Big data refers to a process that is used when traditional data mining and handling techniques cannot uncover the insights and meaning of the underlying data. Data that is unstructured or time sensitive or simply very large cannot be processed by relational database engines. This type of data requires a different processing approach called big data, which uses massive parallelism on readily-available hardware. Quite simply, big data reflects the changing world we live in. The more things change, the more the changes are captured and recorded as data. Take weather as an example. For a weather forecaster, the amount of data collected around the world about local conditions is substantial. Logically, it would make sense that local environments dictate regional effects and regional effects dictate global effects, but it could well be the other way around. One way or another, this weather data reflects the attributes of big data, where real-time processing is needed for a massive amount of data, and where the large number of inputs can be machine generated, personal observations or outside forces like sun spots. Processing information like this illustrates why big data has become so important: • Most data collected now is unstructured and requires different storage and processing tthan that found in traditional relational databases. • Available computational power is sky-rocketing, meaning there are more opportunities to process big data. • The Internet has democratized data, steadily increasing the data available while also producing more and more raw data. Data in its raw form has no value. Data needs to be processed in order to be of valuable. However, herein lies the inherent problem of big data. Is processing data from native object format to a usable insight worth the massive capital cost of doing so? Or is there just too much data with unknown values to justify the gamble of processing it with big data tools? Most of us would agree that being able to predict the weather would have value, the question is whether that value could outweigh the costs of crunching all the real-time data into a weather report that could be counted on.

The final year project is a partial requirement for students to successfully complete their B. Tech degree. There is a sincere effort by the engineering institutes to develop an overall understanding about the discipline rather than just limiting student’s knowledge to textbooks. It is a good idea to incorporate project in the B.Tech courses, because it makes the course much more interesting and rewarding for the students.Find out problems faced by users and try to develop a solution for it. Problem can be anything, it shouldn't be a big problem. For example you can think of something for your college students, may be to improve interaction between students and teachers or between students. If you are developing some application then try to give sometime on it's graphics also.Being a final year student myself, I would suggest you to go through IEEE papers about the latest technologies or come up with a new mind blowing idea and implement the same.I would suggest a few ideas that final year students can keep in mind while opting to choose their project.1. First, choose a language or technology(C, C++, Java, Python, etc) and select a problem statement even though it's been already solved, you can go through it and implement that in your own way.Example : Try increasing the efficiency of a particular algorithm.2. Have a session of brainstorming with your friends, seniors and teachers to know if such a system is feasible.3. There are several competitions where projects having contributions to the society are awarded. So think over this point.Eg. Tcs best project award.4. Last but not the least be prepared for the project, choose your project mates wisely, divide the work and don't equip yourselves with a huge load.5. Refer the ocean of content available on the Internet and often seek help from your guides and seniors. Experience matters a lot.Happy developing.

A whopping number of engineering students graduate every year. It is easy to get lost in the crowd. If you are a final year engineering student, you have only one year left to upgrade your skills and enhance your employability. Here are some tips on how you can improve yourself and get closer to a dream job.Find out More About ‘You’One question that you are sure to face after graduating is ‘Tell us more about you’. Interviewers will ask you this question. You can use this question to direct the interview to your advantage. Prepare well in advance for answering this question. Identify and develop the areas of strength that will set you apart from others. In your answer to the question, you can talk about these strengths and put yourself in a much better position to bag the job.The following tips are to help you develop these strengths. These tips will help you become a valuable employee for an organization.Use Academic Projects to your AdvantageInterviewers will ask you questions about your academic projects. Their main motive is to check how good you are at practical skills. Your project gives you an opportunity to put theoretical knowledge to actual practice. So be honest with your academic project and make the best out of it. Do not try to copy other project ideas. The practical experience gained will not only help with interviews but also help you be a better engineer. By doing your own projects you will develop a good understanding of all principles involved. Also, you have a higher chance of getting a job.Stay Updated with TechnologyEngineering technologies are always evolving. Almost every day a new technology comes into scene. Internet is the best source to keep a watch on recent developments in technology. Remember, your education does not stop after graduation. Try to widen your knowledge base. Read more books, blogs, news articles, etc.Get Practical ExperienceRecruiters look for achievements. As a student a good way to prove achievements is by showcasing the work you have done in projects. Take part in technical training to develop practical skills. These experiences help you to work in a team, be a problem solver, develop creative thinking and find the fun in engineering. Don’t just take up courses or workshops restricted to your engineering domain. Try to take part in interdisciplinary activities. This is because when you become a professional engineer, you do not just have to deal with one subject.Strengthen your BasicsBrush up on all basics of engineering concepts from previous years. Recruiters check if you are strong in fundamental concepts. Prove that you follow the correct approach to learning by demonstrating your basic knowledge. Expertise on fundamental principles will also help you in the future. For instance, it will improve your confidence to take up future roles in industry.Improve Non-Technical SkillsPrepare for aptitude, reasoning tests by practicing daily from online resources. You can improve communication skills by reading books and conversing with more people. Ask questions, seek out answers, compare options and make decisions. Keep things in perspective and learn from experience and practice. Take up courses for improving conversation skills, aptitude skills and other soft skills.Develop your NetworkMake sure that you stay connected with all your professors and peers at college. Get in touch with professionals who do what you want to do. Spread your network through online and social media. Websites like linkedin give you a good opportunity to network in a professional manner. Networking will open up opportunities in the future. And you get to learn from mistakes and success stories of other people in your network.Find Jobs the Right wayMake sure you register on various job portals and forums like naukri.com, monster.com , chetanasforum.com, etc. Make a list of all companies that fit your qualification. Keep checking their websites for internship or full time job opportunities. Use the internet to find potential job openings. And always keep your Resume updated.

