Computer Science and Engineering

A local area network (LAN) is a computer network within a small geographical area such as a home, school, computer laboratory, office building or group of buildings. A LAN is composed of interconnected workstations and personal computers which are each capable of accessing and sharing data and devices, such as printers, scanners and data storage devices, anywhere on the LAN. LANs are characterized by higher communication and data transfer rates and the lack of any need for leased communication lines. Communication between remote parties can be achieved through a process called Networking, involving the connection of computers, media and networking devices. When we talk about networks, we need to keep in mind three concepts, distributed processing, network criteria and network structure. The purpose of this Network is to design a Local Area Network (LAN) for a BAEC (Bangladesh Atomic Energy Commission) Head Quarter and implement security measures to protect network resources and syst...

Now EBOOK ON AMAZON———OUR KNOWLEDGE SNGULARITY—undo harms top ten colleges cripple minds with—-when our best & brightest fail and the rest of us lap venal of their droppings off streets——when to assure that your kids safely get worth not self uberalles religion of business harm and cocaine habits from “top” colleges professors ventures firms and vampire blood sucking media, you must in parallel have them learn from a clever caring deep ANTIDOTE COLLEGE—this book is it!!!!  There is nothing remotely like it anywhere!  But it is an unpleasant read for those wedded to some snob college provided STATUS substitutes for care decency thought.  Buy it instantly 2 days from now. STARTS WITH A NEW KIND OF COLLEGE TEACHING APPLYING INVENTING 33 creativity sciences in parallel. WHEN creativity leads usual MBA and tech venturings ruin lives in baseless enthusiasms.  Read find bedrock instead!!!!?    NOW ALSO———ON AMAZON 2 more Ebooks formatted for iphone reading.  SAVE A KID——SAVE YOUR KID——SAVE A NERD——SAVE YOUR NERD——SAVE A TYRANT BOSS——SAVE YOUR TYRANT BOSS——along the way save your self, whatever remains of it.  We are all sick and tired of dealing with non-people in human form all around us. We are all sick of news about the horrible ways they treat each other and the vile inability of any of them with any wealth at all to take care of other people. We are sick of top colleges top professors top institutions top analyses stealing from entire populations and ruining the planet. There is no chance at all that the people we elect will handle any of this——they are the most horrible among us. In this lovely situation you and I have to forge lives create kids selves care happiness etc etc etc as the king of Siam liked to say. I ACTUALLY RESEARCHED THIS DECADES AGO in great practical detail helped by homework i assigned my U Chicago Booth School MBAs. These 3 ebooks are WITHOUT PEER—and utterly essential reading for those of you who think you are fully human now.  They are NOT for wimps falling for the ways of their own gender nation profession era.  ENJOY—give them to your tyrant boss as present or drop anonymously on their desk and observe LOL

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.

Everyday trillion bytes of data are generated, 90%of which has been created in the last two years alone, from this it can predict the amount of data that will be generated in future. It is necessary, to introduce some techniques for providing security such a huge amount data and to deal with limitation of 'Cloud Security'. Such cloud security can be used nearly in every aspect of cloud environment system. The motive of this paper is to understand how cloud security is prime and the necessity of multi cloud system. This paper also gives a short glimpse of multi cloud security implications in the real world and its role in every field along with challenges and advantages. This paper also explores various techniques, algorithms such as Shamir Secret and Blowfish, systems of multi cloud system in various sectors of digital world.

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.

Facial recognition systems are built on computer programs in order to analyse images of human faces for the purpose of identifying them. The programs take a facial image, detects the face extracts crops the image and stores it in the file called a "template." Using templates, the software then compares that image with another image and produces a score that measures how similar the images are to each other. Typical sources of images for use in facial recognition include video camera signals and preexisting photos such as those in driver’s databases. Facial recognition systems are computer-based security systems that are able to automatically detect and identify human faces. These systems depend on a recognition algorithm, such as Haar cascades. The first step for a facial recognition system is to recognize a human face and extract it for the rest of the scene. Next, the system measures nodal points on the face, such as the distance between the eyes, the shape of the cheekbones and other distinguishable features. Object Detection using Haar feature-based cascade classifiers is an effective object detection method proposed . It is a machine learning based approach where a cascade function is trained from a lot of positive and negative images. It is then used to detect objects in other images. Experimental results suggest that the proposed Haar cascade approach provides a better representation and achieves lower error rates in face recognition.

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.

Dear Reader,

Let's get the introductions out of the way.I am not a recruiter. I am a software engineer. And as such, I know what it's like to be asked to whip up brilliant algorithms on the spot and then write flawless code on a whiteboard. I know because I've been asked to do the same thing-in interviews at Google, Microsoft, Apple, and Amazon, among other companies.

