that are capable of self-configuring network. The development of intelligent IoT based Smart farming is day by day getting its space in developed countries. It facilitates towards precision agriculture and turning the face of agriculture production. Subsequently, it is reducing spoilage of resources such as water, operating cost. The availability and development of cost effective smart miniaturized sensors, processors and communication technologies has made IoT based smart farming feasible. In the System deals with better production and cancelling out all factors leading to crop failure and will give best results based on the necessity of the crops, which will help to deal with the requirement and crisis faced during crop productivity.

4 citations


Journal ArticleDOI
TL;DR: Generative Adversarial Networks (GANs) are a deep learning based generative model which is basically made up of two competing neural network models which compete with each other and are able to analyze, capture and copy the variations within dataset.
Abstract: Generative Adversarial Networks (GANs) are a deep learning based generative model. GANs are a model for training a generative model and it is common to use deep learning models. Generative Adversarial Network(GANs) are a powerful class of neural networks that are used for unsupervised learning. GANs are basically made up of two competing neural network models which compete with each other and are able to analyze, capture and copy the variations within dataset. GANs achieve high level realism by pairing a generator which learns to produce a target output with a discriminator which learns to distinguish true data from the output of the generator. GANs used for Image Synthesis generates high resolution images. Text to face generation is a sub domain of text to image synthesis, and it has a huge impact along with the wide range of applications on public safety domain

Journal ArticleDOI
TL;DR: In this article , a project mainly focuses on extracting the required information from the resumes using Natural Language Processing Techniques (NLP) for shortlisting the candidates and also helps the companies and high-level firms to select the quality employees from the extracted information.
Abstract: Manual extraction of information from the resume is very difficult and time taking process. The project mainly focuses on extracting the required information from the resumes using Natural Language Processing Techniques. The large set of resumes can be parsed using this kind of system. This project helps us know about the needed and important aspects while shortlisting the candidates and also helps the companies and high-level firms to select the quality employees from the extracted information. This project also helps to improve the shortlisting the process.

Journal ArticleDOI
TL;DR: In this paper , a web application has been developed to help the farmers in making appropriate decisions regarding the cultivations with the help of machine learning, where the authors focused on predicting the appropriate crop based on the climatic situations and the yield of the crop by using supervised machine learning algorithms.
Abstract: Agriculture plays an important role in Indian economy. But now-a-days, agriculture in India is undergoing a structural change leading to a crisis situation. The only remedy to the crisis is to do all that is possible to make agriculture a profitable enterprise and attract the farmers to continue the crop production activities. As an effort towards this direction, this research paper would help the farmers in making appropriate decisions regarding the cultivations with the help of machine learning. This paper focuses on predicting the appropriate crop based on the climatic situations and the yield of the crop based on the historic data by using supervised machine learning algorithms. In addition, a web application has been developed.

Journal ArticleDOI
TL;DR: A short depiction of the utilizations of CNNs in two regions will be introduced: first, in PC vision, or at least, scene marking, face acknowledgment, activity acknowledgment, and picture arrangement, and normal language handling, and the fields of discourse acknowledgment and text characterization.
Abstract: As of now, profound learning is generally utilized in an expansive scope of fields. A convolutional brain organizations (CNN) is turning into the star of profound learning as it gives the best and most exact outcomes while breaking true issues. In this work, a short depiction of the utilizations of CNNs in two regions will be introduced: First, in PC vision, by and large, or at least, scene marking, face acknowledgment, activity acknowledgment, and picture arrangement; Second, in normal language handling, that is to say, the fields of discourse acknowledgment and text characterization.

