Volume 9 | Issue 11

 Abstract

worldwide situation, the prime inquiry in each woman mind is about her safety and the badgering issues. Women everywhere throughout the world are confronting much deceptive physical provocation. The main idea frequenting each woman is the point at which they will have the capability to move frankly in the city even in odd hours without stressing over their security. Our task is a dare to determine this issue. This paper describes about a smart intelligent security system for women. This venture concentrates on a security for women so they will never feel vulnerable. The system comprises of different modules such as GPS receiver, shock circuit, buzzer, spray mechanism, Webcam, pulse rate sensor, Raspberry pi-3 module. Today there are many cases which are going on about women all over in the world. It was high time where women required a change. This task depends on women security where women feel ensured. This venture portrays about safety electronic system for women, worked out in the open transport vehicles such as, car, buses and auto-rickshaws as these days women are being at molested, kidnapped and badgering by the drivers. In each field there is an uncommon effect of women like games, dance, training, business, in legislative issues moreover. Women are driving in each field. The question arises that, Are the women in India are extremely secured? Always get the solution No. Henceforth executed Internet of Things based women tracking and security with auto-defender system which is interfaced with Raspberry pi 3 board that will track the location of the women also will auto defend in bad situation.

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Design and development of wearable security jacket for women using IOT

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Since the world is facing the challenge of pandemic covid situation from march 19, there is huge loss to world regarding economy health etc. The infrastructure and construction industry sector which is primarily responsible for Indian growth they also suffering from the damage. The demand of construction project is fallen day by day. In this paper we will study about the different factors comparison in construction industry before and after the pandemic. While low economic activity in other sectors will impact construction services through forward linkages.

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 Keywords

covid 19, economy, construction industry

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Unmanned aerial vehicles, also known as drones, can play a significant role in military and civil emergency medicine. The aim of study was to present the real possibilities of using them in rescue operations and to provide examples from all over the world. Unmanned aerial vehicles can be applied to transport goods on demand, provide blood in urban areas, save sinking people, analyses the scale of damages, monitor large human gatherings, perform exploration activities, deliver blood samples and other analysis material, provide automated external defibrillators, support rescue operations and air transport, and perform agricultural activities. One must, however, be aware of the existing regulations regarding drone flights as an appearance of an unreported unmanned aircraft in the controlled space is identified worldwide as affecting aviation safety.

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Drone; medical supplies; delivery.

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Now a days agriculture crops face many problems like traits or diseases. Each year plant diseases, viruses and fungal attacks lead to crop, losses up to 30 percent of total production. Detection is the process of identifying the presence of symptoms of disease. Farmers in India have minimal access to agricultural experts, who can inspects crop for identifying disease and provide advice about disease. Delayed expert responses or ad- vice to queries of each farmers too late which are useless. Automatic detection of plant disease is an important as it beneficial to monitor large field of crops and identifies the presence of disease symptom on the plant leaf. In this project we develop Mobile app for automatically detecting the plant disease through image processing techniques with the objective providing fast, accurate, ease of use and inexpensive solution for farmers. Today mobile devices are used frequently by everyone, including the farmers and countryside peoples. According to observations of Information and Communication Technologies (ICT) mobile plays vital role in daily life of farmers.

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DEVELOPMENT OF ANDROID APPLICATION FOR SMART FARMING

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Pandemic, Depression, Adolescent Girls, Nutrients Status, Treatment Seeking Behavior.

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This study was primarily concerned with the use of geotextile, a geosynthetic membrane to strengthen the foundation of a flexible pavement. Three soil samples were collected from FUTA environs and all of the samples underwent primary soil tests such as natural moisture content, sieve analysis, compaction and California bearing ratio (CBR) test to determine the geotechnical properties of the samples. In carrying out the project, a flexible pavement model using tested soil samples was constructed with the geotextile material incorporated. Geotextile material design and selection should be based on sound engineering principles as they will serve the long-term interest of both user and industry. The use of geotextiles should be incorporated into the construction of roads as they are economical in reducing the stress of 'borrowing to fill', enhance strength of the sub-grade and increase service life of the roadway.

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GEOSYNTHESIS AS SMART CONSTRUCTION MATERIAL

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The traditional methodology of publishing a research paper in the reputed publication industries has proved to be unpromising due to the various aspects. The outdatedness, costliness, and the lack of flexibility in the legacy systems demand to switch to decentralized ways. We are achieving this through blockchain technology which is widely known for its decentralized and immutable nature that indirectly maintains integrity, accountability, and confidentiality of the systems. Hence the blockchain is thoroughly responsible for demolishing the demerits of the traditional system. This paper presents a comprehensive survey of publishing, peer-reviewing, and also the profit-making ways to the author and the system simultaneously. Our long-term goal is to bring more transparency and profitability by introducing papercoins into the system to exchange papers between peers in the blockchain network. And hence, it will indirectly help in shifting the massive mob of researchers to this new reformative path, thus strengthening the blockchain applications.

