Miracle-dz/UniFAR-FTUs huggingface dataset:
Students' attitudes towards handheld computer algebra systems (CAS) in mathematics: Gender and school setting issues

This paper reports on a recent research study that investigated Victorian year 10-11 mathematics students' attitudes and beliefs on the impact of handheld CAS calculators on students' mathematics achievement. Students were surveyed using the Mathematics and Technology Attitudes Scale, which was used to monitor five affective variables relevant to learning mathematics with CAS. Principal component analysis, t-tests, correlations, and MANOVA were used for the analysis of responses. Students' responses indicated that there is a positive correlation between their attitudes towards CAS and their prior knowledge and experience. The results also reflected the common finding that boys express greater confidence than girls in technology use in mathematics learning.
Effects of Controlled Atmosphere on the Storage Quality and Aroma Compounds of Lemon Fruits Using the Designed Automatic Control Apparatus

‘Eureka' lemon fruits were stored under four controlled atmosphere- (CA-) combinations at 8°C for 20 days to investigate the effects on weight loss (WL), total soluble solids (TSS), titratable acidity (TA), vitamin C (VC), total phenolic content (TPC), sodium carbonate-soluble pectin (SSP), malondialdehyde (MDA), and volatile compounds. Results showed that the contents of TSS, TA, VC, and SSP in the stored fruits reduced during the storage period, while the WL and MDA increased. Fruit stored under CA2-combination (6 % O2+8 % CO2) showed the lower contents of WL and MDA and the higher content of TSS, TA, TPC, and VC than that of other treated fruits. The main volatile compounds present in the lemons were terpenoids, aldehydes, alcohols, and esters. In addition, both the terpenoid and aldehyde content are substantially higher in lemons exposed to CA2 conditions. In contrast, the alcohols and esters displayed elevated levels in the regular air (RA) stored fruit. In conclusion, CA with the suitable conditions proves to be better than RA as a storage regimen to keep the quality of lemons. These results indicated that the application of 6% O2+8% CO2 CA conditions could maintain the quality of ‘Eureka' lemon fruit during the storage time of 20 days and should be the optimal storage environment for postharvest Eureka lemons.
THERMO-HYDRO FRACTURE AND VISCOELASTIC BEHAVIOR OF TIMBER BASED MATERIALS : NUMERICAL ANALYSIS

The rupture in mixed mode coupling of mechanical and thermal loads for isotropic and orthotropic materials such as wood is studied. The analytical formulation of the energy-release rate is introduced by the integral T and A, which couple the rupture in mixed mode, the thermal effects and the pressure applied on the crack lips. This new formulation is based on the laws of energy conservation and real and virtual mechanical and thermal fields based on the arbitrary, Lagrangian and Eulerian configurations. The Mixed-Mode Crack Growth specimen providing a decrease of the energy-release rate during crack propagation is considered in order to compute the various mixed-mode ratios. The analytical formulation is implemented using the finite-element software Cast3m. The efficiency of the proposed model is justified by showing the evolution of the energy-release rate and the stress-intensity factors versus the crack length and versus the temperature variation in a time-dependent material.
Does IFRS Improve Financial Reporting Quality of CMS Firms in Canada

Purpose: The objective of this study is to examine whether controlling-minority structures (CMS) affect financial reporting quality of Canadian firms under International Financial Reporting Standards (IFRS). Design/methodology/approach: We test our research hypothesis using the price model of Ohlson 1995, and the returns model as defined by Kothari and Zimmerman (1995) on a sample of 810 Canadian firm-year observations, over pre and post-IFRS periods from 2008 to 2013. Findings: Our results indicate that IFRS adoption contributes in improving financial reporting quality of Canadian listed firms. As for CMS specifically, we find that the adoption of IFRS has a positive effect on the earnings quality but a negative effect on the value relevance of the book value of equity. Originality/value: Our research aims to provide additional evidence on the effectiveness of the mandatory adoption of IFRS in order to improve financial reporting quality. In this study, we focus on controlling-minority structures (CMS) which are widespread in most countries around the world.
A low-cost video encoder with matching pursuit

The application of matching pursuits in video coding has shown many advantages. However, this method has an extremely high computational cost. We construct a new dictionary that has a tree structure to replace the Gabor dictionary and uses a hierarchical method to search for the 'best' atom. Computational cost can be reduced significantly by using these methods.
15 th-16 th April 11 th STUDENT CONFERENCE