Journal ArticleDOI
TL;DR: In this paper , the authors tried to study about the investment options preferred by the working women and how well do they perceive about different investment avenues available, with the help of convenient sampling technique.
Abstract: The subjective characteristic of investment makes the investment perception more complex. In the today’s world, our economy is blessed with a large number of investment avenues. Each of these avenues has their own peculiarity as well as their own pros and cons. People make their investment decisions based on analyzing all the factors of investment like risk, return, time horizon, taxability and various other crucial factors of different avenues. In the present study, the researcher attempts to study about the investment options preferred by the working women and how well do they perceive about different investment avenues available. The data was collected from workingwomen of Kozhikode District in various sectors, with the help of Convenient Sampling Technique. 20 investors each of selected six investment avenues constitute the population for the study. Findings of the study will help to know the investment perception of the working women in Kozhikode District towards different avenues.

Journal ArticleDOI
TL;DR: In this article , the authors study the problem of controlling loan default in the banking system and compare the nature of different methods and their comparison, and show that the right predictions are very important for the maximization of profits.
Abstract: In our banking system, banks have many products to sell but main source of income of any banks is on its credit line. So they can earn from interest of those loans which they credits. A bank's profit or a loss depends to a large extent on loans, whether the customers are paying back the loan or defaulting. By predicting the loan defaulters, the bank can reduce its Non- Performing Assets. This makes the study of this phenomenon very important. Previous research in this era has shown that there are so many methods to study the problem of controlling loan default. But as the right predictions are very important for the maximization of profits, it is essential to study the nature of the different methods and their comparison.

Journal ArticleDOI
TL;DR: A solar power monitoring system by the IoT is proposed based on the implementation of new cost-effective methodology based on IOT to remotely monitoring a solar plant for performance evaluation.
Abstract: As we know in the present time solar energy is at its booming stage compared to other sources, as it's the perfect alternative for all conventional sources required for electrical energy generation. This paper proposes a solar power monitoring system by the IoT. By using the Internet of things technology for supervision the solar power generation can greatly enhance the performance, monitoring and maintenance of the plant. With gradually increasing the technologies and the cost of renewable energy sources are going down globally encouraging the solar power plant installation. In this project the output of the solar panels is depends upon the radiation of heat. The project is based on the implementation of new cost-effective methodology based on IOT to remotely monitoring a solar plant for performance evaluation. By incorporating the IOT technology the data received from the panels and appliance are sending to the cloud from through internet for the future use as well the remote user can monitor the parameters of the connected devices.

Journal ArticleDOI
TL;DR: The research provides a flexible and efficient deep learning technique that uses the CNN model to predict and detect a patient who is unaffected and affected by the illness based solely on chest X-ray photographs.
Abstract: Pneumonia, an infectious disease caused by a bacterium in the lungs' alveoli, is frequently the result of pollution. A lung infection causes pus to build up in the affected tissue. Professionals conduct bodily examinations and diagnose their patients using a chest X-ray, ultrasound, or lung biopsy to determine if they have certain conditions. Misdiagnosis, incorrect treatment, and failure to recognize the disease will result in a patient's inability to lead a normal life. Deep learning's advancement helps specialists make better decisions when diagnosing patients with certain diseases. The research provides a flexible and efficient deep learning technique that uses the CNN model to predict and detect a patient who is unaffected. Using a chest X-ray photograph, the study applies a flexible and effective deep learning technique of using the CNN model in predicting and detecting a patient unaffected and affected by the illness. To demonstrate the overall performance of the CNN model being trained, the researchers used an amassed dataset of 20,000 photographs and a 224x224 photograph decision with 32 batch lengths. At some point throughout the total performance training, the trained version produced a 95 percent accuracy charge. The research study may detect and predict COVID-19, bacterial, and viral pneumonia illnesses based solely on chest X-ray photographs, according to the results of the testing.

