Miracle-dz/UniFAR-FTUs huggingface dataset:
Turkish EFL Learners’ Views towards the Use of IWB in English Lessons

*This study was produced from the Master's Thesis titled "Turkish EFL Learners’ Views Towards the Use of IWB in English Lessons" by researcher Onur Başdinç, a student at Istanbul Aydın University under the supervision of Dr.HülyaYumru. Abstract: The aim of this investigation is to evaluate the opinions of EFL students towards interactive whiteboards in English lessons in a foundation university located in Turkey. Quantitative research technique was carried out in order to collect information. A questionnaire with four factors “Teachers’ and Students’ Perception of Interactive Whiteboard in the English as a Foreign Language Classroom” prepared by Oz (2014) was conducted to 267 preparatory school learners. The outcomes of the research revealed that most of the learners havepositive views about using IWBs in English lectures.
ROBUST CONTROL OF DISCRETE-TIME UNCERTAIN STOCHASTIC SYSTEMS SUBJECT TO MIXED H2/PASSIVITY PERFORMANCE

This paper investigates a mixed H2/Passivity performance control problem of uncertain stochastic systems. Based on Itô stochastic equation, the considered system is described by a linear difference equation with multiplicative noise term. To minimize output energy and guarantee asymptotical stability, the H2 scheme is employed. Moreover, passivity theory is applied to constrain the effect of external disturbance on the system. According to the passivity theory, a general and flexible mixed performance controller design method is proposed. Based on Lyapunov function, some sufficient conditions are derived into extended Linear Matrix Inequality (LMI) form which reduces conservatism of finding the feasible solutions. Furthermore, the derived conditions can be directly solved by convex optimization algorithm to establish a controller such that asymptotical stability and mixed H2/Passivity performance of the uncertain stochastic system are achieved. At last, an inverted pendulum system is used to show effectiveness and applicability of the proposed method.
Diagnosing Diabetes Type II Using a Soft Intelligent Binary Classification Model

Diabetes, named also silent killer, is a metabolic disease characterized by high blood glucose levels, which result from body does not produce enough insulin or the body is resistant to the effects of insulin. Classification models are one of the most widely used groups of data mining tools that greatly help physicians to improve their prognosis, diagnosis or treatment planning procedures. Classification accuracy is one of the most important features in order to choose the appropriate classification model; hence, the researches directed at improving upon the effectiveness of these models have never stopped. Nowadays, despite the numerous classification models proposed in several past decades, it is widely recognized that diabetes are extremely difficult to classify. In this paper, a hybrid binary classification model is proposed for diabetes type II classification, based on the basic concepts of soft computing and artificial intelligence techniques. Empirical results of Pima Indian diabetes data classification indicate that hybrid model is generally better than other linear/nonlinear, soft/hard, and classic/intelligent classification models presented for diabetes classification. Therefore, our proposed model may be a suitable alternative model for medical classification to achieve greater accuracy, and to improve medical diagnosis.
Quantitative trait loci affecting growth performance in F2 intercross between Golden Montazah and White Leghorn chickens

Quantitative trait loci (QTL) for body weights (BW) at 4, 8, 12, 16 weeks of age and daily gains (DG) at intervals of 0-4, 4-8, 8-12 and 12-16 weeks were identified in F2 crossbred population produced by crossing males of Golden Montazah (GM) with females of White Leghorn (WL). Phenotypic data were analyzed using multi-traits animal model including the genetic group, sex and hatch as fixed effects and the additive genetic and common environmental effects as random effects. After parentage checking and F2 genotyping, data of 1011 chicks of F2 were genotyped using 43 genetic markers in nine autosomal linkage groups, Z chromosome and the genotypes were used for QTL analysis. A mixed model included the sex and hatch as fixed effects along with the additive and dominance effects of QTL as random effects were used for QTL analysis. The heritability estimates for growth traits were high. The genotypic and phenotypic correlations between growth traits were positive and high. The total map length was 1901 cM (ranging from 25 to 568 cM), with an average spacing of markers of 24.39 cM (ranging from 7.8 to 24.3 cM). A total of 34 QTL were detected for BW traits. These QTL were distributed over five distinct regions on 10 chromosomes, and their effects ranged from 1.2 to 13.8% of the phenotypic variation. A total of 19 significant genome QTL that affected BW traits were located on seven macro-chromosomes (1, 2, 3, 4, 6, 8 and Z) and one micro-chromosome (11). A total of 14 significant QTL were detected for DG traits, distributed over 7 distinct regions on 6 chromosomes, and their effects ranged from 2 to 8.9% of the phenotypic variation. A total of 11 significant genome QTL affecting DG traits were located on five macro-chromosomes (1, 2, 3, 4 and 8) and there was statistical evidence for two QTL on chromosome 4. The proportions of phenotypic variation explained by significant and suggestive QTL for BW traits at 4, 8, 12 and 16 weeks were 21.1, 30.8, 29.3 and 25.4%, respectively. The proportions of phenotypic variation explained by significant and suggestive QTL for DG traits during 0-4, 4-8, 8-12 and 12-16 weeks were 25.9, 29.1, 9.35 and 3.9%, respectively. The largest proportion of the phenotypic variation explained by a QTL was 8.9% for DG4-8 at 428 cM on chromosome 4. The additive effects of QTL on growth traits were positive, while the dominance effects were generally negative or not significant. A QTL for BW at 12 weeks of age segregating on chromosome 4 at 179 cM had the largest additive effect (205.7 ± 22.2 g) and explained 13.8% of the phenotypic variation. The largest dominance effect (−188.1 ± 55.0 g) was for QTL of BW at 16 weeks of age segregation on chromosome 4 at 139 cM and the QTL effect accounted for 6.5% of the phenotypic variation. The total trait variances explained by QTL for each growth trait were 21.1, 30.8, 31.7, 25.4, 25.9, 29.1, 9.35 and 3.9 % in BW4, BW8, BW12, BW16, DG04, DG48, DG812 and DG1216, respectively.
Effectiveness of arsenic phytoremediation using Ludwigia octovalvis in a pilot reed bed system

