Chapter 12 - Causes and Effects

This paper is about the development of problem solving method to identify failures in inconel 718 mainly applied in the subsea environment. A3 analysis with support from fishbone diagram and 5 whys analysis techniques were introduced to identify the actual cause of failures. Upon identification of the actual cause of failure, improvement actions were taken to eliminate the actual cause. In this research, the identification of the actual cause of failure related with the Inconel 718 fasteners that were used for Methanol Injection Tree Valve (MITV) was performed. Lab analysis on fresh and failure fasteners was performed by comparing the mechanical properties, chemical composition and microstructure analysis. The data was then compared to understand the characteristics of the failure. Future state and target in A3 stage required a mitigation action to eliminate the cause of failure. This was performed by conducting new material analysis i.e. L7M fasteners for future reference. Standard template for subsea's problem solving method was established upon completion the analysis for future use.

This study is a survey to evaluate the flexible pavement conditions to determine and specify the types of the failures in the pavement for the selected highway. It is very significant to evaluate and identify the causes of the flexible pavement failures and select the proper and best treatment and maintenance type. The study had two major and critical goals which covered by considering the following three tasks; the first was the visual evaluation and inspection of existing flexible pavement conditions including the failures, the second to determine and find out the actual causes of these failures in the pavement, and the third is to select the most and effective treatments and maintenance types. As a case study, Khanaqin-Kalar 2-way 2-lane rural highway was selected for evaluation and inspection purposes. The field evaluation works were achieved on the existing flexible pavement conditions of the selected rural highway. The results were most of the damages and failures in the pavement are serious and extreme surface deformation, cracks, disintegration, and surface defects. These damages and failures are caused by fatigue and other types of failures resulted from the movement of heavy vehicles and trucks, poor drainage design, unsuitable pavement layers thickness design, and improper pavement mix design and selected materials.

Reports the results of an experimental investigation to examine the influence of controlled defects on the long-term degradation mechanisms and life expectancy of polyethylene insulation. Spherical conducting beads have been introduced into low-density polyethylene (LDPE) samples which have been aged at three different frequencies. Comparisons have also been made with control samples without any conducting beads. That failure of the specimens did not occur at the site of deliberately introduced conducting and nonconducting inclusions was unexpected. This has highlighted the problem of identifying the actual cause of failure in the LDPE samples currently under test. >

With the fast-growing sector of information technology in digitizing societies, the attraction and education of qualified recruits in computer science becomes a key task of tertiary education. Considering the high dropout rates and the continuing gender gap in computer science, the current study builds on the “leaky pipeline” phenomenon of women in STEM (science, technology, engineering, and mathematics) by investigating belonging uncertainty in computer science as a predictor of students’ dropout intentions. In a study with first-semester computer science students (N = 217) at two time points, we tested the hypotheses that female students experience a greater belonging uncertainty than male students and that this belonging uncertainty is predictive of students’ dropout intentions. Furthermore, we explored whether belonging uncertainty is a more relevant predictor of female than male students’ intentions to drop out of computer science. In line with our predictions, our results show that female students experienced greater uncertainty about their belonging within the domain of computer science than male students and that belonging uncertainty significantly predicted students’ dropout intentions above and beyond the pertinent predictors academic self-efficacy, expectancy of success, perceived future utility value of the subject, and previous academic performance. Belonging uncertainty, however, was a relevant predictor of both female and male computer science students’ dropout intentions.

The computer science education research community has thought deeply about how students learn computational thinking (CT) as it relates to other domains of computer science (CS; e.g. programming) and core content areas (STEM, humanities), but less work has examined the role of CT in pathways to computer science for K-5 teachers. This panel examines the experiences of practitioners - educators, administrators, and curriculum designers--who have both experienced and supported others in incorporating CT in elementary school settings as a pathway to or component of computer science education. All panelists have worked with teachers not previously trained to teach CS and have encountered the many opportunities and difficulties of bringing CS to in-service teachers. They will reflect on the multiple ways educators grapple with CT: as an entry point to computer science, as a way to enrich core disciplines, and as a way to support equitable practice - for example, several of the panelists have experiences leveraging CT and other domains of CS to support the expression and development of emergent bilingual students. The panel will explore ways in which CT and its associated language and strategies for problem solving may provide a particularly helpful onramp to CS generally, including integration with other disciplines and with language about academic skills more generally.

