001561457 000__ 11413nam\\22005173i\4500 001561457 001__ 1561457 001561457 003__ MiAaPQ 001561457 005__ 20241002095017.0 001561457 006__ m\\\\\o\\d\\\\\\\\ 001561457 007__ cr\cn\nnnunnun 001561457 008__ 240928s2023\\\\xx\\\\\\o\\\\\|||\0\eng\d 001561457 020__ $$a9780750350198 001561457 020__ $$z9780750350181 001561457 035__ $$a(MiAaPQ)EBC31253207 001561457 035__ $$a(Au-PeEL)EBL31253207 001561457 035__ $$a(OCoLC)1429755652 001561457 040__ $$aMiAaPQ$$beng$$erda$$epn$$cMiAaPQ$$dMiAaPQ 001561457 1001_ $$aChiroma, Haruna. 001561457 24510 $$aComputing Research Survival Manual :$$bA Practical Handbook for Beginners. 001561457 250__ $$a1st ed. 001561457 264_1 $$aBristol :$$bInstitute of Physics Publishing,$$c2023. 001561457 264_4 $$c©2023. 001561457 300__ $$a1 online resource (235 pages). 001561457 336__ $$atext$$btxt$$2rdacontent 001561457 337__ $$acomputer$$bc$$2rdamedia 001561457 338__ $$aonline resource$$bcr$$2rdacarrier 001561457 4901_ $$aIOP Ebooks Series 001561457 5050_ $$aIntro -- Preface -- Author biographies -- Haruna Chiroma -- Jemal H Abawjy -- Chapter 1 Computing disciplines ecosystem and origin of research -- 1.1 Introduction -- 1.2 Computing disciplines -- 1.2.1 Computer science -- 1.2.2 Software engineering -- 1.2.3 Computer engineering -- 1.2.4 Information systems -- 1.2.5 Information technology -- 1.2.6 Cybersecurity -- 1.2.7 Data science -- 1.2.8 Emerging areas: artificial intelligence -- 1.3 Comparing the focus of the seven disciplines within the computing ecosystem -- 1.4 Scientific research in computing -- 1.4.1 Types of research -- 1.5 Research philosophy and origin of research in computing -- 1.5.1 Origin of research in computer science -- 1.5.2 Origin of research in software engineering -- 1.5.3 Origin of research in information systems -- 1.5.4 Origin of research in information technology -- 1.5.5 Origin of research in data science -- 1.5.6 Origin of research in cybersecurity -- 1.5.7 Origin of research in computer engineering -- 1.6 Comparing research methods in discipline within the computing ecosystems -- 1.7 Generic procedure for computing research -- 1.8 Features of quality and bad research -- 1.9 MSc, PhD and undergraduate project in computing -- 1.10 Organization of the book -- 1.11 Summary -- References -- Chapter 2 Computing search engines and bibliographic databases -- 2.1 Introduction -- 2.2 The computing academic databases -- 2.2.1 Clarivate Analytics Web of Science -- 2.2.2 Scopus -- 2.2.3 Comparing the Scopus and Web of Science -- 2.2.4 DBLP computer science bibliography -- 2.2.5 ACM digital library -- 2.2.6 Ei-Compendex -- 2.2.7 IEEE Xplore -- 2.2.8 ScienceDirect -- 2.2.9 Springerlink -- 2.2.10 PubMed -- 2.2.11 Google Scholar -- 2.3 Comparing the academic search engines: similarities and differences -- 2.4 Summary -- References. 001561457 5058_ $$aChapter 3 Systematic literature review from a computing perspective and research problem formulation -- 3.1 Introduction -- 3.2 Why conduct literature search and systematic literature review? -- 3.3 Systematic literature review, narrative review and metadata analysis: differences -- 3.3.1 Approach for conventional review -- 3.3.2 Synthesis of existing evidence and research problem -- 3.4 Proposed systematic literature review methodology for computing -- 3.4.1 Focus and selection of research topic -- 3.4.2 Motivation -- 3.4.3 Keywords -- 3.4.4 Research questions -- 3.4.5 Literature search and data sources -- 3.4.6 Study selection procedure -- 3.4.7 Exclusion and inclusion criteria -- 3.4.8 Inclusion and exclusion of papers -- 3.4.9 Screening based on introduction and conclusion (optional) -- 3.4.10 Stopping the search and the number of articles required for the SLR -- 3.4.11 Data extraction and synthesis -- 3.4.12 Answers to research questions -- 3.4.13 Systematic literature review