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How to choose a research topic for phD

A doctoral candidate has to choose a topic out of the lotto begin with his research. The research is processed after the candidate chooses an interesting topic. Researching on a topic and writing a thesis on it is easier than choosing a topic to research. The candidate has to be farsighted to choose a topic and shall pick a topic that has a proper conclusion.

Out of thousands of topics, there is virtually no topic that is left untouched. The researcher should keep in mind that he has to choose a topic that is not researched too much or too little. A too much-researched topic will give a large number of matters for the candidate to study, whereas a too little researched topic will not give sufficient matter to study, and thus the matter in the paper would not be properly researched.

The first step to choose a topic is that it should be interesting. The candidate should pick up a topic that interests himself. There are great papers written in every field but the point is to find an interesting topic for themselves. While choosing a topic one must ask themselves that why
would a person read it. Why would he care to study it?

The candidate should be ready with the history of the selected topic to know what’s coming on his way. He should be well aware of the literature existing on the chosen topic.

The most important thing to keep in mind while choosing a topic is that the research should have closure. Proper closure is very important to the topic. The research should allude at an engaging issue for the readers to ponder on it, with a methodology to resolve the issue. The issue might not be unique and refreshing for the reader but the solution should be.

Your Struggle Ends Here: PhD Topic Selection Made Easy

  • Are you an Engineer looking to pursue PhD in Bangalore?
  • Are you one of those scholars who has a knack for research?
  • Is it becoming tough to start just because you can’t find a unique topics?
  • Are you looking for PhD topic help or PhD project help?
  • Are you waiting for the right people to come and help you?

If your answer to any of these questions is YES then this article is a must read!

Doing a PhD In Engineering-

Engineers are always considered that bunch of studious people right? And then if they say that they want to pursue a PhD further, nobody thinks that it will be difficult for them as they belong to the category of being a scholar already.

But this is achieving a Doctorate and it is not as easy as it seems to be, may be that engineer is a research scholar but doing research in the field of a technical domain is much more tough and lengthy. 

Data, statistics, numbers, values, formulas etc is important in other fields but it is mandatory in a technical field, all your findings, outcomes, conclusions are based on numbers and data.

For engineers it becomes necessary that they consider their topic selection part to be important and that they give proper time to it. 

Why Selecting The Right Topic is Crucial? 

While choosing a topic for your research you should consider your interest area as it becomes very important that you are studying a field which you like and which you prefer.

Selecting a topic just for the sake of choosing something attractive or hard or easy won’t help you in the long run. In worst cases it is also possible that your topic might just not get accepted.

Engineering is a much more technical field than all the other research fields and hence you as a research candidate should take utmost care of choosing a topic that you like and is unique but at the same time sensible and manageable.

You take a decision that you want to do a PhD but you are not able to understand as to how will you select a good topic. That is when we come into the picture. 

We will provide you with: PhD topic selection help as well as with PhD project help.

Who Are We?

We are a team of expert engineers, research consultants, technical consultants, qualified and highly skilled academic writers, topic and title specialists who are here to help you with managing your topic selection process. 

How can we help? 

Thesis and code helps you with a broad variety of topics in domains such as: 

  • Image Processing
  • Big Data
  • Cloud Computing
  • Network Security
  • Embedded Systems
  • Data Mining
  • Computer Science
  • Electronics and Communication Engineering 

Choose any of the domains you want to do your research in and we will help you with the further process of diving deep into that stream and taking a mind blowing topic out of it.

Trust us and see the effective outcome that occurs when you get something which others might miss because they couldn’t reach us for PhD topic selection help and PhD project help.

You can contact us at: https://www.thesisandcode.com/

A Comprehensive Guide to Pen Down an Effective Synopsis for PhD in Architecture

Today, research is being conducted in various domains including pure science, engineering, MBA, etc. While many research domains are contributing to the existing knowledge or the society for a long time, there are a few other fields which have emerged as the hottest research field. And one such domain is architecture. Yes, you read it right. Architecture is one of the blooming concepts in the research field. 

After completion of the research, the strenuous task a scholar faces is crafting a research paper. That is, for an architect, the toughest job in his research journey would be defining and penning down his/her study. Writing a research paper involves various steps and the first step towards reaching the goal is crafting an exceptional synopsis. 

A synopsis is nothing but a short, systematic outline of the proposed study, that gives the supervisor a clear picture of study and enable him/her to spot gaps that have not been taken into account. In the architectural field, a synopsis includes: 

  1. Introduction – Like any other domain, this field too includes an introduction as the first section of a research paper. Here briefly explain the architectural/technological/social significance of the study. Be precise and incorporate relevant background materials in this section. 
  2. Objectives, scope and limitations – Precisely state the questions for which you would like to seek an answer. Define the analytical, experimental, conceptual, and/or methodological boundaries within which the research will be carried out. Also explain the limitations of your study and the difficulties involved in performing the research. 
  3. Description of the research work – Considering the limitations and difficulties, precisely identify the architecturally suitable area and extent of study attempted by you. In addition, provide a detailed explanation on how you are seeking architectural solutions and how the case studies will assist you in identifying the solutions. You must also clear the role of literature studies/experiments/observations and define the detailed methodology to be adopted that lead you towards the solutions.
  4. Summary of the study – Highlight significant conclusions you are working towards. Explain the advantages arising out of the study and the architectural advancement you are seeking via your research paper. If you need some assistance in writing this section, consider approaching professional offering PhD synopsis writing services in Bangalore. 
  5. List of case studies – List the case studies and indicate why you have selected the particular case study. Also mention the ease or difficulty of approach, acquiring information from the case studies. 
  6. Project site – As per the writers providing PhD synopsis writing services in Bangalore, one should include a suitable, possible site for the research proposal where the solutions can be carried out. Although the project site may or may not be a live one but must be suitable for the chosen project. 

Your synopsis is one of the critical deciding factors which tell your supervisor what he/she can expect from the study, what makes it unique, and is the topic researchable.