I also know because I've been on the other side of the table, asking candidates to do this. I've combed through stacks of resumes to find the engineers who I thought might be able to actually pass these interviews.
I've evaluated them as they solved-or tried to solve-challenging questions. And I've debated in Google's Hiring Committee whether a candidate did well enough to merit an offer. I understand the full
hiring circle because I've been through it all, repeatedly. And you, reader, are probably preparing for an interview, perhaps tomorrow, next week, or next year. I am here to help you solidify your understanding of computer science fundamentals and then learn how to apply those fundamentals to crack the coding interview.

The 6th edition of Cracking the Coding Interview updates the 5th edition with 70% more content: additional questions, revised solutions, new chapter introductions, more algorithm strategies, hints for all problems,
and other content. Be sure to check out our website, CrackingTheCodinglnterview.com, to connect with other candidates and discover new resources. I'm excited for you and for the skills you are going to develop. Thorough preparation will give you a wide range of technical and communication skills. It will be well worth it, no matter where the effort takes you!

I encourage you to read these introductory chapters carefully. They contain important insight that just might make the difference between a "hire" and a "no hire:' And remember-interviews are hard! In my years of interviewing at Google, I saw some interviewers ask "easy" questions while others ask harder questions. But you know what? Getting the easy questions doesn't make it any easier to get the offer. Receiving an offer is not about solving questions flawlessly (very few candidates do!). Rather, it is about answering questions better than other candidates. So don't stress out when you get a tricky question-everyone else probably thought it was hard too. It's okay to not be flawless. Study hard, practice- and good luck!

Gayle L. McDowell
Founder/CEO, CareerCup.com
Author of Cracking the PM Interview and Cracking the Tech Career

The wireless sensor network (WSN) is a combination of sensing, computation, and communication into a single tiny device. A sensor network consists of an array of numerous sensor networks of diverse types interconnected by a wireless communication network Sensor data is shared between these sensor nodes and used as input to a distributed estimation system. The system extracts relevant information from the available data. Fundamental design objectives of sensor networks include reliability, accuracy, flexibility, cost effectiveness, and ease of deployment. Each node has at least a sensor with an embedded processor, and low power radius. It acts as information source, sensing and collecting data samples from the environment. Node can also act as information sink, receiving dynamic configuration information from other nodes or external entities. The end portion of a node can be an antenna. A chosen configuration is the microstrip structure which allows for planar circuitry to be integra...

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.

TODAY, The use of a wireless network enables enterprises to avoid the costly process of introducing cables into buildings or as a connection between different equipment locations. The basis of wireless systems are radio waves, an implementation that takes place at the physical level of network structure. Wireless network is installations a method by which homes, telecommunications networks and enterprise (business) avoid the costly process of introducing cables into a building, or as a connection between various equipment locations. Delay tolerant networks (DTNs), such as sensor networks with scheduled intermittent connectivity, vehicular DTNs that disseminate location-dependent information, and pocket-switched networks that allow humans to communicate without network infrastructure, are highly partitioned networks that may suffer from frequent disconnectivity. In DTNs, the in-transit messages, also named bundles, can be sent over an existing link and buffered at the next hop until the next link in the path appears. This message propagation process is usually referred to as the “store-carry-and-forward” strategy, and the routing is decided in an “opportunistic” fashion. We aim to evaluate the added effect of the presence of malicious nodes on ad hoc network performance, and determine appropriate measures to detect malicious nodes. A malicious node advertising itself as having a valid route to the destination. With this intension the attacker consumes or intercepts the packet without any forwarding. An attacker can completely modify the packet and generate fake information, this cause the network traffic diverted or dropped. Let H be a malicious node. When H receives a Route Request, it sends back a Route Reply immediately, which constructs the data and can be transmitted by itself with the shortest path. So S receives Route Reply and it is replaced by H->S. then H receives all the data from S. In this research we propose a new assesment based scheme for detection of Malicious Nodes in DTN. And examine different strategies for prevention to malicious nodes as well as Compare out come proposed scheme with the earliest established schemes.

Now that many shops, offices and institutions are re-opening again after the Corona lockdown, many businesses are faced with the need to provide the best possible protection for their staff and customers. Face masks and body temperature checks play an important part in the protection effort. While this is already done routinely and at a large scale at airports or railway stations, many businesses and institutions are struggling to meet the challenge. Face mask monitoring often requires additional staff resources. At the same time, body temperature checks by staff come with certain risks in terms of hygiene and data privacy.

