Miracle-dz/UniFAR-FTUs huggingface dataset:
Tinjauan Literatur Pengajaran Kemahiran Bertutur Bahasa Arab

Proses pengajaran kemahiran bertutur bahasa Arab yang berlaku selama ini masih lagi kurang memberikan kesan yang baik kepada penguasaan kemahiran tersebut dalam kalangan pelajar. Justeru itu, kajian ini bertujuan untuk mengenal pasti proses pengajaran kemahiran bertutur bahasa Arab yang telah dikaji dalam kajian lepas dan mengenal pasti metodologi kajian yang digunakan dalam kajian lepas yang berkaitan dengan pengajaran kemahiran bertutur bahasa Arab. Pendekatan kualitatif dan reka bentuk analisis kandungan digunakan dalam kajian ini. Data-data kajian ini diperoleh daripada artikel jurnal, tesis, disertasi, buku, kertas kerja seminar dan prosiding yang berkaitan dengan tajuk kajian. Semua data yang telah dikumpulkan dianalisis secara analisis deskriptif dengan menggunakan perisian ATLAS.ti versi 8.0. Dapatan kajian ini telah menunjukkan bahawa terdapat banyak kajian yang berkaitan dengan pengajaran kemahiran bertutur bahasa Arab dengan menggunakan metodologi kajian yang pelbagai. Namun begitu, masih kurang kajian tentang pengajaran bahasa Arab yang menggunakan pendekatan pengajaran berpusatkan pelajar yang merupakan salah satu ciri pengajaran abad ke-21. Begitu juga dengan metodologi kajian yang digunakan, didapati masih kurang kajian yang menggunakan metodologi kajian campuran kerana kebanyakan kajian-kajian lepas lebih tertumpu pada satu pendekatan sama ada kuantitatif atau kualitatif sahaja. Oleh yang demikian, kajian ini mencadangkan agar pendekatan pengajaran berpusatkan pelajar digunakan dalam pengajaran kemahiran bertutur bahasa Arab dan pendekatan kajian campuran diperluaskan dalam kajian berkaitan dengan pengajaran kemahiran bertutur bahasa Arab.
PENERAPAN MEDIA SIMULASI MATLAB BERBASIS INTERACTIVE CONCEPTUAL UNTUK MENINGKATAN PEMAHAMAN KONSEP MAHASISWA

This study aims to know the extent to which the use of Matlab simulation media based conceptual Interactive can overcome the difficulties of students in understanding the Linear Equation System in the course of Numerical Analysis and improve student understanding. This study is a classroom action research, which is carried out in two cycles. Research subjects as many as 25 students grade 7C Prodi Mathematics Education University PGRI Madiun academic year 2016/2017. Research instruments are researchers, learning observation sheets, concept comprehension tests, student response questionnaires and interview guides. Based on the result of the research, it can be concluded that the application of Matlab simulation media based on conceptual interactive in learning can increase the students understanding on Linear Equation System. This is shown by the improvement of students' ability in understanding the system of linear equations in each cycle. The data is also supported by a positive response given by students in learning.
Use of Orange Data Mining Toolbox for Data Analysis in Clinical Decision Making: The Diagnosis of Diabetes Disease

Diabetes is a life-long illness which occurs as a result of lack of insulin hormone or ineffectiveness of insulin hormone. Blood sugar, fructosamine, and hemoglobin A1c (HbA1c) values are widely used for diagnosis of this disease. Although the role of insulin in diagnosing diabetes is great, the HbA1c value is more accurate. This is because HbA1c value gives information about the past two or three months of blood sugar in the treatment of diabetes. This study aims to estimate the HbA1c value with high accuracy. Follow-up data of diabetic patients were used as data. The Orange data mining software is used because it is easy to use in the modeling phase and contains many methods. In this context, the chapter aims to develop an effective prediction model by using a large number of feature selection and classification methods. The results show that the proposed model successfully predicts the HbA1c parameter. In addition, determination of the parameters that are effective in the diagnosis of diabetes has been carried out with the feature selection methods. Use of Orange Data Mining Toolbox for Data Analysis in Clinical Decision Making: The Diagnosis of Diabetes Disease
Les armatures de fer de la cathédrale de Bourges : nouvelles données, nouvelles lectures

