The Analysis of the Freight Rates for the Oil Ships with Big Sizes

The purpose of this work is to approach the evolution of the freight rates for the oil ships of big sizes, that is of those with 200,000 dwt. In this field we intend to analyse the seasonality of the freight rates for the transport of the oil from Persian Gulf to other four destinations, that is: Japan, Korea Republic, Europe and Caribbean/the East Coast of the North America. This patchy evolution during an year is for sure determined by the capacity of processing and stockage from those zones, but this will be also reflected in the levels of the freight. As the analysed period also includes the present crisis which the world economy is passing through, we wish stand the sense of reflecting this on the transport services market. Otherwise, we will analyse the trends of the transport and the seasonality of the transport of this segment of ships. The research of these aspects will be done with the help of decomposition of the time series, with Minitab software. &nbsp

What is the Connection Between Issues, Bugs, and Enhancements? (Lessons Learned from 800+ Software Projects)

Agile teams juggle multiple tasks so professionals are often assigned to multiple projects, especially in service organizations that monitor and maintain a large suite of software for a large user base. If we could predict changes in project conditions changes, then managers could better adjust the staff allocated to those projects.This paper builds such a predictor using data from 832 open source and proprietary applications. Using a time series analysis of the last 4 months of issues, we can forecast how many bug reports and enhancement requests will be generated next month. The forecasts made in this way only require a frequency count of this issue reports (and do not require an historical record of bugs found in the project). That is, this kind of predictive model is very easy to deploy within a project. We hence strongly recommend this method for forecasting future issues, enhancements, and bugs in a project.Comment: Accepted to 2018 International Conference on Software Engineering, at the software engineering in practice track. 10 pages, 10 figure

Software evolution prediction using seasonal time analysis: a comparative study

Prediction models of software change requests are useful for supporting rational and timely resource allocation to the evolution process. In this paper we use a time series forecasting model to predict software maintenance and evolution requests in an open source software project (Eclipse), as an example of projects with seasonal release cycles. We build an ARIMA model based on data collected from Eclipse’s change request tracking system since the project’s start. A change request may refer to defects found in the software, but also to suggested improvements in the system under scrutiny. Our model includes the identification of seasonal patterns and tendencies, and is validated through the forecast of the change requests evolution for the next 12 months. The usage of seasonal information significantly improves the estimation ability of this model, when compared to other ARIMA models found in the literature, and does so for a much longer estimation period. Being able to accurately forecast the change requests’ evolution over a fairly long time period is an important ability for enabling adequate process control in maintenance activities, and facilitates effort estimation and timely resources allocation. The approach presented in this paper is suitable for projects with a relatively long history, as the model building process relies on historic data

Empirical studies of open source evolution

Copyright @ 2008 Springer-VerlagThis chapter presents a sample of empirical studies of Open Source Software (OSS) evolution. According to these studies, the classical results from the studies of proprietary software evoltion, such as Lehman’s laws of software evolution, might need to be revised, if not fully, at least in part, to account for the OSS observations. The book chapter also summarises what appears to be the empirical status of each of Lehman’s laws with respect to OSS and highlights the threads to validity that frequently emerge in these empirical studies. The chapter also discusses related topics for further research

An Empirical Analysis of Vulnerabilities in Python Packages for Web Applications

This paper examines software vulnerabilities in common Python packages used particularly for web development. The empirical dataset is based on the PyPI package repository and the so-called Safety DB used to track vulnerabilities in selected packages within the repository. The methodological approach builds on a release-based time series analysis of the conditional probabilities for the releases of the packages to be vulnerable. According to the results, many of the Python vulnerabilities observed seem to be only modestly severe; input validation and cross-site scripting have been the most typical vulnerabilities. In terms of the time series analysis based on the release histories, only the recent past is observed to be relevant for statistical predictions; the classical Markov property holds.Comment: Forthcoming in: Proceedings of the 9th International Workshop on Empirical Software Engineering in Practice (IWESEP 2018), Nara, IEE