Constructivist approaches to computer science education emphasize that as well as knowledge, thinking skills and processes are involved in active knowledge construction. K-12 computer science curricula must not be based on fashions and trends, but on contents and processes that are observable in various domains of computer science, that can be taught at every intellectual level, that will stay relevant in the longer term, and that are related to everyday language and/or thinking. Only recently, two empirically determined lists, one of central content concepts (algorithm, computer, data, system, etc.) and another of central process concepts (problem solving and problem posing, analyzing, classifying, generalizing, etc.), have become available for computer science education. This paper tackles the problem of finding content and process concepts to be taught in combination. Computer science experts are surveyed in order to identify combinations of content and process concepts-so-called blocks-that are relevant to computer science education. By using cluster analyses, 15 central blocks for teaching computer science in schools are determined. The results of this study may serve as a reference system for the systematic design of instruction in K-12 computer science education.

The knowledge graph, as a significant branch of Library and Information Science, has also become a vital part of Computer Science. In a bid to reveal the research trend and hot topics of the knowledge graph domain, this paper collected latest data about literature on knowledge graphs from SCI-Expanded and EI Compendex database. This paper took advantage of Citespace for visualization analyses of data, which discerned the research topics, hot issues and theme changes of the knowledge graph domain over time. Through analyses, we conclude that the knowledge graph has developed greatly in both Library and Information Science and Computer Science. In Library and Information Science domain, researches focus on the issues like the plotting of knowledge graphs and visualization of knowledge. In Computer Science domain, hot issues are the techniques of constructing knowledge graphs, which include entity recognition, knowledge integration, etc., and their applications in Semantic Web. Among all the research topics, the domain knowledge graph is one of the paramount research trends. Compared with previous researches, this paper keeps up with the times and can reveal the theme evolution of researches on knowledge graphs more precisely.

With regard to road safety issues, a deep understanding of the driver as a logic system is crucial to predict the most probable behavior according to the contextual elements. Knowledge and data about human functional abilities exist. But the problem is to organize and structure them. The development of a computational approach in driver modelization is addressed. In the first part, a brief historical overview is presented of available driver models in ergonomics and psychological areas, and the distinction between predictive and explicative models in an implementation perspective is the focus. In the second part, the computational aspect of the work is described, along with the software concepts, the cognitive modeling needs, and the implementation choices. Object-oriented techniques were chosen because they provide a modular overview of the general system and offer a convenient representation of cognitive processes. Object-oriented formalism, in particular object modeling technique diagrams, acts as a bridge between the two domains of computer science and the human sciences. The objective is to determine whether it is possible to implement reliably a driver model using the techniques from artificial intelligence and based on the theoretical knowledge from cognitive sciences research. This attempt to establish links between different scientific domains, requiring a common tool, is a challenge. A first step of a work that will have to be developed in a long-term time scale, taking into account its quite ambitious objective, is described.

Nowadays information security and in particular web security becomes a key knowledge domain in computer science and engineering education. Because of the rapid change and development of web and network technologies, social network sites, which support social interactions between course instructor and students can be a good venue supporting the teaching and learning of information security. This paper examines an online social network formed over Facebook as a course discussion forum of course for web security. A number of interesting patterns and findings were identified from social network analyses, which offer reflections and suggestions to engineering educators through a practical implementation of online learning community.

