The declaration must have exactly the following syntax:. I, [Name] of [College], being a candidate for Part II of the Computer Science Tripos, hereby declare that this dissertation and the work described in it are my own work, unaided except as may be specified below, and that the dissertation does not contain material that has already been used to any substantial extent for a comparable purpose. You may either include a scanned copy of your signature or type your full name in place of a handwritten signature.
The University drafted the wording, which is similar to that relating to dissertations in a wide range of subjects; thus the "unaided except as may be specified below" clause merits some explanation:. The Department would like past dissertations to be made available for teaching purposes and for your references. These will be accessed on the Computer Science departmental website under Raven password protection.
You should include the last sentence of the declaration if you are willing for your dissertation to be accessed for these purposes; otherwise you may remove it. The single proforma page is a preface that immediately follows the declaration of originality. The proforma page, as well as all subsequent pages of the dissertation should not include direct personal identifiers such as your name or CRSID. The Proforma must be arranged thus:. It is quite in order for the Proforma to point out how ambitious the original aims were and how the work completed represents the triumphant consequence of considerable effort against a background of unpredictable disasters.
The substantiation of these claims will follow in the rest of the dissertation. Student Administration will ask students to resubmit any dissertation which does not include the relevant cover page, declaration and proforma. If such a resubmission occurs after the deadline this will result in a late submission penalty. The introduction should explain the principal motivation for the project and show how the work fits into the broad area of surrounding computer science and give a brief survey of previous related work.
It should generally be unnecessary to quote at length from technical papers or textbooks. If a simple bibliographic reference is insufficient, consign any lengthy quotation to an appendix. Principally, this chapter should describe the work which was undertaken before code was written, hardware built or theories worked on. It should show how the project proposal was further refined and clarified, so that the implementation stage could go smoothly rather than by trial and error.
Throughout this chapter and indeed the whole dissertation, it is essential to demonstrate that a proper professional approach was employed. The nature of this chapter will vary greatly from one dissertation to another but, underlining the professional approach, this chapter will very likely include a section headed "Requirements Analysis" and refer to appropriate software engineering techniques used in the dissertation.
The chapter will also cite any new programming languages and systems which had to be learnt and will mention complicated theories or algorithms which required understanding. It is essential to declare the starting point. This states any existing codebase or materials that your project builds on. The text here can commonly be identical to the text in your proposal, but it may enlarge on it or report variations.
For instance, the true starting point may have turned out to be different from that declared in the proposal and such discrepancies must be explained. This chapter should describe what was actually produced: the programs which were written, the hardware which was built or the theory which was developed. Any design strategies that looked ahead to the testing stage should be described in order to demonstrate a professional approach was taken. Descriptions of programs may include fragments of high-level code but large chunks of code are usually best left to appendices or omitted altogether.
Analogous advice applies to circuit diagrams or detailed steps in a machine-checked proof. The implementation chapter should include a section labelled "Repository Overview". The repository overview should be around one page in length and should describe the high-level structure of the source code found in your source code repository. It should describe whether the code was written from scratch or if it built on an existing project or tutorial.
Making effective use of powerful tools and pre-existing code is often laudable, and will count to your credit if properly reported. Nevertheless, as in the rest of the dissertation, it is essential to draw attention to the parts of the work which are not your own. It should not be necessary to give a day-by-day account of the progress of the work but major milestones may sometimes be highlighted with advantage.
This is where Assessors will be looking for signs of success and for evidence of thorough and systematic evaluation. Sample output, tables of timings and photographs of workstation screens, oscilloscope traces or circuit boards may be included.
Care should be employed to take a professional approach throughout. For example, a graph that does not indicate confidence intervals will generally leave a professional scientist with a negative impression.
As with code, voluminous examples of sample output are usually best left to appendices or omitted altogether. There are some obvious questions which this chapter will address. How many of the original goals were achieved? Were they proved to have been achieved? Did the program, hardware, or theory really work? Assessors are well aware that large programs will very likely include some residual bugs.
