Computer Science And Engineering

Linked Data involves web to create typed links between different sources of data. Source data may vary in location, size, subject-matter and how congruously it is structured. Links produced from this data create equality and define properties to make data easier to read for machines. Linked Data is relatively unexplored in the domain of education. Linked Up Challenge have surfaced to encourage innovative applications focused on open educational data Massive Open Online Courses or MOOCs are online courses accessible to anyone on the web. Many of institutions have joined in an archive to make education more accessible by synchronizing with MOOC providers such as Coursera and NPTEL Delivering course content through lecture videos as well as readings and problem sets, MOOCs encourage interactivity between professors and students around the world by way of discussion forums and graded assessments. For most information associated with their course catalog. This includes properties such as a courses title, instructor, and syllabus details. Although Coursera's course catalog data is easily accessible as JSON, there is no option to retrieve and use it in a Linked Data format such as the RDF .there is no Linked Data available for MOOCs or for ontology that represent properties unlike to MOOCs In order to incorporate MOOC data into the Linked Data cloud as well as demonstrate the potential of Linked Data when applied to education, we propose to (i) developed or extend an RDF ontology which denotes properties of MOOC .(ii)use ontology that generate Linked Data from different MOOC providers.

This paper addresses the subconscious mind and its fascinating effects on a human’s life without their realization. The subconscious and its phenomenon can be considered a significant source to understand the secrets to the power this mankind beholds. People think they know what they are doing, who they are, not even realizing how they are directed by the greatest power of all “the subconscious mind” whose powers in disguise are yet to be discovered. This paper tells the incompatible nature of human subconscious mind. It has always been a topic of great discussions and arguments. This paper considers all the research papers and patterns of information throughout the history and modern period. Hence, it concludes the importance of the subconscious mind and how one can learn utilizing it at its best.

This is an era of technology; we are surrounded with the technology. Now a day’s people become smarter they want to operate each and everything’s with his smart phone/laptop/pc without going anywhere, it happens due to IOT devices. That’s why in this paper we have design a smart home with enhance security. In smart home we can operate the household things(fan, light, ac, any applications, door, windows, etc. )with the mobile. We design a IOT based smart and secure home model in latest released cisco packet tracer. Cisco packet is basically a simulator to teach the student about the network. But in newly released cisco packet tracer 7.2.1 it have more sensors, board, Programming languages, IOE devices. In this we can design, test, see the actual working of the network/model in real time. In testing the IoT home network wireless network gateway system, multiple electronic devices can be controlled and monitored via smartphone based on predefined configuration conditions. The smart and secure home is implemented using different types of IOE devices with enhanced security, house environment prospective and safety.

The identity or verification of humans primarily based on their thermal information isn't always an easy mission to perform, but thermal face biometrics can make contributions to that undertaking. Face reputation is an interesting and a successful application of Image analysis and Pattern recognition. Facial pictures are important for intelligent vision based human machine interaction. Face processing is based at the fact that the records approximately a consumer’s identity may be extracted from the image and the computers can act as a consequence. A thermal face image should be represented with biometrics features that highlight thermal face characteristic and are compact and easy to use for classification. Second, image resolution is basically lower for video sequences. If the subject is present in very far from the camera, the actual face image resolution can be as low as 64 by 64 pixels. Finally, face image variations, such as illumination, expression, pose, occlusion, and motion, are more important in video sequences. The approach can address the unbalanced distributions between still images and videos in a robust way by generating multiple “bridges” to connect the still images and video frames. So in this project, implement still to video matching approach to match the images with videos using Grassmann manifold learning approach to know unknown matches. Finally provide voice alert at the time unknown matching in real time environments. And implement neural network classification algorithms to classify the face images in real time captured videos.

Day by day the number of vehicles is increasing very fast as the demand is increasing. So, the details of the vehicles are very important to maintain for the government of a country. Information like ownership, insurance, emission, road tax etc., need to be maintained and accessed very efficiently and easily. Even for crime purpose the vehicles are used. So, depending on the demand of the requirements we have proposed this model for real time vehicle monitoring and intimating for violation of traffic rules using drone. In our proposed system, the drone is fitted with cameras and Raspberry Pi. The drone will keep on monitoring the non-parking areas from above the level of ground. The drone will capture the image and detect the vehicle and if the vehicle is not moving after two minutes, transmit the vehicle image to the server along with the road signal code.

