Miracle-dz/UniFAR-FTUs huggingface dataset:
A Proposal of In-Service Teacher Training Approach for Computer Science Teachers

Recently, there has been growing interest among practitioners and scientists in teaching children computer programming languages. The international efforts to raise generations who produce technologies are supported at the national level in Turkey too. Programming language education is included beginning from secondary school curricula of computer science education. However, it can be mentioned that up-to-date methodological and pedagogical requirements of the courses are not adequately researched. Therefore, the primary aim of the study is to share innovative methods regarding programming education processes with middle school computer science teachers. This paper presents the details of a project conducted to design an in-service training model for computer science teachers and funded by the Scientific and Technological Research Council of Turkey (TUBITAK) with the project number of 116B298. During the training period, up-to-date methodology and technologies were presented in workshops with an integrated approach. At the end of the courses, the participants’ development and the efficiency of the activities were investigated based on the analyses of qualitative and quantitative data and positive results about the content of proposed in-service teacher training methodology were yielded.
CIRCULAR ECONOMY DRIVEN INNOVATIONS WITHIN BUSINESS MODELS OF RURAL SMEs

The competitiveness of rural SMEs is low due to economic inefficiency and the lack of innovations. The main challenges faced by rural SMEs are the limited scale, the distance form larger sales markets, R&D and business support institutions, and the lack of innovative spirit. The circular and bio-economies are shaping the rural SMEs towards the environmentally friendly and eco-efficient production, the minimization of the generation of waste and less use of natural resources. This potential of the adoption of new business models within rural SMEs is not fully observed.The aim of this research is to analyse the opportunities of rural SMEs in introducing the innovative business models driven by the circular economy. This research explores the innovative business models of rural SMEs that transform the environmental challenges in business opportunities and keep a balance with the growing consumption needs. The results of the research are of both theoretical and practical value, providing recommendations for facilitation of innovative business models within rural SMEs. The research methods: desk research, statistical analysis, a grounded theory approach, case study, primary data gathering through seven focus groups with more than 200 stakeholders from six European countries.
Students’ perceptions of assessed seminar performance in law

Purpose The purpose of this paper is to examine assessed seminars in law modules across first-, second- and third-year students at a higher education academy in Lancashire (England). This form of assessment is essentially a 1 h tutorial, where students are given marks for their oral contribution to class discussions. Assessment is a feature in all degree programmes conducted throughout higher education institutions. Recently, a move has been made from traditional examinations and coursework to assess students learning, to more inclusive forms of assessment following the changing nature of those entering higher education. Design/methodology/approach Using a quantitative survey, participants were asked to answer ten questions on their perceptions of assessed seminars as a form of assessment. To enhance the findings, interviews also took place with members of staff who had experience in teaching both assessed and non-assessed seminars. Findings This research found that although some students were daunted by assessed seminars, over the course of three years, their key legal skills had improved. Key skills enhanced through assessed seminars include communication-based skills and public speaking, whilst also being a positive form of assessment that maintains student retention. Research limitations/implications This is a small-scale research project, completed in the fulfilment of the authors PgCert. However, it does provide a template for other legal institutions to follow. Originality/value With a growing concern across the higher education sector around student retention, assessed seminars are proven to be a form of assessment that ensures student attendance, whilst enhancing skills ready for the workplace.
Improving Flow Completion Time and Throughput in Data Center Networks

Today, data centers host a wide variety of applications which generate a mix of diverse internal data center traffic. In a data center environment 90% of the traffic flows, though they constitute only 10% of the data carried around, are short flows with sizes up to a maximum of 1MB. The rest 10% constitute long flows with sizes in the range of 1MB to 1GB. Throughput matters for the long flows whereas short flows are latency sensitive. This thesis studies various data center transport mechanisms aimed at either improving flow completion time for short flows or throughput for long flows. Thesis puts forth two data center transport mechanisms: (1) for improving flow completion time for short flows (2) for improving throughput for long flows. The first data center transport mechanism proposed in this thesis, FA-DCTCP (Flow Aware DCTCP), is based on Data Center Transmission Control Protocol (DCTCP). DCTCP is a Transmission Control Protocol (TCP) variant for data centers pioneered by Microsoft, which is being deployed widely in data centers today. DCTCP congestion control algorithm treats short flows and long flows equally. This thesis demonstrate that, treating them differently by reducing the congestion window for short flows at a lower rate compared to long flows, at the onset of congestion, 99 th percentile of flow completion time for short flows could be improved by up to 32.5%, thereby reducing their tail latency by up to 32.5%. As per data center traffic measurement studies, data center internal traffic often exhibit predefined patterns with respect to the traffic flow mix. The second data center transport mechanism proposed in this thesis shows that, insights into the internal data center traffic composition could be leveraged to achieve better throughput for long flows. The mechanism for the same is implemented by adopting the Software Defined Networking paradigm, which offers the ability to dynamically adapt network configuration parameters based on network observations. The proposed solution achieves up to 22% improvement in long flow throughput, by dynamically adjusting network element's QoS configurations, based on the observed traffic pattern. iii Dedicated to the infinite power that Creator has put to work in all of us.
Deterministic replay of program execution based on Valgrind framework

