A technology acceptance analysis for mhealth apps: the case of Turkey

The acceptance of mHealth (mobile health) apps has been on the increase throughout the world as well as in Turkey. There are two main indicators of mHealth success and acceptance, such as mHealth apps users’ satisfaction level and intention to use mHealth apps. In this context, the factors, including ease of use, trust, privacy, usefulness, and information quality are critical to analyze how they affect the acceptance of the mHealth apps by the Turkish users, and their satisfaction level with mHealth apps. Thus, the main objectives of this study are to (1) to explain how users perceive and use mHealth apps with technology acceptance analysis, (2) investigate whether the usefulness or uselessness of mHealth apps depends on user feelings about mHealth apps, (3) analyze the impacts of ease of use, trust, privacy, usefulness and information quality on mHealth users’ satisfaction and intention, and (4) identify users’ attitudes towards mHealth apps and their satisfaction level with mHealth apps in Turkey. A total of 282 participants from Turkey completed a survey analyzing the ease of use, trust, privacy, usefulness and information quality of mHealth apps to specify the reasons for mHealth acceptance. Statistical techniques were employed for data analysis. This study provides some managerial implications and scholarly recommendations to increase the acceptance of mHealth apps as well as helping mHealth apps designers to recognize the factors that influence the intention to adopt mHealth

Selection of Suitable Sites for Small Ruminant Production Using Remote Sensing and the Geographic Information System

The aim of this study was to determine the most suitable areas for small ruminant production in the Karaburunarea in Izmir province, Turkey. To this purpose, an inquiry model was first developed using remote sensing and ageographic information system. In developing the model, legal and technical factors were taken into consideration,and eight evaluation criteria (distance from settled areas, distance from lakes or similar water sources, distance fromprotected water catchment basins, distance from wind energy generators, distance from irrigation and drainage canals,slope, aspect-direction of slope-and land use class) and three evaluation classes in relation to these criteria (suitable,conditionally suitable and unsuitable) were planned. Later, the model was used to test the suitability of the study areain general and five sample farms in that area for suitability. According to all of the criteria of evaluation, 3.54% of the42,707.15 ha study area was found to be suitable for small ruminant production, 2.78% was conditionally suitable, and93.60% was unsuitable. As for the five sample farms in the study area, none of them was found to be suitable accordingto all of the evaluation criteria. In addition, suggestions were made for the functionality and effectiveness in use of thegeography information inquiry models used in the choice of places for small ruminant production

Mid-term outcomes of a smoking cessation program in hospitalized patients in Türkiye

INTRODUCTION 'Teachable moments', such as inpatient treatment periods, can be turned into opportunities for smokers to acquire healthy living behaviors. This study was conducted to evaluate the outcomes of smoking cessation interventions in an inpatient hospital setting. METHODS Data were collected for this single-arm prospective intervention cohort study between October 2021 and March 2022 from hospitalized patients at Recep Tayyip Erdo & gbreve;an University Training and Research Hospital in T & uuml;rkiye. Smoker patients received smoking cessation counseling and brief smoking cessation interventions during their hospitalization and were informed about how to apply to our hospital's smoking cessation outpatient clinic after discharge. They were followed via phone on the 3rd, 5th, and 7th day and the 1st, 3rd, 6th, and 12th month after their discharge, regarding their quit status as well as admissions to smoking cessation clinics. Quitters were confirmed by exhaled air carbon monoxide testing. Logistic regression analysis was performed to evaluate the presence of admission to the emergency department and family physicians at follow-up at 1st year. The model was adjusted in terms of age, sex, presence of malignancy, and education level. RESULTS Of the 183 patients included in the study, 163 participants completed periodic follow-up during one year, with quit rate of 47.2%. The rate of anxiety was higher among non-quitters compared to quitters (9.4% vs 1.2%) (p=0.024). Non-quitters were 19 times more likely to have emergency department admissions (AOR=19.64; 95% CI: 8.08-47.68) and eight times more likely to have family doctor visits (AOR=8.43; 95% CI: 4.05-17.53) than quitters. CONCLUSIONS This cessation program evaluated the quit rates of hospitalized patients in the first year and revealed that the rate of anxiety was higher in non-quitters compared to quitters. It would be an important approach to include psychiatric support in this practice

Güzel Yurt-Topaluşağı-Abbaslar (kahramanmaraş ili) jeolojisi ve petrografisi

TEZ5162Tez (Yüksek Lisans) -- Çukurova Üniversitesi, Adana, 2004.Kaynakça (s. 53-56) var.vii, 56 s. ; rnk. res. ; 30 m.