It should always be possible to demonstrate that a program works in simple cases and it is instructive to demonstrate how close it is to working in a really ambitious case. This chapter is likely to be very short and it may well refer back to the Introduction.
It might offer a reflection on the lessons learned and explain how you would have planned the project if starting again with the benefit of hindsight. It is common, but not mandatory, to have a bibliography. Attention should be given to correct and consistent formatting. It is common, but not mandatory, to have one or more appendices.
Assessors like to see some sample code or example circuit diagrams, and appendices are the sensible places to include such items. Accordingly, software and hardware projects should incorporate appropriate appendices. Note that the 12, word limit does not include material in the appendices, but only in extremely unusual circumstances may appendices exceed pages.
If you feel that such unusual circumstances might apply to you you should ask your Director of Studies and Supervisor to discuss this with the Chairman of Examiners. Appendices should appear between the bibliography and the project proposal. A copy of the original project proposal must be included at the very end of the dissertation. Information provided by pagemaster cst. Tech and Ph.
In the field of academics, we need to get rid of obsolete ideas and focus on new innovative topics which are fast spreading their arms among the vast global audience. Computer Science students both in bachelors and in masters are studying the same topics and subjects from the past few years. For project and thesis work also they are relying on outdated topics.
Projects like school management system, library management system etc. Students should shift their focus to latest technologies which are highly in demand these days and future depend upon these. Here is the list of latest topics in Computer Science that you can choose and work for your project work or thesis and research:.
Data Warehousing is the process of analyzing data for business purposes. Data warehouse store integrated data from multiple sources at a single place which can later be retrieved for making reports. The data in the warehouse is historical data which is helpful in understanding business goals and make decisions for future prospects. It is a relatively new concept and have high growth in future.
Data Warehouse finds its application in the following areas:. Internet of Things IoT is a concept of interconnection of various devices, a vehicle to the internet. IOT make use of actuators and sensors for transferring data to and from the devices. This technology is developed for better efficiency and accuracy apart from minimizing human interaction with the devices. The example for this is home heating in some countries when the temperature drops done through motion sensors which automatically detect the weather conditions.
Another example for this is the traffic lights which changes its colors depending upon the traffic. Following are the application areas of Internet of Things IoT :. Many people are not aware of this concept so you can choose for your project work and learn something new. Big Data is a term to denote the large volume of data which is complex to handle. The data may be structured or unstructured. Structured data is an organized data while unstructured data is an unorganized data.
Big data can be examined for the intuition that can give way to better decisions and schematic business moves. The definition of big data is termed in terms of three Vs. These vs are:. Cloud Computing is a comparatively new technology. It is an internet-based service that creates a shared pool of resources for consumers. There are three service models of cloud computing namely:. The common examples of cloud computing include icloud from Apple, Google-based Services like Google Drive and many more.
The field is very demanding and is growing day by day. You can focus on it if you have interest in innovation. Semantic Web is also referred to as Web 3. It is standardized by World Wide Web Consortium W3C to promote common data formats and exchange protocols over the web. It is machine-readable information based and is built on XML technology. It is an extension to Web 2. In the semantic web, the information is well defined to enable better cooperation between the computers and the people.
In the semantic web, the data is interlinked for better understanding. It is different from traditional data sharing technologies. MANET stands for mobile ad hoc network. It is an infrastructure-less network with mobile devices connected wirelessly and is self-configuring. It can change locations independently and can link to other devices through a wireless connection. Instead, the nodes directly send packets to each other.
It is also a relatively new concept in the field of computer science and is a technique of guiding computers to act in a certain way without programming. It makes use of certain complex algorithms to receive an input and predict an output for the same.