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Blockchain, decentralization, transparency

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The aim of this intelligent surveillance system is to detect, track and classify objects detected. The intelligent video surveillance allows segregation of all the instances present in the image or a video according to their classes and their respective positions. A class of an instance in an image is the identification of any entity and correlate it with the real world it might be a living or non-living thing or a specific part of any instances in an image that can be uniquely identified such as, car on a road or mobile phone on desk. Also, along with the identification of class of an entity the respective position of an instance in an image or video is also an important aspect while extracting information from the image let us consider that a tiger is chasing a boar or a boar is chasing a tiger in this example the respective position of tiger and boar has a huge impact to ones understanding about the situation. An approach towards intelligent surveillance system along with object detection is proposed in this paper

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 Keywords

Image processing, CNN, Deep learning, YOLO. Object Detection, Surveillance

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Growth of internet touched upon every sphere of life. There is some evidence that online videos are increasingly used by people for informal scholarly communication and teaching.According to one study students can learn more fastly and effectively using videos but now a days videos are used as a tool to advertise and promote the Business so, it is difficult to find most relevant and useful video content. People tend to choose the top ranked and the most viewed videos irrespective of their relevance. To provide students most relevant and useful content free of cost we choosed the 2nd most visited application on internet which is YouTube. According to one survey YouTube uploads 5000 hr duration videos pern minute. With respect to time this number is increasing constantly so peoples are facing problems regarding finding useful video contents. WebGist enable users to take advantage of constantly growing video resources like, for example, video on demand, Internet television and YouTube, for a wide variety of applications including entertainment, education and communications.

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WebGist, Youtube API, Video Search Engine, Online Learning, Gist,API.

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Phishing is a type of cybersecurity attack that involves stealing personal information such as passwords, credit card numbers, etc. To avoid phishing scams, we have used Machine learning techniques to detect Phishing Websites. Therefore, in this paper, we are trying to find the total number of ways to find Machine Learning techniques and algorithms that will be used to detect these phishing websites. We are using different Machine Learning algorithms such as KNN, Naive Bayes, Gradient boosting, and Decision Tree to detect these malicious websites. The research is divided into the following parts. The introduction represents the focused zone, techniques, and tools used. The Preliminaries section has details of the preparation of the information that is required to move further. Later the paper emphasizes the detailed discussion of the sources of information.

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Algorithms, Cybersecurity, Machine Learning, Phishing

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Investing in the stock market is complex and challenging for people because prices are changing every second. For that, they have to update with the latest financial news. But nowadays, understanding financial information or news is hard. To solve this problem, this paper proposes a model of stock price forecasting based on financial news sentiment. The model is using Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) network. Using the latest research in Natural Language Processing, the model analyzes the sentiment of financial news, and then autoregressive integrated moving average model (ARIMA) forecasts the result. For this model, data is coming from Twitter and Yahoo API which after preprocessing going through a model.

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Data analytics, Sentiment Analysis, News Articles ,LSTM-RNN, Arima, Deep-Learning.

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Brain tumors are the most common and aggressive disease, leading to a very short life expectancy at its highest degree. Therefore, treatment planning is a critical step in improving the quality of life of patients. Generally, various imaging techniques such as computed tomography (CT), magnetic resonance imaging (MRI) and ultrasound are used to evaluate the tumor in a brain, lung, liver, breast, prostate, etc. Especially in this work, MRI scans are used to diagnose tumors in the brain. However, the sheer amount of data generated by MRI images frustrates the manual classification of tumors versus non-tumors at any given time. But it has some limitations (that is, precise quantitative measurements are provided for a limited number of images). Therefore, automatic and reliable classification schemes are essential to prevent the mortality rate of humans. The automatic classification of brain tumors is a very challenging task in the great spatial and structural variability of the surrounding region of the brain tumor. In this work, we propose the automatic detection of brain tumors using the classification of tumor, Che convolutional neural network (CNN). If a tumor is detected, the system classifies the tumor and tells the patient what stage of the cancer they are likely to have.