The whole process of picking up a good idea to develop a project as a part of your curriculum. It's because working on a project puts all your knowledge into practical use and it's a great learning experienceThat means you will have to come up with a project idea that is in sync with your existing knowledge. You wil be required to learn a lot of new things while you are working on the project. Lets discuss how to pick a project idea.1. You need not think an idea that is out of world No one expects you to develop a project that the humans haven't seen before. All you should focus on is 'improvements in the things around you'. If you wish to develop an app : think of a problem that you have faced and have felt that there should have been an app to do that! If you are an electronics / electrical engineer - think of something that you can do with electronics. Look for improvements and things that can be done better than current solutions. Of course you might just take up a study project - but you should have your project guide's approval. 2. BudgetMake sure that the topic selection is always a team effort. Every person in the team should be convinced that the topic is the right one for them. If a topic is of interest to only few members of the team; the team won't be able to function together throughout the duration of the project. If you want the entire team to stick together and work with enthusiasm; you need everyone's consent for the topic.3.TeamBudget is always the criteria that you and your team should consider when deciding on your final year or third year engineering project. Also analyse if you will ever need funding for your project. If the answer is yes; you need to start looking for the sources right away.4. Technology NeededOne of the most important factors in your topic selection will be the overall requirements of the project - and whether the team is comfortable with them. If your project requires you to have Raspberry Pi; ensure that all the team members are comfortable using it. If not - have the consent of all the users to learn the required resources as fast as they can.

19thInternational Conference on Modern Research in Engineering and Technology (ICMRET2017) Held on 13 & 14 October 2017, Hyderabad, India Organized by International Organization of Scientific Research and Development(IOSRD), India. The ICMRET is an annual conference aimed at presenting current research being carried out in the fields of Science, Management, Engineering and Technology. The conference brings together the scientists, scholars, engineers and students from various colleges, universities, research organizations and industries all around the world to present ongoing research in the field of Science, Engineering, Management and Technology.The primary goal of the conference is to promote research and developmental activities in Science, Engineering & Technology. Another goal is to promote scientific information interchange between researchers, engineers, scientists, academicians, developers, students, and practitioners working in and around the world. The conference will be held every year to make it an ideal platform for people to share views and experiences in Science, Engineering & Technology related areas. English is the official language of the conference. We welcome paper submissionsAll accepted papers will be published in ANNA UNIVERSITY ANNEXURE-II, SCOPUS, Thomson Reuters (ISI), Google Scholar International journalsThe ICMRET is an annual conference aimed at presenting current research being carried out in the fields of Science, Management, Engineering and Technology. The conference brings together the scientists, scholars, engineers and students from various colleges, universities, research organizations and industries all around the world to present ongoing research in the field of Science, Engineering, Management and Technology.

You can submit your paper and get it published for free in many journals under Elsevier. Though, your paper will not be an open access. Most of the journals are quite flexible when it comes to publishing papers. If the authors are not paying, the journal will take the accessing free from the readers. Prepare Your Paper For SubmissionPreparing your journal paperRead the Guide for Authors, which you can find on the journal’s homepage. It contains specific requirements related to ethics, open access options, copyright and funding body agreements. It also provides guidelines for preparing your paper, covering:• article structure• abstract• highlights and keywords• accepted formats for artwork, data sources and videoEnrich your articlePublishing in an Elsevier journal gives you the opportunity to enrich your article with a different content, such as graphical abstracts, interactive maps, 3D data visualizations and multimedia. adding valuable context to an article by connecting it with other resources on the web. You will need to prepare this content before you submit.Share Research DataBefore sharing your data, you should consider not only the metadata you will need to provide along with the data to make it easily understood, but also the privacy, intellectual property, copyright, or licensing issues to be addressed with regard to the sharing.When preparing your manuscript, think about giving your final article more visibility by sharing your research data. You can upload your research data directly with your manuscript to Mendeley Data, link to research data hosted in repositories or co-submit a data or methods article. You can also include interactive data visualizations with your article. Don’t let your language get you rejectedPoor English is one of the most common reasons for rejection. You can avoid this by having your manuscript proofread or edited

Python is a general-purpose language. It has wide range of applications from Web development (like: Django and Bottle), scientific and mathematical computing (Orange, SymPy, NumPy) to desktop graphical user Interfaces (Pygame, Panda3D).The syntax of the language is clean and length of the code is relatively short. It's fun to work in Python because it allows you to think about the problem rather than focusing on the syntax.Major uses of Python• System utilities (system admin tools, command line programs).• Web Development.• Graphical User Interfaces (Tkinter, gtk, Qt).• Internet scripting.• Embedded scripting.• Database access and programming.• Game programming.• Rapid prototyping and development.• Distributed programmingPython a good language for beginning programmersYes. It is still common to start students with a procedural and statically typed language such as Pascal, C, or a subset of C++ or Java. Students may be better served by learning Python as their first language. Python has a very simple and consistent syntax and a large standard library and, most importantly, using Python in a beginning programming course lets students concentrate on important programming skills such as problem decomposition and data type design. With Python, students can be quickly introduced to basic concepts such as loops and procedures. They can probably even work with user-defined objects in their very first course.For a student who has never programmed before, using a statically typed language seems unnatural. It presents additional complexity that the student must master and slows the pace of the course. The students are trying to learn to think like a computer, decompose problems, design consistent interfaces, and encapsulate data. While learning to use a statically typed language is important in the long term, it is not necessarily the best topic to address in the students’ first programming course.Many other aspects of Python make it a good first language. Like Java, Python has a large standard library so that students can be assigned programming projects very early in the course that do something. Assignments aren’t restricted to the standard four-function calculator and check balancing programs. By using the standard library, students can gain the satisfaction of working on realistic applications as they learn the fundamentals of programming. Using the standard library also teaches students about code reuse. Third-party modules such as PyGame are also helpful in extending the students’ reach.