La cathedrale Saint-Etienne de Bourges est le premier edifice majeur de la periode gothique a avoir fait, au debut des annees 1990, l’objet d’une etude architecturale quant aux usages du fer dans sa construction, qui posait notamment les questions du role et de l’origine des armatures de fer identifiees dans la structure de l’edifice. La multiplication des travaux sur cette thematique au cours des annees 2000 et le developpement des methodes archeometriques appliquees aux metaux permettent de jeter un regard nouveau sur ces questionnements. Cet article presente les resultats d’une campagne d’etude archeologique du bâti menee sur la cathedrale de Bourges en 2010-2011, couplee a l’analyse chimique de 70 prelevements de fer et de 58 scellements de plomb. L’integration des armatures dans la maconnerie comme leur composition chimique revelent que les tirants et chainages installes au niveau du triforium de la cathedrale sont bien contemporains de son edification, mais que leur mise en œuvre n’etait pas prevue des l’origine du chantier : ils n’ont ete implantes qu’en cours de construction, probablement comme consolidation de desordres observes dans l’edifice inacheve. Ces resultats permettent ainsi de replacer la cathedrale de Bourges comme un jalon dans l’histoire de l’usage du fer dans l’architecture gothique et de reconsiderer l’evolution du savoir-faire des bâtisseurs medievaux quant a l’integration progressive de ce materiau dans les maconneries au debut du XIIIe siecle, fruit d’une experimentation constante.
Stable auto-tuning of adaptive controllers for nonlinear systems /

This dissertation focuses on improving the performance of direct and indirect adaptive control methodologies for nonlinear discrete and continuous-time systems via the use of additional cost functions to achieve stable and hopefully higher per­ formance operation. We will in particular focus on adjusting the parameters of the adaptive laws by optimizing some cost functions of interest (e.g., instantaneous con­ trol energy). In this dissertation, the adaptation gain and the direction of descent for discrete-time systems are updated on-line to optimize some cost function. The auto­ tuning is performed in such a way th a t stability is m aintained for any value of the adaptation gain within the feasible range. We show tha t auto-tuning the adaptation gain can be viewed as a special case of auto-tuning the direction of descent. Based on simulation results, we find tha t the lower bound of the adaptation gain tends to be used when the output error is very small. In the case where the output error is fairly large, a large adaptation gain tends to be used. Also, for one example in the direct case the auto-tuning algorithm is able to achieve a mean squared error (MSE) that is smaller in magnitude than the MSE tha t can be achieved using any fixed adaptation gain, with a relatively small control energy. In the indirect case, however, for this example the auto-tuning algorithm is only able to achieve an acceptable MSE with a
Evaluating Quality of Students’ Support Services in Open Distance Learning

Evaluating the quality of students’ support services in distance education institutions is vital because by nature Open Distance Learning (ODL) is a high-involvement service industry, with multiple student support service encounters. Most quality evaluation models tend to view quality from the institutional perspective. As a result, little is known about the determinants of service quality, which distance education students can use to evaluate the support services provided by their institutions. The aim of this study is to evaluate the quality of support services from the current users of the services. It is through students’ expectations and perceptions of their experiences that we shall understand the quality of the support services needed. Semi-structured interviews were conducted to understand distance students’ perceptions and expectations of the service received. The results of the study indicated that service quality in distance education can be measured by six dimensions namely; tangibles, reliability, responsiveness, delivery, assurance and student participation. Each dimension can be measured by a number of attributes. The dimensions will be useful in helping distance education institutions evaluate the quality of their support services from students’ perspective; by so doing monitoring the overall performance of their services.
Face recognition via Gabor and convolutional neural network