A Guide to Writing a Technical Journal Paper

The Template of a Technical Paper

 

TITLE

 An effective title should…Answer the reader’s question:

  • Is this article relevant to me?
  • Grab the reader’s attention
  • Describe the content of a paper using the fewest possible words
  • Is crisp, concise
  • Uses keywords

Example:

Title selected:

A Human Expert-based Approach to Electrical Peak Demand Management

Title Rejected:

 A better approach of managing environmental and energy sustainability via a study of different methods of electric load forecasting

ABSTRACT

The abstract allows a researcher to quickly evaluate the content of your paper, and judge whether it is relevant to their research. As a result, an abstract need to convey a complete synopsis of the paper, but within a tight word limit.

A standalone condensed version of the article with not more than 250 words which I written in the past tense using keywords.

Writing an abstract includes briefly introducing the general topic of the work and then explaining the exact research question, including the aims. It should then include a brief description of the methodology, the results, and the discussion.

Example:

Good Abstract:

The objective of this paper was to propose a human expert-based approach to electrical peak demand management. The proposed approach helped to allocate demand curtailments (MW) among distribution substations (DS) or feeders in an electric utility service area based on requirements of the central load dispatch center. Demand curtailment allocation was quantified taking into account demand response (DR) potential and load curtailment priority of each DS, which can be determined using DS loading level, capacity of each DS, customer types (residential/commercial) and load categories (deployable, interruptible, or critical). Analytic Hierarchy Process (AHP) was used to model a complex decision-making process according to both expert inputs and objective parameters. Simulation case studies were conducted to demonstrate how the proposed approach can be implemented to perform DR using real-world data from an electric utility. Simulation results demonstrated that the proposed approach is capable of achieving realistic demand curtailment allocations among different DSs to meet the peak load reduction requirements at the utility level.

Bad Abstract:

This paper presents and assesses a framework for an engineering capstone design program. We explain how student preparation, project selection, and instructor mentorship are the three key elements that must be addressed before the capstone experience is ready for the students. Next, we describe a way to administer and execute the capstone design experience including design workshops and lead engineers. We describe the importance in assessing the capstone design experience and report recent assessment results of our framework. We comment specifically on what students thought were the most important aspects of their experience in engineering capstone design and provide quantitative insight into what parts of the framework are most important

*First person, present tense No actual results, only describes the organization of the paper

KEYWORDS

The Title and Abstract will be used for enhanced Search Engine Optimization to select the appropriate keywords.

INTRODUCTION

The introduction gives an overall review of the paper, but does address a few slightly different issues from the abstract. It works on the principle of introducing the topic of the paper and setting it in a broader context, gradually narrowing the topic down to a research problem, thesis, and hypothesis. A good introduction explains how you mean to solve the research problem, and creates ‘leads’ to make the reader want to delve further into your work.

An introduction should comprise the description of the problem you researched and should move step by step through, should be written in present tense.

The introduction should not be too broad or vague and should be limited to not more than 2 pages.

METHODOLOGY

The methodology needs to give a completely accurate description of the equipment and the techniques used for gathering the data. Finally, you must provide an explanation of how the raw data was compiled and analyzed.

The methodology can usually be divided into a few sections.

  • Describe the materials and equipment used in the research.
  • Explain how the samples were gathered, any randomization techniques and how the samples were prepared.
  • Explain how the measurements were made and what calculations were performed upon the raw data.
  • Describe the statistical techniques used on the data.
  • Use illustrations to clarify ideas, support conclusions.

The writing for the method should be clear and concise. The major point is not to stray off into giving background info, interpretation, or irrelevant detail. Write from your reader’s perspective. You will not need to explain things they already know, but you will need to paint a precise picture of your methods.

RESULTS/DISCUSSION

Results:

These should be a quick synopsis of the facts, figures and statistical tests used to arrive at your final results.

  • Summarized Data
  • Should be clear and concise
  • Use figures or tables with narrative to illustrate findings

Be sure to include negative results – writing a results section without them not only invalidate the paper, but it is extremely bad science. The negative results, and how you handle them, often gives you the makings of a great discussion section, so do not be afraid to highlight them.

Discussion:

  • Interprets the Results
  • Why your research offers a new solution
  • Acknowledge any limitations

You should always put your findings into the context of the previous research that you found during your literature review. Do your results agree or disagree with previous research?

Do the results of the previous research help you to interpret your own findings? If your results are very different, why? Either you have uncovered something new, or you may have made a major flaw with the design of the experiment.

Finally, after saying all of this, you can make a statement about whether the experiment has contributed to knowledge in the field, or not.

CONCLUSION

Conclusion explain what the research has achieved. This is a very quick synopsis of the results and discussion. Writing a conclusion involves summing up the paper and giving a very brief description of the results, although you should not go into too much detail about this.

When writing a conclusion, you should try to answer a few questions, as succinctly as possible:

  • It relates to the problem stated in the Introduction
  • Include a summary of the main findings, important conclusions, and implications for the field
  • Provides benefits and shortcomings of the solution presented and research methodology. You should then point out the importance of the study and point out how it relates to the field. Whilst writing the conclusion, you should highlight any deficiencies in your methods, explaining how they may have affected your results.

Suggests future areas for research, do your findings open up any suggestions for future research?

REFERENCES

Support and validate the hypothesis your research proves, disproves, or resolves

  • There is no limit to the number of references
  • But use only those that directly support our work Ensure proper author attribution
  • Author name, article title, publication name, publisher, year published, volume, chapter, and page number

IEEE journals generally follow a citation numbering system

FINAL TASK OF WRITERS ONCE ALL SECTIONS ARE WRITTEN:

  • How do they fit together?
  • Does each section perform its appointed task?
  • Is the order logical?
  • Do the ideas flow together? Is it easy to read?
  • Does the same material appear more than ones?
  • Can it be clearer?
  • Is there enough detail?

LIST OF PHRASES THAT COULD BE USED IN WRITING RESEARCH PAPER:

Lists of frequently used phrases that have a general acceptance in all disciplines that you can use in specific sections of writing paper:

  1. Establishing why your topic (X) is important

X is the main / leading / primary / major cause of ..