1) Check your institution’s policies and practicesInstitutional policies and practices vary. Find out who will attend your viva (eg will a supervisor attend, will there be an independent chair?) and what their roles are.Penny Tinkler and Carolyn Jackson, authors of The Doctoral Examination process: A Handbook for Students, Examiners and Supervisors2) Re-read your thesis – and keep up-to-date with researchDon’t underestimate the amount of time the examiners will have spent reading and thinking about your thesis – however, you should remember that you are still likely to be the “expert in the room” on this particular topic. Check to see if any relevant recent papers have emerged since submitting the thesis and, if so, read these.Dianne Berry, dean of postgraduate research studies, University of Reading3) As an examiner, you tend to stick to things you’re an expert in when driving the questioningYour viva panel will consist of an external expertise in your subject area and an internal which may be in a subject field associated or directly related to yours. The external examiner is the one who mainly calls and fires all the shots and so it’s pretty important to have a knowledge of their published contributions, especially those that are related to your thesis in any way.4) Think about what you will or won’t defendConsider carefully what you will defend to the hilt in the viva, and what you are prepared to concede. It’s important to defend your claims about the originality of the thesis and its contribution to knowledge. However, no research is perfect, and showing that you have considered what could have been done differently, or even better, is not a bad thing.Penny Tinkler and Carolyn Jackson, authors of The Doctoral Examination process: A Handbook for Students, Examiners and Supervisors5) Draw up lists of possible questions – especially ones you dreadI collected questions from a bunch of different places (listed here) which I then tailored to my PhD. Somebody I worked with also recommended that I put together my 10 nightmare questions. I found this really useful, by writing down and thinking about my dreaded questions, they were no longer so bad – it was almost as if I’d faced the beast.Generally speaking, I was able to predict the questions that I was asked. There were a couple that were unexpected but they were either conceptual points or based on literature that I just didn’t know.Richard Budd, research assistant, University of Bristol who sat his viva in summer 2014 and has blogged about the experience6) It’s not like sitting at a laptop where you can edit a sentence as you go alongBy the time you finish your PhD you’ll know your thesis inside out. One of the things you won’t be as practised at is talking about it. When I was preparing for my viva, I practised vocalising answers. It’s not a case of needing to learn to answers verbatim – this would only work as a technique if you could guarantee the exact way your examiner will ask a question – but it is about thinking about how you will articulate certain things. A viva isn’t like sitting at a laptop where you can edit a sentence as you go along. Richard Budd, research assistant, University of Bristol who sat his viva in summer 2014 and has blogged about the experience7) Bring a printed copy that is exactly the same as that of your examinersEnsure you and your supervisor have a printed copy that is exactly the same as that of your examiners (specifically the same pagination). Mark with tabs the key sections and highlight for reference important quotes and points you might want to refer to. If you have some key diagrams it may help to have these printed larger on A4 sheets that can be used in a discussion.There is a chance, albeit slim, that an examiner will wish to see some piece of experimental data, software, or other supporting evidence. Have this all neatly archived and accessible. You can do this after submission.Anthony Finkelstein, dean of the UCL faculty of engineering sciences who has blogged about surviving vivasDuring the viva8) Get off to a good startGive a few detailed answers in the opening 15 minutes, demonstrating knowledge, describing your thinking and working - then the examiners are likely to relax into the viva. If the first few answers are short and non-specific, not demonstrating knowledge, this can begin to raise concerns, and that can set the tone for the whole viva. This is avoidable. Rowena Murray, author of How to Survive Your Viva: Defending a Thesis in an Oral Examination9) Prepare for the icebreakerEvery viva opens with that dreaded icebreaker that is supposed to break you in gently but often seems to be the thing that gets students into a pickle. It’s so basic, students almost forget about it. Most often this would be to give a five to 10 minute introduction to your work and your key findings. This is such a common question that not preparing for it would be silly.Dr Bhavik Anil Patel, senior lecturer in physical and analytical chemistry10) Silence doesn’t mean bad newsDon’t assume that you will be given any indication of the outcome at the start of the viva. The examiners may or may not offer comments on the thesis at this stage and candidates should not interpret a lack of comments at this point as a negative sign. In some cases institutional policy prohibits it. Penny Tinkler and Carolyn Jackson, authors of The Doctoral Examination process: A Handbook for Students, Examiners and Supervisors11) Don’t point out your own weaknessesAvoid shooting yourself in the foot by highlighting the weaknesses in the thesis by being overly humble (eg “I didn’t think this would be an acceptable piece of research given the way I handled x or y”) or by saying what you “failed to achieve” or “did not manage to carry out in a robust manner” etc. Leave that to the examiners to pick up in their reading, they don’t need help.12) Don’t talk like a politicianThere’s a danger of trying to over-prepare. Don’t learn answers off by heart – it removes the spontaneity and is obvious to examiners. If a student has pre-prepared answers they become a bit like politicians, answering questions they weren’t asked rather than the ones they were. I have come across mixed views on mock vivas. Some people really like them – and they can settle nerves – but other times it can remove spontaneity and steal your thunder.Jerry Wellington, head of research degrees at University of Sheffield and author of Succeeding with Your Doctorate13) You may need to move from friendly questions to complex debatesVivas can appear friendly and then suddenly go very conceptually complex. The language used is an alternation between accessible normal language and really specialised arguments. The student needs to be able to move orally between the two.Gina Wisker, professor of higher education and contemporary literature at Brighton University14) If things get on top of you, use the excuse of having a look at the thesisMake sure that before the viva you get plenty of sleep, eat properly and de-stress. If things get too much when you’re in there, use the excuse of having to look something up in your thesis. You could also pause and say “Can I write that down for a moment?” Stall for time until you get yourself back together again. Gina Wisker, professor of higher education and contemporary literature at Brighton University15) Focus on your contributionOne of the most important things that the examiners will be looking for in your thesis, is the “contribution to knowledge”. It is the contribution which makes your work doctoral level. Be sure that you understand exactly what your contribution is, and that you are able to express and explain it clearly and concisely.Write it down in a paragraph. Discuss it with you supervisor and fellow students. Make sure that you can relate your contribution to other work in your field and that you are able to explain how your work is different.16) Expect your viva to last between one and three hoursStudents frequently ask how long the viva is likely to be. Obviously they vary. Discipline differences are important. Our research suggests that most natural and applied sciences vivas were completed in one to three hours, whereas arts, humanities and social science vivas were typically less than two hours long. In the natural and applied sciences 43% of vivas lasted two hours or less, compared to 83% in arts, humanities and social sciences.Penny Tinkler and Carolyn Jackson, authors of The Doctoral Examination Process: A Handbook for Students, Examiners and Supervisors17) Enjoy itThe best advice I ever got was “Try to enjoy it”. It seemed ludicrous at the time, but I actually found myself really getting into the discussion as the viva went on. It’s one of the earliest chances you get to talk to someone who not only informed your research (ideally) but is also conversant with your own. It’s a great chance to explore the contours of your research – treat it as such, and it doesn’t seem quiteso daunting.