Anonymization techniques are enforced to provide privacy protection for the data published on cloud. These techniques include various algorithms to generalize or suppress the data. Top Down Specification in k anonymity is the best generalization algorithm for data anonymization. As the data increases on cloud, data analysis becomes very tedious. Map reduce framework can be adapted to process on these huge amount of Big Data. We implement generalized method using Map phase and Reduce Phase for data anonymization on cloud in two different phases of Top Down Specification

Time series is a scientific process of determining an ordered sequence of values of a variable within equally spaced time intervals. Mostly this is applied when looking at technical data and its influences on the neighboring surroundings. This type of scientific analysis that can be applied twofold. Firstly, it can be used to obtain a knowledge of the triggering forces and structure that produced the observed data. Additionally, it can be used to fit a model and to predict, monitor the area of interest. This scientific form of analysis can be applied in various sectors so long as the data can be measured over time. The following are some of the applications: Economic and sales forecasting, Crop Yield prediction, Forest cover changes, urbanization, among many other uses. In this analysis, we will focus on time series change detection using image differencing of a classified image and representing the outcome area in a bar graph. The area of study is Seshachalam Hills, Tirupathi an ecological zone in Andhra Pradesh, India.

The Public Distribution System in India is the largest retail system in the world. Major problem in this system are the inefficiency in the targeting of beneficiaries, improve weighing machines used an illegal selling of goods. Automated public ration distributed system aim to replace the manual work in Public Distribution System there by reducing the corruption an illegal selling of stock. This paper gives the review on the E- Ration card system to distribute the grains automatically. The proposed system is used the conventional ration card which is replaced by smart card by using RIFD card. The RFID card redirect to the web of the shop , the required item are selected and payment is done and then item are collected from the machine. In this system, the government has control overall transaction that occurs in the ration shop and all the stock records are updated to the government databases so as to refill the stock with material thereby reducing the corruption.

In today's world women safety is one of the most important issues to be addressed in our country. When a women needs urgent help at the time of harassment or molestation, proper reachability is not present for them. Apart from being aware about the significance of women's safety, it is essential that they are provided with protection during those crucial times. The earlier existing system are helpful in detecting the women's location after the crime has been committed. In this project we will be using the women's handbag in which we will be fixing camera lenses and which will be carried anywhere they go. Whenever she comes in contact with any person outside, an image of that person is taken and the activities of the person can be monitored continuously. If the person behaves normally the image can be of no use and can be deleted. But if the activities of the person varies resulting in any harmful action then our system will detect it and process the captured image and it will send to the police and family members with GPS location tracked from IP address. Thus our project helps in saving the life of a women and safeguarding her in the present situation.

https://www.ijert.org/speed-detection-software

https://www.ijert.org/research/speed-detection-software-IJERTV10IS030296.pdf

In this research paper, we are going to introduce a very general problem which is a curse for all. The problem is related to the ongoing accidents phenomenon due to the carelessness and inability of humans in controlling the speed of vehicles[1]. Vehicles are one of the great inventions, we can say, which were introduced for the comfort of humans in travelling from one place to another. Due to this equipment only, it is possible for each human to go to very distant places in no time which was almost impossible before their existence. As a human nature, humans started to treat this auspicious gift not for their need but for their greed also. It also became a standard of respect among many of us to drive the vehicles out of controllable speed disregarding the harm it can cause to ourselves as well as to others. It doesn’t cause the loss of only vehicles but also to properties, nature and even to human lives. Humans either by giving the priority to reach their destination on time or thinking to compete with others or show off to others they cross the limits of speed of their vehicles which could not be controlled by them at the instant any emergency occurs to stop the vehicle immediately

Augmented Reality is the presentation of objects superimposed on the real world view of the environment. It is an innovative technology that allows multidimensional viewing and understanding of concepts. This paper aims to use this concept of Augmented Reality in the field of Education to create an application that generates 3D models of the images embedded in textual materials using the software Unity and Vuforia. The application uses a smartphone’s camera to scan the embedded image of a textbook, e-book or photocopy and generates a 3D working model with live animations as well as on-click functionalities to view various movements of the model by providing user interaction. This application aims to provide an active learning experience to students.

