A semantic modelling approach to knowledge based statistical software

The topic of this thesis is the development of knowledge based statistical software. The shortcomings of conventional statistical packages are discussed to illustrate the need to develop software which is able to exhibit a greater degree of statistical expertise, thereby reducing the misuse of statistical methods by those not well versed in the art of statistical analysis. Some of the issues involved in the development of knowledge based software are presented and a review is given of some of the systems that have been developed so far. The majority of these have moved away from conventional architectures by adopting what can be termed an expert systems approach. The thesis then proposes an approach which is based upon the concept of semantic modelling. By representing some of the semantic meaning of data, it is conceived that a system could examine a request to apply a statistical technique and check if the use of the chosen technique was semantically sound, i.e. will the results obtained be meaningful. Current systems, in contrast, can only perform what can be considered as syntactic checks. The prototype system that has been implemented to explore the feasibility of such an approach is presented, the system has been designed as an enhanced variant of a conventional style statistical package. This involved developing a semantic data model to represent some of the statistically relevant knowledge about data and identifying sets of requirements that should be met for the application of the statistical techniques to be valid. Those areas of statistics covered in the prototype are measures of association and tests of location.

Content-based VLE designs improve learning efficiency in constructivist statistics education

Background: We introduced a series of computer-supported workshops in our undergraduate statistics courses, in the hope that it would help students to gain a deeper understanding of statistical concepts. This raised questions about the appropriate design of the Virtual Learning Environment (VLE) in which such an approach had to be implemented. Therefore, we investigated two competing software design models for VLEs. In the first system, all learning features were a function of the classical VLE. The second system was designed from the perspective that learning features should be a function of the course's core content (statistical analyses), which required us to develop a specific-purpose Statistical Learning Environment (SLE) based on Reproducible Computing and newly developed Peer Review (PR) technology. Objectives: The main research question is whether the second VLE design improved learning efficiency as compared to the standard type of VLE design that is commonly used in education. As a secondary objective we provide empirical evidence about the usefulness of PR as a constructivist learning activity which supports non-rote learning. Finally, this paper illustrates that it is possible to introduce a constructivist learning approach in large student populations, based on adequately designed educational technology, without subsuming educational content to technological convenience. Methods: Both VLE systems were tested within a two-year quasi-experiment based on a Reliable Nonequivalent Group Design. This approach allowed us to draw valid conclusions about the treatment effect of the changed VLE design, even though the systems were implemented in successive years. The methodological aspects about the experiment's internal validity are explained extensively. Results: The effect of the design change is shown to have substantially increased the efficiency of constructivist, computer-assisted learning activities for all cohorts of the student population under investigation. The findings demonstrate that a content-based design outperforms the traditional VLE-based design. © 2011 Wessa et al.

Does reviewing lead to better learning and decision making? Answers from a randomized stock market experiment

Background - The literature is not univocal about the effects of Peer Review (PR) within the context of constructivist learning. Due to the predominant focus on using PR as an assessment tool, rather than a constructivist learning activity, and because most studies implicitly assume that the benefits of PR are limited to the reviewee, little is known about the effects upon students who are required to review their peers. Much of the theoretical debate in the literature is focused on explaining how and why constructivist learning is beneficial. At the same time these discussions are marked by an underlying presupposition of a causal relationship between reviewing and deep learning. Objectives - The purpose of the study is to investigate whether the writing of PR feedback causes students to benefit in terms of: perceived utility about statistics, actual use of statistics, better understanding of statistical concepts and associated methods, changed attitudes towards market risks, and outcomes of decisions that were made. Methods - We conducted a randomized experiment, assigning students randomly to receive PR or non–PR treatments and used two cohorts with a different time span. The paper discusses the experimental design and all the software components that we used to support the learning process: Reproducible Computing technology which allows students to reproduce or re–use statistical results from peers, Collaborative PR, and an AI–enhanced Stock Market Engine. Results - The results establish that the writing of PR feedback messages causes students to experience benefits in terms of Behavior, Non–Rote Learning, and Attitudes, provided the sequence of PR activities are maintained for a period that is sufficiently long.