The shallow and land-surrounded north-eastern Adriatic Sea has seen a change in terms of environmental drivers in the last decades [1]. These were in turn reflected in seasonal and inter-annual variability of phytoplankton community, which was already described in this area [2]. However, the fine-scale community structure at species/genus level still lacks the connection to driving forces. Here the structural changes in the phytoplankton community from a LTER station in the Slovenian coastal sea (2005-2017) have been analyzed using a statistical method based on hierarchical clustering and Bayesian probability following the method proposed in literature [3]. The monthly probability distribution of assemblages and the inter-annual succession patterns were obtained. Each sample was then allocated in a group using its sampling date and its group associated probability. Then, using this temporal composition model as grouping factor, the IndVal index was calculated [3] and the typical community for each group was obtained [4, 5]. Six groups of phytoplankton taxa were identified and their distribution through years has been described. The methodology seems to show a relevant improvement in terms of classification fit in comparison of using months as grouping factor.
Computational tools for the determination of factor of safety and location of the critical circular failure surface for slopes in Mohr-Coulomb dry ground

This paper presents computational tools for the quick estimation of factor of safety and location of the critical circular failure surface for simple slope problems. The analysis presented here applies to slopes of arbitrary height and inclination angle excavated in homogeneous/isotropic dry ground, assumed to obey the Mohr-Coulomb shear failure criterion, and characterized by arbitrary values of unit weight, cohesion and internal friction angle. The proposed procedure is based on ideas originally laid out in the classical book Rock Slope Engineering by Hoek and Bray (1981) and more recently in the books by Read and Stacey (Guidelines for Open Pit Slope Design) and by Wyllie (Rock Slope Engineering, Civil Applications) from 2009 and 2018, respectively. Development of the proposed procedure involved computation of approximately 3,400 selected cases of slopes using the Bishop Method in the limit equilibrium software SLIDE by Rocscience. Results obtained from the analysis are summarized in dimensionless graphical representations that not only allow factors of safety and location of the critical circular failure surface to be estimated, but also important, to put light into the fundamental problem of establishing the concept of mechanical similarity of slopes excavated in Mohr-Coulomb ground with regard to factors of safety and position of the critical circular failure surface. In addition to the graphical representation of factor of safety, the paper also provides an equation to compute the factor of safety of slopes based on these representations. Considering that in the current practice of geotechnical engineering design the use of computer spreadsheets may be preferred over the use of dimensionless charts, the proposed procedure is implemented in a simple to use EXCEL workbook that is freely available to readers, and that allows determination of factor of safety and location of the failure surface, as it would be obtained with the Bishop Method in the limit equilibrium method software SLIDE. Finally, to illustrate the application of the proposed tools, a practical example involving the analysis of stability of a slope in an actual open pit mine is provided.
A framework for video transcoding and management in cloud manufacturing

Cloud-based manufacturing has been defined as CMfg. It is a system built on cloud computing technology that can integrate a large number of manufacturing resources. In a CMfg system, there are huge amounts of data and one of them is the video used to monitor manufacturing processes and learn knowledge. In cloud platform, the video data generate fast and have diverse formats, so the need for unified transcoding and management is necessary. In this article, an elastic cloud framework for fast video transcoding process and management is proposed. The core of this framework is a distributed system based on Hadoop that is designed for massive data storage and parallel computing.
A perception based, domain specific expert system for question-answering support

The ability to search has become an integral part of our interaction with technology. However, the current search technologies mostly use a keyword based searching mechanism, which does not have any deductive abilities. The recent introduction of the idea of computing with words, which can give deduction abilities to existing technologies, provides a new base for developing frameworks. This paper proposes implementation of a domain specific fuzzy expert system based on a question-answer system, which employs computing with words. In order to perform the translation of natural language sentences into a standard format, probabilistic context-free grammar is used.
Logit stick-breaking priors for partially exchangeable count data

Recently, Rigon and Durante (2018) discussed a Bayesian nonparametric dependent mixture model, which is based on a predictor-dependent stick-breaking construction. They provided theoretical support and proposed a variety of algorithms for posterior inference, including a Gibbs sampler. Their results rely on a formal representation of the stick-breaking construction, which has an appealing interpretation in terms of continuation-ratio logistic regressions. In this paper we review the contribution of Rigon and Durante (2018), and we extend their proposal to the case of partial exchangeability with count data. As an illustration of this methodology, we analyze the number of epileptic seizures of a single patient in a clinical trial. Abstract Recentemente, Rigon e Durante (2018) hanno discusso un modello di mistura bayesiano nonparametrico basato su una costruzione di tipo stick-breaking e dipendente da covariate. Gli autori hanno fornito sostegno teorico e hanno introdotto vari algoritmi per condurre inferenza a posteriori, incluso un campionamento di tipo Gibbs. I loro risultati si basano su una rappresentazione formale della costruzione stick-breaking, la quale ha un’interessante interpretazione in termini di regressioni logistiche sequenziali. In questo contributo, viene sintetizzata la proposta di Rigon e Durante (2018), e viene estesa la loro proposta nel caso parzialmente scambiabile con dati di conteggio. Per illustrare le loro metodologie, vengono analizzati il numero di attacchi epilettici di un singolo paziente durante un test clinico.
Combined Independent Component Analysis and Kalman Filter Based Real-Time Digital Video Stabilization