An adaptive stigmergy-based system for evaluating technological indicator dynamics in the context of smart specialization

Regional innovation is more and more considered an important enabler of welfare. It is no coincidence that the European Commission has started looking at regional peculiarities and dynamics, in order to focus Research and Innovation Strategies for Smart Specialization towards effective investment policies. In this context, this work aims to support policy makers in the analysis of innovation-relevant trends. We exploit a European database of the regional patent application to determine the dynamics of a set of technological innovation indicators. For this purpose, we design and develop a software system for assessing unfolding trends in such indicators. In contrast with conventional knowledge-based design, our approach is biologically-inspired and based on self-organization of information. This means that a functional structure, called track, appears and stays spontaneous at runtime when local dynamism in data occurs. A further prototyping of tracks allows a better distinction of the critical phenomena during unfolding events, with a better assessment of the progressing levels. The proposed mechanism works if structural parameters are correctly tuned for the given historical context. Determining such correct parameters is not a simple task since different indicators may have different dynamics. For this purpose, we adopt an adaptation mechanism based on differential evolution. The study includes the problem statement and its characterization in the literature, as well as the proposed solving approach, experimental setting and results.Comment: mail: [email protected]

A virtual world of paleontology

Computer-aided visualization and analysis of fossils has revolutionized the study of extinct organisms. Novel techniques allow fossils to be characterized in three dimensions and in unprecedented detail. This has enabled paleontologists to gain important insights into their anatomy, development, and preservation. New protocols allow more objective reconstructions of fossil organisms, including soft tissues, from incomplete remains. The resulting digital reconstructions can be used in functional analyses, rigorously testing long-standing hypotheses regarding the paleobiology of extinct organisms. These approaches are transforming our understanding of long-studied fossil groups, and of the narratives of organismal and ecological evolution that have been built upon them

Search based software engineering: Trends, techniques and applications

© ACM, 2012. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version is available from the link below.In the past five years there has been a dramatic increase in work on Search-Based Software Engineering (SBSE), an approach to Software Engineering (SE) in which Search-Based Optimization (SBO) algorithms are used to address problems in SE. SBSE has been applied to problems throughout the SE lifecycle, from requirements and project planning to maintenance and reengineering. The approach is attractive because it offers a suite of adaptive automated and semiautomated solutions in situations typified by large complex problem spaces with multiple competing and conflicting objectives. This article provides a review and classification of literature on SBSE. The work identifies research trends and relationships between the techniques applied and the applications to which they have been applied and highlights gaps in the literature and avenues for further research.EPSRC and E

Estimativa de expoentes de Hurst para séries temporais de imagens NDVI / MODIS em regiões de pastagens da Zona da Mata de Minas Gerais.

The Zona da Mata region in Minas Gerais State is configured in a traditional dairy production chain, whose grasslands have subtle dynamics in their phenology, and currently there is a strong concern regarding degradation and vegetative development trends. The Hurst exponents (H) are a potential tool to describe the evolution scale of time series, sensitive to short- and long-term memory. This study was aimed at developing an algorithm in the GIS that presents reliable results of the Hurst exponents for NDVI from MODIS imagery, using binary blocks method applied to R/S analysis (range rescaled) in the Gretl, an econometrics and time series software. We produced H values identical to those estimated H for time series of pixels extracted from the satellite imagery dataset, processed in the Gretl. In order to estimate and evaluate the area of occurrence of the H exponents classes for imagery over time, we performed a processing highlighting the slightly trend of low sustainability of grasslands (H class 0.52 to 0.65), with 833,768 ha (68.71%), and moderate sustainability or persistence (H class 0.65 to 0.70), with 162,068 ha. We emphasized the fact that the estimated class between 0.37 and 0.52 resulted in a considerable area of grasslands, with about 135,000 ha, possibly indicating that this region faces remarkable changes, such as degradation, crop rotation, fallow or others land use changes. Despite the long processing time to estimate H, we highlight the usefulness of this methodology for detection of change trends in the short- and long-term periods