Ludwigia octovalvis (Jacq.) P.H. Raven is a terrestrial tropical plant in Malaysia having the ability to uptake and accumulate arsenic in their tissue. The effectiveness of arsenic phytoremediation by L. octovalvis in pilot reed bed system using arsenic spiked sand was conducted to determine the feasibility using this plant in a large scale of phytoremediation. The depth of arsenic spiked sand in a reed bed system was 10 cm with another two fine and medium gravels layer below, each at 10 cm depth. All treatments were carried out without addition of fertilizer, bacteria or aeration. The higher arsenic uptake and accumulation reached 528.5 ± 68.3 mg/kg in leaves of L. octovalvis after 42 days of exposure at arsenic concentration of 39 mg/kg. Based on the translocation factor (TF) and bioaccumulation factor (BF) values, indicating phytoextraction has role process in arsenic phytoremediation using L. octovalvis in a pilot reed bed system using spiked sand. The effectiveness of arsenic phytoremediation increased with time exposure. The effectiveness uptake percentages of total arsenic mass at concentrations of 5, 22 and 39 mg/kg on Day 42 were 100, 43.8 and 18.5% respectively. It was concluded that L. octovalvis has the potential to be used in pilot arsenic phytoremediation. Keywords— arsenic, uptake, accumulation, performance, pilot reed bed, effectiveness.
Readily Available Technologies for Building Community Resilience: Lessons from India during the Covid-19 pandemic

Information and communication technologies (ICTs) have played a pivotal role in assisting communities with building resilience by responding to and recovering from crises. For example, ICTs continue to assist with the recovery process during the ongoing COVID-19 pandemic. We focus on a set of these ICTs – Readily Available Technologies (RATs) – and show how they can be used to assist low-resource communities during crises. We develop a community-focused conceptual framework for crisis management that emphasizes the role and impact of RATs. Furthermore, we provide two examples from India to illustrate the applicability of our framework in the current pandemic context. We invite future researchers to build further on our framework and we highlight its potential contributions.
Developing regional approach for transport industry: the role of port system in the Balkans

AbstractThe paper presents a wider perspective on possibilities to develop a regional strategy for efficient management of the transport industry in the region of the Balkans. The focus is mainly on ports, their actual and future role in transport industry and regional economy. A complete overview of the actual situation of port industry and inland infrastructure is presented. Based on a seven pillar model, other key elements, such as Information Technology (IT) systems in use, documentary procedures and managing strategies of ports in the Balkans were analysed. The main proposal is connected to the development of a regional role for ports on the eastern coast of the Adriatic Sea in order to secure port regionalization and specialization. On this basis, the inland infrastructure and other supporting elements as IT platforms and documentary procedures should be developed accordingly. The entire region and economy should benefit from such cooperation as new supply chains might be attracted.
Design Procedures for a Fully Differential Telescopic Cascode Two-Stage CMOS Operational Amplifier

In this paper, a fully differential telescopic operational amplifier design is presented which achieve both high dc gain and high unity-gain frequency. Trade-offs among such factors as bandwidth, gain, phase, margin, bias current, signal swing, slew rate, and power are made evidently. The characteristic of this kind of two-stage operational amplifier is investigated theoretically, in this paper. The results indicate that proposed two-stage operational amplifier achieves broader unity bandwidth, increases the DC gain. Simulation results show that, at 5V power supply, the output swing is ±4.3 V, settling time is 167.4ns. Based on the two-stage operational amplifier structure, the operational amplifier with 2.5V output common voltage shows a DC gain greater than 87 dB, Gain Bandwidth over 39 MHz (5pF load) and a phase margin larger than 84° with power dissipation of 3mW. These good results could be used in ∑ - △ modulation and A/D conversion etc.
Mathematical relationships between spinal motoneuron properties