Defending your thesis can be an intensely nerve-wracking experience. How can you best prepare to face your examiners?Know the format of your thesis defenseThe format of the defense varies from country to country. Having studied in the UK, my viva-voce defense was essentially an interview with one internal and one external examiner. In other countries it’s common to have public examinations with a whole panel of examiners and an audience of colleagues, family and friends.The first and most obvious tip then is to make sure you know what the format of your exam will be; whether you will have to prepare a presentation and so on.Prepare and practice your presentationIf you have to give a presentation, check any time restrictions so you can prepare accordingly. You don’t want to show up with 100 slides for a 15-minute presentation, nor do you want to show up with 10 slides for a 1-hour presentation.The most important thing to do for any presentation is to practice so that;• You know the material inside out• You know how long it takes• You can refine the presentationYou can practice on your own and with an audience, and you should do both if possible. Practicing on your own and speaking out loud to an empty room may feel silly, but overcoming that discomfort is good preparation for the discomfort of facing an actual audience.Practicing with an audience of peers is then a good way of getting feedback and finding out what questions people ask.The dreaded “awkward question”Whether you have to give a presentation or not, one of the scariest aspects of the defense is the possibility of being asked a question you can’t answer.It’s tempting to try to read a ton of literature to prepare for this, but since it’s very difficult to predict what the examiners will ask and it’s impossible to read everything, this approach isn’t always effective or reassuring (it might make you realize how much you don’t know).There will always be gaps in your knowledge, but actually it doesn’t matter if you don’t know the answer to an awkward question- you can still respond in a way that will make the examiners happy.When you don’t know the answer…You aren’t expected to know everything. Sometimes, an examiner will ask a question they don’t know the answer to, either out of interest (since you are the expert in your research) or because they want to see how you think.While it is OK, sometimes, to just say “I don’t know”, you could also say something like, “I don’t know, but I would think that […] because of x and y, but you would need to do […] in order to find out”. This shows that you have the ability to think as an academic.Core contentOf course there is some core content which you will be expected to know well, but this is set by you, not the examiner. To a large extent, the content of the examination is determined by the content in your thesis.When you choose what to cover in your thesis you are choosing your battleground for the thesis defense, so the best strategy is to stick to the material you know best in your writing!Make sure you have read through your complete thesis at least once before your defense, so you know what you have written about.Dealing with nervesYou will be nervous before your examination. You will almost certainly get an adrenaline rush which can set your heart racing, give you sweaty palms, make your stomach churn and make you want to go to the toilet 10 times in 20 minutes. This is normal!The worst part is the waiting before you start, because there isn’t much you can do to use up all that nervous energy! But once the defense starts, you can do some things to keep it under control.Slow downOne symptom of nerves is to talk really fast and to try to show how much you know and speak in this kind of long stream of consciousness that diverges away from the question until you forget what the actual question was but then you don’t know how to get back to the point and so you just keep talking and that makes you more nervous and how are you going to get off this train of thought…Try to deliberately slow down, and give yourself time to breathe.Try to remember the question, and come back to the point.Once you have answered, stop talking!The examiners expect you to be nervousRemember that the examiners expect you to be a bit nervous, and they will help you through if necessary.It is OK to ask them to repeat or clarify a question. It is OK to pause to think. It is OK to take a sip of water if you need to!Ultimately…Success or failure is determined mainly by the content of your thesis. If your research is good, and you actually did the work, it is highly unlikely that a nervous performance in your defense will lead to failure.Generally speaking, once your thesis is submitted, there isn’t much you can do to affect the outcome (positively or negatively).Read through your thesis, read up on one or two key points if necessary, practice your presentation, and trust that whatever happens you will be OK.Good luck!