There are three types of learning;. Machine Learning is closely related to statistics. If you are good at statistics then you should opt this topic. Data Mining is the process of identifying and establishing a relationship between large datasets for finding a solution to a problem through analysis of data. There are various tools and techniques in Data Mining which gives enterprises and organizations the ability to predict futuristic trends. Data Mining finds its application in various areas of research, statistics, genetics, and marketing.
Following are the main techniques used in the process of Data Mining:. Artificial Intelligence is the intelligence shown by machines and it deals with the study and creation of intelligent systems that can think and act like human beings. In Artificial Intelligence , intelligent agents are studied that can perceive its environment and take actions according to its surrounding environment.
Students doing a Senior Project that results in original contributions can apply to turn their Senior Project into a Senior Thesis see Requesting Consideration for Honors. The thesis is reviewed by a committee of three professors who will decide whether to award the Honors.
As per college rules, students with a GPA of 3. Students below the 3. To help develop their ideas for a project or thesis, students should engage their professor s in the process sometime in the spring semester of their Junior year. The advisor can help student with outlining the scope of the project, selecting background reading, computing materials, software, and other logistics of the project. Occasionally, there may even be external funding that may be available for carrying out the project see below.
The advisor can help students identify possible funding sources. Students should make sure that they set a weekly meeting time to meet with their advisors about the project. The abstract should be submitted to the department by Nov. A more definite and detailed proposal will be required by the end of Week 1 of the CS course in the spring. Students can then spend the summer doing some background research on the topic before finalizing a specific project.
Excellent Summer Research opportunities are available at Bryn Mawr and at other national and international venues. Consult with your advisor about these. Fall Semester of Senior Year: Students can spend this semester doing initial feasibility studies and further honing their projects.
Try and meet with your thesis advisor s at least once every two weeks, if you have one. Generally, most good projects begin their work in earnest by the end of the fall semester. You are also required to submit a thesis proposal to the department by Nov.
Based on the domain knowledge and interest, we help scholars to choose their topic. We will select the best topic which will give a unique identification to your research. Scrutinizing and analyzing the complete domain Identify the problem statement and create a novel idea. It is not an easy task to scrutinize the topic under any domain.
Also It is our knowledge and experience which makes us to find a novel idea and topic. For example, if we take networking, finding a topic in such a wide domain is difficult; we narrow it down according to the latest trend like IPv6 security attacks. Again we work on this sub domain and find a novel idea as we are aware of every novel idea registered up to date.
Our immense knowledge makes us to create original research. Topic selection must also ensure the time it requires for complete research. Topics must also selected in such a way that it must be finished within the specified time limit. Based on the topic, we can also identify the estimated cost for overall research. Generally, if we choose a topic in Pervasive computing, it always cost little high ten other domain due to the use of devices like sensors, cameras etc.
So, we also suggest our scholar the approximate cost based on the topic. If sometimes, scholars wish to work in low budget but select domains like pervasive computing, we also help them to choose the topic with optimum cost. We also consider cost as a factor while selecting a topic. We also give complete focus on thesis topic selection as we believe that one should be ingenious from the very beginning.
A scholar must select a topic correctly as they are the one who is going to face their internal guides and also external reviewers. Scholars dedication and interest is the prime factor to take up a research topic. It is a free guidance which we also support for our scholars. Our team of experts will assist the scholars to choose the most recent and apt topic for their research.
Our advisers are also abreast of the current developments and trends in the field of research who can guide you the best. We also advice our scholars to take up a right decision as it is the right time to approach us. We work on the following domains:. We also cannot confine our domain list and knowledge in this short page. Also, We wish our scholars to approach us to know about our knowledge and experience in each domain.
We have a list of sub domains under each domain which in turns contain list of topics. Like this we also cover every aspect of computer science. So scholars can also blindly approach us to get their thesis topics from us. Yes, we always work on most recent trends of computer science. Updating knowledge and skill is our passion.
Yes we can provide solution for any topic you bring due to our expertise in all the domains. We feel pleasure to work in new and unknown topics due to our inquisitive research team.
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