A comparative analysis of the effects of instructional design factors on student success in e-learning: multiple-regression versus neural networks

This study explores the relationship between the student performance and instructional design. The research was conducted at the E-Learning School at a university in Turkey. A list of design factors that had potential influence on student success was created through a review of the literature and interviews with relevant experts. From this, the five most import design factors were chosen. The experts scored 25 university courses on the extent to which they demonstrated the chosen design factors. Multiple regression and supervised artificial neural network (ANN) models were used to examine the relationship between student grade point averages and the scores on the five design factors. The results indicated that there is no statistical difference between the two models. Both models identified the use of examples and applications as the most influential factor. The ANN model provided more information and was used to predict the course-specific factor values required for a desired level of success

Çok kademeli tedarik zincirlerinde kamçı etkisinin azaltılması için yeni bir model önerisi : genişletilmiş satıcı yönetimli envanter modeli

06.03.2018 tarihli ve 30352 sayılı Resmi Gazetede yayımlanan “Yükseköğretim Kanunu İle Bazı Kanun Ve Kanun Hükmünde Kararnamelerde Değişiklik Yapılması Hakkında Kanun” ile 18.06.2018 tarihli “Lisansüstü Tezlerin Elektronik Ortamda Toplanması, Düzenlenmesi ve Erişime Açılmasına İlişkin Yönerge” gereğince tam metin erişime açılmıştır.Tedarik zincirlerinde, küreselleşen pazarlar ile talepteki belirsizliğin artması sonucunda ortaya çıkan kamçı etkisi önemli bir problemdir. Bu olumsuz etkinin üstesinden gelebilmek için firmalar, bilgi paylaşımı temelli yeni yönetim yaklaşımlarını tercih etmektedirler. Satıcı yönetimli envanter; üst kademenin alt kademe stok yönetimi sürecinin kontrolünü ele aldığı, bilgi paylaşımı temelli bir yönetim felsefesidir. Aynı zamanda tedarik ağı boyunca kamçı etkisi değerlerinin azaltılmasında önemli faydalar sağlamaktadır.Bu çalışma da; satıcı yönetimli envanter yaklaşımlarının sağladığı faydaların çok kademeli tedarik ağlarına genişletilmesi amacıyla yeni bir ?genişletilmiş satıcı yönetimli envanter? modeli önerilmiştir. Genişletilmiş modelde, değişken talep ve değişken teslim süreleri koşulları ile çalışan talep tahmini tabanlı dinamik stok kontrol politikası ele alınmıştır. Önerilen yeni modelin klasik tedarik zinciri yönetimi ve satıcı yönetimli envanter yaklaşımları ile karşılaştırılması için benzetim uygulaması gerçekleştirilmiştir. Karşılaştırılan modellerin sonuçları toplam zincir maliyeti, kamçı etkisi, sipariş erteleme oranı ve stok miktarı performans ölçütleri açısından tek yönlü varyans analizi (ANOVA) testi ile değerlendirilmiştir. Genişletilmiş satıcı yönetimli envanter modeli ile kamçı etkisi değerlerinde önemli düşüşler sağlanmıştır. Ayrıca toplam zincir maliyetleri ve stok miktarlarını düşürülürken, sipariş erteleme oranlarında müşteri hizmet seviyesi hedeflerinden sapmanın olmadığı sonucuna ulaşılmıştır.Geliştirilen modelin, üretici odaklı yapısından dolayı farklı sektörlerde kullanım alanı (beyaz eşya, otomotiv ve benzeri) bulunabileceği düşünülmektedir. Ayrıca genişletilmiş model kullanımıyla üreticilerin elde etikleri faydaların, dağıtıcı ve perakendecilerine, miktar, fiyat veya maliyet indirimleri şeklinde dağıtılması sonucunda, kullanılabilecek sektörlerin sayısında artış sağlanabileceği öngörülmektedir.In supply chains, bullwhip effect, which was emerged due to raising demand uncertainties in global markets, has been considered as an essential problem in the current body of the literature and causes negative financial impact on companies. Firms prefer adopting new management approaches that are based on information sharing in order to overcome this negative effect. Vendor managed inventory is one of the information based management approaches that suggests upstream supply chain member takes control of the inventory management processes of the downstream member. Also it provides important benefits on reducing the bullwhip effect values along with the supply chain network.In this thesis, a new model that is called ?extended vendor managed inventory? was proposed with purpose of extending the benefits of the vendor managed inventory to multi echelon supply network. In the extended inventory model, a dynamic inventory control policy based on demand forecasting was followed in which demand and lead time variables may vary during the process. A simulation study was developed and conducted in order to compare the proposed model with traditional supply chain management and vendor managed inventory approaches. The comparison results were evaluated using one way analysis of variance (ANOVA) based on the following performance criteria; total supply chain costs, bullwhip effect, backorder rate and inventory level. Through utilizing the proposed extended vendor managed inventory model, a significant reduction was achieved in bullwhip effect values. Also, the results showed that there was no deviation on customer service level targets in backorder rate amongst the comparative models while the proposed model produced better outcomes by achieving decreased values on total supply chain costs and inventory levels.The proposed model may be applicable on different industrial application domain areas eg., home appliances and automotive due to its producer-driven structure. Furthermore, expanding the benefits obtained by the producers using the proposed model to its distributors and retailers in the forms of quantity, price and cost discounts may facilitate further applicability of the model in different application domains