A large number of people have attempted to create mathematical models in order to develop and optimize agricultural production; however almost none of them address the factors such as use of fertilizers (N, K, P). More use of fertilizers can deteriorate the fertility of soil and can lead to the low production for years to come. In this study a predictive model is formulated that aims to predict the best crop to be grown in available weather conditions and nutrients present in the soil thereby reducing the use of chemicals and taking a step forward towards organic and chemical free agriculture.

Any data that user creates or owns is known as the user's data (For example: Name, USN, Phone number, address, email Id). As the number of users in social networks are increasing day by day the data generated by the user's is also increasing. Network providers will publish the data to others for analysis with hope that mining will provide additional functionality to their users or produce useful results that they can share with others. The analysis of social networks is used in modern sociology, geography, economics and information science as well as in various fields. Publicizing the original data of social networks for analysis raises issues of confidentiality, the adversary can search for documented threats such as identity theft, digital harassment and personalized spam. The published data may contain some sensitive information of individuals which must not be disclosed for this reason social network data must be anonymized before it is published. To do the data in nominate the anonymization technique should be applied, to preserve the privacy of data in the social network in a manner that preserves the privacy of the user whose records are being published while maintaining the published dataset rich enough to allow for the exploration of data. In order to address the issue of privacy protection, we first describe the concept of k-anonymity and illustrate different approaches for its enforcement. We then discuss how the privacy requirements characterized by k-anonymity can be violated in data mining and introduce possible approaches to ensure the satisfaction of k-anonymity in data mining also several attacks on dataset are discussed.

In today's world reality has moved toward becoming digitized, on the off chance that we make fuel meter in the vehicle as digital it will help know the accurate measure of fuel present in the fuel tank. In our task, we have made a digital fuel meter. Here, we are showing the measure of fuel present in the tank digitally. Fuel robbery is additionally an issue in everywhere throughout the world. In our undertaking at whatever point there is fuel burglary happens, because of the commotion of thief alert individuals know about fuel robbery and furthermore amid fuel robbery an instant message is conveyed on portable to the proprietor of the bicycle. This is the constant happening process. The past vehicle framework doesn't have such usefulness that there is no presentation gear level whatever might be the condition through the bicycle is running or not. In any case, in our framework, we can defeat the above issue by utilizing the digital meter which demonstrates the rigging level in the enduring state or running condition of the vehicle.

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.

In this paper, we are just going to develop the concept for online payment for tollgate, and using this same system we just detect the theft vehicle. Time and efficiency are a matter of priority of present day. In order to overcome the major issues of vehicle congestion and time consumption RFID technology is used. RFID reader fixed at tollgate frame reads the tag attached to number plate of vehicle0. The RFID sensor in the tollgate detects the approach of the incoming vehicle's tag and toll deduction takes place through a prepaid card assigned to the concerned RFID tag that belongs to the owners' account. The concept proposed is of automatic toll tax payment system and the amount transaction information sends to the cell phone of the motorists through the GSM modem technology. This makes tollgate transaction more convenient for the public use.In this same process, once the user registered with his vehicle number which was already in number plate, if the user was lost his vehicle means just he can request in the website to find the vehicle. And if the theft vehicle come across the tollgates the RFID sensor will send the signal to the tollgate booth, and then the vehicle will be hand over to the particular user who have left his/her vehicle.

Today, Image Processing has become one of the popular and essential research domains in the field of computer science and information technology. Important tasks of image processing are image enhancement, image compression and information extraction. Image enhancement techniques are used to improve the quality of image where as information extraction techniques extract the statistical information about portion of an image or any particular image. Image compression is reducing the size of the digital image and allows more images to be stored in a computer disk. In this digital era, people can handle large amount of digital documents and with this documents we need to perform several tasks. Digital images may contain both machine printed documents and handwritten documents. Machine printed document images might have been produced using various technologies with good quality. A handwritten digital document has poor quality like blurred images, old handwritten manuscripts and handwritten variations, hence difficult to identify the texts. Hence the main objective of this paper is to enhance the handwritten image quality using various image enhancement techniques like Noise Removal, Contrast Stretching, Morphological Operations and Interpolations.

Now a day, Information Security has primarily more attractive concern and today when most of the sensitive data is stored on Cloud with client organization having lesser control over the outsourced data, the fundamental way to fix this problem is to do encryption of data. So, a secure user can impose with information get to control system must be given before the clients store any information on the cloud storage. Attribute Based Encryption (ABE) is an asymmetric key based crypto system that has received much focus that provides fine-grained data access control to data files deployed on the cloud. Here, we present a more proficient and most important type of ABE technique that not only considers the Outsourced ABE construction but also address the issue of revocation in case of user leaving the group or organization; the keys are updated once a specific user is removed from the group, and these updated new keys are shared between the existing users also our system supports the keywo...