Illumination invariance remains the most researched, yet the most challenging aspect of automatic face recognition. In this paper we investigate the discriminative power of colour-based invariants in the presence of large illumination changes between training and test data, when appearance changes due to cast shadows and non-Lambertian effects are significant. Specifically, there are three main contributions: (i) we employ a more sophisticated photometric model of the camera and show how its parameters can be estimated, (ii) we derive several novel colour-based face invariants, and (iii) on a large database of video sequences we examine and evaluate the largest number of colour-based representations in the literature. Our results suggest that colour invariants do have a substantial discriminative power which may increase the robustness and accuracy of recognition from low resolution images.

The primary goal of this thesis is to simulate the causes of human face ageing and to detect skin illnesses. This project combines the capabilities of a Deep Learning model, notably EfficientDet, with the capabilities of a machine learning model and Advanced Computer Vision to identify and locate aging and skin disease. In an uploaded photo there are irregularities which can be detected. The appearance of age-related face changes is determined by a variety of factors. Wrinkles, dark patches, and swollen eyes are all variables to consider. The TensorFlow Objection Detection API is used to investigate the factors. TensorFlow Zoo's EfficientDet model is pre-trained. The proposed models are found to be effective based on the outcomes. Very effective in predicting the indications of ageing in people of all ages. Python was used to implement this project.

Cloud computing associate the computing and storage resources controlled by different operating systems to make available services such as large-scaled data storage and high performance computing to users. The benefits of low-cost, negligible management (from a user’s perspective), and greater flexibility come with increased security concerns is one of the most crucial aspects among those prohibiting the wide-spread adoption of cloud computing. The data outsourced to a public cloud must need to be secured. This work gives Division and Replication of Data (DROPs) inside the Cloud for Optimal Performance and Security that judicially fragments user files into portions and replicates them at strategic places in the cloud. The division of a files into fragments is achieved based on a given consumer standards such that the individual fragments do not comprise any meaningful facts. The node separation is ensured by the means of the Grid Topology algorithm. To further improve the retrieval time, replicate fragments over the nodes that generate the highest read/write requests. The data encrypted using AES encryption algorithm. Duplication checking is implementing to provide efficient storage and time based access control for secure file access system.

Data warehouse is used to provide effective results from multidimensional data analysis. The accuracy and correctness of these results depend on the quality of the data. To improve data quality, data must be properly extracted, transformed and loaded into the data warehouse. This ETL process is the key to the success of a data warehouse. In this paper we propose a conceptual ETL framework for an object oriented data warehouse design, the framework is called UCLEAN. This framework takes into account the concept of requirements of the users .The data is extracted from different UML sources and is converted into a multidimensional model. It is then cleaned and loaded in the data warehouse. We validate the effectiveness of the framework through a case study.

Digitalization of money transfer is a must in the present situation of banking operations. Clients have a variety of ways to carry out transactions, such as credit, wiring money, and so forth. However, depositing cash requires the physical presence of the depositor at the bank, and cashier needs to enroll the transaction into the system, which slows down the rate of money deposit and teller's activity. To accelerate the process, banks around the world have to adapt and construct guidelines for a digital deposit. To accurately digitize and transmit deposit slip information from smartphones to the bank, a scheme called 'Automating Data Entry Forms for Banks Using OCR and CNN'. The deposit slip scanner algorithm is based on input from the Smartphone camera.

Heart attack is most common disease that engulfs the patient’s precious life. This disease attacks a man so in a flash that it barely gets treated. Many systems that detect heart attack came into the picture but they do have many flaws. Some system does not work properly in cold weather and other doesn’t give accuracy. To have a solution for Heart attack utilization of IoT and sensor system could be beneficial. Heart Attack Early Prediction System predicts the Heart rate and accordingly sends the notification to the patient’s doctor and acquaintances.