We present an online approach for digital video stabilization. This paper builds upon the work presented in where the authors have proposed the use of Independent Component Analysis (ICA) for video stabilization. Their scheme however is intended for offline systems and cannot be used for online systems. We propose a window based approach to combine the ICA based technique with Kalman filter, in order to make the method suitable for online systems. The proposed approach is tested using simulations and the mean square error between the outcome and the ground truth is used as performance measure. The performances of the proposed method, separate ICA and separate Kalman filter application are compared. The performance of the proposed method turns out to be better than separate application of Kalman filtering or ICA alone. 
ACEIs/ARBs for the prevention of type 2 diabetes in patients with cardiovascular diseases: a systematic review and meta-analysis

Purpose: Several studies have demonstrated that angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) reduce the incidence of type 2 diabetes in patients with cardiovascular diseases. Therefore, a systematic review and meta-analysis was performed to assess the clinical efficacy of ACEIs and ARBs in preventing type 2 diabetes. Methods: Randomized controlled trials (RCTs) were retrieved from PubMed, Embase, the Cochrane Library and Clinical Trials go through August 2015. Two reviewers independently assessed search results, extracted data, and appraised risk of bias. Results: A total of 21 studies met the inclusion criteria with a total of 111,768 subjects. Thereinto, 55962 patients randomly received ACEIs or ARBs, and 55824 received anti-hypertensive agents or a placebo. ACEIs and ARBs were associated with reductions in the incidence of newly diagnosed type 2 diabetes (ACEIs RR 0.76, 95% CI 0.67-0.87, P < 0.001; ARBs RR 0.79, 95% CI 0.74-0.85, P < 0.001; pooled analysis RR 0.78, 95% CI 0.73-0.84, P < 0.001). Conclusions: ACEIs or ARBs can reduce the incidence of type 2 diabetes, especially in patients with hypertension, metabolic syndrome, pre-diabetes phase, congestive heart failure, or coronary heart disease. ACEIs or ARBs is accordingly recommended as the first line antihypertensive agents in patients with cardiovascular diseases.
Polarization Diversity System for Mobile Radio

Conventional space diversity reception at typical elevated base locations requites separation of 30λ for broadside incidence and even more for in-line incidence and is therefore difficult to implement. A polarization diversity system for mobile radio is proposed. This is a two-branch receiver diversity system with the advantage that the base station antennas can be spaced as closely as desired. An experimental program has been carried out to obtain the statistical properties of vertically and horizontally polarized electromagnetic waves in a suburban environment at 836 MHz. It was observed that signals of both polarizations were Rayleigh plus log normal, where one is uncorrelated and other is correlated irrespective of base or mobile antenna spacings. The local means of the two signals were highly correlated and were with ± 3 dB for almost 90 percent of the time. Variation of base transmitter heights appeared to have little effect on the ratio of the local means of the two signals. The analysis and experiment demonstrated the feasibility of providing two diversity branches at UHF by polarization diversity.
Estimation of distribution programming based on Bayesian network

We propose estimation of distribution programming (EDP) based on a probability distribution expression using a Bayesian network. EDP is a population-based program search method, in which the population probability distribution is estimated, and individuals are generated based on the results. We focus our attention on the fact that the dependency relationship of nodes of the program (expressed as a tree structure) is explicit, and estimate the probability distribution of the program population using a Bayesian network. We compare EDP with GP (genetic programming) on several benchmark tests, i.e., a max problem and a Boolean function problem. We also discuss the trends of problems that are the forte of EDP.
Data analysis for collaborative filtering systems

The overabundance of information and the related difficulty to discover interesting content has complicated the selection process for the end-user who gets overloaded with data and risks to get lost. Recommender systems try to assist users in this content-selection process by using intelligent personalisation techniques which filter the information. Most commonlyused recommendation algorithms are based on Collaborative Filtering (CF) techniques which generally provide better results than ContentBased (CB) techniques and require no metadata of the content [1]. This research investigates the amount of data required for these CF algorithms.
A method of learning implication networks from empirical data: algorithms and Monte Carlo simulation based validation

This paper describes an algorithmic method of inducing implication networks from empirical data samples and reports some validation results with this method. The induced network enables efficient inferences about the values of network nodes given certain observations. This implication induction method is approximate in nature as probabilistic network requirements are relaxed in the construction of dependence relationships based on statistical testing. In order to examine the validity of the induced networks, several Monte Carlo simulations were conducted where predefined Bayesian networks were used to generate empirical data samples-some of which were used to induce implication relations whereas others were used to verify the results of evidential reasoning in the induced networks. The valves in the implication networks were predicted by applying a modified version of the Dempster-Shafer belief updating scheme. The results of predictions were, furthermore, compared to the ones generated by Pearl's stochastic simulation method, a probabilistic reasoning method that operates directly on the predefined Bayesian networks. The comparisons consistently show that the results of predictions based on the induced networks would be comparable to those generated by Pearl's method when reasoning in a variety of uncertain knowledge domains.
Enterprise Resource Planning ( ERP ) System as an Innovative Technology in Higher Education Context in Egypt

