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A Guide to Deal With Uncertainties in Software Project Management

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Sensitive and accurate cell tracking system is important to cell motility studies. Recently, researchers have developed several methods for detecting and tracking the living cells. To improve the living cells tracking systems performance and accuracy, we focused on developing a novel technique for image processing. The algorithm we propose presents novel image segmentation and tracking system technique to incorporate the advantages of both Topological Alignments and snakes for more accurate tracking approach. The results demonstrate that the proposed algorithm achieves accurate tracking for detecting and analyzing the mobility of the living cells. The RMSE between the manual and the computed displacement was less than 12% on average. Where the Active Contour method gave a velocity RMSE of less than 11%, improves to less than 8% by using the novel Algorithm. We have achieved better tracking and detecting for the cells, also the ability of the system to improve the low contrast, under and over segmentation which is the most cell tracking challenge problems and responsible for lacking accuracy in cell tracking techniques.
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  International Journal of Computer Science & Information Technology (IJCSIT) Vol 6, No 5, October 2014 DOI:10.5121/ijcsit.2014.6501 1  A    G UIDE TO D EAL  W  ITH U NCERTAINTIES IN S OFTWARE P ROJECT M  ANAGEMENT   Marcelo Marinho 1, 2  , Suzana Sampaio 2 , Telma Lima 3  and Hermano de Moura 1 1 Informatics Center (CIn), Federal University of Pernambuco (UFPE), Recife, PE, Brazil 2 Statistics and Informatics Department (DEINFO), Federal Rural University of Pernambuco (UFRPE), Recife, PE, Brazil 3 Administration Department (DADM), Federal Rural University of Pernambuco (UFRPE), Recife, PE, Brazil  A  BSTRACT    Various project management approaches do not consider the impact that uncertainties have on the project. The identified threats by uncertainty in a projec day-to-day are real and immediate and the expectations in a project are often high. The project manager faces a dilemma: decisions must be made in the present about future situations which are inherently uncertain. The use of uncertainty management in project can be a determining factor for the project success. This paper presents a systematic review about uncertainties management in software projects and a guide is proposed based on the review. It aims to present the best  practices to manage uncertainties in software projects in a structured way including techniques and strategies to uncertainties containment.  K   EYWORDS   Software Project Management; Systematic literature review; Uncertainties in Projects Management; Uncertainty in Software Projects. 1.   I NTRODUCTION   The complexity and challenges involving software development, the use of techniques, practices and project management tools have become common in software engineering. Nowadays it is very common for companies to deal with software development or service provision as a project which needs to be planned, organized, conducted, monitored and controlled. However, IT projects are notoriously disaster-prone, not necessarily because of technological failure but more often due to their inherent complexity. The Standish Group [1] were reporting that only 39% of projects, on average are delivered on time, within budget and with the agreed requirements (therefore those projects perceived as successful). 43% are delivered late, and/or over budget and/or under certain conditions and finally, 18% are cancelled on delivery and never used. In more than a decade, little seems to have changed. Many projects with all the ingredients for success fail. It happens because executives, managers and project teams are not used to evaluating the uncertainties and complexities involved  beforehand, and fail to adapt their management style to the situation [2]. Most projects face restrictions regarding time, costs and scope as well as certain criteria concerning to quality. Additionally, there is a high uncertainty level which can have both positive and negative effects on any project. The traditional approach to project management still emphasises assuring compliance with time, budget and scope constraints. Moreover, in project risk management literature, there is no common understanding as to what uncertainty is [3].  