Journal ArticleDOI
TL;DR: In this paper , the authors proposed an IoT and ML-based agriculture system that can assist farmers or agriculturist in crop prediction based on Metrological Agriculture theory by getting live metrological data from the crop field using IoT technology and ML for prediction which will enable smart farming and increase their overall yield and quality of products.
Abstract: Agriculture is the backbone for a developing economy like India and there is an enormous need to maintain the agricultural sustainability. Hence it is a significant contribution towards the economic and agricultural welfare of the countries across the world. Effective utilization of agricultural land is crucial for ensuring food safety and security of a country. The aim of this paper is to propose an IoT and ML based Agriculture system that can assist farmers or agriculturist in crop prediction based on Metrological Agriculture theory by getting live Metrological data from the crop field using IoT technology and M.L for prediction which will enable smart farming and increase their overall yield and quality of products.

Journal ArticleDOI
TL;DR: The purpose of this current project is to receive a spam email in the morning or effectively using the Multinomial Naïve Bayes method, a machine learning method that filters spam and non-spam emails.
Abstract: In todays world, all activities depend upon the internet. In that Receiving Spam email send messages is a major problem. Many times, this kind of mail contains viruses and hacking links and they affect our system. For solving this kind of problem, we need some method that can filter spam mails and non spam emails. In this paper, we presented one machine learning method that filters spam and non-spam emails. Our algorithm generates the dictionary and features vector and trains them with a machine learning algorithm. Email is one such communication medium that comes to mind when we think of secure communication. As the popularity of email increases, the number of unsolicited data has also increased rapidly. A lot of unwanted stacks of emails called as Spam has created a need for further development Nowadays Machine learning methods have been able to detect and filter out spam emails. The purpose of this current project is to receive a spam email in the morning or effectively using the Multinomial Naïve Bayes method. Naïve approach is a machine-readable algorithm used to classify sample email as spam or not. This filter can be used by other email service providers as fully functional spam filters.

Journal ArticleDOI
TL;DR: A chatbot is demonstrated that uses Artificial Intelligence to produce dynamic responses to online client enquiries to reduce human dependency in every organisation and reduce the need for different systems for different processes.
Abstract: A Chatbot is a software application that replaces a live human agent to conduct a conversation via text or text to speech. It is designed to behave like a human would behave in that conversation. In this system, we demonstrate a chatbot that uses Artificial Intelligence to produce dynamic responses to online client enquiries. This web-based platform provides a vast intelligent base that can help humans to solve problems. The chatbot recognises the user's context, which prompts an intended response. Because this is a dynamic response, the user's desired response will be generated. This also uses a machine-learning algorithm to learn the chatbot by experiencing various requests and responses. Chatbots come to use in numerous fields of our daily life. Because AI enhances the human touch in every communication, chatbots are becoming increasingly robust.. It triggers accurate responses after understanding a user's query. Its objective is to reduce human dependency in every organisation and reduce the need for different systems for different processes.

Journal ArticleDOI
TL;DR: In this paper , the authors proposed the design and implementation of an electric vehicle (EV) charging station finder application developed in android studio using Java and Kotlin language, which helps EV owners to locate a charging station near them and to plan a journey.
Abstract: We are living in 21st century where all the work is done using technology and has become an integrated part of life. In this article we proposed the design and implementation of an electric vehicle (EV) charging station finder application developed in android studio using Java and Kotlin language. Due to the limitation of electrical power distribution network, Electric Vehicles charging stations are limited and to find them is hard for new EV owner. In order to provide information to users about the charging stations and to help user to navigate, it was also created a mobile application to help the EV owners on these processes. This Proposed EV finder Application helps EV owners to locate a charging station near them and to plan a journey and with many features.