Xs are a common / useful / critical part of…

Xs are among the most widely used / commonly discussed / well-known / well-documented / widespread / commonly investigated types of …

X is recognized as being / believed to be / widely considered to be the most important …

 It is well known / generally accepted / common knowledge that X is …

X is increasingly becoming / set to become a vital factor in …

Xs are undergoing a revolution / generating considerable interest in terms of …

 Xs are attracting considerable / increasing / widespread interest due to …

X has many uses / roles / applications in the field of …

A striking / useful / remarkable feature of …

The main / principal / fundamental characteristics of X are: X accounts / is responsible for

  1. Outlining the past-present history of the study of X (no direct references to the literature)

Last century X was considered to be / viewed as / seen as the most …

Initial / Preliminary / The first studies of X considered it to be Traditionally X / In the history of X, the focus has always been …

Scientists / Researchers / Experts have always seen X as …

Until now / For many years / Since 1993 Xs have been considered as …

X has received much attention in the last two years / in the past decade / over the last two decades …

For the past five years / Since 2011 there has been a rapid rise in the use of Xs

The last two years have witnessed / seen a huge growth in X …

The past decade / last year has seen a renewed importance in X …

Recent developments in / findings regarding X have led to …

X has become a central / an important / a critical issue in …

  1. Outlining the possible future of X

The next decade is likely to see / witness a considerable rise in X In the next few years X will become / is likely to have become Within the next few years, X is set / destined / likely to become an important component in …

By 2025 / Within the next ten years, X will have become …

X will soon / shortly / rapidly / inevitably be an issue that …

  1. Indicating the gap in knowledge and possible limitations

 Few researchers have addressed the problem / issue / question of … Previous work has only focused on / been limited to / failed to address …

A basic / common / fundamental / crucial / major issue of …

The central / core problem of A challenging / An intriguing / An important / A neglected area in the field of …

Current solutions to X are inconsistent / inadequate / incorrect / ineffective / inefficient / oversimplistic / unsatisfactory Many hypotheses regarding X appear to be ill-defined / unfounded / not well grounded / unsupported / questionable / disputable / debatable

The characteristics of X are not well understood / are misunderstood / have not been dealt with in depth. It is not yet known / has not yet been established whether X can do Y. X is still poorly / not widely understood. X is often impractical / not feasible / costly …

Techniques to solve X are computationally demanding / subject to high overheads / time consuming / impractical / frequently unfeasible. A major defect / difficulty / drawback / disadvantage / flaw of X is …

One of the main issues in our knowledge of / what we know about X is a lack of …

 This particular / specific area of X has been overlooked / has been neglected / remains unclear …

Despite this interest, no one to the best of our knowledge / as far as we know has studied … Although this approach is interesting, it suffers from / fails to take into account / does not allow for …

In spite of / Despite its shortcomings, this method has been widely applied to …

However, there is still a need for / has been little discussion on …

Moreover, other solutions / research programs / approaches have failed to provide …

Most studies have only focused / tended to focus on …

To date / Until now this methodology has only been applied to …

There is still some / much / considerable controversy surrounding …

There has been some disagreement concerning / regarding / with regard to whether There is little / no general agreement on …

The community has raised some issues / concerns about …

Concerns have arisen / been raised which question / call into question the validity of …

 In the light of recent events in x, there is now some / much / considerable concern about …

  1. Stating the aim of your paper and its contribution

 In this report / paper / review / study we …

 This paper outlines / proposes / describes / presents a new approach to …

 This paper examines / seeks to address / focuses on / discusses / investigates how to solve … This paper is an overview of / a review of / a report on / a preliminary attempt to …

The present paper aims to validate / call into question / refute Peng’s findings regarding …

 X is presented / described / analyzed / computed / investigated / examined / introduced / discussed in order to …

The aim of our work / research / study / analysis was to further / extend / widen / broaden current knowledge of …

 Our knowledge of X is largely based on very limited data.

The aim of the research was thus / therefore / consequently to

 The aim of this study is to study / evaluate / validate / determine / examine / analyze / calculate / estimate / formulate …

 This paper calls into question / takes a new look at / re-examines / revisits / sheds new light on …

With this in mind / Within the framework of these criteria / In this context we tried to …

We undertook this study / initiated this research / developed this methodology to

We believe that we have found / developed / discovered / designed an innovative solution to…

We describe / present / consider / analyze a novel / simple / radical / interesting solution for … 6. Explaining the key terminology in your field

 The term ‘X’ is generally understood to mean / has come to be used to refer to / has been applied to …

 In the literature, X usually refers / often refers / tends to be used to refer to …

 In the field of X, several / various / many definitions of Y can be found.

The term X is / was / has been used by Molotov [2011] to refer to …

Molotov uses the term X [2011] to refer to / denominate …

 X is defined by Peng [1990] to refer to / to mean …

Vitous [2015] has provided / put forward / proposed a new definition of X, in which …

X is defined / identified / described as …

[Njimi 2004]. In the literature there seems to be no general definition of X / a general definition of X is lacking / there is no clear definition of X. Several authors have attempted to define X, but as yet / currently / at the time of writing there is still no accepted definition. In broad / general terms, X is / can be defined as a way to …

The broad / general / generally accepted use of the term X refers to …

X is sometimes equated with / embodies a series of …

X, Y and Z are three kinds / types / categories / classes of languages.

There are three kinds of languages: / The three kinds of languages are: / Languages can be divided into three kinds: X, Y and Z.

  1. Explaining how you will use terminology and acronyms in your paper

The acronym PC stands for / denotes …

 The subjects (henceforth named / hereafter ‘X’) are…

The subject, which we shall call / refer to as ‘X’, is …

Throughout this paper / section we use the terms ‘mafia’ and ‘the mob’ interchangeably, following / in accordance with the practice of this department where this study was conducted. The fonts, i.e. / that is to say the form of the characters, are of various types.