Our understanding of the behaviour of spinal alpha-motoneurons (MNs) in mammals partly relies on our knowledge of the relationships between MN membrane properties, such as MN size, resistance, rheobase, capacitance, time constant, axonal conduction velocity and afterhyperpolarization period. We reprocessed the data from 40 experimental studies in adult cat, rat and mouse MN preparations, to empirically derive a set of quantitative mathematical relationships between these MN electrophysiological and anatomical properties. This validated mathematical framework, which supports past findings that the MN membrane properties are all related to each other and clarifies the nature of their associations, is besides consistent with the Henneman’s size principle and Rall’s cable theory. The derived mathematical relationships provide a convenient tool for neuroscientists and experimenters to complete experimental datasets, to explore relationships between pairs of MN properties never concurrently observed in previous experiments, or to investigate inter-mammalian-species variations in MN membrane properties. Using this mathematical framework, modelers can build profiles of inter-consistent MN-specific properties to scale pools of MN models, with consequences on the accuracy and the interpretability of the simulations.
Violence detection in videos using Conv2D VGG-19 architecture and LSTM network

Violence identification from surveillance videos can be considered as a special form of Activity recognition, that targets at recognizing human actions in public places. A video sequence is a collection of consecutive frames that is sampled in both temporal and vertical directions and the given input video is converted into frames and the preprocessing is done at the frame level. For Feature extraction the 2D convolutional neural network (Conv2D) is used and it adapts the layers of VGG-19 net architecture with global average pooling and learns the spatial information in the given video. Those extracted features are then combined using Long Short Term Memory (LSTM) and it learns about temporal information from the video. The model is validated using the Hockey data set and a loss of 0.02 and accuracy of 98 is achieved.
Relationship of Absolute Speed and Sextydriving Liability

Research This study aims to identify the relationship between absolute speed and agility towards the ability to dribble in the students participating in the 2020 GSI SMP Yogyakarta City level selection. This research is a correlational study. The method used was a survey with data collection techniques using an absolute speed test (10 m run), agility test (Illinois test), and dribbling test (dribbling test). The research subjects were 48 students participating in the GSI SMP Yogyakarta City level selection in 2020. Data analysis techniques used partial test analysis and simultaneous testing. The results showed that there is a partial significant relationship with the absolute speed of 72.4% and agility of 87.6% and simultaneously 77.3% of absolute speed and agility abilities to the ability to dribble the students participating in the GSI SMP selection Yogyakarta City level. 2020. So it can be concluded that the ability to dribble has a close relationship with absolute speed and agility of 77.3%, the remaining 22.7% is from other factors outside of this study such as psychological factors or mental maturity and flexibility of the legs.
Modelling and control of cascaded multilevel converters for dynamic compensation

Purpose – This paper aims to integrate cascaded multilevel converters in the static compensator (STATCOM) systems in order to assure dynamic compensation of the reactive power absorbed by fixed speed wind turbines.Design/methodology/approach – The cascaded multilevel converter topology is incorporated as a variable source of reactive power required by the wind farm. The evaluation of reference reactive currents is assured by the technique of instantaneous power theory. Thus, the STATCOM, with its appropriate control strategy, continuously compensates the reactive currents.Findings – A developed non‐linear state representation makes possible the analysis of static and dynamic behaviour of the proposed system. The STATCOM‐based cascaded multilevel converter is able to provide continuous compensation and proves highly dynamic under steady state and transient operating conditions.Practical implications – The paper formulates a mathematical model which includes all parameters describing the system composed by .
Developing indicators of sustainability: US experience

Sustainability indicators integrate environmental, social, and economic factors such that the complex cause and-effect relationships between these multiple factors can be more readily investigated. The whole systems approach of sustainable development differs from traditional environmentalism by its inclusion of economic and social factors. The selection of sustainability indicators will therefore inevitably be a human value-driven process. Environmental health will nonetheless be paramount. Empirical studies in the USA have found that states with lower pollution levels and more environmental regulation have healthier economies and fewer disparities in income between economic classes (Templet, 1995). In construction, indicators of sustainable construction are a necessary parallel to the macro-national and regional-scale indicators measuring society's movement toward or away from some approximation to sustainable development. Les indicateurs de viabilite integrent des facteurs ecologiques, sociaux et econo.
PIAP-DF: Pixel-Interested and Anti Person-Specific Facial Action Unit Detection Net with Discrete Feedback Learning