quality assessment -- 3.4.14 Discussion -- 3.4.15 Limitations -- 3.4.16 Challenges and future research opportunities -- 3.5 The brief structure of systematic literature review -- 3.6 Common mistakes in conducting systematic literature review -- 3.7 Research problem formulation -- 3.7.1 Developing problem statement -- 3.7.2 The problem statement-computer science perspective -- 3.7.3 Research questions -- 3.7.4 Aim and objectives of the research -- 3.7.5 Significance of the research -- 3.7.6 Research scope -- 3.8 Summary -- References -- Chapter 4 Computing research tools and resources -- 4.1 Introduction -- 4.2 Research productivity tools -- 4.2.1 Reference management software -- 4.2.2 EndNote -- 4.2.3 Plagiarism detection tool -- 4.2.4 Spelling and grammar checkers: Ginger Software spelling and grammar checker -- 4.2.5 Google documents -- 4.2.6 ShareLaTeX. 001561457 5058_ $$a4.2.7 Backup tools -- 4.2.8 Finding a suitable journal for submitting a paper -- 4.3 Computing research tools -- 4.3.1 Software engineering -- 4.3.2 Information systems and information technology -- 4.3.3 Data science -- 4.3.4 Libraries and frameworks -- 4.4 Computer engineering -- 4.4.1 Gem5 simulator -- 4.4.2 Webots -- 4.5 Hardware and software platforms -- 4.6 Summary -- References -- Chapter 5 Computing datasets and data engineering -- 5.1 Introduction -- 5.2 Large-scale datasets as today's reality compared to small-size datasets -- 5.2.1 Definition of big data -- 5.2.2 Characteristics of big data -- 5.2.3 Case studies -- 5.2.4 Content large-scale data format -- 5.2.5 Challenges regarding big data -- 5.3 Benchmark, real-world and synthesis datasets -- 5.4 Characteristic of real-world datasets -- 5.4.1 Missing values -- 5.4.2 Inaccurate values -- 5.4.3 Imbalanced data -- 5.4.4 Outliers and noise -- 5.4.5 Redundant and irrelevant features -- 5.5 Case study: collecting data from a real physical environment-smart city -- 5.6 Knowing your dataset -- 5.7 Cross-datasets -- 5.8 Dark datasets -- 5.9 Research data management -- 5.9.1 Storing, preservation and discarding -- 5.9.2 Safety, security and confidentiality -- 5.9.3 Third party access -- 5.9.4 Data storage facilities -- 5.9.5 Data retention and publication -- 5.9.6 Confidentiality management -- 5.9.7 Responsibilities of researchers on data and developing a data management plan -- 5.10 Research data repositories and sources -- 5.10.1 IEEE DataPort -- 5.10.2 University of California Irvine machine learning repository -- 5.10.3 Kaggle and Code Ocean -- 5.10.4 GitHub platform -- 5.10.5 Google Dataset Search -- 5.10.6 Quantitative and qualitative means of data collection -- 5.10.7 Knowledge discovery in database 99-DARPA, ADFA Linux and NSL-KDD -- 5.11 Features engineering -- 5.12 Summary -- References. 001561457 5058_ $$aChapter 6 Methodology from a computing perspective -- 6.1 Introduction -- 6.2 Research methodology in computing -- 6.2.1 Process -- 6.2.2 Modeling -- 6.3 Relating the methodology to the computing disciplines -- 6.4 Algorithms -- 6.4.1 Algorithm performance analysis -- 6.5 Solving real-world problems using algorithms -- 6.5.1 Existing algorithm -- 6.5.2 Modified algorithm -- 6.5.3 New algorithm -- 6.6 Conceptual framework -- 6.7 Comparative study: hardware and software -- 6.8 Case studies -- 6.8.1 Case study 1: software engineering -- 6.8.2 Case study 2: cybersecurity -- 6.8.3 Case study 3: cybersecurity -- 6.8.4 Case study 4: data science -- 6.8.5 Case study 5: computer science -- 6.8.6 Case study 6: information systems -- 6.8.7 Case study 7: computer engineering -- 6.8.8 Case study 8: information technology -- 6.9 Summary -- References -- Chapter 7 Scientific publishing in computing: beginners guide -- 7.1 Introduction -- 7.2 PhD/MSc thesis, journal and conference proceedings publications -- 7.3 Tips for developing an