Journal ArticleDOI
TL;DR: In this paper , the authors investigated the impact of occupational stress on psychological wellbeing and job satisfaction among teachers of self-financing colleges and identified the various factors influencing the occupational stress among teachers.
Abstract: The teachers of self-finance colleges have the same responsibility while comparing with the aided and government college teachers but the environment is entirely different. They are not getting proper salary and denying PF, ESI and many other benefits also. These teachers community has been ignored by the management. So the occupational stress of self-finance college teachers is more while comparing with the other teachers. This study attempts to investigate the impact of occupational stress on psychological wellbeing and job satisfaction. The study also identifies the various factors influencing the occupational stress among teachers of self-finance colleges. Descriptive research design used for this study and data are collected through structured questionnaire.Simple random sampling method is used to select sample of 103 teachers from different self-financing colleges in Kozhikode district, Kerala. To measure the psychological well-being of teachers 18 items were used utilizing six components (Self-Acceptance, Positive Relations with Others, Autonomy, Environmental Mastery, Purpose in Life, and Personal Growth) developed by carol Ryff. This study reveals that the occupational stress (work context, job content and organisational climate) has significant negative impact on job satisfaction and psychological wellbeing among teachers of self-finance colleges.

Journal ArticleDOI
TL;DR: The Random Forest algorithm in the diagnosis of PCOS on given data has the maximum accuracy, i.e., 96 percent, according to the validation metrics.
Abstract: Artificial intelligence can be used to manage enormous amount of clinical data with great accuracy and precision in healthcare systems for diagnostic reasons. we used machine learning algorithms such as AdaBoost, Gradient Boosting, KNN, Random Forest, and Logistic Regression to diagnose PCOS based on patient clinical data. The data was analysed, and the algorithms' accuracy and precision were validated. The Random Forest algorithm in the diagnosis of PCOS on given data has the maximum accuracy, i.e., 96 percent, according to the validation metrics.

Journal ArticleDOI
TL;DR: In this paper , a research work has been done to measure the satisfaction level of employees about current HR practices with special reference to MSEDCL, which is analyzed for three major HRM Practices namely Performance Management System, Employee Relations & Remuneration and Benefits Administration.
Abstract: This research work has been done to measure the satisfaction level of employees about current HR practices with special reference to MSEDCL. Today to sustain in such a competitive market it’s very important to retain good employees that contribute towards the attainment of Organizational goal and customer satisfaction as well. The information is analyzed for 3 major HRM Practices namely Performance Management System, Employee Relations & Remuneration and Benefits Administration.

Journal ArticleDOI
TL;DR: Intrapreneurship is the process in which big corporate encourage entrepreneurial characteristics in their own managers as discussed by the authors . They have a desire to achieve, and if they are not provided with freedom, autonomy, adequate resources; they leave the organization and launch their own ventures.
Abstract: Intrapreneurship is the process in which big corporate encourage entrepreneurial characteristics in their own managers. Intrapreneurs are intra-corporate entrepreneurs. They have a desire to achieve. If they are not provided with freedom, autonomy, adequate resources; they leave the organization and launch their own ventures. They are creative. With their creative ideas, they enable their companies to adapt to the changing environment and achieve growth and prosperity. Rural entrepreneurship plays an important role for economic development in developing countries like India. Rural entrepreneurship helps in development of backward regions and removes poverty. Rural entrepreneurs need support for infrastructure development, investment in agriculture, promotion of non-farm rural activities, education, health services, etc. Social entrepreneurs are interested in social mission. They create and sustain social value by engaging in the process of innovation and adaptation. They tackle a social need that is unattended by others. They create new social opportunities. They bring about social changes. They strive to maximize some form of social impact. They face numerous difficulties in fulfilling their social mission. Women entrepreneurs are mainly motivated by economic incentives, desire for independence, and better social status. They get satisfaction, economic independence, and flexibility of operations, work location and working hours through entrepreneurship. In addition to the problems faced by entrepreneurs in general, they have to face additional problems related to their womanhood. They have to maintain an appropriate degree of workhome balance.