Centrality measures have been proved to be a salient computational science tool for analyzing networks in the last two to three decades aiding many problems in the domain of computer science, economics, physics, and sociology. With increasing complexity and vividness in the network analysis problems, there is a need to modify the existing traditional centrality measures. Weighted centrality measures usually consider weights on the edges and assume the weights on the nodes to be uniform. One of the main reasons for this assumption is the hardness and challenges in mapping the nodes to their corresponding weights. In this paper, we propose a way to overcome this kind of limitation by hybridization of the traditional centrality measures. The hybridization is done by taking one of the centrality measures as a mapping function to generate weights on the nodes and then using the node weights in other centrality measures for better complex ranking.

In this chapter, we deal with a quite recent and important domain in Computer Science: Bioinformatics. In concrete, we solve the DNA fragment assembly problem using a parallel GA. DNA fragment assembly is a technique that attempts to reconstruct the original DNA sequence from a large number of fragments, each one being several hundred base-pairs (bps) long. The DNA fragment assembly is needed because current technology, such as gel electrophoresis, cannot directly and accurately sequence DNA molecules longer than a few thousands bases. However, most real genomes are much longer. For example, a human DNA is about 3.2 billion bases in length and cannot be read at once.

Internet of things has emerged to be a ubiquitous technology which has been proved to be a boon for the field of computer science. Many of the domains of computer science can be enhanced by the novel technology of IoT. With the advent of IoT, the need for unique identity to each IoT device came to the scene. Since IoT is comparatively a new domain in computer science and also involves the technology of embedded systems, there comes the necessity to focus on a secure architecture for IoT. This paper will focus on the enhancement of security in IoT by merging the technology of blockchain with it. IoT currently has a centralized architecture and has the security issues but blockchain is a decentralized and distributed platform and implementing blockchain in IoT thus resolves many security threats and vulnerabilities. Furthermore, the issues of data distortion can also be resolved since blockchain includes cryptographic algorithms at the backend. IoT with integrated blockchain can be competent of decentralization, autonomy and trustworthiness. The coordination between millions of IoT devices which in future is also going to increase rapidly can be tracked with high security of blockchain. This paper explores efficiency of blockchain in IoT application. Along with this paper discusses some case studies which is based on blockchain based IoT. There are some steps are described which will give a theoretical idea about how to build a blockchain in an IoT system.

Running experiments on modern systems like supercomput-ers, cloud infrastructures or P2P networks became very complex, both technically and methodologically. It is difficult to rerun an experiment or understand its results even with technical background on the technology and methods used. Storing the provenance of experimental data, i.e., storing information about how the results were produced, proved to be a powerful tool to address similar problems in computational natural sciences. In this paper, we (1) survey provenance collection in various domains of computer science, (2) introduce a new classification of prove-nance types, and (3) sketch a design of a provenance system inspired by this classification.

Does animation play a role in multimedia learning? Animation in multimedia is said to be beneficial to learning especially when the learning material demands visual movements. The emergence of 3-Dimensional animated visuals has extended the presentation mode in multimedia learning. It is said that animated visuals in a 3-D representation not only possess motivational value that promotes positive attitudes toward instruction but also facilitate learning when the subject matter requires dynamic motion and 3-D visual cue. The field of computer science, especially in operating systems concepts uses an array of abstract concepts such as virtual memory, paging, fragmentations etc to describe and explain the underlying processes. Various studies together with our own observations strongly indicate that students often find these concepts difficult to learn, as they cannot easily be demonstrated. This study investigates the effects of animation on student understanding when studying a complex domain in computer science, that is, the subject of memory management concepts in operating systems. A multimedia learning system was developed in two different versions: 2-D animation and 3-D animation. A hundred and one students took part in this study and they were assigned into one of these groups. All the students who took part in this experiment had low prior knowledge in this subject and after viewing the treatment, they were asked to take a test which tested them for recall and transfer knowledge. This test was used to determine if, in fact, improved learning actually occurred and which version of the animation produced the better outcome. Initial analysis of results indicates no statistical difference between the scores for the two versions and suggests that animations, by themselves, do not necessarily improve student understanding.Keywordsmultimedia learninganimation3-D animationmemory management

Human-centered automation for resilient nuclear power plant outage control