Abstract—Deterministic replay is execution of the same sequence of instructions with the same arguments as at the first run. Developers spend a lot of time in trying to fix bugs in their software. Sometimes it is very difficult even to reproduce the bug. This often occurs in multithreaded applications. According to NIST[1] errors in software are estimated $59.5 billion annually. Therefore deterministic replay of program execution has become a problem of interests of many researches recently. Deterministic replay could help to solve the problem of bug reproduction and provide more abilities for program analysis. Valgrind is a framework for dynamic binary analysis. It provides infrastructure for translation and instrumentation of executable code. The goal of the work is to create a tool providing deterministic replay of program execution based on Valgrind infrastructure.
Financial Crisis, Stock Market and Economic Growth: Evidence from ASEAN-5

Abstract:This paper examines the effects of the Asian Financial Crisis (AFC) and Global Financial Crisis (GFC) on economic growth in the ASEAN-5 countries. Indonesia, Malaysia and Thailand were found to be most affected by the AFC but not the GFC. Additionally, for Malaysia and Thailand, real output responded positively and significantly to shocks in the stock market. These findings are consistent with the results that show that the shock in the Kuala Lumpur Stock Exchange has a larger effect on real output than other variables for twenty periods. However, a shock in the Bangkok stock exchange has a higher effect on real output and the effect remained strong until the tenth period. This suggests that the stock market is an important economic growth driver in Malaysia and Thailand.
Adaptive Class Data Layouts for the Synchronized-by-Default Approach

Adaptive class data layouts are not determined at compile-time. Instead, the system relies on information learned at runtime to generate and employ new data layouts on demand. This thesis provides a brief overview over related works and then outlines the hows and whys of an adaptive class data layouts implementation for use in a Synchronized-by-Default [6] prototype written in Java. Although the implementation is still in an unoptimised state and suffers from teething troubles, the thesis is able to show that it is possible for the adaptive class data layouts to yield a speedup with a fairly aggressive inlining strategy for the benchmarks it was tested on. After dealing with aforementioned teething troubles, further improvements can be made by reducing the number of checks inserted, cutting down on the amount of unnecessary transaction abort-and-retries or by reducing the bookkeeping overhead.
LeTs Preprocess: The multilingual LT3 linguistic preprocessing toolkit

This paper presents the LeTs Preprocess Toolkit, a suite of robust high-performance preprocessing modules including Part-of-Speech Taggers, Lemmatizers and Named Entity Recognizers. The currently supported languages are Dutch, English, French and German. We give a detailed description of the architecture of the LeTs Preprocess pipeline and describe the data and methods used to train each component. Ten-fold cross-validation results are also presented. To assess the performance of each module on dierent domains, we collected real-world textual data from companies covering various domains (a.o. automotive, dredging and human resources) for all four supported languages. For this multi-domain corpus, a manually veried gold standard was created for each of the three preprocessing steps. We present the performance of our preprocessing components on this corpus and compare it to the performance of other existing tools.
Using general-purpose processor cores as prefetching engines in chip multiprocessor architectures

Scaling the performance of applications with little thread-level parallelism is one of the most serious impediments to the success of multi-core architectures. At the same time, the long latency of memory accesses represents one of the largest performance bottlenecks for individual program threads. As a result, a typical microprocessor spends a significant amount of time waiting for data to be delivered from memory instead of performing useful computation. Fortunately, it is often possible to guess which memory data will be needed by a program thread in the near future. Various hardware and software prefetching techniques have been developed to fetch critical data before they are requested by the processor. This way prefetching can eliminate processor stalls otherwise induced by the slow response from the memory system. The main contribution of this dissertation is the development of two techniques that utilize extra cores of a chip multiprocessor (CMP) as prefetching engines to increase the performance of single program threads. The proposed approaches effectively leverage the execution capabilities of chip multiprocessors to compute data addresses that are likely to miss in the cache and prefetch them ahead of program thread load requests. I demonstrate the effectiveness of the proposed approaches by performing cycle-accurate simulations of a chip multiprocessor consisting of two four-way superscalar cores running the single-threaded SPEC CPU2000 benchmark suite. The proposed mechanisms provide significant performance improvements over a baseline that already includes an aggressive hardware stream prefetcher. A comparison with other multi-core prefetching mechanisms from the literature shows that the techniques proposed in this dissertation provide competitive performance, incur less energy overhead, and require considerably simpler hardware support.
Research on Object Tracking Algorithm Based on Sparse Representation