A conceptual framework of a cloud-based customer analytics tool for retail SMEs

Since customers are seen as a strategic element in a company’s downstream supply chain, many retail organizations have been employing a customer-centric business strategy and started investing into such technologies and solutions known as customer analytics that are capable of processing huge amount customer data for enhanced decision making. Customer analytics has been of significant importance in most developed economies around the world particularly for large organizations. The off-the-shelf analytics solutions provided by vendors are perceived to be unmanageable, risky and unaffordable especially for Small and Medium Enterprises (SMEs) operating in retail sector. This becomes more vital for the SMEs in developing countries especially in the Eastern part of Europe where they constitute a noteworthy part of the economy. The majority of the SMEs in these countries lack of facilities, infrastructure and abilities to perform such analytical applications. Not being able to extract strategic knowledge using customer data is a missing component for them to be competitive and sustainable in the market from relationship marketing point of view. The aim of this paper is to propose a conceptual model that addresses this problem by providing retail SMEs with a cloud-based open platform for customer data analytics and knowledge extraction. The platform will be able to connect with numerous apps already employed at the retail SMEs, acquire customer data and then perform customer analytics in order to produce a rich set of reports and knowledge

An Empirical Assessment of Customer Lifetime Value Models within Data Mining

Customer lifetime value has been of significant importance to marketing researchers and practitioners in specifying the importance level of each customer. By means of segmentation which could be carried out using value-based characteristics it is indeed possible to develop tailored strategies for customers. In fact, approaches like data mining can facilitate extraction of critical customer knowledge for enhanced decision making. Although the literature has several analytical lifetime value models, comparative assessment of the existing models especially within the context of data mining seems a missing component. The aim of this paper is to compare two different customer lifetime value models within data mining. The evaluation was carried out within the context of customer segmentation using a database of a company operating in retail sector. The results indicated that two models yield the same segmentation structure and no statistical differences detected on the select control variables. However, the remaining model produced rather different segmentation results than their peers and it was possible to identify the most lucrative model according to the statistical analyses that were carried out on the select control variables

Clinical Characteristics and Visual Outcomes of Pediatric Optic Neuritis: A Single Center Experience

INTRODUCTION: The aim of this study was to describe the clinical characteristics, visual outcomes of pediatric patients presenting with first-episode of optic neuritis. METHODS: We reviewed medical records of the patients newly diagnosed with optic neuritis younger than 18 years between January 2014 and December 2018 retrospectively. RESULTS: Twenty-eight patients were included to this study. The mean age at first onset of optic neuritis was 13.2+-3.1 years (range 6.2-17.3 years). The mean follow-up period was 4.2+-3.2 (range 0.6-13.08) years. 7 of 28 (25%) patients had recurrent optic neuritis. Optic neuritis involvement was unilateral in 17 of 28 (60%) patients. Forty percent of the patients had idiopathic optic neuritis. Of the six patients with demyelinating lesions in cranial magnetic resonance imaging (MRI) at the first admission, three were diagnosed with multiple sclerosis (MS) at the time of first optic neuritis attack, and three were diagnosed within 13.4+-4.8 months after the first episode. Eight of 21 optic neuritis patients (38%) had oligoclonal band positivity and the incidence of MS was significantly higher in these patients (p=0.014). The mean visual acuity at nadir was 0.48+-0.27 at admission. Whereas it was 0.74+-0.31 and 0.76+-0.33 at 1 and 6 months respectively. There was a strong correlation between first and sixth-month visual acuity (r=0.98, p=0.00). DISCUSSION AND CONCLUSION: Our study demonstrated that poor visual acuity (worse than 0.5) at 1 month can predict poor vision at 6 months. The patients with demyelinating lesions in cranial MRI at their first optic neuritis episode, are more likely to develop MS during the follow-up