excellent journal paper -- 7.3.1 Title of the paper -- 7.3.2 Abstract -- 7.3.3 Keywords -- 7.3.4 Introduction -- 7.3.5 Theoretical background -- 7.3.6 Methodology -- 7.3.7 Results and discussion -- 7.3.8 Conclusions -- 7.3.9 References -- 7.4 Common reasons for desk rejection and tips to avoiding it during initial screening -- 7.4.1 Disregard for journal aims and scope -- 7.4.2 Poor grammar, writing and formatting -- 7.4.3 Ethical issue: plagiarism/self-plagiarism -- 7.4.4 Insufficient contribution or lack of novelty -- 7.4.5 Resubmitting a rejected paper to a new journal without modification -- 7.4.6 Duplicate submission -- 7.4.7 Poorly developed paper -- 7.4.8 Poor literature reviews -- 7.4.9 Failure to respond to feedback -- 7.4.10 Lack of relevance to an international audience -- 7.5 Cover letter -- 7.6 Research highlights. 001561457 5058_ $$a7.6.1 Highlights -- 7.7 Supplementary materials -- 7.8 Suggesting reviewers for a researcher's own paper -- 7.9 Quality measurement in computing publications -- 7.9.1 Peer review in the research community -- 7.9.2 Peer review cycle -- 7.9.3 Types of peer review in the research community -- 7.10 Responding to reviewer comments -- Letter of Response to Reviewer Comments -- 7.11 Handling of rejections -- 7.12 Understand different publishing models-open access, subscription, and hybrid -- 7.12.1 Open access journals -- 7.12.2 Subscription journals -- 7.12.3 Hybrid journals -- 7.13 Summary -- References -- Chapter 8 Research ethics in computing -- 8.1 Introduction -- 8.2 Research ethics from the perspective of computing -- 8.2.1 Trust -- 8.2.2 Privacy -- 8.2.3 Consent -- 8.2.4 Inclusion and digital divides -- 8.2.5 Visual ethics -- 8.2.6 Research ethics using wearable cameras -- 8.3 The six domains of research ethics -- 8.4 Research misconduct -- 8.4.1 Plagiarism -- 8.4.2 Disciplinary action against plagiarism -- 8.4.3 Plagiarism types -- 8.4.4 Authorship -- 8.4.5 Conflict of interest -- 8.5 Tips to avoid conflict of interest -- 8.5.1 Participation in editorial board -- 8.6 Avoiding research misconduct -- 8.7 Ethics committees and institutional research boards -- 8.8 Research ethics in the context of disciplines in computing -- 8.8.1 Ethics in software engineering -- 8.8.2 Ethics in computer science -- 8.8.3 Ethics in information system -- 8.8.4 Ethics in cyber security -- 8.8.5 Ethics in data science -- 8.8.6 Ethics in information technology -- 8.8.7 Ethics in computer engineering -- 8.9 Negative research results and tips to get published -- 8.9.1 Publishing negative results -- 8.10 Summary -- References -- Chapter 9 Emerging research trends in computing -- 9.1 Introduction -- 9.2 Emerging research topics in computing -- 9.2.1 Computer science. 001561457 5058_ $$a9.2.2 Computer engineering. 001561457 506__ $$aAccess limited to authorized users. 001561457 520__ $$aA survival manual detailing computing research procedure including problem formulation, dataset sources, methodologies, systematic literature review, ethics, trending topics, academic databases and tips for journal publications, all from the perspective of computing. 001561457 588__ $$aDescription based on publisher supplied metadata and other sources. 001561457 655_0 $$aElectronic books 001561457 77608 $$iPrint version:$$aChiroma, Haruna$$tComputing Research Survival Manual$$dBristol : Institute of Physics Publishing,c2023$$z9780750350181 001561457 830_0 $$aIOP Ebooks Series 001561457 852__ $$bebk 001561457 85640 $$3ProQuest Ebook Central Academic Complete $$uhttps://univsouthin.idm.oclc.org/login?url=https://ebookcentral.proquest.com/lib/usiricelib-ebooks/detail.action?docID=31253207$$zOnline Access 001561457 909CO $$ooai:library.usi.edu:1561457$$pGLOBAL_SET 001561457 980__ $$aBIB 001561457 980__ $$aEBOOK 001561457 982__ $$aEbook 001561457 983__ $$aOnline