Role of the educator in social software initiatives in Further and Higher Education:a conceptualisation and research agenda

Higher and further education institutions are increasingly using social software tools to support teaching and learning. A growing body of research investigates the diversity of tools and their range of contributions. However, little research has focused on investigating the role of the educator in the context of a social software initiative, even though the educator is critical for the introduction and successful use of social software in a course environment. Hence, we argue that research on social software should place greater emphasis on the educators, as their roles and activities (such as selecting the tools, developing the tasks and facilitating the student interactions on these tools) are instrumental to most aspects of a social software initiative. To this end, we have developed an agenda for future research on the role of the educator. Drawing on role theory, both as the basis for a systematic conceptualization of the educator role and as a guiding framework, we have developed a series of concrete research questions that address core issues associated with the educator roles in a social software context and provide recommendations for further investigations. By developing a research agenda we hope to stimulate research that creates a better understanding of the educator’s situation and develops guidelines to help educators carry out their social software initiatives. Considering the significant role an educator plays in the initiation and conduct of a social software initiative, our research agenda ultimately seeks to contribute to the adoption and efficient use of social software in the educational domain.

ERP-rendszerek a számítási felhőben (cloud computing) - A felhőtechnikával összefüggő új ERP-kiválasztási kritériumok elemzése (ERP systems within cloud – Criteria for selection of ERP systems in a cloud environment)

Néhány éve vonult be a köztudatba a cloud computing fogalom, mely ma már a szakirodalomban és az informatikai alkalmazásokban is egyre nagyobb teret foglal el. Ez az új IT-technológia a számítási felhő számítástechnikai szolgáltatásaihoz kapcsolódó ERP-rendszerek szabványosítását, elterjedését eredményezi. A szerzők cikkükben áttekintést adnak a cloud computing mai helyzetéről és a számítási felhőben működő adatfeldolgozó rendszerekkel (kiemelten ERP) kapcsolatos felhasználói elvárásokról, illetve kezdeti, németországi alkalmazási tapasztalatokról. Külön tárgyalják az ERP-rendszerek új kiválasztási céljait és kritériumait, melyek a felhőkörnyezet speciális lehetőségei miatt alakultak ki. _____ The concept of ‘Cloud’ as an IT notion emerged in the past years and proliferated within the business and IT professional community. The concept of cloud gained awareness both in the professional and scientific literature and in the practice of IT/IS world. The cloud has a profound impact on the Business Information Systems, especially on ERP systems. Indirectly, the cloud leads to a massive standardization on ERP systems and their services. In this paper, the authors provide a literature overview about the current situation of Cloud Computing and the requirements established by end-users against the other data processing facilities and systems, outstandingly the ERP systems. The majority of investigated cases are based on samples from Germany. Furthermore, the initial experiences of application are discussed. Separately, the recent selection objectives and criteria for ERP systems are investigated that came into existence because the appearance of Cloud in the IT environment.

Cascade failure analysis of power grid using new load distribution law and node removal rule

The work is supported in part by NSFC (Grant no. 61172070), IRT of Shaanxi Province (2013KCT-04), EPSRC (Grant no.Ep/1032606/1).

Cascade failure analysis of power grid using new load distribution law and node removal rule

The work is supported in part by NSFC (Grant no. 61172070), IRT of Shaanxi Province (2013KCT-04), EPSRC (Grant no.Ep/1032606/1).