İnternet destekli öğretimde öğrencilerin başarısını etkileyen faktörlerin istatistiksel yöntemler ve yapay sinir ağları ile analizi

Bu tezin, veri tabanı üzerinden yayınlanma izni bulunmamaktadır.ÖZET Anahtar Kelimeler: Uzaktan Öğretim, İnternet Destekli Öğretim, istatistiksel Analiz, Yapay Sinir Ağlan Internet destekli öğretim sistemlerinde öğrenci başarısını etkileyen faktörler kişisel ve demografik karakteristikler, öğretim yönetim sistemi ve öğretimsel ortam tasarımı şeklinde dört grupta sınıflandırılır. Kesin sınırların ve standartların belli olması yüzünden öğretim yönetim sistemlerinin basan üzerindeki etkisi sınırlı sayılabilir. Kişisel değişkenler ise tahmin edilmesi ve nümerikleştirilmesi zor değerlerdir. Bu yüzden demografik değişkenlerin ve öğretimsel ortam tasarımı faktörlerinin basan üzerindeki etkisinin araştınlmasmda fayda vardır. Çalışama, internet destekli öğretim öğrencilerinin başanlanmn demografik ve öğretimsel ortam tasarımı faktörleri ile ne ölçüde değiştiğinin belirlenmesi amacıyla hazırlanılmıştır. Çalışmaya genel bir giriş yapıldıktan sonra ikinci bölümde literatürde bu alanda yapılan çalışmalar hakkında kısa bilgiler verilmiştir. Üçüncü bölümde uzaktan öğretim ve internet destekli öğretim kavramları tanıtılmıştır. Dördüncü bölümde istatistiksel analiz yöntemleri ve yapay sinir ağlan hakkında teorik bilgi sunulmuştur. Beşinci bölümde ise istatistiksel analizler ve yapa sinir ağlan ile öğrenme uygulamaları anlatılmıştır. Son bölümde sonuçlar tartışılmış ve öneriler sunulmuştur. Yapılan istatistiksel testler sonucunda demografik etkenlerden yaş, aile reisinin meslek kategorisi, mezun olunan lisenin bulunduğu bölge ve liseden mezuniyet yılı değerleri ile basan düzeyleri arasında anlamlı bir ilişki bulunmuş, kardeş sayısı ile basan düzeyi arasında anlamlı bir ilişkiye rastlanmamıştır. Yapılan regresyon analizi sonucunda öğretimsel ortam tasanmı faktörleri olarak belirlenen, metin uzunluğu, örnek ve uygulama kullanımı, çalışma sorulan, kısa sınav ve ödevler, çoklu ortam uygulamalan ve görsel bütünlük ile basan düzeyleri arasında anlamlı bir ilişki bulunmuştur. Aynca aym değerle yapay sinir ağı modellerinden çok katmanlı algılayıcı modeli ile tekrar işlenmiş. Ağa öğretilen değerler sonucunda tahmin sonuçları elde edilmiştir. Bu kısımda regresyon sonuçlan ile yapay sinir ağının ürettiği değerler arasında karşılaştırmalı bir analiz yapılmış, yapılan test sonucunda iki farklı yöntemin benzer sonuçlar ürettiği sonucuna ulaşılmıştır.ANALYZING FACTORS EFFECT ON THE SUCCESS OF WEB BASED LEARNING STUDENTS' WITH STATISTICAL METHODS AND NEURAL NETWORKS SUMMARY Key words : Distant Learning, Internet Based Learning, Statistical Analysis, Neural Networks The factors which effect to student's success on Internet Based Learning can be classified in four group as personal characteristics, demographic characteristics, learning management system and instructional design. With explicit limits and standards of learning management systems' effects on student's success can be respected as finite. Personal variables are hard values to predict and to be numerical. So, researching the effects of demographic variables and instructional desing would be more effective. This study was prepared to determine how the demographic and instructional design factors change the internet based learning students' successes. After a general introduction, in second chapter short briefings was presented about this literature. In third chapter, distant learning and internet based learning concepts are explained. In fourth chapter, teorical information about statistical analysis methods and neural networks are given. In fifth chapter, learning applications about statistical analysis and neural networks were presented. In last chapter, consequences were discussed and suggestions were presented. After making statistical tests, a meaningful relationship was found between success factors and demographic factors such as age, profession of family man, distinct of the graduation of high school and high school graduation year. A meaningful relationship between success factors and number of brothers/sisters could'nt found. After a regression analysing, a meaningful relationship was found between success factors and instructional design factors before such as length of text, sample and application usage, study questions, short exams and studies, multimedia applications and visual entirety. Furthermore, same values will be processed with multi layer perception model from neural network models. After teaching these values to the network, prediction values were found. In this chapter, a comparative analysis made between regression consequences and values produced by neural network, so two different methods were produced same consequences. X