PhD study tip #1: Write early and write oftenObviously the more papers you write the better – but that’s not what I mean. I mean write as often as possible, even if you don’t have a paper on the horizon.Start writing as early as possible in your PhD, and write regularly. Some people write daily, others once a week. The goal is to consistently document your progress, what you did, how, and the obstacles you encountered. Writing early will help you to develop and maintain your writing skills for when the time comes to write a full-fledged paper. By writing often you will accumulate content that you can reuse when you need to write abstracts, papers or proposals.I didn’t follow this PhD study tip myself and I regret it. I think I could have written my papers in half the time if I had. Not only this, their quality would have been much higher.PhD study tip #2: Read lots of papersAt the beginning of your PhD you have to read lots of papers. The goal is that you get a clear overview of your research field. You must understand all the important research already done. This is what people call the "state of the art”.Once you know the state of the art in your field, you can see where your PhD fits in. How you are going to contribute and expand the scope of research? It also gives you a roadmap to avoid duplicating existing research and reinventing the wheel. Once you have done most of the reading, you will need to keep track of new developments in your field, by reading new papers and speaking to others about what research is underway. PhD study tip #3: Read other thingsPhD students don’t just encounter academic problems; they also face challenges in time management, motivation or creativity. Reading papers may help you in some of these areas – but not always. That’s why you need to read other types of material. Productivity, personal skills and business books can help you grow as a PhD student. They provide practical advice, including study tips and also general guidance on how to develop essential skills applicable in all kinds of roles.Following blogs such as Thesis Whisperer, Next Scientist or TopUniversities.com can also help you boost your motivation and show you inspiring stories from other PhD students. Remember that you must think creatively, and reading only one type of content (scientific papers in your specific field) may narrow your thoughts.PhD study tip #4: Work in short sprintsAnother study tip that boosted my productivity came from the world of software development. Some people call this agile development, others talk about fast prototyping, short sprints, or ‘ship it fast and get feedback’.Have you ever waited a long time to show something until you felt it was perfect, only to find that, well, the other person disagreed? That waste of time is what you want to avoid. The idea here is to work very fast to produce something that is just good enough, show it, get feedback and improve it in another sprint. And iterate on and on.PhD study tip #5: Focus on small signs of progressHalfway through my PhD I lost motivation because I felt I hadn’t produced anything substantial. My mistake was to bind my satisfaction to having reached important milestones like publishing a paper. Wrong. Those things take too long. I needed some small doses of sweet PhD love along the way.Once I started focusing on smaller signs of progress, everything started to look brighter. I knew that if on a given day I finished three small tasks then I was on the right track, I was making enough progress.Instead of thinking “Am I there yet?” you should ask yourself, “Am I closer than I was three months ago?”PhD study tip #6: Don’t cut cornersSo far we’ve focused on productivity study tips for the PhD student. These allow you to skip unnecessary tasks and focus on what really matters for your PhD. But there is one area where you cannot find shortcuts. That’s in your reputation.During your PhD you may be tempted to do things that seem like a benefit in the short term, but that could harm your reputation in the long term. These shortcuts involve your credibility, your thoroughness and your accountability.Imagine: after six months of preparing your paper, you are almost there. You find there’s a little mistake in the data, but you don’t think it will harm the overall outcome. So why waste your time fixing it? Or why cite all the relevant papers when with a few will do? Even worse, why not use somebody else’s method but not acknowledge that, so it looks like it was your own creation? This sloppiness will eventually come back to haunt you. Sooner or later people won’t trust you. They will not want to collaborate with you. They will not cite your papers. So, even it if means extra work, stay away from cutting corners!

Typical Format of the Project ReportTitle pageTitle page FormatTitle page FormatAll the letters of the title page must be capitalized, and the title page should not contain page numbers. The other aspects of the title page like the title should be like a report, and should contain the name of the organization to which the project is intended to be submitted.Next, the course name should be followed by the student’s name, his roll number, guide’s name and designation, and at the end of the title page, organization’s logo and address should be written, as shown in the above figure.Declaration and ApprovalThe declaration is a statement written by the student who declares that he or she has sincerely completed his or her project. The declaration statement concludes with the signature of the student.The Approval page is also a confirmation from the head of the department, guide, and external examiner about their acceptance of the project. The approval page is endorsed with the signatures of the heads confirming their approval of the project.AcknowledgementThe acknowledgement page depicts the gratitude, respect and thankfulness of the student towards the people who helped him in pursuing the project successfully and ensured successful completion and implementation of the project. In this page, the author expresses his gratitude and concern by using praising and thanksgiving words.AbstractAbstract represents a summarized report of the complete project in a very concise and informative format covering main objective and aim of the project, the background information, processes and methods used, and methodologies implemented, followed with a brief conclusion of two to three lines talking about the results and scope of the project.The entire abstract of a project report should be written in about 250 to 350 words, and therefore, should not exceed any further.Table of Contents, List of Figures and TablesTable of contents provides a complete sketch of the title, subtitles, headings, topics and the project elements that are involved in those headings. In other words, different sections and their titles are included here.The whole project report in a nutshell is made known in the table of contents section, and therefore, it should include the titles of the first, second and third level headers, and must give a clear picture of the report to the reader.Similarly, a list of figures and tables helps the reader to locate diagrams, charts and tables in the document, and therefore, it should be numbered accordingly by chapter and page number. It is not necessary to indicate page numbers for symbols and abbreviations used in the document.The Main Body of the ProjectThe main body of the project should comprise several chapters with the corresponding titles, and each page within these chapters must be numbered in numerals as page numbers. The usual way of presenting these chapters is given below.Chapter 1: Introduction chapter. This chapter should contain brief background information about the project, the methodology implemented for problem solving and the outlines of the results and future scope of the project. It rarely contains drawings and graphical illustrations.Chapter 2: Chapter of Literature Review. It evaluates the current work with the previous one. It depicts the current implementations that overcome the previous problems and limitations of the project, and draws the attention and focus on the foreknowledge work that would be conducted based on the ongoing work at present. It must be clear and simple to understand.Chapter 3-4 or 5: These chapters describe the overall in-depth information about the project. These chapters also involve the basic theoretical information about each and every component & aspect of the project, such as circuit design, simulation implementation and modeling, software implementation, statistical analysis and calculations done, results gained, and so on.The appropriate information should always be accompanied with pictorial representations, tabular demonstrations, diagrams, flow charts, visible graphs, Images, photos other representations and depictions of the project, along with simulation results with good resolution and clarity.Conclusion and RecommendationsThe conclusion and recommendations part summarizes the whole report by highlighting all the chapters and their significance and the importance of the project and about the achievements.The Recommendations are interlinked with conclusion. The conclusion drawn from the project report can be further implemented in the recommendation section to overcome the constraints of the project.Referencing and AppendicesThe project report must be considered as a very standard report, and therefore, it should follow all rules, guidelines and protocols of gathering and presenting information, and implementing that and drawing conclusions out of it.All these activities require appropriate and authentic sources of information and that particular information must be referenced or cited according to the copyrights and other guidelines. Therefore, to make the report original, it should be free from plagiarism and must follow standard citations and guidelines of citations to represent the reference names.The appendices of a project report should be written in Times New Roman format of font size 10, and it should contain the information which is appropriate and added to the main text like Embedded C program code, raw data, and so on.These are the exceptional and very informative guidelines about drafting a project report along with a very simple, user-friendly project report format for those students who are earnestly seeking project report format.