Facial Action Units (AUs) are of great significance in communication. Automatic AU detection can improve the understanding of psychological conditions and emotional status. Recently, several deep learning methods have been proposed to detect AUs automatically. However, several challenges, such as poor extraction of fine-grained and robust local AUs information, model overfitting on person-specific features, as well as the limitation of datasets with wrong labels, remain to be addressed. In this paper, we propose a joint strategy called PIAP-DF to solve these problems, which involves 1) a multi-stage Pixel-Interested learning method with pixel-level attention for each AU; 2) an Anti Person-Specific method aiming to eliminate features associated with any individual as much as possible; 3) a semi-supervised learning method with Discrete Feedback, designed to effectively utilize unlabeled data and mitigate the negative impacts of wrong labels. Experimental results on the two popular AU detection datasets BP4D and DISFA prove that PIAP-DF can be the new state-of-the-art method. Compared with the current best method, PIAP-DF improves the average F1 score by 3.2% on BP4D and by 0.5% on DISFA. All modules of PIAP-DF can be easily removed after training to obtain a lightweight model for practical application.
Representation of radar sea clutter

Sea clutter data obtained with a land-based X-band radar are analysed in terms of a correlated gamma-distributed noise model. Results obtained with both vertical-vertical and horizontal–horizontal transmit-receive polarisations are shown to be broadly compatible with the model. As a test of the assumptions inherent to the model, we next simulate textures having the same autocorrelation function as the original image data. General agreement is again observed; discrepancies can be ascribed to specific failures of the assumptions.
Single-Trial Dynamics of Competing Reach Plans in the Human Motor Periphery

Contemporary motor control theories propose competition between multiple motor plans before the winning command is executed. While most competitions are completed before movement onset, movements are often initiated before the competition has been resolved. An example of this is saccadic averaging, wherein the eyes land at an intermediate location between two visual targets. Behavioral and neurophysiological signatures of competing motor commands have also been reported for reaching movements, but debate remains about whether such signatures attest to an unresolved competition, arise from averaging across many trials, or reflect a strategy to optimize behavior given task constraints. Here, we recorded EMG activity from an upper limb muscle (m. pectoralis) while 12 (8 female) participants performed an immediate response reach task, freely choosing between one of two identical and suddenly presented visual targets. On each trial, muscle recruitment showed two distinct phases of directionally tuned activity. In the first wave, time-locked ∼100 ms of target presentation, muscle activity was clearly influenced by the nonchosen target, reflecting a competition between reach commands that was biased in favor of the ultimately chosen target. This resulted in an initial movement intermediate between the two targets. In contrast, the second wave, time-locked to voluntary reach onset, was not biased toward the nonchosen target, showing that the competition between targets was resolved. Instead, this wave of activity compensated for the averaging induced by the first wave. Thus, single-trial analysis reveals an evolution in how the nonchosen target differentially influences the first and second wave of muscle activity. SIGNIFICANCE STATEMENT Contemporary theories of motor control suggest that multiple motor plans compete for selection before the winning command is executed. Evidence for this is found in intermediate reach movements toward two potential target locations, but recent findings have challenged this notion by arguing that intermediate reaching movements reflect an optimal response strategy. By examining upper limb muscle recruitment during a free-choice reach task, we show early recruitment of a suboptimal averaged motor command to the two targets that subsequently transitions to a single motor command that compensates for the initially averaged motor command. Recording limb muscle activity permits single-trial resolution of the dynamic influence of the nonchosen target through time.
A STRATEGY ON PERSONAL WEB REVISITATION USING CONTEXT AND CONTENT KEYWORDS BY RELEVANCE FEEDBACK

: Getting back to previously viewed web pages is a common yet uneasy task for users due to the large volume of personally accessed information on the web.This paper leverages human’s natural recall process of using episodic and semantic memory cues to facilitate recall, and presents a personal web revisitation technique called WebPagePrev through context and content keywords. Underlying techniques for context and content memories’ acquisition, storage, decay, and utilization for page re-finding are discussed.A relevance feedback mechanism is also involved to tailor to individual’s memory strength and revisitation habits. Our 6-month user study shows that: (1) Compared with the existing web revisitation tool Memento, History List Searching method, and Search Engine method, the proposed WebPagePrev delivers the best re-finding quality in finding rate (92.10%), average F1-measure (0.4318) and average rank error (0.3145). (2) Our dynamic management of context and content memories including decay and reinforcement strategy can mimic users’ retrieval and recall mechanism. With relevance feedback, the finding rate of WebPagePrev increases by 9.82%, average F1-measure increases by 47.09%, and average rank error decreases by 19.44% compared to stable memory management strategy. Among time, location, and activity context factors in WebPagePrev, activity is the best recall cue, and context+content based re-finding delivers the best performance, compared to context based re-finding and content based re-finding.