There are three different types, namely / specifically: X, Y and Z. Throughout the / In this paper we use / will use the term X to refer to …

 In this chapter X is used / will be used to refer to …

 In this paper the standard meaning of X is / will be used.

This aspect is / will be dealt with in more detail in Sect. 2. We will see / learn / appreciate how relevant this is in the next subsection.

  1. Giving the structure of paper – what is and is not included

 This paper is organized as follows / divided into five sections.

The first section / Section 1 gives a brief overview of …

The second section examines / analyses …

In the third section a case study is presented / analyzed …

A new methodology is described / outlined in the fourth section …

We / I propose a new procedure in Section 4. Some / Our conclusions are drawn in the final section. This paper / chapter / section / subsection begins by examining …

 The next chapter looks at / examines / investigates the question of …

 Problems / Questions / Issues regarding X are discussed in later sections. A discussion of Y is / falls outside the scope of this paper. For reasons of space, Y is not addressed / dealt with / considered in this paper. 9. Giving general panorama of past-to-present literature There is a considerable / vast amount of literature on …

 In the literature there are many / several / a surprising number of / few examples of

What we know / is known about X is largely based on …

Much / Not much / Very little is known about …

 Many / Few studies have been published on …

[Ref] Various approaches have been proposed / put forward / suggested / hypothesized to solve this issue [Ref]. X has been identified / indicated as being …

[Ref] X has been shown / demonstrated / proved / found to be …

 [Ref] X has been widely investigated / studied / addressed …

 [Ref] Xs have been receiving / gaining much attention due to …

 In the traditional / classical approach, X is used to …

In recent years there has been considerable / growing interest in …

[Ref] A growing body of literature has examined / investigated / studied / analyzed / evaluated…

[Ref] Much work on the potential of X has been carried out [Ref], yet / however there are still some critical issues … [Ref]

  1. Reviewing subsequent and more recent literature

Experiments on X were conducted / carried out / performed on X in 2009 by a group of researchers from …

In a major advance in 2010, Berlusconi et al. surveyed / interviewed …

 Jeffries and co-workers [2011] measured / calculated / estimated …

In [67] the authors investigated / studied / analyzed …

A recent review of the literature on this topic / subject / matter / area [2012] found that …

 A number / An increasing number of studies have found that …

Since 2011 / In the last few years, much more information on X has become available … Several studies, for example / instance [1], [2], and [6], have been carried out / conducted / performed on X. More recent evidence [Obama, 2013] shows / suggests / highlights / reveals / proposes that …

 It has now been suggested / hypothesized / proposed / shown / demonstrated that …

[Cosimo 2010] Many attempts have been made [Kim 2009, Li 2010, Hai 2011] in order to / with the purpose of / aimed at …

Mentioning positive aspects of others’ work Smith’s [22] use of X is fully justified / very plausible / endorsed by experience. Kamos’s [23] assumptions seem to be realistic / well-founded / well-grounded / plausible / reasonable / acceptable. The equations given in [24] are accurate / comprehensive …

 It has been suggested [25] that … and this seems to be a reliable / useful / innovative approach … Research has tended to focus on X rather than Y. An additional problem is that / Moreover X is

The main limitation / downside / disadvantage / pitfall / shortfall of X is … One of the major drawbacks to adopting / using / exploiting this system is …

This is something of a pitfall / disadvantage … A well-known / major / serious criticism of X is

A key problem with much of the literature on / regarding / in relation to X is that …

This raises many questions about / as to / regarding whether X should be used for … One question / issue that needs to be asked / raised is … Unfortunately, it does not / fails to / neglects to explain why … This method suffers from a number / series / plethora of pitfalls. There is still considerable ambiguity / disagreement / uncertainty with regard to …

Many experts contend, however / instead / on the other hand, that this evidence is not conclusive. A related hypothesis holds / maintains that X is equal to Y, suggesting / indicating that …

Other observations indicate / would seem to suggest that this explanation is insufficient …

9.Describing purpose of testing / methods used

In order to identify / understand / investigate / study / analyze X …

To enable / allow us to … , we … To see / determine / check / verify / determine whether … To control / test for X, Y was done. So that we could / would be able to do X, we …

In an attempt / effort to do X, we … X was done / We did X in order to …

The setup we used can be found / is reported / is detailed in [Ref 2]. Our experimental set up bears a close resemblance to / is reminiscent of / is based on / is a variation on / was inspired by / owes a lot to / is more or less identical to / is practically the same as the one proposed by Smith [2014]. We used a variation of Smith’s procedure.

The procedure used is as described / explained / reported / proposed by Sakamoto [2013]. The method is in line with a variation of / essentially the same as that used by Kirk [2009] with some changes / modifications / alterations / adjustments. We refined / altered / adapted / modified / revised the method used / reported / suggested / explained / proposed / put forward by Bing [2012]. Our technique was loosely / partially / partly / to some extent based on … More details can be found / are given in our previous paper [35].

  1. Describing the apparatus and materials used and their source

The instrument used / utilized / adopted / employed was …

The apparatus consists of / is made up of / is composed of / is based on …

The device was designed / developed / set up in order to …

X incorporates / exploits / makes use of the latest technological advances. The system comes complete / is equipped / is fully integrated / is fitted with a …

 It is mounted on / connected to / attached to / fastened to / fixed to / surrounded by / covered with / integrated into / embedded onto / encased in / housed in / aligned with … It is located in / situated in / positioned on ….

  1. Reporting software used

The software application / program / package used to analyze the data was SoftGather (Softsift plc, London).

The data were obtained / collected using SoftGather. Data management / analysis was performed by / using SoftGather.

X was carried out / performed / analyzed / calculated / determined using SoftGather. Statistical significance was analyzed by using / through the use of SoftGather.

 We used commercially available software / a commercially available software package. Free software, downloaded from www.free.edu, was used / adopted to …

  1. Reporting customizations performed

 X was tailored / customized for use with …

X can easily be customized / adapted / modified to suit all requirements.

Measurements were taken using purpose-built / custom-built / customized equipment.