Working on MBA Projects is not an easy task and most students find themselves stressed out when they have to prepare for them out of the blue. This is because MBA projects can take about 6 to 8 months to complete properly, depending on work commitments. When tasked with this for the first time, students often have no idea how it’s done.Here some tips that’ll help you choose researchable MBA project topics, so you can get to work on your. project as soon as possible1. Recall the ModulesTaking an in-depth review of the modules that you have found interesting throughout the study will help you search for relevant modules. This aids in choosing a perfect topic for your MBA project.2. Explore Various Ideas from the StartWhile most students prefer to get themselves ready in the second semester of an MBA program, smarter ones start exploring various ideas and project topics during their first year of study, which better prepares them compared to the average student.3. Don’t Undertake a Company ProjectIf you have less time to complete your MBA project, you’ll need to be sure that you are not undertaking a company project as it can take a lot of time to find appropriate sponsors. In addition, getting approval of the project can be quite frustrating.4. Does it Provide Any Future Benefit?When choosing a topic for your MBA project, don’t just aim to complete it in the hopes of gaining good grades; consider it more of an opportunity to become a specialist in a certain concept which will help you forge a great career, particularly if you have high interest in the topic.5. Is it an Interesting Topic?In order to keep yourself motivated and focused on working 6 – 8 months on the MBA project, you need to make sure that the topic interests you. Otherwise, it becomes difficult to successfully complete the project and expect a good grade. Having no interest in the topic at all means a poor-quality outcome, in addition to less than stellar grades.6. Access to Knowledge and SocietyIf you want to produce a high-quality MBA project efficiently that compels your professor to appreciate your efforts – you need to be sure that you have adequate access to knowledge and society that’ll make the learning process and background reading easier to do.Apart from that, having firms and people in your circle that can provide you with relevant data from which you can draw conclusions, is a very smart move. The data you acquire from these companies and individuals is highly reliable and sufficient for a good report.

1) Make sure you meet the PhD requirements for your institution“PhD students and their supervisors often presume things without checking. One supervisor told his student that a PhD was about 300 pages long so he wrote 300 pages. Unfortunately the supervisor had meant double-spaced, and the student had written single-spaced. Getting rid of 40,000 extra words with two weeks to go is not recommended.” 2) Keep perspective“Everyone wants their thesis to be amazing, their magnum opus. But your most important work will come later. Think of your PhD as an apprenticeship. Your peers are unlikely to read your thesis and judge you on it. They are more likely to read any papers (articles, chapters, books) that result from it.” 3) Write the introduction last“Writing the introduction and conclusion together will help to tie up the thesis together, so save it for the end.” 4) Use apps“Trello is a project management tool which allows you to create ‘boards’ on which to pin all of your outstanding tasks, deadlines, and ideas. It allows you to make checklists too so you know that all of your important stuff is listed and to-hand, meaning you can focus on one thing at a time. It’s satisfying to move notes into the ‘done’ column too.”5) Address the unanswered questions“There will always be unanswered questions – don’t try to ignore or, even worse, obfuscate them. On the contrary, actively draw attention to them; identify them in your conclusion as areas for further investigation. Your PhD viva will go badly if you’ve attempted to disregard or evade the unresolved issues that your thesis has inevitably opened up.” 6) Checking is important“On days when your brain is too tired to write, check quotations, bibliography etc so you’re still making progress.” 7) Get feedback on the whole thesis“We often get feedback on individual chapters but plan to get feedback from your supervisor on the PhD as a whole to make sure it all hangs together nicely.” 8) Make sure you know when it will end“Sometimes supervisors use optimistic words such as ‘You are nearly there!’ Ask them to be specific. Are you three months away, or do you have six months’ worth of work? Or is it just a month’s load” 9) Prepare for the viva“Don’t just focus on the thesis – the viva is very important too and examiners’ opinions can change following a successful viva. Remember that you are the expert in your specific field, not the examiners, and ask your supervisor to arrange a mock viva if practically possible.” 10) Develop your own style“Take into account everything your supervisor has said, attend to their suggestions about revisions to your work but also be true to your own style of writing. What I found constructive was paying attention to the work of novelists I enjoy reading. It may seem that their style has nothing to do with your own field of research, but this does not matter. You can still absorb something of how they write and what makes it effective, compelling and believable.” 11) Remember that more is not always better“A PhD thesis is not a race to the highest page count; don’t waste time padding.” 12) Get a buddy“Find a colleague, your partner, a friend who is willing to support you. Share with them your milestones and goals, and agree to be accountable to them. This doesn’t mean they get to hassle or nag you, it just means someone else knows what you’re up to, and can help to check if your planning is realistic and achievable.” 13) Don’t pursue perfectionism“Remember that a PhD doesn’t have to be a masterpiece. Nothing more self-crippling than perfectionism.”14) Look after yourself“Go outside. Work outside if you can. Fresh air, trees and sunshine do wonders for what’s left of your sanity.”