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

There is much news that reads smuggling of trees like sandal, sagwan etc. The wood from these trees are very costly and are not widely available everywhere. The scope of the project is to provide alerts about changes happening in the forest due to intrusion. The system not only provides data regarding intruder but also helps to monitor forest fire, fall detection as well as pH content of soil. The system sends various alerts regarding to the type of issue occurred. Multiple sensors are used in this system to monitor data. These sensors reduce the extent of danger that may be caused in a forest. This system can prove very helpful for monitoring areas in forests which have such issues.

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.

Shiva Sagar Lake which is also called as Shiva Reddy Peta cheruvu or Sir Vikar-ul-Umra is situated at Shiva Reddy Peta village near Vikarabad town in Ranga Reddy which is about 70 kilometers from Hyderabad. It spreads an area of around 93 hectares of land and it is 50-100 meters depth. The present paper deals mainly with the study of physico-chemical parameters in Shivasagar Lake. Detailed Physico-chemical characteristics of this lake were analyzed. The various physico-chemical parameters like Temperature, and sulphates were analysed. The values of Physico-chemical parameters which were found in the lake always below the drinking water quality standards. Therefore, it can be concluded that the water of the Lake is fit for consumption according to drinking water quality standards (BIS, 2003).

Organizational architecture is composed under a process called organizational architecture process. This process is complicated and architecture can use its framework as a modulator of structure to control complicacy and apply the method as a behavior director. In architecture, behavior is prior to structure, and a structure may have different behaviors. But which behavior (method) best suite architecture and thus meet the concerned needs? Evaluation of architecture is needed to answer this question. As an instance, this article aims to demonstrate validity of architecture behavior on intelligent fuel card using colored Petri networks. As result, it revealed up that the given solution led to identify traffic points and thus helped the architecture designers in choosing the right method.

https://sites.google.com/site/ijcsis/

Big Data has become a very important part of all industries and organizations sectors nowadays. All sectors like energy, banking, retail, hardware, networking, etc all generate a huge amount of unstructured data which is processed and analyzed accurately in a structured form. Then the structured data can reveal very useful information for their business growth. Big Data helps in getting useful data from unstructured or heterogeneous data by analyzing them. Big data initially defined by the volume of a data set. Big data sets are generally huge, measuring tens of terabytes and sometimes crossing the sting of petabytes. Today, big data falls under three categories structured, unstructured, and semi-structured. The size of big data is improving in a fast phase from Terabytes to Exabytes Of data. Also, Big data requires techniques that help to integrate a huge amount of heterogeneous data and to process them. Data Analysis which is a big data process has its applications in various areas such as business processing, disease prevention, cybersecurity, and so on. Big data has three major issues such as data storage, data management, and information retrieval. Big data processing requires a particular setup of hardware and virtual machines to derive results. The processing is completed simultaneously to realize results as quickly as possible. These days big data processing techniques include Text mining and sentimental analysis. Text analytics is a very large field under which there are several techniques, models, methods for automatic and quantitative analysis of textual data. The purpose of this paper is to show how the text analysis and sentimental analysis process the unstructured data and how these techniques extract meaningful information and, thus make information available to the various data mining statistical and machine learning) algorithms.

In wireless sensor network, random deployment of nodes may cause serious coverage overlapping and the death of the nodes may also cause severe coverage problems in original network. There are several hole repair algorithms which take density of the nodes in the post deployment scenario. These algorithms consider limited mobility of the nodes and nodes with higher degree of coverage overlapping is selected. Coverage holes of the network are repaired by moving nodes which has high degree of density. This maintains uniform network density without increasing the coverage degree of the neighbor node. Single and multiple node failure is considered. Due to continuous node failure, the network may not be healed after certain healing process. The node cannot move when the energy goes below the critical level. To avoid this type of problem, the failure detection based on the energy loss is proposed. Nodes with low energy level are identified and are completely replaced by actor nodes.Actors are usually resource-rich devices equipped with better processing capabilities, stronger transmission powers and longer battery life.Here the hole detection and replacing are based on three distinct phases 1) hole identification 2) hole discovery and border detection 3) Node healing and replacement. Distributed and localized holedetection and healing algorithm deals with the holes of various forms and sizes despite node distribution and density. The proposed algorithm consumes less amount of energy when compared to existing algorithm.