Etiketsiz verileri kullanarak web sayfası sınıflandırmasının etkinliğini arttırmak.

TEZ11780Tez (Doktora) -- Çukurova Üniversitesi, Adana, 2019.Kaynakça (s. 146 s. ) var.xx, 146 s. : tablo ; 29 cm.Etiketlenmemiş verilerle birçok alanda sıklıkla karşılaşılmakta ve bu verileri kullanmak için de etkili yollara ihtiyaç duyulmaktadır. Etiketlenmemiş verilerden faydalı bilgiler elde etmek için yarı-denetimli öğrenme yöntemleri kullanılmaktadır. Bu tez çalışmasında Çapraz Doğrulamalı Artımlı Paralel Eğitim (APE-ÇD) ve Artımlı Seri Eğitim (ASE) olarak adlandırılan iki farklı yarı-denetimli öğrenme yöntemi önerilmiştir. Önerilen yarı-denetimli öğrenme yöntemleri etiketlenmemiş verileri verimli bir şekilde etiketlemek için denetimli sınıflandırıcıları ve veri kümelerinin farklı görünümlerini kullanmaktadır. Bu nedenle öncelikle önerilen yarı-denetimli sınıflandırıcılarda hangi sınıflandırıcıların ve özellik çıkarma algoritmalarının kullanılması gerektiğini belirlemek amacıyla denemeler yapılmıştır. Önerilen yöntemlerin etkinliğini değerlendirmek için, bilinen iki yarı-denetimli öğrenme yöntemi olan Eş-Eğitim (“Co-Training”) ve Yinelemeli Çapraz Eğitim (“Iterative Cross Training”) metotları seçilmiştir. Web üzerinde yüksek miktarda etiketlenmemiş veriye ulaşılabileceği için tez kapsamında yapılan denemeler bu alandan toplanmış veri kümeleri ile yapılmıştır. Tezde herkese açık “SyskillWebert”, “WebKB” ve “Banksearch” ile elle toplanan Konferans veri kümelerinden elde edilen 13 adet iki sınıflı veri kümesi kullanılmıştır. Her bir veri kümesi için 30 adet rastgele seçilmiş etiketli başlangıç eğitim seti ile yöntemler karşılaştırılmış ve sonuçlar istatistiksel olarak analiz edilmiştir. Bu analizlere göre, önerilen iki yöntemin de performansının çok yüksek olduğu, özellikle APE-ÇD yönteminin tüm yöntemler arasında en yüksek sınıflandırma performansına sahip olduğu gösterilmiştir.There are plenty of unlabeled data in different areas and effective ways are needed to be found to use them. In order to drive the useful information from these unlabeled data, semi-supervised learning methods are used. In this thesis, two different semi-supervised learning methods are proposed, namely Incremental Parallel Training with Cross-Validation (IPT-CV) and Incremental Serial Training (IST). The proposed semi supervised learning methods employ supervised classifiers and different views of the datasets for labeling unlabeled data efficiently. Therefore, to determine which classifiers and feature extraction algorithms should be used in the proposed semi-supervised learning methods experiments are performed. Then, to evaluate the effectiveness of the proposed methods, two known semi-supervised learning methods are implemented; Co-Training, and Iterative Cross-Training (ICT). Since web is a land of unlabeled files that is increasing tremendously, the web domain is chosen for the experiments. In the thesis, 13 binary classification datasets are used from the publicly available WebKB (i.e., Course, Faculty, Project, and Student), Banksearch (i.e., Biology, Commercial Banks, Motor Sport, and Programming), SyskillWebert (i.e., Bands, Biomedical, Goats, and Sheep) datasets, as well as manually collected Conference dataset. Experiments on 30 different randomly chosen initial labeled sets are made for each dataset and the results are analyzed statistically. According to these analyses, it is observed that the performance of the two proposed methods are very high, especially the IPT-CV method has the highest classifying performance among all methods