How to choose Project ideaThe whole process of picking up a good idea begins with understanding why the college/University requires you to develop a project as a part of your curriculum. It's because working on a project puts all your theoretical knowledge into practical use; and it's a great learning experience! That means you will have to come up with a project idea that is in sync with your existing knowledge. This is *very important*. Please note that you will be required to learn a lot of new things while you are working on the project. Now let's discuss how should you go about picking up a project idea.1. You don't have to come up with Earth-breaking, Nobel Winning Idea. No one expects you to develop a brand-new project that the humans haven't seen before. All you should focus on is 'improvements in the things around you'. If you wish to develop an app : think of a problem that you have faced and have felt that there should have been an app to do that! If you are an electronics / electrical engineer - think of something that you can do with electronics. For example: Can you help moms track their tiny babies with sensors and a mobile app? Isn't that a cool idea? The same goes with Chemical, Mechanical, Structural, Metallury, Civil and Biotech engineers. Look for improvements and things that can be done better than current solutions. Of course you might just take up a study project - but you should have your project guide's approval. 2. TeamMake sure that the topic selection is always a team effort. Every person in the team should be convinced that the topic is the right one for them. If a topic is of interest to only few members of the team; the team won't be able to function together throughout the duration of the project. If you want the entire team to stick together and work with enthusiasm; you need everyone's consent for the topic.3. BudgetBudget is always the criteria that you and your team should consider when deciding on your final year or third year engineering project. Make a correct estimate 4. Hardware / Software / Tools / Technology NeededOne of the most important factors in your topic selection will be the overall requirements of the project - and whether the team is comfortable with them. If your project requires you to work on Java - is everyone in your team comfortable coding in Java? If your project requires you to have Raspberry Pi; ensure that all the team members are comfortable using it. If not - have the consent of all the users to learn the required resources as fast as they can.

Few Guidelines for Perfect Final Year Project For an effective project, it is advisable to carry out the following activities:? Defining the project Objective.? Acquiring the information about the problem and its possible solutions.? Establishing the criteria by which your solution(s) to the problem will be judged.? Determining by what process the work will be carried out.? Planning the detailed phases of the project.? Adopting one or more design methodologies.? Analyzing requirements.? Constructing tools.? Construction of one or more artifacts (hardware, software, document).? Evaluating your solution to the problem.? Reporting on your work.? Whatever the nature of the problem you set out to solve, the conclusion of your project should be whether you solved it successfully or not.Format and tips for preparing your initial project proposal report:• Table of Contents• AbstractIn one page, certainly not more than two, summarize the main features of your project, what problem it is solving and how you propose to solve it. This brief overview should give a snapshot of the overall structure of your final year project.• IntroductionOutline the scope of your project. How did the problem present itself to you in the first place? Describe the nature of the problem in detail.• Case Study and Literature ReviewDescribe what you have discovered in your literature search or market survey. Does this problem exist anywhere else? Who is working on it? How have others solved it? Give references to some of the main articles/books/Web pages discussing this problem.• Proposed SolutionOutline in detail your approach to solving the problem. Describe the proposed solution methods and the progress you have achieved. Reference your formal specifications and design documents, which can be placed in the Appendix. If you have implemented a prototype of your solution, discuss it, and describe its behavior.• Implementation PlanLay out the project implementation plan for your study. Discuss the project’s target and milestone dates. If you will be implementing your project in discrete stages, describe them and discuss how far you think you will be able to get.• Conclusion• ReferencesInclude here all materials referenced within your report.• AppendixSome of the highly technical details from the above sections can be placed in the Appendix and referenced from the body of the report. Include all relevant technical documentation, such as specification documents, design documents, and code listings.In summary, the Initial Report is written in the style of a working document rather than a finished report. It introduces your problem, looks at what others have done in this area, presents a proposed solution, and describes an implementation plan.

WHAT IS AIFrom SIRI to self-driving cars, artificial intelligence AI is progressing rapidly. While science fiction often portrays AI as robots with human-like characteristics, AI can encompass anything from Google’s search algorithms to IBM’s Watson to autonomous weapons.Artificial intelligence today is properly known as narrow AI or weak AI in that it is designed to perform a narrow task e.g. only facial recognition or only internet searches or only driving a car. However, the long-term goal of many researchers is to create general AI AGI or sstrong AI)While narrow AI may outperform humans at whatever its specific task is, like playing chess or solving equations, AGI would outperform humans at nearly every cognitive task.WHY RESEARCH AI SAFETYIn the near term, the goal of keeping AI’s impact on society beneficial motivates research in many areas, from economics and law to technical terms such as verification, validity, security and control. Whereas it may be little more than a minor nuisance if your laptop crashes or gets hacked, it becomes all the more important that an AI system does what you want it to do if it controls your car, your airplane, your pacemaker, your automated trading system or your power grid.In the long term, an important question is what will happen if the quest for strong AI succeeds and an AI system becomes better than humans at all cognitive tasks. Such a system could potentially undergo recursive self-improvement, triggering an intelligence explosion leaving human intellect far behind. By inventing revolutionary new technologies, such a superintelligence might help us eradicate war, disease, and poverty, and so the creation of strong AI might be the biggest event in human history. Some experts have expressed concern, though, that it might also be the last, unless we learn to align the goals of the AI with ours before it becomes superintelligent.There are some who question whether strong AI will ever be achieved , and others who insist that the creation of superintelligent AI is guaranteed to be beneficial. At FLI we recognize both of these possibilities, but also recognize the potential for an artificial intelligence system to intentionally or unintentionally cause great harm. We believe research today will help us better prepare for and prevent such potentially negative consequences in the future, thus enjoying the benefits of AI while avoiding pitfalls.CAN AI ALSO BE DANGEROUSMost researchers agree that a superintelligent AI is unlikely to exhibit human emotions like love or hate, and that there is no reason to expect AI to become intentionally benevolent or malevolent. Instead, when considering how AI might become a risk, experts think two scenarios most likely:1. The AI is programmed to do something beneficial, but it develops a destructive method for achieving its goal: This can happen whenever we fail to fully align the AI’s goals with ours, which is strikingly difficult. If you ask an obedient intelligent car to take you to the airport as fast as possible, it might get you there chased by helicopters and covered in vomit, doing not what you wanted but literally what you asked for. If a superintelligent system is tasked with a ambitious geoengineering project, it might wreak havoc with our ecosystem as a side effect, and view human attempts to stop it as a threat to be met.2. The AI is programmed to do something devastating: Autonomous weapons are artificial intelligence systems that are programmed to kill. In the hands of the wrong person, these weapons could easily cause mass casualties. Moreover, an AI arms race could inadvertently lead to an AI war that also results in mass casualties. To avoid being thwarted by the enemy, these weapons would be designed to be extremely difficult to simply “turn off,” so humans could plausibly lose control of such a situation. This risk is one that’s present even with narrow AI, but grows as levels of AI intelligence and autonomy increase.As these examples illustrate, the concern about advanced AI isn’t malevolence but competence. A super-intelligent AI will be extremely good at accomplishing its goals, and if those goals aren’t aligned with ours, we have a problem. You’re probably not an evil ant-hater who steps on ants out of malice, but if you’re in charge of a hydroelectric green energy project and there’s an anthill in the region to be flooded, too bad for the ants. A key goal of AI safety research is to never place humanity in the position of those ants.