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MRI, brain NN, feature extraction, classification

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Machine Learning appears as one of the key features to derive information from corporate operating datasets. Machine Learning in medical health care evolving as an enormous research field for delivering deeper understanding on medical data. Most methods of machine learning depend on several features defining the behavior of the algorithm, influencing the output, and thus the complexity of the resulting models either directly or indirectly. Many Machine Learning methods are utilized within the past to detect diseases. Prior detection of disease or low immune can help person to reinforce immune so on guard our body from harmful germs and viruses. Process is completed with the assistance of things like RBC counts, WBC, HB, MCV, MCH, MCHC, Neutrophils and platelet count. Observing and identifying of immune isn't an easy task to do manually because it takes a lot of time and effort. So it's easier to predict immune with an automatic processing and Machine Learning System. Different types of knowledge processing and Machine Learning algorithms are available to make best algorithm like rectilinear regression, Logistic regression and KNN algorithm. Various machine learning algorithm are often used to predict, so that the immune can often predicted easily and clearly because accuracy is vital in machine learning algorithm. This paper presents a study of various methods of predicting human immune.

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Machine learning, KNN, Immune, Logistic regression

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The latest developments in Deep Learning based Machine Translation and Computer Vision based Object Detection have led to high accuracy Image Captioning models. Although these models are very accurate, they tend to rely on the use of expensive computational power making it difficult to use these models in real-time applications like processing the video streams in real time and extracting the information. In this paper, we carefully follow some of the heuristic strategies and core ideas of Image Captioning and its common methods and present our simple sequence to a sequence based implementation with a remarkable transformation and efficiency such as using beam search instead of greedy search that allows us to implement these on low-end hardware. The proposed system compares the results calculated using a variety of metrics with high-quality models and analyses the reasons behind the model trained on the MS-COCO dataset that are lacking due to trade-off between computation speed and quality. In this proposed system, Restful API endpoint will be created to be used on any device with an internet connection such as a mobile phone, IoT devices, clock, etc, this endpoint used to sent an image to the model running on remote server which in response will generate and sent an caption describing the objects and their relationship with each other in image in a natural language.

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Sapio Enumerator based on video is an important field in Computer Vision. When Sapio Enumerator is implemented it may accompany by some problems. This paper proposed a method that may mix some existing technologies to overcome some problems. The Sapio Enumerator requires more powerful processing since it deals with real-time video, so the proposed method converts a color image into binary to minimize data of an image. Also, the image may contain a noise, the proposed method uses Erosion and Dilation processes to erase the noises. Reducing development time is an important term in Software Engineering to build an application. The method depends on existing packages for reducing development time. The proposed method is implemented in the Python programming language.

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Android application, image processing, cloud storage, motion detection, people detection, computer vision, pixel.

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Version Control Systems; Distributed Version Control Systems; Centralized Version Control Systems; Software Development; Collaborative Development.

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Web personalization, Search Engines, User interests.

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The improvements in the internet infrastructure and the increased affordability has led to an increase in the number of users on this platform. This has put a large impact on the services being offered on this platform especially on the e-commerce websites. These websites cater to the individual and the increased number of users has led to an increase in customer data. This data is highly valuable as it can allow for the effective prediction of customer behavior. Therefore, these predictions can allow for effective and accurate product recommendations based on the interests and the behavior of the customer. To achieve this approach, this research article analyzes a collection of related works based on the paradigm of product recommendation. After a thorough analysis, an improved product recommendation system is devised through the effective implementation of Natural Language Processing and machine learning algorithms. The proposed methodology performs preprocessing, Bag of Words, and TF-IDF along with Fuzzy Artificial Neural Networks and Collaborative Filtering to achieve an effective Product Recommendation system. This approach will be expanded further in the upcoming researches.

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Natural Language Processing, Fuzzy Artificial Neural Networks and Collaborative Filtering

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A wide range of conveniences for the users have been enabled in the recent past of wireless technology. The hungry for wireless connectivity has increased much larger than the businessfield and has entered the consumer market. At present, the wireless WPAN and LAN technology cannot meet theneeds of the future connectivity of such a host of emerging electronic devices that need higher bandwidth. Ultra wide band wireless communication offers a completely different approach to wireless communication. It is a cost effective technology which brings the convenience and potential of wireless communication to high speed interconnects in devices. It is designed for short range, person area networks and is the leading technology for getting people from wires. Globally the interest in this technology is huge and has been described as one of the most promising technologies of our times.

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UWB,Wireless Technology, Positioning System.

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Every country is having its economic source. The Indian economy depends on agricultural productivity. This technique is used to improve the performance of existing technology or to develop and design new technology for the growth of plants. The proposed agenda consists of four parts. They are Image preprocessing, Segmentation of the leaf, feature extraction, and classification of diseases. The first disease region is found using the segmentation technique, then both color and texture features are extracted. Finally, the classification technique is used to detect the type of leaf disease. The proposed system can effectively detect and categorize the examined disease with an accuracy of 80.05%.

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Leaf disease detection, Image segmentation, masking, feature extraction, gradient boosting classification

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