The apparatus was adapted as in [Ref] / in accordance with [Ref] / as follows:

The following changes / modifications were made:

The resulting ad hoc device can / is able to / has the capacity to …

  1. Formulating equations, theories, and theorems

This problem can be outlined / phrased / posed in terms of …

The problem is ruled by / governed by / related to / correlated to …

This theorem asserts / states that …

 The resulting integrals / solution to X can be expressed as … …

 where T stands for / denotes / identifies / is an abbreviation for time. By substituting / Substituting / Substitution into …

 Combining / Integrating / Eliminating ..

we have that: … Taking advantage of / Exploiting / Making use of X, we …

On combining this result with X, we deduce / conclude that … Subtracting X from Y, we have that / obtain / get …

Equation 1 shows / reveals that This gives the formal solution / allows a formal solution to be found … It may easily / simply verified that …

 It is straightforward / easy / trivial to verify that …

 For the sake of simplicity / reasons of space, we

  1. Explaining why you chose your specific method, model, equipment, sample etc.

The aim / purpose of X is to do Y. Consequently we / As a result we / Therefore we / We thus This method / model / system was chosen because it is one of the most practical / feasible / economic / rapid ways to …

 We chose this particular apparatus because / on account of the fact that / due to / since …

 It was decided that the best procedure / method / equipment for this investigation / study was to …

An X approach was chosen / selected in order to …

The design of the X was based on / is geared towards …

We opted for / chose a small sample size because / due to / on the basis of …

By having / By exploiting / Through the use of X, we were able to …

Having an X enabled us to / allowed us to / meant that we could do Y. 24. Explaining the preparation of samples, solutions etc. We used reliable / innovative / classic / traditional techniques based on the recommendations of …

 Xs were prepared as described by / according to / following Jude [2010]. Xs were prepared in accordance with / in compliance with / as required by….

Y was prepared using the same / a similar procedure as for X. All samples were carefully / thoroughly checked for …

X was gradually / slowly / rapidly / gently heated

The final / resulting solutions contained … This was done by means of / using / with a calculator.

  1. Describing benefits of your method, equipment etc.

This method represents a viable / valuable / useful / groundbreaking / innovative alternative to

This equipment has the ability / capacity / potential to outperform all previous Xs. This apparatus has several / many interesting features / characteristics. Our method has many interesting / attractive / beneficial / useful / practical / effective / valuable applications. Of particular / major / fundamental interest is …

The key / basic / chief / crucial / decisive / essential / fundamental / important / main / major / principal advantages are: Our procedure is a clear improvement / advance on current methods. We believe this solution will aid / assist researchers to …

This solution improves on / enhances / furthers / advances previous methods by …

The benefits / advantages in terms of X far outweigh the disadvantages with regard to Y. 30. Outlining alternative approaches.

A less lengthy / time-consuming / cumbersome / costly approach is …

 A neater / more elegant / simplified / more practical solution for this problem …

 An alternative solution, though with high overheads / slightly more complicated / less exhaustive is …

One / One possible / A good way to avoid the use of X is to use Y instead.

  1. Explaining how you got your results

To assess X / evaluate X / distinguish between X and Y, Z was used. X analysis was used to test / predict / confirm Y. Changes in X were identified / calculated / compared using …

The correlation / difference between X and Y was tested. The first set of analyses investigated / examined / confirmed / highlighted the impact of …

  1. Highlighting significant results and achievements

The most striking / remarkable result to emerge from the data is that …

Interestingly / Curiously / Remarkably / Inexplicably, this correlation is related to …. Significantly / Importantly / Crucially / Critically, X is …

The correlation between X and Y is interesting / of interest / worth noting / noteworthy / worth mentioning because …

The most surprising / remarkable / intriguing correlation is with the …

The single most striking / conspicuous / marked observation to emerge from the data comparison was …

It is interesting / critical / crucial / important / fundamental to note that …

We believe that / As far as we know / As far as we aware this is the first time that X …

 We believe that / We are of the opinion that / In our view the result emphasizes the validity of our model. This result has further strengthened our confidence in X / conviction that X is / hypothesis that X is …

Our technique shows a clear / clearly has an advantage over …

 The importance of X cannot be stressed / emphasized too much. This underlines / highlights / stresses / proves / demonstrates just how important X is. The utility of X is thus underlined / highlighted / stressed / proved / demonstrated. This finding confirms / points to / highlights / reinforces / validates the usefulness of X as a …

 Our study provides additional support for / further evidence for / considerable insight into X. These results extend / further / widen our knowledge of X. These results offer compelling / indisputable / crucial / overwhelming / powerful / invaluable / unprecedented / unique / vital evidence for …

  1. Stating that your results confirm previous evidence

Our experiments confirm / corroborate / are in line with / are consistent with previous results [Wiley 2009]. The values are barely / scarcely / hardly distinguishable from [Li 2010] who …

This value has been found to be / is typical of X. This is in good agreement / in complete agreement / consistent with …

 This fits / matches / concurs well with [65] and also confirms our earlier / previous findings [39, 40, 41]. This confirms / supports / lends support to / substantiates previous findings in the literature …

These values correlate favorably / satisfactorily / fairly well with Svenson [2009] and further support the idea / role / concept of …

 Further tests carried out with X confirmed / corroborated / concurred with our initial findings. As proposed / suggested / reported / indicated / put forward by Dong [2011], the evidence we found points to …

Our results share / have a number of similarities with Claire et al.’s [2012] findings …

  1. Stating that your results are in contrast with previous evidence

It was found that X = 2, whereas / on the other hand Kamatchi [2011] found that …

 We found much higher values for X than / with respect to those reported by Pandey [2000]. Although / Despite the fact that Li and Mithran [2014] found that X = 2 we found that X = 3. In contrast to / contradiction with earlier findings [Castenas, 2009], we …

 This study has not confirmed previous research on X. However, / Nevertheless / Despite this, it serves to …

Even though these results differ from some published / previous / earlier studies (Cossu, 2001; Triana, 2002), they are consistent with those of …