Determination Of The Critical Success Factors In Disaster Management Through The Text Mining Assisted Ahp Approach

In the academic field and as well as the application field, substantial attention has been drawn to coping with disasters. Since natural dangers causing a large proportion of disasters cannot be avoided, attempts to combat disasters have centered on preventing hazards from evolving into disasters through measures and restructuring works taken before, during, and after the disaster. There are many players involved in the disaster management process and many factors are influential in the effectiveness of this process. Among these factors, deciding the critical ones offers significant advantages, particularly in terms of practical studies. Concentrating on a single stakeholder in deciding the factors crucial to the success of this management structure, which has many stakeholders, can cause to ignoring the significant viewpoints of other stakeholder groups. Accordingly, for the evaluation of several success factors achieved as a result of a thorough and systematic literature review, the purpose of our study is to develop a common critical success factor model that will represent both the viewpoints of operational experts and academic experts, who constitute the stakeholders of this domain. Analytical Hierarchy Process (AHP) is utilized to determine the opinions of field experts while the text mining method was used to determine the perspectives of academics. In the study, therefore, a new AHP model assisted by text mining is introduced. Socio-cultural factors were brought to light by the analysis results of the suggested model. It has been determined by the results of the study that these two perspectives are overlapped largely in the organizational field and relatively in socio-cultural, environmental, and legal fields

Investigation of the effect of cutting parameters on cutting quality in laser cutting of AISI 310 Quality austenitic stainless steel sheet material