International Journal of Computer Science & Information Technology (IJCSIT) Vol 6, No 5, October 2014 2 Uncertainty has no independent existence, it is not an object that can be identified and eliminated in the same way that a virus which invades a project can. The uncertainty arises naturally from complex situations, being only an inevitable factor of most projects. Uncertainty is simply an ambiguity expression and project indeterminacy in the same way that yellow is a colour attribute of daffodils, but is not a discrete or a separable part of the flower [4]. Aiming to better understand and explore the topic, a systematic review has been prepared. It is a  planned and ideally repeatable way of synthesizing results from the existing body of scientific literature. It proceeds by discovering, evaluating and interpreting all available research relating to a particular question. A systematic review process has three main phases: planning, conducting and reporting the review. The authors developed it with related studies from 1994 to 2013. Guided by research questions, the research aims to investigate: what the best practices to manage the uncertainties in software projects are; what the sources of uncertainty perceived by studies are; and what techniques or strategies are used for the recognition of the problem nature and containment of uncertainties in projects. To answer those core questions, the study dismembered the same three research questions that guided the work:    Research question 1:   How is it possible to reduce the uncertainty level in software  projects?    Research question 2:  What techniques or strategies can help reduce the uncertainties in  project management software?    Research question 3:   What are the sources of uncertainty perceived? This research helps identifying the difficulties and the actions that may minimize the uncertainty effects in projects and how managers and teams may prepare themselves for the challenges in their project scenarios, based on the systematic review which was done. It has been created a uncertainty management guide for software projects to support project managers and teams in their day-by-day so it may reduce the uncertainty level in the project. Besides the introductory section, this paper is structured as follows: Section 2 presents the systematic review process adopted for this study; Section 3 describes a data analysis extracted from the selected studies; in Section 4 the results for each research question are presented and summarized; Section 5 offers an overview of a guide for uncertainty management in software  projects and Section 6 contains the conclusion. 2.   S YSTEMATIC R EVIEW P ROCESS   Systematic literature reviews evaluate evidence in a systematic and transparent way. In a traditional literature review, the research strategy and results evaluation criteria are usually hidden from the reader, which means that the revision may perfectly be done in an unstructured way, ad hoc and evidence that do not support the researcher's preferred hypothesis might be ignored. However, in a systematic literature review the research strategy and the evaluation criteria are explicit and all relevant evidence are included in the evaluation [5],[6],[7]. This section describes the course of each step in the methodology used to carry out this systematic review study. We followed Kitchenham's methodological guideline for systematic reviews [8]. A systematic review protocol was written to describe the plan for the review. Details on the course of these steps are described in the following subsections. 2.1. Search environment Before starting the researches, we decided to create a directory in the cloud. A free web store service was used by all researches to store all artifacts used; for example, electronic versions of  International Journal of Computer Science & Information Technology (IJCSIT) Vol 6, No 5, October 2014 3  publications, generated datasheets, partial reports and other documents. This enabled a total standardization and control of artifacts, so all researchers could access the artifacts as if they were in a local environment, thought they were remote. Furthermore, we developed some datasheets to be used in all phases. The datasheets facilitated the organization of data in many aspects, for example a standard to enumerate publications searched, filters to extract objective information, the access of data of reasons by study and  publications, and more. The datasheets also enabled the future access of data more precisely, where each phase could depend of other phase. After this, we decided create responsibilities to researchers during the study, where the researchers should have responsibilities during to search and in each phase of search. The responsibilities were configuration management, artefacts development, analyzers and synthesizers. The responsibility that was aggregated to all researches was Analyzers. 2.2. Search strategy and search A systematic review incorporates a search strategy for a research aiming to identify and retrieve even the slightest possibility of publications superset which meet the systematic review eligibility criteria. They are conditions to determine if primary studies are about the systematic review research questions. The search results are transformed into in a sequential publication list of the chosen engines. Each resource has a different community with differing interests, using different language and examining different issues. The engines provide different search syntaxes as well. Therefore, different resources might require different search strings. After that, we conducted initial studies for all phases of the major study, that we called “pilot studies”. These were performed to align a phase-to-phase understanding among researchers, all search engines mechanisms test and the adjust of some search terms. Only IEEE Explore search engine showed problems, which were solved with simply adjustments in the search terms for adapting to the search engine mechanism. The