Performance of Using Tag-based Feature Sets in Web Page Classification

As the Web is a large collection of data growing daily, an automatic Web page classification mechanism is needed to effectively reach to useful information. Majority of the Web pages are in the form of HTML documents, therefore the aim of this study is to explore the effect of HTML tags on classification process, and try to determine the most valuable HTML tags for feature extraction of the classification task. To achieve this goal, we employ 13 different datasets, and use 5 popular classifiers that are SVM, naïve bayes (NB), kNN, C4.5, and OneR. The statistical analysis shows that, the features extracted by using solely the anchor, <p> or <title> tags can be used as an alternative to the features extracted from the whole Web page. SVM is the best among the classifiers used in this study. Using the HTML tags for feature extraction improves classification accuracy

Selection of Suitable Sites for Small Ruminant Production Using Remote Sensing and the Geographic Information System

Bu araştırmada, İzmir ili Karaburun yöresinde küçükbaş hayvancılık işletmeleri için en uygun alanların belirlenmesi amaçlanmıştır. Bu amaçla, ilk olarak uzaktan algılama ve coğrafi bilgi sistemi kullanılarak bir sorgu modeli geliştirilmiştir. Modelin geliştirilmesinde, küçükbaş hayvancılık işletmeleri için uygun yer seçimine ilişkin yasal ve teknik esaslar dikkate alınarak, sekiz değerlendirme ölçütü (yerleşim yerlerine uzaklık, göl ve benzeri su kaynaklarına uzaklık, su havzaları koruma alanlarına uzaklık, rüzgar enerji santrallerine uzaklık, sulama ve drenaj kanallarına uzaklık, eğim, bakı ve arazi kullanım sınıfı) ve bu ölçütlere ilişkin üç değerlendirme sınıfı (uygun, koşullu uygun ve uygun değil) öngörülmüştür. Sonra, geliştirilen sorgu modeli ile araştırma alanı genelinin ve bu alan içerisindeki mevcut beş örnek işletmenin uygunluğu sorgulanmıştır. Tüm değerlendirme ölçütlerine göre, 42,707.15 ha’lık araştırma alanının % 3.54’ünün küçükbaş hayvancılığın yapılmasına “uygun”, % 2.78’inin “koşullu uygun” ve % 93.60’ının ise “uygun olmayan” alanlar olduğu belirlenmiştir. Araştırma alanındaki mevcut beş örnek işletmenin yerlerinin ise tüm değerlendirme ölçütlerine göre hiçbirinin uygun olmadığı belirlenmiştir. Ayrıca araştırmada, hayvancılık işletmesi yerlerinin seçiminde kullanılacak coğrafi bilgi sistemi sorgu modellerinin işlevselliğinin ve kullanım etkinliğinin arttırılmasına yönelik öneriler sunulmuştur.The aim of this study was to determine the most suitable areas for small ruminant production in the Karaburun area in Izmir province, Turkey. To this purpose, an inquiry model was first developed using remote sensing and a geographic information system. In developing the model, legal and technical factors were taken into consideration, and eight evaluation criteria (distance from settled areas, distance from lakes or similar water sources, distance from protected water catchment basins, distance from wind energy generators, distance from irrigation and drainage canals, slope, aspect-direction of slope-and land use class) and three evaluation classes in relation to these criteria (suitable, conditionally suitable and unsuitable) were planned. Later, the model was used to test the suitability of the study area in general and five sample farms in that area for suitability. According to all of the criteria of evaluation, 3.54% of the 42,707.15 ha study area was found to be suitable for small ruminant production, 2.78% was conditionally suitable, and 93.60% was unsuitable. As for the five sample farms in the study area, none of them was found to be suitable according to all of the evaluation criteria. In addition, suggestions were made for the functionality and effectiveness in use of the geography information inquiry models used in the choice of places for small ruminant production