GPS is in actuality the main answer for outdoor positioning, no unmistakable arrangement has so far risen for indoor positioning notwithstanding the business hugeness. Along these lines, the principal point is to grow ongoing indoor following framework and utilizing cell phone sensors to give dependable and precise indoor localization. Indoor navigation is a vital empowering innovation for application, for example, finding a gathering room in a place of business, security exit amid a crisis or focused on the retail commercial in a shopping center. Utilizing this thought, an application can be made and by methods for that application, we are handling indoor navigation utilizing continuous navigation. The android application gives mindfulness, straightforwardness to discover your direction, commercial and effortlessness. To give solid indoor navigation to business structures like shopping centers, enterprises, universities, hospitals, inns. In this paper, we give an order and arrangement of the current indoor positioning systems and distinguish some conceivable zones of improvements.

The film industry is not only the center of Entertainment but also a huge source of employment and business. Well, famous actors and directors can ensure the publicity of a movie but can’t promise a good IMDB score. We have collected the data available online about these Hollywood movies and their IMDB ratings to create our dataset. After getting the dataset we have incorporated various exploratory analysis techniques and then applied various machine learning algorithms to predict the IMDB rating. Finally, identified the best-fit algorithm which gives the most accurate prediction.

International Journal of Computer Science and Technology (IJCST) is devoted to fields of Computer Science and Technology. The IJCST is a open access peer-reviewed scientific journal published in electronic form as well as print form. The mission of this journal is to publish original contributions in its field in order to propagate knowledge amongst its readers and to be a reference publication.

A large section of World Wide Web is full of Documents, content; Data, Big data, unformatted data, formatted data, unstructured and unorganized data and we need information infrastructure, which is useful and easily accessible as an when required. This research work is combining approach of Natural Language Processing and Machine Learning for content-based classification of documents. Natural Language Processing is used which will divide the problem of understanding entire document at once into smaller chucks and give us only with useful tokens responsible for Feature Extraction, which is machine learning technique to create Feature Set which helps to train classifier to predict label for new document and place it at appropriate location. Machine Learning subset of Artificial Intelligence is enriched with sophisticated algorithms like Support Vector Machine, K – Nearest Neighbor, Naïve Bayes, which works well with many Indian Languages and Foreign Language content’s for classification. This Model is successful in classifying documents with more than 70% of accuracy for major Indian Languages and more than 80% accuracy for English Language.

Cloud computing is a field which has been fast growing over the last few years. The fact that cloud can provide both computation and storage at low rates makes it popular among corporations and IT industries. This also makes it a very captivating proposition for the future. But in spite of its promise and potential, security in the cloud proves to be a cause for concerns to the business sector. This is due to the out sourcing of data onto third party managed cloud platform. These concerns security also make the use of cloud services not so much flexible. We provide a secure framework to stored data to be securely in the cloud, at the same time allowing operations to be performed on data without compromising of the sensitive parts of the data. A combination of searchable encryption with Partial Homomorphism is proposed.

The age of computer advancement has caused a revolutionary change in the corporate sector. From on-campus working hours to remote work from home scenarios, from meetings in a conference room to meeting online in a virtual environment, things are changing continuously in the corporate environment. This paper tries to educate and generate awareness about cyber security in the non-technical human resource and try to make them understand the potential risks to their organization which can be caused because of not giving much attention to smaller details. This paper concentrates on those attacks which can be mitigated by any non-technical employee and which are easy to understand and give preventive measures for the same.

https://www.ijert.org/detection-and-classification-of-objects-in-satellite-images-using-custom-cnn

https://www.ijert.org/research/detection-and-classification-of-objects-in-satellite-images-using-custom-cnn-IJERTV10IS060287.pdf

Satellite image analysis is being increasingly used for many applications like surveillance, military, geo-spatial surveys and environmental impacts and change monitoring. Automatic detection and classification of objects is an important functionality of satellite image analysis. Due to the nature and size of objects and the varied visual features, it becomes challenging to detect and classify objects in aerial images. Manual detection of objects in these images is very timeconsuming due to the nature and that data captured in these images. It is desirable to automate the detection of various features or objects from these satellite images. The conventional methods for object classification involve two stages: (i) identify the regions with object presence in the image and (ii) classify the objects in the regions. Additionally, detection of objects becomes challenging in presence of complexities in background, size, noise, and distance parameters. This work proposes a customized convolutional neural network to detect and classify three different objects such as trees, building and cars in the images. It also aims to understand and outline briefly the performance characteristics of the considered custom CNN.

