On the Process of Understanding the Reading of Students with Mental Disabilities: An Examination of Teacher Practices

This study aims to examine the teacher adaptations related to the stages of the reading process used in the process of understanding the reading of students with mental disabilities according to different variables. A descriptive survey model which is one of the quantitative research methods was used in the study. In 2018-2019, to ensure the research sample, reliability, and validity of the scale, 361 classroom teachers were gathered from 18 primary schools of Meray and Kartay districts of Konya province. It was applied to 93 more classroom teachers to provide a confirmatory factor analysis of the scale. After ensuring validity and reliability, it was applied to 99 special education teachers working in primary schools in Karatay, Meram, and Selcuklu districts of Konya province for descriptive analysis. Scores of male teachers are a little higher than female teachers in the scale of teacher practices related to the stages of the reading process. Graduate-level teachers, who have received training in the scale of teacher practices related to the stages of the reading process, score at the undergraduate level. Yet, the observed difference was not statistically significant in question

Selectıon of the Most Effectıve Contractor Company in Insulatıon Sector wıth Grey Relational Analysıs Method

DergiPark: 497910ejovocGünümüz rekabet koşullarında işletmelerin özellikleyönetim boyutunda yüz yüze geldiği çok değişkenli karar problemleri dahakarmaşık hâl almaktadır. Bu denli girift hale gelen karar problemlerinin çokkriterli karar verme (ÇKKV) yöntemleri ile çözülmesi gerekli duruma gelmiştir.Amaç:Çalışmanın amacı, yalıtım sektörü işletmelerinin karşılaştığı kararproblemlerinin çözümü ve değerlendirilmesinde ÇKKV yöntemlerininkullanılabilirliğini göstermektir. Literatürde tedarikçi seçimine yönelikbirçok çalışma olmasına rağmen yalıtım sektöründe en etkin taşeron firmaseçimine yönelik çalışmaya rastlanmadığından bilimsel açıdan bu boşluğundoldurulması amaçlanmıştır.Veri Toplama ve Metodoloji: Çalışmanın uygulama kısmında Düzce ilinde yalıtımsektöründe faaliyet gösteren bir işletme için ihtiyacı olan bir konuda en etkintaşeron firmanın seçiminde gri ilişkisel analiz yöntemi kullanılmıştır. İlgiliveriler söz konusu işletmenin idarecilerinden sağlanmıştır. Bu kişiler aynızamanda karar vericiler olarak kabul edilmişlerdir. Sonuç ve Değerlendirme: Gerçekleştirilen karar analizi neticesinde; en etkintaşeron firma A5 (Hedef Metal) olmuştur. Sırası ile ikinci A4 (Özdoğan Metal)ve üçüncü A3 (Hakoğlu) çıkmıştır. Bulunan analiz sonuçları söz konusuişletmenin yetkilileri ile paylaşılmıştır. Bu konuda ileride yapılacakçalışmalar için modelin genel yapısında değişikliklere gidilerek güncelmetotlar ve hibrit yöntemlerin kullanılabileceği ön görülmektedir.In today's competitiveconditions, multivariate decision problems frequently encountered byenterprises are becoming more complex. It has become necessary to solve thedecision problems which have become so intrusive by using multi-criteriadecision making (MCDM) methods.Objective: The aim of thisstudy is to demonstrate the availability of MCDM methods in the solution andevaluation of decision problems encountered by the insulation sectorenterprises. Although there are many studies on the selection of suppliers inthe literature, there is no study of the most efficient subcontractor selectionin the insulation sector. It is aimed to fill this gap in terms of scientific.Data Collection andMethodology: Inthe application part of the study, grey relational analysis method was used inthe selection of the most effective subcontractor for a company in the insulationsector in Düzce province. The relevant data were obtained from the managers ofthe enterprises. They were also considered as decision-makers.Conclusion andEvaluation: Asa result of the conducted decision analysis; the most effective subcontractorwas A5 (Hedef Metal). The second A4 (Özdoğan Metal) and the third A3 (Hakoğlu)respectively. The results of the analysis were shared with the authorities ofthe relevant enterprise. It is foreseen that, current methods and hybridmethods can be used by making changes in the general structure of the model forfuture studies

Automated Hypertension Detection Using ConvMixer and Spectrogram Techniques with Ballistocardiograph Signals