In recent years, the powerful feature learning and classification ability of convolutional neural network have attracted widely attention. Compared with the deep learning, the traditional machine learning algorithm has a good explanatory which deep learning does not have. Thus, In this paper, we propose a method to extract the feature of the traditional algorithm as the input of convolution neural network. In order to reduce the complexity of the network, the kernel function of Gabor wavelet is used to extract the feature from different position, frequency and direction of target image. It is sensitive to edge of image which can provide good direction and scale selection. The extraction of the image from eight directions on a scale are as the input of network that we proposed. The network have the advantage of weight sharing and local connection and texture feature of the input image can reduce the influence of facial expression, gesture and illumination. At the same time, we introduced a layer which combined the results of the pooling and convolution can extract deeper features. The training network used the open source caffe framework which is beneficial to feature extraction. The experiment results of the proposed method proved that the network structure effectively overcame the barrier of illumination and had a good robustness as well as more accurate and rapid than the traditional algorithm.
System for audio analysis and perception enhancement

An audio perception system is described, comprising a capture module configured to capture acoustic speech signal information; a feature extraction module configured to extract features that identify a candidate unvoiced portion in an acoustic signal; a classification module configured to identify if the acoustic signal is or contains an unvoiced portion based on the extracted features; and a control module configured to generate a control signal to a sensory stimulation actuator for generating an aero- tactile stimulation to be delivered to a listener, the control signal based at least in part on a signal representing the identified unvoiced portion. Related methods are also described.
An Improved and More Accurate Expression for a PDF Related to Eigenvalue-Based Spectrum Sensing

Cooperative spectrum sensing based on the limiting eigenvalue ratio of the covariance matrix offers superior detection performance and overcomes the noise uncertainty problem. While an exact expression exists, it is complex and multiple useful approximate expressions have been published in the literature. An improved, more accurate, integral solution for the probability density function of the ratio is derived using order statistical analysis to remove the simplifying, but incorrect, independence assumption. Thereby, the letter makes an advance in the rigorous theory of eigenvalue-based spectrum sensing.
Adaptive mesh refinement method. Part 2: Application to tsunamis propagation

Numerical simulations of multi dimensional large scale fluid-flows such as tsunamis, are still nowadays a challenging and a difficult problem. To this purpose, a parallel finite volume scheme on adaptive unstructured meshes for multi dimensional Saint-Venant system is presented. The adaptive mesh refinement method is based on a block-based decomposition (called BB-AMR) which allows quick meshing and easy parallelization. The main difficulty addressed here concerns the selection of the mesh refinement threshold which is certainly the most important parameter in the AMR method. Usually, the threshold is calibrated according to the test problem to balance the accuracy of the solution and the computational cost. To avoid " hand calibration " , we apply an automatic threshold method based on the decreasing rearrangement function of the mesh refinement criterion. This method is applied and validated successfully to the one and two dimensional non homogeneous Saint-Venant system through several tsunamis propagation test cases.
Kecenderungan Pembelian Impulsif Ditinjau dari Perspektif Islam (Studi Kasus Pada Pengunjung Malioboro Mall Yogyakarta)

Saat ini kebutuhan masyarakat semakin kompleks dan beragam. Sehingga seringkali masyarakat dalam berbelanja dilakukan secara spontan karena berbagai variasi produk yang ada. Penelitian ini bertujuan untuk melihat seberapa besar kecenderungan masyarakat provinsi DIY sebagai pengunjung Mall Malioboro dalam melakukan pembelian secara impulsif berdasarkan tipe pembelian impulsif dan menganalisis bagaimana tipe pembelian impulsif tersebut dalam pandangan Islam. Metode yang digunakan dalam penelitian ini adalah metode kuantitatif dengan menggunakan analisis uji pra survey berupa : Uji validitas, uji reliabilitas dan analisis frekuensi untuk menjelaskan hasil rata-rata jawaban dari para responden. Hasil dari penelitian ini adalah pengunjung Mall Malioboro Yogyakarta cenderung melakukan pembelian impulsif dengan tipe Pure Impulse dengan presentase sebesar 44% dan terdapat setidaknya tiga tipe pembelian impulsif yang tidak bertentangan dengan prinsip konsumsi Islami, yaitu Suggestion Impulse, Reminder Impulse, Planned Impulse.
Social presence and motivation in online environments: Second Life versus the Enocta Learning Management System/Adobe Connect