The Importance of Learning History and Philosophy of Computing

Computers have invaded our offices, our homes, cars and coffee-pots; they have become ubiquitous. However, the advance of computing technologies is associated with an increasing lack of “visibility” of the underlying software and hardware technologies. While we use and accept the computer, we neither know its history nor functionality. In this paper, we argue that this is not a healthy situation. Also, recruitment onto UK Computing degree courses is steadily falling; these courses are appearing less attractive to school-leavers. This may be associated with the increasing ubiquity. In this paper we reflect on an MSc. module of instruction, Concepts and Philosophy of Computing, and a BSc. module Computer Games Development developed at the University of Worcester which address these issues. We propose that the elements of these modules form a necessary part of the education of all citizens, and we suggest how this may be realized. We also suggest how to re-enthuse our youth about computing as a discipline and halt the drop in recruitment.

The Importance of Learning History and Philosophy of Computing

Computers have invaded our offices, our homes, cars and coffee-pots; they have become ubiquitous. However, the advance of computing technologies is associated with an increasing lack of “visibility” of the underlying software and hardware technologies. While we use and accept the computer, we neither know its history nor functionality. In this paper, we argue that this is not a healthy situation. Also, recruitment onto UK Computing degree courses is steadily falling; these courses are appearing less attractive to school-leavers. This may be associated with the increasing ubiquity. In this paper we reflect on an MSc. module of instruction, Concepts and Philosophy of Computing, and a BSc. module Computer Games Development developed at the University of Worcester which address these issues. We propose that the elements of these modules form a necessary part of the education of all citizens, and we suggest how this may be realized. We also suggest how to re-enthuse our youth about computing as a discipline and halt the drop in recruitment.

Early investigation towards defining and measuring sustainability as a quality attribute in software systems

Sustainability in software system is still a new practice that most software developers and companies are trying to incorporate into their software development lifecycle and has been largely discussed in academia. Sustainability is a complex concept viewed from economic, environment and social dimensions with several definitions proposed making sometimes the concept of sustainability very fuzzy and difficult to apply and assess in software systems. This has hindered the adoption of sustainability in the software industry. A little research explores sustainability as a quality property of software products and services to answer questions such as; How to quantify sustainability as a quality construct in the same way as other quality attributes such as security, usability and reliability? How can it be applied to software systems? What are the measures and measurement scale of sustainability? The Goal of this research is to investigate the definitions, perceptions and measurement of sustainability from the quality perspective. Grounded in the general theory of software measurement, the aim is to develop a method that decomposes sustainability in factors, criteria and metrics. The Result is a method to quantify and access sustainability of software systems while incorporating management and users concern. Conclusion: The method will empower the ability of companies to easily adopt sustainability while facilitating its integration to the software development process and tools. It will also help companies to measure sustainability of their software products from economic, environmental, social, individual and technological dimension.