Visual tracking has been an active research topic which has a wide application in many computer vision tasks such as intelligence surveillance, vehicle navigation, human computer interaction, and so on. Introducing the background into the template set as the negative sample, the representative ones combine with positive samples as to build a new template set which is used to classify the sampling particles. The classification method filters out many samples which are largely dissimilar to the target, avoids the following computationally expensive cost of matching. Experiment shows that it cut down the redundant calculations.
Native T1 mapping comparison of mean and median assessment reveal reduced T1 in normal anterior and anterolateral segments compared to the rest of the myocardium

Poster: "ECR 2017 / B-1197 / Native T1 mapping comparison of mean and median assessment reveal reduced T1 in normal anterior and anterolateral segments compared to the rest of the myocardium" by: "P. Triadyaksa, T. Akinci D'Antonoli, N. H. Prakken, M. Oudkerk, P. E. Sijens; Groningen/NL"
Between Automation and Exploration: SAS Graphing Techniques for Visualization of Survey Data

The objective of this presentation is to introduce SAS graphing techniques for visualization of survey data. There is always a tension between automation and exploration. Automation is a common practice in the context of large-scale data processing. When there are many variables, it is more efficient to automate the graphing processes via SAS/Macros and SAS/Graph. However, hidden patterns of the data may not be revealed. On the other hand, SAS/Insight, which is a tool for exploratory data analysis, requires manual manipulation of the data and thus is timeconsuming. In this case study, both SAS/Macros and SAS/Insight are employed for a survey study situated Arizona State University. SAS/Macros codes are written in a way that enables the researcher to gain some degree of manipulation and exploration.
Reducing Latency In Data Delivery In Wireless Sensor Network With Mobile Elements

— Introducing sink mobility to combat this lifetime issue has recently generated a lot of interest among the sensor network research community. But latency may increase due to relatively low speed of the mobile elements which results in buffer over flow and increase latency. We propose two approaches for reducing the latency in a wireless sensor network when there is a mobile sink and hence maximizing the lifetime of the network. The first approach is a stop and wait disk covering (SWDC) , in which it try to reduce the tour length of mobile element, thus the travel time. Second, it proposes a multi-hop SWDP scheme which jointly optimizes the sink trajectory and the packet routing paths. This paper focuses on studying the performance of the approaches proposed.
The Effects of Posttraumatic Stress and Trauma-Focused Disclosure on Experimental Pain Sensitivity Among Trauma-Exposed Women.

Previous studies evaluating the impact of trauma history and posttraumatic stress disorder (PTSD) on pain sensitivity have yielded inconsistent findings. The presence of trauma-related negative affective states may account for these discrepancies. The current study aimed to evaluate the effect of PTSD and trauma-related negative affect on sensory, affective, physiological, and neuroendocrine responses to an experimental pain task. Trauma-exposed adult women (N = 87) with or without probable PTSD underwent an emotional disclosure paradigm during which they wrote about a traumatic event or a neutral topic. Participants then completed a pain induction procedure. Sensory and affective reports of pain, as well as physiological and neuroendocrine reactivity, were assessed. Compared to women without PTSD, those with PTSD demonstrated decreased sensory pain responses, ηp ² = . 11, including increased time to pain detection (i.e., threshold) and ability to withstand the pain stimuli (i.e., tolerance) after accounting for relevant covariates. Women with PTSD also demonstrated increased cortisol reactivity following the pain stimulus, ηp ² = . 06. The main and interactive effects of PTSD group and writing condition did not significantly predict alterations in affective reports of pain or heart rate reactivity. The results suggest that PTSD symptoms may contribute to alterations in pain sensitivity in trauma-exposed women, but this association is complex and requires further exploration.
A Scoping Review of Barriers to Investment in Climate Change Solutions

The finance sector has engaged with policy development processes associated with climate solutions for well over a decade, with the aim of overcoming barriers to investment. In this paper we analyse 31 practice-based policy reports which highlight key barriers to such investing. We use those practice-based policy reports to identify themes associated with barriers to investment to conduct a scoping literature review of academic research. We identify 91 relevant papers and use content analysis to summarise the barriers identified in a structured way to help inform the research landscape in a timely manner. Given the urgency of this issue, we call on the academic community to focus more effort in this new and emerging discipline and, in particular, on the need for an independent view on the validity of some of the claims made in these practice-based policy reports.
AJAX 2 IN 1: INTERACTIVE EDUCATION AND MODERN WEB TECHNOLOGY