study only proceed when the two researchers agreed with the pilots results. The resources used to searches are: IEEEXplore Digital Library (httt://ieeexplore.ieee.org/); ACM Digital Library (http://portal.acm.org); Elsevier ScienceDirect (www.sciencedirect.com); Springer Link (http://link.springer.com). To search all results from sources, all researchers grouped to search publications. The sources (engines) were divided among all. Each researcher was responsible to find results in your engine and, finally catalogued. Then, when was performed the search, where was identified 3044  publications, according to results from engines mechanisms. The searches results were extracted in Bibtex files to merge in the datasheet developed to consolidate all results from all engines. After exclude duplicated results from datasheet, we found 2933 articles to start the first phase. 2.3. Paper selection The idealized selection process has two parts: an initial selection of document research results that could plausibly satisfy the selection criteria, based on a reading of the title and summary of the articles, followed by a final selection of the list of initially selected works that meet the selection criteria, based on a reading of the introduction and conclusion of the work. To reduce  potential bias, the selection process was conducted in pair, in which both researchers individually worked on the inclusion or exclusion of the work and then compared spreadsheets. Divergences were discussed and thus a consensus was reached. If there was not a consensus, a third researcher and should be consulted in case of doubt, the work would be inserted in the list.  International Journal of Computer Science & Information Technology (IJCSIT) Vol 6, No 5, October 2014 4 In the pilot study performed before the first phase beginning, the first ten results in all engines were catalogued and all group read the titles and the abstracts and discussed about them to calibrate comprehension. Other pilot study was performed having more five publications done,  because the researches were not ready to continue after the first pilot. After a reliability agreement, the first phase initiated. Each researcher read the publications` titles and abstracts to select or exclude the publication. together, they discussed about their results to gather them together according to a new datasheet agreement. Out of the initial selection of 2,933 papers, 111 articles were selected to second phase. After the first phase and before second phase, a new pilot study was done. Then, we selected a single article to be read by researchers team aiming a consensus for both. In this phase, the introduction and the conclusion should be read. Similarly to the first phase, each researcher read the articles individually and later discuss its results together. After phase two selection, the researches eliminated 88 and selected 23 papers to be read for data extraction phase. 2.4. Study Quality Assessment During the data extraction phase, the methodological quality of each publication was assessed. One researcher performed the quality assessment. Three factors were assessed as follows, and were each marked yes  or no : Does the publication mention the possibility of selection,  publication, or experimenter bias?;Does the publication mention possible threats to internal validity? and Does the publication mention possible threats to external validity? The quality assessment was made solely on the basis of whether the publication explicitly mentioned these issues. We did not make judgements about whether the publication had a “good” treatment of these issues. The results of the study quality assessment were not used to limit the selection of publications. 2.5. Data Extraction Before this stage, a new pilot was done to calibrate this design. We selected two relevant articles found by the authors (relevant for better quality in defined criteria) and we compared the extraction data performed so far with our data extraction. Thus, a pilot was carried out with an article found by us with one of the 23 selected works. In the data extraction phase, researchers must read the papers selected for extracting structured information according to the datasheet model. We had selected 23 works, but during the extraction phase, the extractors identified 2 articles that showed no relevant citations or possible reasons to be extracted, thus, there were 21 articles. For each publication there were extracted information about the attributes defined in the datasheet. From each study, there was extracted a list of shares, where each share described answer a research question. Or else, each simple sentence that answered one or more research question was considered a quota. We had a total of 147 quotas extracted from 21 studies. These shares were recorded on a datasheet. 2.6. Data Synthesis The data extraction stage was over. The two researchers worked on the synthesis work to generate combinations of quotas with answers of the research questions. There was a good level of inter-rater agreement, differences in opinion were discussed in a joint meeting, and it was easily resolved without the need of involving a third researcher arbitrating, as  planned.

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