The building industry, especially construction materials’ production, is a major user of the world’s resources and together with energy production one of the most important sources of the CO2 production. Among building materials, concrete is element which is the second most consumed substance in the world, whereas only water is used in greater quantities. Apparently, almost one ton of concrete is used for each person in the world each year. From the point of view of ecological and sustainable aspects, concrete industry is now recognized as the largest consumer of natural resources and significant producer of waste. In order to preserve clean environment, there is a need for improvement of existing production technologies of concrete by transforming them into sustainable and environmentally friendly. Municipal solid waste incineration (MSWI) materials as fly ashes and bottom ashes have not dissimilar average chemical composition from that of coal fly ashes and slag from iron production. On that account one can assume possible use of MSWI materials as partial Portland cement replacement in concrete mix design or in a raw state as partial aggregate replacement. Since waste treatment represents serious problem for advanced as well as for developing countries, the use of MSWI materials in concrete production is beneficial for both ecological and financial reasons.

Three kinds of MSWI fly ashes in state “as received” were characterized and their potential use as filler in cement based mortars was tested. The motivation of this utilization was to replace part of the fine aggregate dose in the mortars. All tested ashes made the mortars properties worse; the reasons and possible solutions are discussed.

Internet of Things (IoT) plays a important role in connecting the over all environmental things to the network and it is easy to access those un-internet things from any remote location. It’s unavoidable for the people to update with the increase technology. [1] And generally people are facing problems on parking vehicles in parking slots in a parking area. In this study we plan a Smart Parking System (SPS) which enables the user to find the nearest parking area and gives availability of parking slots in that respective parking area. It mainly concentrates on reducing the time in finding the parking area and also it avoids the unnecessary travelling through filled parking areas in a parking area. Thus it decreases the fuel consumption which in turn reduces carbon footprints in an atmosphere.

In traditional intrusion detection system (IDS) environments, little activity has been applied to using visual analysis as an aid to intrusion detection. With more information systems being attacked and attack techniques evolving, the task of detecting intrusions is becoming an increasingly difficult. Efficient
information visualization is an important element required for urgent detection of intruders. This paper presents a survey on using visualization techniques in intrusion detection system.
Finally authors proposed a framework for visualization system for ID.

Dynamically changing background ("dynamic background") still presents a great challenge to many motion-based video surveillance systems. In the context of event detection, it is a major source of false alarms. There is a strong need from the security industry either to detect and suppress these false alarms, or dampen the effects of background changes, so as to increase the sensitivity to meaningful events of interest. In this paper, we restrict our focus to one of the most common causes of dynamic background changes: that of swaying tree branches and their shadows under windy conditions. Considering the ultimate goal in a video analytics pipeline, we formulate a new dynamic background detection problem as a signal processing alternative to the previously described but unreliable computer vision-based approaches. Within this new framework, we directly reduce the number of false alarms by testing if the detected events are due to characteristic background motions. In addition, we introduce a new dataset suitable for the evaluation of dynamic background detection. It consists of real-world events detected by a commercial surveillance system from two static surveillance cameras. The research question we address is whether dynamic background can be detected reliably and efficiently using simple motion features and in the presence of similar but meaningful events such as loitering. Inspired by the tree aerodynamics theory, we propose a novel method named local variation persistence (LVP), that captures the key characteristics of swaying motions. The method is posed as a convex optimization problem whose variable is the local variation. We derive a computationally efficient algorithm for solving the optimization problem, the solution of which is then used to form a powerful detection statistic. On our newly collected dataset, we demonstrate that the proposed LVP achieves excellent detection results and outperforms the best alternative adapted from existing art in the dynamic background literature.

https://www.ijert.org/counterfeit-detection-of-documents-using-blockchain

https://www.ijert.org/research/counterfeit-detection-of-documents-using-blockchain-IJERTV10IS070155.pdf