Journal ArticleDOI
TL;DR: In this article , the hair root activation is needed to ameliorate hair growth and to help hair loss, and different sauces were used to formulate herbal hair serum for general purposes (hair operation).
Abstract: In the mammalian system, the hair follicle is known to be the most significant organ that determines appearance, gender distinction, give violent temperature protection, and plays a part in tone- defense. The youngish generation have begun to suffer from extreme hair loss problems due to numerous life- related changes similar as fatigue, anxiety, input of junk foods, use of diiferent hairstyling/ coloring styles, etc. The loss of hair isn't temporary in utmost cases, but it results in alopia. numerous people suffering from hair loss are in hunt of multiple treatments due to extreme anxiety and pressure, from tradition to traditional and remedial mending to the use of minoxidil and finasteride. To ameliorate hair growth and to help hair loss, hair root activation is needed. Herbal dress are still generally used by average citizens because of smaller side goods and lesser protection and safety profile. The present study was intended to use different sauces to formulate herbal hair serum for general purposes (hair operation).

Journal ArticleDOI
TL;DR: In this paper , a cosmetic preparation polyherbal face cream made from herbal ingredients has been presented in which aloe vera powder, hibiscus powder, senna powder were procured from the local market in the form of dried powder and extraction of dried crude herbal ingredients were done by maceration process.
Abstract: Herbal medicinal products are most preferable and safer with very less side effects than the synthetic products. Now a days there is a increasing in demand of herbal formulations in the world pharmaceutical market .The main objective of this work is to formulate and evaluate a cosmetic preparation polyherbal face cream made from herbal ingredients. In that aloe vera powder, hibiscus powder, senna powder were procured from the local market in the form of dried powder .extraction of dried crude herbal ingredients were done by the maceration process. After extracting the polyherbal face cream is prepared and evaluated for its various charecteristics. Herbal face creams are used to moisturizing, cleansing, protecting skin from damaging Uv rays, improving skin tone and beautifying skin. Due to anti-bacterial and anti-inflammatory activity of herbs used in the formulation helps to overcomes various problems related to the skin. Thus, in the present work, we founds good quality of herbal face cream, with their beneficial effects.

Journal ArticleDOI
TL;DR: To come across the information as faux or actual the authors’re evaluating numerous classifying strategies to discover the first-class version that would be used to come across fake information.
Abstract: The sharing of facts thru net has been growing over the years. The net has been a supply of smooth facts and is used greater than conventional approaches like newspapers or magazines. It is critical to become aware of facts from the net as actual or faux, as lie to facts should motive numerous havoc withinside the society. Fake facts may be the motive of riots, chaos and may have an effect on a huge institution of society. In this paper, we speak approximately the method used to come across fake information the usage of gadget studying classifiers and herbal language processing to authenticate whether or not information is actual or now no longer For the technology of function vectors, we use the TF-IDF vectorizer. To come across the information as faux or actual we’re evaluating numerous classifying strategies to discover the first-class version that would be used to come across fake information. The preprocessing features carry out a few operations like tokenizing, lemmatization and exploratory facts evaluation like reaction variable distribution and facts excellent check (i.e., null or lacking values). Simple Count Vectorization, TF-IDF is used as function extraction strategies.

Journal ArticleDOI
TL;DR: The background and the various methods of big data Analytics in healthcare are reviewed, various platforms and algorithms for big data analytics are elaborated and discussion on its advantages and challenges are discussed.
Abstract: Like Oxygen, the world is surrounded by data today. The quantity of data that we harvest and eat up is thriving aggressively in the digitized world. Increasing use of new innovations and social media generate vast amount of data that can earn splendid information if properly analyzed. This large dataset generally known as big data, do not fit in traditional databases because of its rich size. Big Data is a collection of data that is huge in volume, yet growing exponentially with time. It is a data with so large size and complexity that none of traditional data management tools can store it or process it efficiently. Organizations need to manage and analyze big data for better decision making and outcomes. So, big data analytics is receiving a great deal of attention today. In healthcare, big data analytics has the possibility of advanced patient care and clinical decision support. In this paper, we review the background and the various methods of big data analytics in healthcare. This paper also elaborates various platforms and algorithms for big data analytics and discussion on its advantages and challenges. This survey winds up with a discussion of challenges and future directions.