 Kosov et al. noted that x = y. Our results do not support / appear to corroborate / seem to confirm their observation, in fact …

 Georgiev is correct to argue / propose / claim that x = y. However, his calculation only referred to the limited case of ….

 and our conclusion of x = z, would thus seem to be justified / justifiable / defensible / correct / acceptable / warranted. Although our results differ slightly / to some extent / considerably from those of Minhaz [2001], Erturk [2007], and Hayk [2014], it can / could nevertheless be argued that … Our findings do / The current study does not support previous research in this area. In fact, contrary to / unlike / in contrast with what was previously thought, we found that …

These findings refute / disprove / are in contradiction with / contrast with / significantly differ from previous results reported in the literature. 38. Stating and justifying the acceptability of your results

As expected / anticipated / predicted / forecast / hypothesized, our experiments show / demonstrate / prove that …

Our formula captures / reproduces the response of …

Apart from this slight discordance / discrepancy / disagreement / non-alignment, the result is confirmation of … Despite / Notwithstanding the lack of agreement, we believe our findings compare well with … Although / Even though / Despite the fact that there was some inconsistency …

There is satisfactory / good / exceptional / perfect agreement between …

No significant / substantial / appreciable / noteworthy differences were found … Our findings appear to be well substantiated / supported by …

The number of Xs that confirmed our findings was appreciable / significant / substantial.

  1. Explaining and justifying undesired or unexpected results

 It is very likely / probable / possible that participants may have erroneously …

 and this may have led to / brought about changes in …

The prime / primary / foremost cause of the discrepancy is due to / a result of / a consequence of X. This apparent lack of correlation can be attributed to / explained by / justified by …

The reason for this rather contradictory result is still not entirely / completely clear, but … There are several possible explanations for this result / finding / outcome.

These differences can be explained / justified / accounted for in part by …

It can thus be suggested / conceivably hypothesized / reasonably assumed that …

 The unexpectedly high / low level of X is undoubtedly / certainly / without any doubt due to A possible / reasonable / satisfactory explanation for X may be that ….

 Another possible explanation / rationalization / reason for this is that … Clearly / Evidently / Naturally there may be other possible explanations. This happened / occurred / may have happened / may have occurred because we had not examined X sufficiently / in enough depth due to …

 The reasons for this result are not yet wholly / completely / entirely understood. It cannot be ruled out / ignored that there was some unintended bias in …

 An unintended bias cannot be ruled out / should be taken into consideration. We cannot rule out that X might / may have influenced Y. The observed increase in X could be attributed to / might be explained by it / could be interpreted as being a result of …

Despite the fact that / Although X was expected to do Y, it was not predicted that X would also do Z. However, this is not particularly surprising given the fact / in light of the fact / if we consider that …

  1. Announcing your conclusions and summarizing content

 In conclusion / In summary / In sum / To sum up, our work …

Our work has led us to conclude / the conclusion that …

We have presented / outlined / described …

In this paper / study / review we have …

This paper has investigated / explained / given an account of …

have obtained accurate / satisfactory / comprehensive results proving / demonstrating / showing that …

have devised a methodology / procedure / strategy which … We have confirmed / provided further evidence / demonstrated that …

Considerable progress has been made / insight has been gained with regard to …

The present study has only investigated / examined X. Therefore / Consequently …

The project / analysis / testing / sampling was limited in several ways. First, …

 Finally, a number of potential limitations / weaknesses / shortfalls / shortcomings / weak points need to be considered. First, …

However, given the small sample size, caution must be exercised / taken / used / applied. The findings might not be transferable to / generalized to / representative of …

The present findings might help to solve / have important implications for solving / suggest several courses of action in order to solve this problem. X is suitable for / has the potential to

Our method / technique / approach / procedure could be applied to …

 One possible / potential / promising application of our technique would be … Results so far have been very promising / encouraging and …

 This approach has the potential / requirements / characteristics / features to …

This could eventually / conceivably / potentially / hypothetically lead to …

  1. Future work already underway or planned by the authors We are currently / now / in the process of investigating … Research into solving this problem is already underway / in progress. To further our research, we plan / are planning / intend to …

 Future work will concentrate on / focus on / explore / investigate / look into …

Further studies, which take X into account, will need to be undertaken / performed. We hope that further tests will prove our theory / confirm our findings. These topics are reserved for / deferred to future work.

  1. Future work proposed for third parties to carry out

 Further work needs to be done / carried out / performed to establish whether …

 Further experimental investigations / tests / studies are needed to estimate …

 More / Additional / Further work on X, would help us to do Y. We hope / believe / are confident that our research will serve as a base for future studies on …

 It is recommended / We recommend / We suggest / We propose that further research should be undertaken in the following areas: More broadly / On a wider level, research is also needed to determine ….

This research has raised / given rise to / thrown up many questions in need of further investigation / study / examination. This is an important / a fundamental / a vital issue for future research.

The design and development of Xs will challenge / be a challenge for us for years. Future work should concentrate / focus on enhancing the quality of X.

Future studies should target / aim at / examine / deal with / address X.

Future studies on the current topic are therefore required / needed / recommended / suggested in order to establish / verify / validate / elucidate …

 Our results are encouraging / promising and should be validated by a larger sample size.