Document verification is a domain that involves various challenges and monotonous processes to authenticate the documents. The verification for each type of document is to be processed in distinct ways. The issuing of documents is not transparent and hence fake documents can be created. Documents or certificates generated by organizations play a vital role for students. With the increase of forged documents, credibility of both the students and the organization is imperiled. Verifying a document takes some time and also requires more human resources to request for the confirmation of the data provided. Managing documents or records often comes at the cost loss of data or document counterfeits. In the digital world, blockchain technology has recently emerged as a potential mean for authenticating the document verification process and is a significant tool to combat document fraud and misuse. In this paper, we aim to enhance the document verification process using blockchain. We propose a system which uses the InterPlanetary File System [IPFS] protocol and also a peer-to-peer-network for storing and sharing data in a distributed file system. By using this blockchain technology, we can provide a more secure and efficient digital certificate validation.

In today's world cloud computing is widely used in many it industries. Cloud computing is an emerging model of business computing. Cloud computing which is based on internet has the most powerful architecture of computation. Because of the newly in innovative technologies in cloud computing, the number of labs is transformed into cloud named as the virtual labs. It considers a collection of integrated and networked hardware, software and internet infrastructure. Cloud computing is a development of parallel computing, distributed computing, grid computing and virtualisation technologies from cloud computing adoption accept and also focuses on cloud interoperability issues. We also present the popular platforms of cloud computing. In this paper, we explore several cloud computing system providers about their concerns on security and privacy issues. We also present the characteristics and applications of different well-known cloud computing platforms. We also purpose to recognise the challenges and issues of cloud computing. However, security and privacy issues present a strong roadblock for users to adapt into cloud computing systems.

In the present study, we have obtained Bianchi type VI anisotropic model of the universe filled with a bulk viscous stress in the presence of variable gravitational and cosmological constants. Here we have assumed the cosmological term in the form Λ∝H to discuss the effect of cosmological variables. It is found that the bulk viscosity coefficient (ξ) is a decreasing function of time. The expression for proper distance, luminosity distance, angular diameter distance, look back time and distance modulus curve have been analyzed and also the distance modulus curve of derived model nearly matches with Supernova Ia (SN Ia) observations.

The usage of mobile phones in today's world is more than ever. Mobile phones are everywhere and the mobile technology is growing at an exponential rate. The capabilities of a mobile phone have made it provide us services that make human life better. One such service that mobile phones can offer us is digital healthcare. Also, it is recognized that mobile phone applications that provide healthcare solutions are trending. Such applications provide a convenient and portable healthcare solutions to all the individuals. Such applications provide a rich experience to a user and in this way, the users will come to know more about their health and body. Digital healthcare mobile applications are capable of diagnosing a disease that a patient is suffering from using his/her symptoms. This information can be used further by a medical practitioner for later on consultation.

In the modern world, people receive various bills through post, sms, emails etc. They use cards, e-wallets and net banking to pay them in online. This manual process can be automated if the user wishes to pay selective or each bill he/she receives monthly. It is common that, most of the bills we receive nowadays are through sms and emails,with the help of Natural Language Processing , the message can be classified i.e whether the message is a bill or not. If the message is a bill, then there will be sufficient details to pay it, such as cost, user unique number, purpose of payment. From these details, the application can pay through online from the registered card details. A push notification is sent to the user regarding the transaction, whether it is successful or not. The details are completely stored in the cloud. The selected type of bills are stored in the app itself. Moreover the application is capable of paying others bill if the user wishes to pay.

Evolution in the field of web technology has made an enormous amount of data available in the web for the internet users. These internet users give their useful feedback, comments, suggestion or opinion for the available product or service in the web. User generated data are very essential to analyze for business decision making. TextBlob is one of the simple API offered by python library to perform certain natural language processing task. This paper proposed a method for analyzing the opinion of the customer using TextBlob to understand the customer opinion for decision making. This paper, provide a result for aforesaid data using TextBlob API using python. The paper includes advantages of the proposed technique and concludes with the challenges for the marketers when using this technique in their decision-making.