Big data is an evolving term that describes any voluminous amount of structured, semistructured and unstructured data that has the potential to be mined for information.Big data is often characterized by 3Vs: the extreme volume of data, the wide variety of data types and the velocity at which the data must be processed. Although big data doesn't equate to any specific volume of data, the term is often used to describe terabytes, petabytesand even exabytes of data captured over time.Breaking down the 3Vs of big dataSuch voluminous data can come from myriad different sources, such as business sales records, the collected results of scientific experiments or real-time sensors used in the internet of things. Data may be raw or preprocessed using separate software tools before analytics are applied.Data may also exist in a wide variety of file types, including structured data, such as SQLdatabase stores; unstructured data, such as document files; or streaming data from sensors. Further, big data may involve multiple, simultaneous data sources, which may not otherwise be integrated. For example, a big data analytics project may attempt to gauge a product's success and future sales by correlating past sales data, return data and online buyer review data for that product.Finally, velocity refers to the speed at which big data must be analyzed. Every big data analytics project will ingest, correlate and analyze the data sources, and then render an answer or result based on an overarching query. This means human analysts must have a detailed understanding of the available data and possess some sense of what answer they're looking for.How big data works.Velocity is also meaningful, as big data analysis expands into fields like machine learning and artificial intelligence, where analytical processes mimic perception by finding and using patterns in the collected data. Big data infrastructure demandsThe need for big data velocity imposes unique demands on the underlying compute infrastructure. The computing power required to quickly process huge volumes and varieties of data can overwhelm a single server or server cluster. Organizations must apply adequate compute power to big data tasks to achieve the desired velocity. This can potentially demand hundreds or thousands of servers that can distribute the work and operate collaboratively.Achieving such velocity in a cost-effective manner is also a headache. Many enterprise leaders are reticent to invest in an extensive server and storage infrastructure that might only be used occasionally to complete big data tasks. As a result, public cloud computinghas emerged as a primary vehicle for hosting big data analytics projects. A public cloud provider can store petabytes of data and scale up thousands of servers just long enough to accomplish the big data project. The business only pays for the storage and compute time actually used, and the cloud instances can be turned off until they're needed again.To improve service levels even further, some public cloud providers offer big data capabilities, such as highly distributed Hadoop compute instances, data warehouses, databases and other related cloud services. Amazon Web Services Elastic MapReduceis one example of big data services in a public cloud.

Cloud computing is not a new topic or trend in corporate. Enterprises want an easy and more connected way of keeping themselves and their business together so as they can access anything on the go. It has given birth to a new era of connectivity with the trend of cloud computing touching distinct domains. Education, banking, corporate nothing is left untouched from the impact of cloud computing. But what is making it that much popular and pursued?Cloud computing offers several benefits both in terms of financial and user experience. Where you don’t need to keep everything organized manually, you can access or update anything on the go, automated updates have brought a new level of flexibility into account. This has just transformed the overall perspective of business and management.This transformation is easily understandable as cloud computing offers a wide range of virtual resources which are not easy to afford in real environment. For IT enterprises where the development requirements keep on changing, the companies can’t afford to re-assemble their infrastructure every time. This is where cloud computing and shared virtual resources help them. With a minimal cost, the companies can have dynamic access to all the resources and infrastructure they need. This has boosted the trend of Cloud computing in other sectors as well and all at understandable reasons.THE COST OF TRENDWe know that every single thing comes at a cost and so is Cloud computing. It has several security problems associated with it. From problems regarding security threats to network management, there are several domains which need to be taken care of by the companies before they can actually put cloud computing to use.NEED OF CLOUD AND SECURITY ENGINEERSThese security threats and network management requirements have increased the requirements for cloud and network engineers, cyber security experts and other associated workforce. This increased demand has created a number of opportunities for fresher technocrats. You will have a chance to work for top brands like Amazon and IBM. They offer several cloud systems like Amazon AWS, Amazon pinpoint and IBM Blue mix.Cloud Computing describes a scenario whereby computing resource is delivered as a service over a network connection, usually the internet.Cloud computing relies on sharing a pool of physical and/or virtual resources, rather than deploying local or personal hardware and software. It is somewhat synonymous with the term ‘utility computing’, as users are able to tap into a supply of computing resource rather than manage the equipment needed to generate it themselves. THE FUTURE OF CLOUD COMPUTING IS MOBILEThe popularity of mobile devices—such as smart phones and tablets—is also having a major impact on the business world. Instead of being tied to desks in an office, today's workers can use their mobile devices to do their jobs at any time from just about anywhere.The flexibility demanded by the mobile workforce is one of the key reasons cloud computing is on the rise. The anytime, anywhere access that cloud-based applications provide is ideal for workers who are always on the go. Rather than having to stop by the office to use their desktop computers, employees can simply log into an application with a web-enabled device like a smartphone or tablet and perform their task in the cloud.