There are various algorithms and methodologies used for automated screening of cervical cancer by segmenting and classifying cervical cancer cells into different categories. This study presents a critical review of different research papers published that integrated ML methods in screening cervical cancer via different approaches analyzed in terms of typical metrics like dataset size, drawbacks, accuracy etc. An attempt has been made to furnish the reader with an insight of Machine Learning algorithms like SVM (Support Vector Machines), k-NN (k-Nearest Neighbors), RFT (Random Forest Trees), for feature extraction and classification. This paper also covers the publicly available datasets related to cervical cancer. It presents a holistic review on the computational methods that have evolved over the period of time, in detection of malignant cells. In this paper, we are going to train our model using various machine learning techniques and all the models thus made are compared in terms of accuracy, precision and recall.

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

Advanced plant monitoring system is a method which is used to identify the health and hydration level of plants. The status of the hydration level of a plant is updated through SMS using smiley application. This system has the ability to detect the possibility level of infection of plants and to detect hydration level in plants. In order to make farmers understand the information given by the application, the smiley intimate system is used.

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.

https://www.ijert.org/q-learning-fingerprint-representations-method-for-matching-low-quality-fingerprint-features

https://www.ijert.org/research/q-learning-fingerprint-representations-method-for-matching-low-quality-fingerprint-features-IJERTV8IS090081.pdf

Due to its non-invasiveness, high recognition accuracy and the use of fingerprints are one of the consistent biometric characteristics in the context of human recognition and identification. In this paper here they proposed a new machine learning method can be utilized for minutiae detection in low quality fingerprint images. Traditional methods have using initial preprocessing step but due to lack of robustness on highly sensitive to noise and image quality. We propose a more robust approach in which detects fingerprint images to recognize minutiae. Here they use machine learning to improve image quality an most advantageous policy. Multi-layer perceptions are used to large state space and select right reward structure and learning location to learn the assignment. One of the major problem is that the enhance minutiae points states are easily find and their learning job as well. An experimental result shows that our algorithm gives better results on both parameters.

Cluster is a gathering of information individuals having comparable qualities. The procedure of setting up a connection or getting data from crude information by performing a few operations on the information set like grouping is known as information mining. Information gathered in reasonable situations is usually totally arbitrary and unstructured. Consequently, there is dependably a requirement for examination of unstructured information sets to determine important data. This is the place unsupervised calculations come into picture to prepare unstructured or even semi organized information sets by resultant. K-Means Clustering is one such method used to give a structure to unstructured information so that significant data can be separated. Discusses the implementation of the K-Means Clustering Algorithm over a distributed environment using Apache Hadoop. The key to the implementation of the K-Means Algorithm is the design of the Mapper and Reducer routines which has been discussed in the later part of the paper. The steps involved in the execution of the K-Means Algorithm has also been described and this based on a small scale implementation of the K-Means Clustering Algorithm on an experimental setup to serve as a guide for practical implementations.

One of the key issues that need to be addressed in wireless sensor network field is how to create a most efficient energy system. Ad-hoc Networks are becoming an effective tool for many mission critical applications such as troop coordination, situational awareness Etc. Ad-hoc Networks having limited computation and communication resources. To unguaranteed connectivity to trust authorities make known solutions for trusted authorities make knows solutions for single hop wireless networks. In this Project I am presenting A  Distinct Authentication Key for New TAM Protocol For large scale dense ad-hoc networks. TAM exploits network clusters to reduce overhead and ensure scalability. Multicast traffic with in a cluster employs a “One way hash function” chain in order to authenticate the message source. Cross cluster multicast traffic includes Message Authentication Codes (MAC’s) that are based on a set of keys. Result in terms of bandwidth overhead and delivery delay

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 world is changing rapidly, so is academics. E-learning has altered the area of academics and education. ICT enabled learning has given ideal services to students by providing any type of content on demand which is proportional to the performance of students. The concentration of learner has been found instinctive; thus there is a need of engaging mind towards course progress with its entirety till the objectives of the course will be achieved. There are several e-learning platforms available as EdX, Udacity, Khan Academy, Alison those have a number of learners registered for various courses. Studies suggest that these platforms suffer from the common problem of learners’ dropping out. Investigations also claim early leaving rate is increasing due to lack of quality of content, distraction factors, learners’ mind change, outdated and succinct information, and some more detraction factors. These issues have been observed on the basis of early leaving rates in various MOOCs. Thus t...

Here in this text, I aim to discuss briefly the basics of how Artificial Neural Networks function and also how they have been present in our daily life. My purpose is to do that in a way someone with just basic knowledge or even no knowledge at all about this topic would be able to understand it at least a little.