This study aims to compare the social presence and motivation of students taking a database II course using either the virtual world Second Life (SL) or the Enocta learning management system (LMS)/Adobe Connect. The study group consisted of 60 undergraduate sophomore students enrolled in a fully online computer programming program. Students were divided into two groups of 30. The first group was the experimental group taking the course on Second Life and the latter was control group taking the course through the Enocta LMS/Adobe Connect. A matching-only pre- and post-test control group design was applied. The data were collected through the Perceived Sociability Scale of Computer-Supported Collaborative Learning Environments (Sociability Scale) and the Motivated Strategies for Learning Questionnaire (MSLQ). The results of the study showed significant differences in motivation and social presence scores in favour of the students taking the course through Second Life.
Measurement and modelling of temperature cold pools in the Cerdanya valley (Pyrenees), Spain

The Cerdanya valley in northeast Spain experiences intense cold air pooling which decouples the valley atmosphere from the regional circulation, especially in winter. This makes air temperature prediction a challenge. A network of 40 temperature sensors was installed in 2012 along seven elevational transects to collect hourly temperatures throughout the cold pool, enabling measurement of the detailed cold pool structure for the first time. Sensors were also installed in the upper Conflent valley to the northeast for comparison, where previous research has shown that there is reduced cold air pooling. Sensor data were validated against automatic weather station observations at two locations. Through calculation of hourly lapse rates in various elevation bands for 2 years, frequent inversions developing up to 1450 m are shown, and sometimes extending much higher than this, concentrating in winter. Case studies of two intense episodes in December 2012 and January 2013 show that model simulations, despite being able to simulate broad mechanisms of cold air pooling formation, underestimate the amount of cooling. This is due to over‐enthusiastic simulation of a low level jet in the first case and mountain waves in the second. Solving these model problems has important consequences for the future ability to predict episodes of extreme low temperatures and associated hazards (frost, fog) in Cerdanya and mountain valleys elsewhere.
Versatile multidimensional pattern analysis for automated facial modeling and architecture parsing

This thesis presents a methodology that demonstrates how 2D image processing techniques can be applied to provide solutions for 3D models. Moreover, for the research sets the aim of evaluating the feasibility and effectiveness of this methodology by its implementation in two specified areas, namely, 3D facial mesh alignment and objects recognition in CAD floor plans, respectively. Regarding the former, an image processing method called optical flow is applied in order to help the registration of 3D meshes. Additionally, the novel algorithm is evaluated by comparing its performance with that of the-state-of-art techniques. In relation to the second application, the aspect of component recognition in CAD floor plans, image processing based automatic system for analysis and labelling floor plans drawn in Computer-aided Design (CAD) form is covered. Experiments comparing the proposed system against other mature systems are evaluated, along with the outcomes of a comprehensive user survey on the novel system being presented.
On self-organizing reservoirs and their hierarchies

Current advances in reservoir computing have demonstrated that fixed random recurrent networks with only readouts trained often outperform fully-trained recurrent neural networks. While full supervised training of such networks is problematic, intuitively there should also be something better than a random network. In this contribution we investigate a different approach which is in between the two. We use reservoirs derived from recursive self-organizing maps that are trained in an unsupervised way and later tested by training supervised readouts. This approach enables us to train greedy unsupervised hierarchies of such dynamic reservoirs. We demonstrate in a rigorous way the advantage of using the self-organizing reservoirs over the traditional random ones and using hierarchies of such over single reservoirs with a synthetic handwriting-like temporal pattern recognition dataset.
Metode Penelitian Komunikasi : dengan pendekatan kuantitatif