Yapılan çalışmada, AISI 310 paslanmaz sac malzemesinin lazer tezgâhında kesilmesiyle kesmeparametrelerinin yüzey pürüzlülüğü ve kerf genişliğine etkileri araştırılmıştır. Lazer kesme deneyleri iki farklı gazbasıncı (0.8 bar ve 1 bar), dört farklı kesme hızı (20 mm.dak-1, 24 mm.dak-1, 28 mm.dak-1ve 32 mm.dak-1) ve dörtfarklı frekansta (3500 Hz, 4000 Hz, 4500 Hz ve 5000 Hz) yapılmıştır. Deneyler sonucunda numunelerin yüzeypürüzlülüğü ve kerf genişliği ölçülmüştür. Ayrıca lazer kesme parametrelerinin yüzey pürüzlülüğü ve kerfgenişliği üzerine etkilerini belirlemek amacıyla varyans analizleri yapılmıştır. Lazer kesme deneylerinde en düşük(2.78 µm) yüzey pürüzlülüğü için optimum lazer kesme parametresi olarak 1 bar basınç, 5000 Hz frekans ve 32mm.dak-1 kesme hızı olmuştur. En düşük (0.79 mm) kerf genişliği için optimum lazer kesme parametresi 0.8 barbasınç, 3500 Hz frekans ve 20 mm.dak-1 kesme hızı olarak tespit edilmiştir. Lazer kesme deneylerinde kesmehızının ve frekansın artması ile yüzey pürüzlülük değerlerinin azaldığı görülmüştür. Kesme hızının artırılmasıkerf genişliğinin azalmasına neden olurken, frekans değerinin artması kerf genişliğinin artmasına neden olmuştur.Varyans analizlerinin sonucunda da % 38.67 ile yüzey pürüzlülüğü ve % 49.50 ile kerf genişliği üzerine en etkinparametre kesme hızının olduğu tespit edilmiştir.In this study, the cutting experiments of AISI 310 stainless sheet material on the laser bench were done and the effects of the processing parameters on the surface roughness and kerf width were investigated. Laser cutting experiments were carried out at two different gas pressures (0.8 bar and 1 bar), four different cutting speeds (20 mm.min-1, 24 mm.min-1, 28 mm.min-1 and 32 mm.min-1 ) and four different frequencies (3500 Hz, 4000 Hz, 4500 Hz and 5000 Hz). As a result of the experiments, the surface roughness and kerf width of the samples were measured. In addition, variance analysis were carried out to determine the effects of laser cutting parameters on surface roughness and kerf width. In laser cutting experiments, the optimum laser cutting parameter for the lowest (2.78 µm) surface roughness was 1 bar pressure, 5000 Hz frequency and 32 mm.min-1 cutting speed. For the lowest (0.79 mm) kerf width, the optimum laser cutting parameter was determined as 0.8 bar pressure, 3500 Hz frequency and 20 mm.min-1 cutting speed. In laser cutting experiments, it was observed that surface roughness values decreased with increasing cutting speed and frequency. While increasing the cutting speed caused the kerf width to decrease, the increase in the frequency value caused the kerf width to increase. As a result of variance analysis, it was determined that the most effective parameter cutting speed on surface roughness with 38.67% and kerf width with 49.50%

Investigation the effect of cutting parameters on surface roughness, kerf width and dross height in laser processing of AISI 304 stainless sheet material

Yapılan çalışmada, AISI 304 paslanmaz sac malzemenin lazer kesim işleminde kesme parametrelerinin yüzey pürüzlülüğü, kerf genişliği ve çapak yüksekliği üzerine etkileri araştırılmıştır. Lazer kesme işleminde iki farklı gaz basıncı (0.8 bar ve 1 bar), dört farklı kesme hızı (20 mm/sn, 24 mm/sn, 28 mm/sn ve 32 mm/sn) ve dört farklı frekans (3500 Hz, 4000 Hz, 4500 Hz ve 5000 Hz) değerleri kullanılmıştır. Yüzey pürüzlülüğü ölçümleri, değişken kesme parametreleriyle kesilmiş sac malzeme üzerinde yapılmıştır. Dijital mikroskop kullanılarak numunelerin kerf genişlikleri ve çapak yükseklikleri ölçülmüştür. Sonuç olarak, kesme hızının artması ile yüzey pürüzlülüğü, kerf genişliği ve çapak yüksekliğinin azalmasına neden olmuştur. Frekans değerinin artırılması yüzey pürüzlülük ve çapak yüksekliğinin azalmasına ve kerf genişliğinin artmasına neden olmuştur. Frekans değerinin değiştirilmesinin çapak yüksekliği üzerine önemli bir etkisinin olmadığı görülmüştür.In the study, laser cutting of AISI 304 stainless sheet material were investigated the effects of cutting parameters on surface roughness, kerf width and dross height. In laser cutting were used two different gas pressures (0.8 bar ve 1 bar), four different cutting speeds (20 mm/sec, 24 mm/sec, 28 mm/sec ve 32 mm/sec) and four different frequency (3500 Hz, 4000 Hz, 4500 Hz ve 5000 Hz). Surface roughness measurements were made on the sheet material cut with variable cutting parameters. Kerf widths and dross heights of the samples were measured using a digital microscope. As a result, the increase in cutting speed has caused surface roughness, kerf width and dross height to decrease. Increasing the frequency value has caused the surface roughness and dross height to decrease and kerf width to increase. It has been observed that changing the frequency value does not have a significant effect on the burr height