Contributions to 3D Data Registration and Representation

Nowadays, new computers generation provides a high performance that enables to build computationally expensive computer vision applications applied to mobile robotics. Building a map of the environment is a common task of a robot and is an essential part to allow the robots to move through these environments. Traditionally, mobile robots used a combination of several sensors from different technologies. Lasers, sonars and contact sensors have been typically used in any mobile robotic architecture, however color cameras are an important sensor due to we want the robots to use the same information that humans to sense and move through the different environments. Color cameras are cheap and flexible but a lot of work need to be done to give robots enough visual understanding of the scenes. Computer vision algorithms are computational complex problems but nowadays robots have access to different and powerful architectures that can be used for mobile robotics purposes. The advent of low-cost RGB-D sensors like Microsoft Kinect which provide 3D colored point clouds at high frame rates made the computer vision even more relevant in the mobile robotics field. The combination of visual and 3D data allows the systems to use both computer vision and 3D processing and therefore to be aware of more details of the surrounding environment. The research described in this thesis was motivated by the need of scene mapping. Being aware of the surrounding environment is a key feature in many mobile robotics applications from simple robotic navigation to complex surveillance applications. In addition, the acquisition of a 3D model of the scenes is useful in many areas as video games scene modeling where well-known places are reconstructed and added to game systems or advertising where once you get the 3D model of one room the system can add furniture pieces using augmented reality techniques. In this thesis we perform an experimental study of the state-of-the-art registration methods to find which one fits better to our scene mapping purposes. Different methods are tested and analyzed on different scene distributions of visual and geometry appearance. In addition, this thesis proposes two methods for 3d data compression and representation of 3D maps. Our 3D representation proposal is based on the use of Growing Neural Gas (GNG) method. This Self-Organizing Maps (SOMs) has been successfully used for clustering, pattern recognition and topology representation of various kind of data. Until now, Self-Organizing Maps have been primarily computed offline and their application in 3D data has mainly focused on free noise models without considering time constraints. Self-organising neural models have the ability to provide a good representation of the input space. In particular, the Growing Neural Gas (GNG) is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation. However, this type of learning is time consuming, specially for high-dimensional input data. Since real applications often work under time constraints, it is necessary to adapt the learning process in order to complete it in a predefined time. This thesis proposes a hardware implementation leveraging the computing power of modern GPUs which takes advantage of a new paradigm coined as General-Purpose Computing on Graphics Processing Units (GPGPU). Our proposed geometrical 3D compression method seeks to reduce the 3D information using plane detection as basic structure to compress the data. This is due to our target environments are man-made and therefore there are a lot of points that belong to a plane surface. Our proposed method is able to get good compression results in those man-made scenarios. The detected and compressed planes can be also used in other applications as surface reconstruction or plane-based registration algorithms. Finally, we have also demonstrated the goodness of the GPU technologies getting a high performance implementation of a CAD/CAM common technique called Virtual Digitizing.

Classifying And Predicting Software Security Vulnerabilities based on Reproducibility

Security defects are common in large software systems because of their size and complexity. Although efficient development processes, testing, and maintenance policies are applied to software systems, there are still a large number of vulnerabilities that can remain, despite these measures. Some vulnerabilities stay in a system from one release to the next one because they cannot be easily reproduced through testing. These vulnerabilities endanger the security of the systems. We propose vulnerability classification and prediction frameworks based on vulnerability reproducibility. The frameworks are effective to identify the types and locations of vulnerabilities in the earlier stage, and improve the security of software in the next versions (referred to as releases). We expand an existing concept of software bug classification to vulnerability classification (easily reproducible and hard to reproduce) to develop a classification framework for differentiating between these vulnerabilities based on code fixes and textual reports. We then investigate the potential correlations between the vulnerability categories and the classical software metrics and some other runtime environmental factors of reproducibility to develop a vulnerability prediction framework. The classification and prediction frameworks help developers adopt corresponding mitigation or elimination actions and develop appropriate test cases. Also, the vulnerability prediction framework is of great help for security experts focus their effort on the top-ranked vulnerability-prone files. As a result, the frameworks decrease the number of attacks that exploit security vulnerabilities in the next versions of the software. To build the classification and prediction frameworks, different machine learning techniques (C4.5 Decision Tree, Random Forest, Logistic Regression, and Naive Bayes) are employed. The effectiveness of the proposed frameworks is assessed based on collected software security defects of Mozilla Firefox.

Comparison between 5G private network and Wifi6 in industrial environment

Industry 4.0 refers to the 4th industrial revolution and at its bases, we can see the digitalization and the automation of the assembly line. The whole production process has improved and evolved thanks to the advances made in networking, and AI studies, which include of course machine learning, cloud computing, IoT, and other technologies that are finally being implemented into the industrial scenario. All these technologies have in common a need for faster, more secure, robust, and reliable communication. One of the many solutions for these demands is the use of mobile communication technologies in the industrial environment, but which technology is better suited for these demands? Of course, the answer isn’t as simple as it seems. The 4th industrial revolution has a never seen incomparable potential with respect to the previous ones, every factory, enterprise, or company have different network demands, and even in each of these infrastructures, the demands may diversify by sector, or by application. For example, in the health care industry, there may be e a need for increased bandwidth for the analysis of high-definition videos or, faster speeds in order to have analytics occur in real-time, and again another application might be higher security and reliability to protect patients’ data. As seen above, choosing the right technology for the right environment and application, considers many things, and the ones just stated are but a speck of dust with respect to the overall picture. In this thesis, we will investigate a comparison between the use of two of the available technologies in use for the industrial environment: Wi-Fi 6 and 5G Private Networks in the specific case of a steel factory.