Penelitian dalam bidang ilmu komunikasi merupakan penelitian yang unik dan terus berkembang baik dari aspek pendekatan, metode, jenis maupun bentuknya. Terlebih lagi dengan objek yang ditelitinya berkembang begitu cepat seiring melesatnya fenomena dunia komunikasi. Untuk itu, para peneliti dalam bidang ini tidak dapat hanya mengandalkan satu atau dua pendekatan dan metode penelitian yang tepat, tetapi harus terus mempelajari berbagai pendekatan dan metode yang sesuai. Untuk menjawab itu semua, tentunya referensi buku-buku metode penelitian dalam bidang ini dituntut juga untuk terus mengimbanginya. Demikian yang diinginkan dalam buku sederhana ini, yaitu buku Metode Penelitian dengan pendekatan Kuantitatif dalam bidang Riset Komunikasi akan menyuguhkan bahasan mulai dari : (1) Akar Filsafat Penelitian; (2) Ilmu dan Penelitian Ilmiah; (3) Perumusan Masalah; (4) Teori, Kerangka Pemikiran dan Hipotesis; (5) Objek, Metode, Desain; (6) Operasionalisasi Variabel; (7) Sampling; (8) Pengumpulan Data dan Instrumentasi; (9) Analisis Data dan Pengujian Hipotesis; (10) Pembahasan, Simpulan, Referensi, dan Lampiran; (11)Menulis Proposal Kuantitatif riset Komunikasi; (12) Beberapa Aliran Kuantitatif dalam Ilmu Komunikasi; landasan praktis; (13) Teori-teori Komunikasi Bermazhab Kuantitatif. Demikian lengkapnya kajian dalam buku Metode penelitian bidang Ilmu Komunikasi ini sehingga mulai dari konsep sampai dengan bagaimana menyusun proposal hingga pelaporan, diharapkan mampu menjadi salah satu kekayaan referensi buku-buku metode penelitian ilmu komunikasi sebelumnya.
SPATIAL VISUALIZATION SKILLS OF HUNGARIAN AND TURKISH PROSPECTIVE MATHEMATICS TEACHERS

This report investigated spatial visualization skills of two samples of junior level prospective elementary mathematics teachers from Hungary (n=78) and Turkey (n=81) who were enrolled to elementary mathematics teacher training departments. This work was a correlational study and in the work a reduced version of Heinrich spatial visualization test (HSVT), which is a paper-pencil test consists of 25 items of spatial visualization problems related to synthesis and decomposition of pieces, was used. According to results, there was a significant difference between Hungarian and Turkish prospective mathematics teachers’ scores of HSVT in favor of Hungarian sample and there was no gender difference for each and overall groups. Moreover, we finally give descriptive results of the least and the most items marked correctly in HSVT in a brief way.
Identity, context collapse, and Facebook use in higher education: putting presence and privacy at odds

Abstract This study examines university student’s attitudes toward Facebook use, focusing specifically on how they feel about using a social network that encourages the performance of personal and social identity to support learning and interaction among classmates and instructors. Two surveys elicited student habits, preferences, and beliefs related to identity, privacy, and context collapse. Findings show mixed feelings about Facebook use in a formal school context. Although some students were amenable to it, other students were not. They also expressed concern about requiring non-users, who had clear reasons for avoiding Facebook, to obtain accounts. Students preferred to think about Facebook as a primarily social space for interacting with friends and family, and many expressed reluctance about being Facebook friends with their instructors. Students engaged in practices such as adjusting privacy settings and self censoring in order to avoid context collapse between their social identities and their classroom identities.
The quantification of the online control of goal-directed movement using frequency domain analysis

The field of motor control has devoted a lot of attention to the use of sensory information during movements for the maintenance of accuracy. This sensorimotor processing has been colloquially termed online control. Its accurate quantification and identification has posed a continual challenge to motor control researchers. Consequently, many measures of online control have been developed and have shaped the concurrent state of the field. Recent theories of online control have posited the existence of multiple distinct feedback processes. The current dissertation sought to gain insights into the multi-faceted nature of online control by evaluating the utility of frequency domain analyses as a tool for its quantification. Frequency domain analyses were hypothesized to be sensitive to the aforementioned distinct feedback processes given the assumption that they operate at unique timescales. Four experiments were conducted and evidence was obtained in favour of the utility of frequency domain analyses for the quantification of online control. Specifically, frequency domain analyses were found to be both one of the most sensitive measures to online control and the most robust measure to offline contamination. Thus frequency domain analyses represent an excellent choice for the evaluation of online control processes. Additionally, theoretical insights were attained through the sensitivity of frequency domain analyses to the contribution of two distinct processes contributing to reaching performance. The first was an iterative visuomotor process that influenced reaching performance at relatively stable rates. Notably, the specific rate of influence was found to be flexible based on the spatio-temporal requirements of reaching movements. Additionally, frequency domain analyses were found to be sensitive to a second, non-visual