During forensic examination, analysis of unallocated space of seized storage media is essential to extract the previously deleted or overwritten files when the file system metadata is missing or corrupted. The process of recovering files from the unallocated space based on file type-specific information (header and footer) and/or file contents is known as Data Carving. The research in this domain has witnessed various
technological enhancements in terms of tools and techniques over the past years. This paper surveys various data carving techniques, in particular multimedia files and classifies the research in the domain into three categories: classical carving techniques, smart carving techniques and modern carving
techniques. Further, seven popular multimedia carving tools are empirically evaluated. We conclude with the need to develop the new techniques in the field for carving multimedia files due to the fact that the fragmentation and compression are very common issues for these files.

Software testing is used to test the developed system to find the errors and defects in the software. To find the errors and defects in the software system test cases are generated. Test cases generation based on three parts i.e. coding, design and specification. Specification based testing deals with the generation of test cases from the functional requirements of Software Requirement Specification. This approach deals with the automated generation of functional test cases. This approach proposes a framework for the automated generation of use case diagram. Use cases of automated generated use case diagram are used to develop one or more use case activity diagrams. By using depth first search technique, functional test cases from the use case activity diagrams are generated. Automated generation of functional test cases and use case diagrams saves the maximum effort and time consumed by software tester to test the software system.

Blockchain (BC) in the Internet of Things (IoT) is a novel technology that acts with decentralized, distributed, public and real-time ledger to store transactions among IoT nodes. A blockchain is a series of blocks, each block is linked to its previous blocks. Every block has the cryptographic hash code, previous block hash, and its data. The transactions in BC are the basic units that are used to transfer data between IoT nodes. The IoT nodes are different kind of physical but smart devices with embedded sensors, actuators, programs and able to communicate with other IoT nodes. The role of BC in IoT is to provide a procedure to process secured records of data through IoT nodes. BC is a secured technology that can be used publicly and openly. IoT requires this kind of technology to allow secure communication among IoT nodes in heterogeneous environment. The transactions in BC could be traced and explored through anyone who are authenticated to communicate within the IoT. The BC in IoT may help to improve the communication security. In this paper, I explored this approach, its opportunities and challenges.

To improve the corrosion resistant properties of carbon steel usually cladding process is used. It is a process of depositing a thick layer of corrosion resistant material over carbon steel plate. Most of the engineering applications require high strength and corrosion resistant materials for long term reliability and performance. By cladding these properties can be achieved with minimum cost. The main problem faced on cladding is the selection of optimum combinations of process parameters for achieving quality clad and hence good clad bead geometry. This paper highlights an experimental study to optimize various input process parameters (welding current, welding speed, gun angle, contact tip to work distance and pinch) to get optimum dilution in stainless steel cladding of low carbon structural steel plates using Gas Metal Arc Welding (GMAW). Experiments were conducted based on central composite rotatable design with full replication technique and mathematical models were developed using multiple regression method. The developed models have been checked for adequacy and significance. In this study, Artificial Neural Network (ANN) and Simulated Annealing Algorithm (SA) techniques were integrated labels as integrated ANN-SA to estimate optimal process parameters in GMAW to get optimum dilution.

https://www.ijert.org/weather-based-electricity-consumption-prediction-using-big-data-analytics-model

https://www.ijert.org/research/weather-based-electricity-consumption-prediction-using-big-data-analytics-model-IJERTV10IS040052.pdf

Electricity is being consume in every home at present time , we are using electricity for lots of purposes like watching television, charging cell phones, Electric bulb and many more things. Analyzing this electricity data will give us a better understanding of how consumer consumes electricity in their daily life. Apart from user daily electricity consumption there are also External factor which plays a major role in defining the amount of electricity consumed. One of the major external factor is Weather , like in a sunny day a family can use Cooler , AC, Refrigerator which increases the electrical consumption similarly on a cold day user can use Heater , geezer kind off things. By inspecting the convolution, volatility, and variability of the users' electricity consumption behavior and weather data, this paper proposes a machine learning model using data analytics to analyze this behavior. A Big Data Analytics model for tracking and monitoring household electricity consumption based on External Factor like weather is developed. Using the big data analytics techniques, machine learning algorithms and descriptive analysis of data obtained from weather and consumers, the model provides the required information and prediction.