Benthic macrofauna structure in the northeast area of Todos os Santos Bay, Bahia State, Brazil: patterns of spatial and seasonal distribution

Structure of intertidal and subtidal benthic macrofauna in the northeastern region of Todos os Santos Bay (TSB), northeast Brazil, was investigated during a period of two years. Relationships with environmental parameters were studied through uni-and multivariate statistical analyses, and the main distributional patterns shown to be especially related to sediment type and content of organic fractions (Carbon, Nitrogen, Phosphorus), on both temporal and spatial scales. Polychaete annelids accounted for more than 70% of the total fauna and showed low densities, species richness and diversity, except for the area situated on the reef banks. These banks constitute a peculiar environment in relation to the rest of the region by having coarse sediments poor in organic matter and rich in biodetritic carbonates besides an abundant and diverse fauna. The intertidal region and the shallower area nearer to the oil refinery RLAM, with sediments composed mainly of fine sand, seem to constitute an unstable system with few highly dominant species, such as Armandia polyophthalma and Laeonereis acuta. In the other regions of TSB, where muddy bottoms predominated, densities and diversity were low, especially in the stations near the refinery. Here the lowest values of the biological indicators occurred together with the highest organic compound content. In addition, the nearest sites (stations 4 and 7) were sometimes azoic. The adjacent Caboto, considered as a control area at first, presented low density but intermediate values of species diversity, which indicates a less disturbed environment in relation to the pelitic infralittoral in front of the refinery. The results of the ordination analyses evidenced five homogeneous groups of stations (intertidal; reef banks; pelitic infralittoral; mixed sediments; Caboto) with different specific patterns, a fact which seems to be mainly related to granulometry and chemical sediment characteristics.

Influência da proteína de soja e dos exercícios com pesos sobre o gasto energético de repouso de mulheres na pós-menopausa

OBJETIVO: Analisar a influência da ingestão alimentar de proteína da soja e dos exercícios com pesos sobre o gasto energético de repouso (GER) de mulheres na pós-menopausa. MÉTODOS: Ensaio clínico, 16 semanas, envolvendo 60 mulheres, 59 (7) anos, distribuídas em quatro grupos: G1 (proteína da soja e exercício), G2 (placebo e exercício), G3 (proteína da soja e sem exercício) e G4 (placebo e sem exercício). A proteína da soja e o placebo (maltodextrina) foram distribuídos, aleatoriamente, sob a forma de pó, na porção de 25 gramas/dia. Foram 10 exercícios com pesos, realizados em três sessões semanais, com 3 séries de 8-12 repetições cada, carga de 60 por cento-80 por cento de uma repetição máxima (RM). O GER foi calculado a partir do O2 e CO2, obtidos por calorimetria indireta (Quinton-QMC®), durante 30 minutos, sob temperatura e umidade controladas. Na análise estatística foi utilizada ANOVA, teste T de Student e regressão múltipla, por meio do software Stata 9.2, α<0,05. RESULTADOS: As mulheres apresentaram homogeneidade em todas as variáveis do estudo. Houve aumento, significante, do GER (p<0,05) no G1 (158 kcal/dia) e G2 (110 kcal/dia), correspondente a 17 por cento e 9 por cento, respectivamente, enquanto, o G4, diminuição em 4 por cento (p<0,05). CONCLUSÃO: Exercícios com pesos são determinantes para o aumento do gasto energético de repouso, de mulheres na pós-menopausa, podendo ser potencializado pela ingestão de proteína da soja