The global adoption of ERP Systems in Higher Education Institutions (HEIs) has improved substantially over the past decade. Although this demand continues to grow, with HEIs now a chief target market for ERP vendors, a few studies has been published on the topic. This paper reports a sub-study of a larger research effort that lead to contribute to understanding the phenomenon of ERP adoption in Egyptian HEIs. The educational ERP of business activities in higher education go through different modules. ERP in higher education should respond the real requirements of the education system. Enhancements or mere adaptations of legacy solutions, which stemmed from the experience in business practice, are not always successful. The current paper shows the contents of the ERP system that serve the education system successfully and describes the ERP system as an innovative technology for better higher education and hence invite Egyptian HEIs to adopt these systems. Enterprise Resource Planning systems have emerged as solutions oriented to effectively manage organization ́s resources. They allowed the automation of its department’s activities, made information accessible to users as needed, supporting more accurately their decision-making needs. Furthermore, the implementation of these systems has brought significant benefits to users and organizations.
Software Configuration Management –A Collaborative Approach with CMMI

crucial aspect in this area to avoid such problems. So, the aim is to formulate a new model and to implement the proposed model as a single CM tool solution for preventing the problems as mentioned above. The method is to propose a model based solution by integrating a new front end interface with Subversion (SVN) in the back end which preserves stringent access restriction ultimately resulting in CM work products as per Capability Maturity Model Integrated (CMMI) guidelines. In this new concept, employees other than CM specialists no longer need to toil exclusively with the CM tool and its standards but can reap the benefits of collaboration with automated CMMI process areas instead.
Reinforcement Learning in a Generalized Platform Game

The platform game genre is a relatively new benchmark domain in reinforcement learning. The generalized Mario domain of the Reinforcement Learning Competition is based on the classic platform game Super Mario Bros, and features a complex control task with a large state space, many possible interactions between agent and environment, and a non-trivial optimal solution. Unique to the domain are the availability of various reward systems and physics systems. This thesis contributes a detailed analysis of two novel approaches to finding control policies for this domain: Hierarchical task decomposition and direct policy search. For both approaches, a general agent and an adaptive agent are developed, the latter being able to adapt to different reward systems and physics systems. The approach using hierarchical task decomposition is not successful in this research, because the initially intuitive decomposition of the problem turns out to be a disadvantage. Empirical evidence demonstrates that the Adaptive Hill Climber, a direct policy search approach that learns different parameter vectors for different environmental parameterizations, performs significantly better than the other agents, as well as the example agent provided by the Reinforcement Learning Competition. In order to be able to win the Reinforcement Learning Competition, several aspects of the Adaptive Hill Climber still need to be improved. However, on fitness evaluations of 2000 steps, the Adaptive Hill Climber is able to beat the RL Competition winner of 2009 by scoring up to 320% more reward.
POSTER : Diversity for Software Resilience

The current software “monoculture” presents a common avenue of attack against all computers running the vulnerable software [1]. Due to this concern, a taxonomy of software diversity techniques has been developed (see Larsen et al. [2]) and researchers have applied diversity as a defensive strategy to a range of attack types from SQL injection [3] to returnoriented programming (ROP) [4]–[6]. Two key areas of open research within the study of software diversity are (1) measuring the impact of diversity and (2) application of software diversity in n-variant systems to achieve cyber resilience. Quantitative metrics to compare efficacy of software diversity strategies would optimally differentiate strategy types and also correlate with actual attacker effort. For example, doubling the distance between two diversity strategies with such a metric might be directly correlated with a proportionate increase in attacker effort to compromise a diversified software population. However, approximating attacker effort is a difficult problem due to the challenge of collecting reliable measures of effort from a sufficient number of human attackers. Many proxy approaches depend on a particular class of attacks, such as comparing the number of ROP gadgets that are shared between variants [7], [8]. These approaches have begun to address the problem of evaluating diversity strategies, but further investigation is required. Second, software diversity can be used to protect a single physical platform by running several variants of an application simultaneously. This is known as n-variant execution [9], [10], and resilience is assumed to be incurred via the inability of common inputs to compromise the majority of variants. A monitoring application is typically used to analyze the system and behavior divergence of a portion of the variants is considered indicative of a potential fault. Managing overall performance, monitor design, and methods of detecting divergence are open challenges for n-variant systems.