Online networks have many threats regarding security. The threats are targeting agency networks, private networks or other networks via gaining access to or changing essential information. Less secure networks deliver authorization to the users to access records in a network. Communication managers need powerful police forces to prevent access, misuse or alteration of secure network information. Small businesses or small businesses use firewalls, antibiotics or anti-spam software to protect the network, but do not provide sufficient network protection. Security in the corporate network is an important part of network protection due to the most common hacker goals. A private network is a reliable way of communicating with various business units and communicating with internal networks. Internet Protocol Security (IPsec) Virtual Private Network (VPN) is one of the most powerful security tools in the field of recording and security options. This is the safest and most secure option available in the Private Network store as a combination of two or more networks in remote areas. The goal of this research is to integrate VPN Services and establish IPsec protocols for small business security. The study is based on the networks of National College of business administration & economics (NCBA&E BWP) and its campuses by using the Cisco routers for a secure and private communication interchange between them. The result shows that IPsec VPN is an appropriate way of communication for Small and Medium-Sized Enterprises (SMEs).

The increasing popularity of micro-blogging sites like Twitter, which facilitates users to exchange short messages (tweets) is an impetus for data analytics tasks for business development. Twitter has a huge amount of data. Twitter’s API allows you to do complex queries like pulling every tweet about a certain topic. So, Companies can know more about consumers’ sentiments towards their products and services and use them to better understand the market and improve their brand. In this paper selected a popular food brand to evaluate a given stream of customer comments on Twitter. Several metrics in classification and clustering of data were used for analysis. A Twitter API is used to collect twitter corpus and feed it to a classifier algorithm that will discover the polarity lexicon of English tweets, whether positive or negative. A clustering technique is used to group together similar words in tweets in order to discover certain business value.

Over the recent years, several smart applications like RFID?s, sensor networks, including industrial systems, critical infrastructures, private and public spaces as well as portable and wearable applications in which highly constrained devices are interconnected, typically communicating wirelessly with one another, working in concert to accomplish some task. Advanced safety and security mechanisms can be very important in all of these areas. Lightweight cryptography enables secure and efficient communication between networked smart objects. The CLEFIA algorithm is a suitable lightweight cryptographic algorithm used in medium security systems. In order to increase safety and security mechanisms, modify CLEFIA are proposed which uses the Linear Feedback Shift Register (LFSR) to overcome the security weakness of the CLEFIA algorithm against attacks. In this paper an implementation of modify CLEFIA algorithm using C++ programming language. We have also compared the results with the standard CLEFIA.

Due to the rapid growth in networks communication security issue are being a challenging task. In this project deep analysis is to be made in the cyber security using proxy re-encryption and cipher text crypto system. Various algorithm are been proposed for the cipher text encryption and decryption in decentralized mobile networks with mobile user policy. Based on the existing study it is to propose a new algorithm for encryption and decryption. Ciphertext-policy attribute-based encryption scheme delegating attribute revocation process to cloud server by proxy re-encryption. The proposed scheme does not require secret sharing schemes (LSSS) access structure. Proposed scheme is secure against attack by unauthorized users and cloud server. Sharing of the cloud storage has a risk of information leakage caused by service. In order the protect data, the data owner encrypts data shared on the cloud storage so that only authorized users can decrypt the cloud data.

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Autonomous driving will increasingly require more and more dependable network-based mechanisms, requiring redundant, real-time implementations. Object detection is a growing field of research in the field of computer vision. The ability to identify and classify objects, either in a single scene or in more than one frame, has gained huge importance in a variety of ways, as while operating a vehicle, the operator could even lack attention that could lead to disastrous collisions. In attempt to improve these perceivable problems, the Autonomous Vehicles and ADAS (Advanced Driver Assistance System) have considered to handle the task of identifying and classifying objects, which in turn use deep learning techniques such as the Faster Regional Convoluted Neural Network (F-RCNN), the You Only Look Once Model (YOLO), the Single Shot Detector (SSD) etc. to improve the precision of object detection. YOLO is a powerful technique as it achieves high precision whilst being able to manage in real time. This paper explains the architecture and working of YOLO algorithm for the purpose of detecting and classifying objects, trained on the classes from COCO dataset.