  1. Referring to tables and figures, and to their implications

Table 1 compares / lists / details / summarizes the data on X. Table 2 proves / shows / demonstrates / illustrates / highlights that X is …

Figure 1 presents / reports / shows / details the data on X. Figure 3 pinpoints / indicates exactly where X meets Y. As shown / highlighted / illustrated / detailed / can be seen in Fig. 1, the value of …

The value of X is greater when Y = 2 (Fig. 1 / Eq. 2) The results on X can be seen / are compared / are presented in Fig. 1. From the graph / photo / chart / histogram we can see / note that …

It can be seen in / is apparent from Fig. 1 that …

We observe / note from Table 1 that .. The graph above / below / to the left / to the right shows that …

Figure 8 shows a clear trend / significant difference in … The table is revealing / interesting in several ways. First …

  1. Making transitions, focusing on a new topic

 If we now turn to / Turning now to / Let us know look at the second part …

As far as X is / Xs are concerned …

As regards / Regarding / Regarding the use of / As for X, it was found that …

  1. Referring backwards and forwards in the paper

As was mentioned / stated / noted / discussed / reported in the Methods, …

reported above / previously / earlier / before …

As mentioned / stated / outlined in the literature review …

above- / afore-mentioned X is …

More details on this will be given below / in the next section / in the appendix. The following is / Here follows / Below is a list of …

Please refer to Appendix 2 / Table 6 / the Supplementary Material for

 

IEEE TEMPLATE:

 

The Essence of MATLAB as a Career Option

MATLAB is a programming language that is frequently used for mathematical modeling and data acquisition across different industry verticals such as the aerospace and aviation industry. It is used to build sophisticated simulations, data mining and machine learning algorithms  that are used in almost every branch of engineering – from mechanical to electrical to chemical to computer science. It is also frequently used at universities by professors and students for high-end research purposes. MATLAB is an acronym for matrix laboratory and is a property of MathWorks. It is extremely popular and has millions of users worldwide across different industry and academia.  

Mathematical modeling and simulation are frequently used in engineering and economics. MATLAB has a GUI (Graphic User Interface), which makes mathematical modeling very easy. It also has some additional features such as Simulink, which facilitates multi-domain simulation. Akin to any other programming languages MATLAB has a procedure for naming variables and a stringent structure that controls the program flow. It allows interfacing in other languages such as Fortran or C. Furthermore, MATLAB can be used to directly call libraries written in Java.NET, Perl or ActiveX. It also has toolboxes such as Distributed Systems, and Fuzzy Toolbox, that is designed to benefit developers to build long term solutions. Freshers in MATLAB may avail the mentoring options from MATLAB developers in India and industry leaders in order to use MATLAB like an expert.

MATLAB developers in India design, develop, simulate and test software on numerous MATLAB platforms. They are highly skilled and possess different subject matter knowledge. They have a thorough and comprehensive understanding of mathematics such as Game theory, Fourier Deep learning neural networks, Vector Algebra, and more. As thorough geeks that they are, they are also surprisingly equally capable of fruitful client interactions. MATLAB developers in India are highly qualified and they most often possess a B.Tech/B.E. and/or M.Tech degrees. MATLAB professionals in India are rigorously screened and only most eligible candidates are offered employment. MATLAB developers in India can earn a lucrative salary. The annual salary ranges from 3 to 5 lakh per annum. Several MATLAB developers in India also work on a freelance basis on numerous projects. Such developers may charge up to Rs 3000 per hour. A career in MATLAB programming is highly lucrative and is replete with different opportunities. There are a lot of growth opportunities along with skill development.

PhD in Big Data:The next big thing! Are you made for it?

“Big Data”, well the phrase is there almost everywhere. The term was coined quite a while back but got officially incorporated in the Oxford English Dictionary in the year 2013. It has surpassed all levels of inflated expectations and has become nothing less than a rage. But do all of us know what it actually means?

In a very fundamental definition of Big Data, there are three V’s: Volume, Velocity and Variety. However, there are some counter arguments associated with it, which say that thesis of the data is not determinant for categorising it.  Rather, it is based on the tools being used in the data and the kind of insights that are being drawn from it.

If this definition excites you and generates interest in your mind, I have some good news for you. The demand for Big Data scientists is far ahead than the supply at present. With the way the data scientists are getting in demand and the highly competitive industries are looking for them, only those candidates which have qualification of the top most level are the ones who have the brightest chances. If you want to acquire a PhD as a data scientist, here are some quick tips for you:

Have a strong focus on academics: Successful data scientists can be from diverse backgrounds. A good data scientist is the one who has the multi disciplinary experience of applying scientific tools, as this proves quite useful in the application aspect of the data scientist. Stay abreast with latest research trends and read as many journals as possible.

Have the knowledge of business background: A strong background in business and strategy can make a good foundation for the career of a data scientist and can help to jettison the career of a data scientist in the preliminary stage itself. As data scientist you must know:

  • How the business works?
  • How is the data collected?
  • How is the data intended to be used?
  • What is expected to be achieved from the data analysis?

The curriculum of PhD in Big Data in your university: Not all universities at the moment are abreast and equipped enough to offer a PhD in Big Data. If you are sure off doing one and have shortlisted a few options, do look into choosing the one that gives you lot of practical exposure and understanding of application of concepts with a business acumen as eventually, if you do a PhD in Big data, you wouldn’t be getting into academics. Corporate would be your calling and you must enter into it, equipped enough to justify your education.

What after the dissertation? A new beginning again…….

Getting a doctorate is not the end of the journey for a researcher. This is more true when we talk of an academician because in the life of an academician, regular publications are integral for not just growth prospects but also for the sake of mere survival. You can mine your dissertation for one or more articles or convert it into a book and give a new life and dimension to your PhD research study.

Even if you have given a couple of mandatory publications during your PhD study, there would surely be a chunk of research that you did in your PhD that would be untouched and would have a scope for publication. All that is required, is to repurpose the dissertation and give it a new life.

The new beginning for your dissertation can be by either attempting to create it into a book or else a couple of scholarly articles could be extracted from it. In most of the cases what is observed is that those in the humanities discipline often convert their dissertation into a book while those in social sciences prefer to publish scholarly articles.

It is always a good idea to take into account the trend and expectations of your department and discipline. If most of your peers are into converting their thesis into books then you must also follow suit.This depends primarily on  the ranking of books and articles in your institution. Sometimes three refereed publications are considered equivalent to publishing a book. If these kind of norms are not explicitly specified in your university, you can gauge about the criteria by assessing the trend of the scholarly work of the other faculty members in your institution and the kind of promotions and benefits they have availed from it.