In our days, in the age of WEB 2.0 it is very important that our web applications should be real applications instead of websites. In this article we talk about the AJAX, which has revolutionised the making of web applications, with it, we can build better, faster and user friendly Internet contents. In our research, we call the AJAX to serve education. With this technology we create an adaptive practise test, which not only evaluates the answers in real time, but it has an abbility to change the following questions, depending on the correct or incorrect answers of the student. The article touches the area of the artifical intelligence and data mining, and we get a taste of real time semantic answer analysis, everyone makes sure that the AJAX satisfies the expectations of the most obesseed WEB 2.0 fans. You can also discover its possibilities and understand, why iWiW and Google like this technology. The AJAX word is familiar for most people. Mentioning the word men are immediately interested in the result of Ajax - Arsenal final, while women are asking the name of the supermarket where the 750 ml version has the cheapest price. But in this article, we discuss the AJAX which has revolutionised the making of web applications, with the help of which we can build better, faster and user friendly Internet contents. 2. What is AJAX? AJAX is not a new technology. It is really several technologies, each flourishing in its own right, coming together in powerful new ways. Ajax incorporates  XHTML and CSS for standard-based presentation  dynamic display and interaction using the DOM (Document Object Model)  data interchange and manipulation using XML  XMLHttpRequest object for the asynchronous data communication - this is the heart of the AJAX.  and JavaScript for client-side data processing, and binding everything together Altogether they build up a powerful team, so the name is Asynchronous JavaScript And XML 3. Communication
Detecting manager’s fraud risk using text analysis: evidence from Iran

Purpose In accounting and finance, researchers have used many ways to detect manager’s fraud risk. Until now, many researchers have used some data mining methods in these two fields to detect this risk. The purpose of this paper is to compare the precision of two data mining methods in detecting such a risk. Design/methodology/approach For this purpose, this paper analyzed the texts of board’s reports and used two methods including the convex optimization (CVX) method and least absolute shrinkage and selection operator (LASSO) regression method. In this way, the words of these reports, which have the greatest power in explaining the manager’s high fraud risk index, were identified. Using these words, this paper presented a model that could detect manager’s high fraud risk index in companies. Findings The results indicated that both methods can detect the manager’s high fraud risk index with a precision between 82.55 and 91.25 percent. The LASSO method was significantly more precise than the CVX method. Research limitations/implications The lack of access to an official and reliable list of firms suspected to fraud and the lack of access to the Microsoft Word (MS Word) file of board’s reports were two of the most important limitations of this study. Practical implications Regulatory bodies and independent auditors can consider the proposed methods in this study for assessing the fraud risk for a firm or other legal parties. Originality/value This paper avoided using merely financial statements data to detect the manager’s fraud risk index and focused on texts of board’s reports for the detection process. The capabilities of data mining and text mining methods for detecting the manager’s fraud risk index using board’s reports were tested in this paper. By comparing CVX and LASSO results, this paper indicated that methods with a binary-dependent variable have more power and are more precise than methods with continuous-dependent variables for detecting fraud.
TOTEM: a digital processor for neural networks and Reactive Tabu Search

The Reactive Tabu Search (RTS) algorithm permits the training of neural networks with low number of bits per weight, low computational accuracy, no local minima "trapping", and limited sensitivity to the initial conditions. Two architectures for the implementation of multilayer perceptrons based directly on the properties of RTS are presented. They are characterized by high-speed integer computation, tunable precision, I/O balanced design, internal storage of the weights and compact processing units. TOTEM, a silicon implementation which uses only 8 bits per weight and 16 bits per input, is then presented. A triggering problem in high energy physics is used as a test-bed for the algorithm and the processor. The expected performance is briefly compared with those of two alternative processors.
A New Design for Wire-Driven Parallel Robot

Wire-driven parallel robots offers potential advan- tages for various applications such as medical rehabilitation, entertainment, virtual reality. However as any parallel robot their performances is greatly varying with their geometry and no fixed geometry allows to fulfill all requirements for all possible applications. Hence it is interesting to consider a modular parallel robot, whose geometry may be adapted to the task at hand. We describe the original mechanical hardware of our modular wire-driven robot Marionet and give some prospective on the algorithms that will allow to determine which geometry is the most appropriate for a given task, taking into account the unavoidable uncertainties in the manufacturing.