Blood pressure is the pressure exerted by the blood in the veins against the walls of the veins. If this value is above normal levels, it is known as high blood pressure (HBP) or hypertension (HPT). This health problem which often referred to as the “silent killer” reduces the quality of life and causes severe damage to many body parts in various ways. Besides, its mortality rate is very high. Hence, rapid and effective diagnosis of this health problem is crucial. In this study, an automatic diagnosis of HPT has been proposed using ballistocardiography (BCG) signals. The BCG signals were transformed to the time-frequency domain using the spectrogram method. While creating the spectrogram images, parameters such as window type, window length, overlapping rate, and fast Fourier transform size were adjusted. Then, these images were classified using ConvMixer architecture, similar to vision transformers (ViT) and multi-layer perceptron (MLP)-mixer structures, which have attracted a lot of attention. Its performance was compared with classical architectures such as ResNet18 and ResNet50. The results obtained showed that the ConvMixer structure gave very successful results and a very short operation time. Our proposed model has obtained an accuracy of 98.14%, 98.79%, and 97.69% for the ResNet18, ResNet50, and ConvMixer architectures, respectively. In addition, it has been observed that the processing time of the ConvMixer architecture is relatively short compared to these two architectures

The effect of chromium supplementation on egg production, egg quality and some serum parameters in laying hens

The effects of chromium (Cr) on egg production, egg quality, egg yolk cholesterol level and selected serum parameters of laying hens were investigated. Sixty 16-wk-old Hyline White 77 strain were randomly assigned to two groups of 30 hens each and fed either a basal diet or basal diet supplemented with 20 ppm Cr (CrCl3.6H(2)O). Egg and blood samples were collected at monthly intervals after the egg production reached peak level. Sera were analysed for:chromium, calcium, inorganic phosphorus, magnesium, triglycerides and total cholesterol. Eggs were examined for interior or exterior quality and for yolk cholesterol content. Chromium supplementation resulted in a 1.88% reduction in feed consumption and 4.28% improvement in the efficiency of feed utilisation. Chromium had no effect on live weight change, overall mean egg production, egg weight, specific gravity, shape index, shell thickness and Haugh unit, but increased shell breaking strength, albumen and egg yolk index values were noted, Supplemental chromium had no significant effect on serum phosphorus, while it resulted in increases in calcium and magnesium concentrations at first sampling. Serum total cholesterol concentrations slightly decreased while triglyceride levels significantly decreased. Significant reductions were observed in yolk cholesterol content in chromium supplemented group at weeks 36 and 40 (p<0.001). The results of the experiment indicated that chromium supplementation to the diet of layers may be of practical value due to the slight reduction in feed consumption and improvement in efficiency of feed utilisation and reduced egg cholesterol content without any adverse effect on egg quality

Use of Differential Entropy for Automated Emotion Recognition in a Virtual Reality Environment with EEG Signals

Emotion recognition is one of the most important issues in human&ndash;computer interaction (HCI), neuroscience, and psychology fields. It is generally accepted that emotion recognition with neural data such as electroencephalography (EEG) signals, functional magnetic resonance imaging (fMRI), and near-infrared spectroscopy (NIRS) is better than other emotion detection methods such as speech, mimics, body language, facial expressions, etc., in terms of reliability and accuracy. In particular, EEG signals are bioelectrical signals that are frequently used because of the many advantages they offer in the field of emotion recognition. This study proposes an improved approach for EEG-based emotion recognition on a publicly available newly published dataset, VREED. Differential entropy (DE) features were extracted from four wavebands (theta 4&ndash;8 Hz, alpha 8&ndash;13 Hz, beta 13&ndash;30 Hz, and gamma 30&ndash;49 Hz) to classify two emotional states (positive/negative). Five classifiers, namely Support Vector Machine (SVM), k-Nearest Neighbor (kNN), Na&iuml;ve Bayesian (NB), Decision Tree (DT), and Logistic Regression (LR) were employed with DE features for the automated classification of two emotional states. In this work, we obtained the best average accuracy of 76.22% &plusmn; 2.06 with the SVM classifier in the classification of two states. Moreover, we observed from the results that the highest average accuracy score was produced with the gamma band, as previously reported in studies in EEG-based emotion recognition