So, by now you are very clear that there is much more to research after completing your PhD. The hard work and effort that you put into your research during your doctoral study can be given a new dimension and life and further brighten your professional prospects. Further on we would also walk through the process of getting your thesis book ready and the step by step process to break your manuscript into worthy articles that can add on to your profile as a researcher and give you an ace in your professional appraisal and a new life to your PhD thesis.

5 reasons why Big Data is in Trend

Nowadays Big Data is seen everywhere and there is suddenly a crucial requirement for collecting and preserving whatever data gets generated, due to the fear of missing out something vital. Do you know that there is significant amount of data floating around? What we actually do is what will lead to our business success. This is the reason why Big Data has suddenly become in rage in the IT sector.

Bid Data has become vital as it helps in providing much needed leverage over competitors, aids in decision making and improving business. This is true for professionals as well as organizations in the analytics domain. For professionals who are well versed with Big Data Analytics, there are significant opportunities to explore. If you still require more convincing, read on to know the 5 reasons why Big Data is in trend.

Top priority of large numbers of organizations
Various surveys have concluded that Big Data Analytics is one of the key priorities for the organizations. They are of the opinion that it enhances the performances of their organization significantly.

Big Data Analytics Adoption is Enhancing
The advent of new technologies is making it extremely easy to perform highly sophisticated data analytics on a large and diverse datasets. Various reports have clearly indicated that large numbers of organizations are using some form of Big Data analytics for data mining tasks, predictive analytics and business intelligence.

Big Data is Utilized Everywhere
Due to its extraordinary features, big data analytics is nowadays in huge demand. The significant growth is also due to the various domains across which Big Data is used.

A Key Factor in Decision Making
Do you know that today analytics is a crucial competitive resource for various companies. It plays a crucial role in driving business strategy and making vital business decisions.

Significant job opportunities
According to various researches, the demand for analytics skills is going up significantly, but there is still a tremendous deficit on the supply side. Do you know that the gap between demand and supply is happening globally and is not confined to any particular country? Even though Big Data Analytics is a hot job opportunity, but still there are significant numbers of unfilled jobs across the world. The demand for talents Big Data experts are expected to be significant as large numbers of global organizations is nowadays outsourcing their work to the companies and people who understand and viably use Big Data!

5 trending PhD research topics in Big Data

In the past decade, Big Data has emerged as a powerful technology tool and is growing in leaps and bounds. There are a number of industry sectors in which PhD research is being conducted for Big Data, including Ecommerce, banking, insurance, telecom, and the health sector.

There are a number of quality research programs being pursued by PhD scholars on the vast and growing field of Big Data. While the maximum number of Big Data research papers is in the field of computer science (171), other academic fields for this line of research include Engineering (75), Mathematics (33), and Business Management (26).

Listed below are the 5 trending research topics being pursued by PhD scholars around the globe:

  • Big Data analytics

Big Data analytics tool has emerged as a powerful tool used to harness the potential use of big data for industry-specific uses. A number of E-commerce retailers are using analytics for online sales conversion and determining customer behaviour. Other potential use is in the performance improvement of sporting athletes.

  • Improving the quality of healthcare

Currently, research is being conducted in the areas of drug discovery, drug response, bioinformatics, clinical data analysis, and public health data. According to the Mckinsey report on Big Data in 2011, Big Data has the potential of reducing the US national health care costs by around 8%.

  • Data visualization

Big Data users are able to see and analyse big data sets using much improved visualization tools. The advent of touch-sensitive navigation has brought huge improvements in interactive visualization technology.

  • Hadoop framework

Research on Apache Hadoop framework is aimed at developing software applications that can be deployed on a larger and distributed network. Deployed across network clusters, the Hadoop framework has been used by a host of popular web platforms including Twitter, LinkedIn, Amazon, and Facebook. Other research topics include the MapReduce programming model, used for executing code for processing large amounts of data over distributed network clusters.

  • Distributed Storage systems

Other areas of PhD research include the efficient way of storing volumes of data over large-scale distributed network clusters. Examples include the Google File System used for storing high-data applications over distributed systems, and Bigtable used for structured storage of Big data.

The constant evolution of Big Data presents researchers with dynamic challenges, while also presenting them with opportunities of determining the evolution of science.

Choosing the right network simulator

Depending on the type of your PhD research work, you can use a variety of network simulator softwares that are available in the market. Network simulators are particularly useful in academic research work as it is expensive and time-consuming to test your project over real-time network of computers and data connectors.

There are a number of network simulators, including the popular ones like OPNET, NS2/NS3, and OMNeT++. Network simulators can be classified on basis of the following criteria:

  • Commercial use or Open source

For commercial software such as OPNET and QualNet, researchers have to pay for the license and cannot modify the source code. Advantages include regular updates and fixes and documentation set for easy learning. Open source software such as NS2/NS3 and OMNeT++ are free for downloads and are very flexible. Open source network simulators are more popular in academic circles.

  • Ease of use

GUI-based simulators such as OPNET and OMNeT++ provide a visual interface to the user, making it easier to understand the working. Alternatively, simulators with text-based interfaces are easier to customize for your project requirements.

For your convenience, OPNET simulator allows you to model, simulate, and analyse networks. Additional features include user-friendly graph and chart generation, statistics, and even animation.

  • Programming features

Simulators with strong programming features provide a highly-customizable framework to design your own network simulating application for testing. NS2 uses C++ object-oriented language with Tcl script language. This programming code allows you to write your own event scheduler and network component objects, thus reducing the network packet and event processing time. NS3 that uses C++ with Python scripting is an open source simulator that is aimed particularly for research work.

The strength of OMNeT++ is in its component-based architecture with a number of modules assembled using reusable software components. Besides this, OMNeT++ can run on both Windows-based and Linux-based systems.

  • Performance

For a network comprising of 400 to 2000 nodes, among NS2, NS3, and OMNeT++, NS2 uses the highest amount of memory with NS3 utilizing the lowest amount of memory. With a gradual increase in nodes, there is a corresponding increase in memory consumption among all the network simulators. With respect to the computational time, NS2 shows a rapid increase in time with increase in nodes. NS3 is the most efficient in computation time and scalability as compared to the other simulators.