– The purpose of this paper is to investigate the factors that affect the adoption of cloud computing by firms belonging to the high‐tech industry. The eight factors examined in this study are relative advantage, complexity, compatibility, top management support, firm size, technology readiness, competitive pressure, and trading partner pressure., – A questionnaire‐based survey was used to collect data from 111 firms belonging to the high‐tech industry in Taiwan. Relevant hypotheses were derived and tested by logistic regression analysis., – The findings revealed that relative advantage, top management support, firm size, competitive pressure, and trading partner pressure characteristics have a significant effect on the adoption of cloud computing., – The research was conducted in the high‐tech industry, which may limit the generalisability of the findings., – The findings offer cloud computing service providers with a better understanding of what affects cloud computing adoption characteristics, with relevant insight on current promotions., – The research contributes to the application of new technology cloud computing adoption in the high‐tech industry through the use of a wide range of variables. The findings also help firms consider their information technologies investments when implementing cloud computing.

Understanding the determinants of cloud computing adoption

A survey on gaps, threat remediation challenges and some thoughts for proactive attack detection in cloud computing

Detecting outliers is a significant problem that has been studied in various research and application areas. Researchers continue to design robust schemes to provide solutions to detect outliers efficiently. In this survey, we present a comprehensive and organized review of the progress of outlier detection methods from 2000 to 2019. First, we offer the fundamental concepts of outlier detection and then categorize them into different techniques from diverse outlier detection techniques, such as distance-, clustering-, density-, ensemble-, and learning-based methods. In each category, we introduce some state-of-the-art outlier detection methods and further discuss them in detail in terms of their performance. Second, we delineate their pros, cons, and challenges to provide researchers with a concise overview of each technique and recommend solutions and possible research directions. This paper gives current progress of outlier detection techniques and provides a better understanding of the different outlier detection methods. The open research issues and challenges at the end will provide researchers with a clear path for the future of outlier detection methods.

Progress in Outlier Detection Techniques: A Survey

We present a descriptive literature review and classification scheme for cloud computing research. This includes 205 refereed journal articles published since the inception of cloud computing research. The articles are classified based on a scheme that consists of four main categories: technological issues, business issues, domains and applications, and conceptualising cloud computing. The results show that although current research is still skewed towards technological issues, new research themes regarding social and organisational implications are emerging. This review provides a reference source and classification scheme for IS researchers interested in cloud computing, and to indicate under-researched areas as well as future directions.

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A Descriptive Literature Review and Classification of Cloud Computing Research

In this review, the applications of molecularly imprinted polymer (MIP) materials in the area of electrochemical sensors have been explored. The designs of the MIPs containing different polymers, their preparation and their immobilization on the transducer surface have been discussed. Further, the employment of various transducers containing the MIPs based on different electrochemical techniques for determining analytes has been assessed. In addition, the general protocols for getting the electrochemical signal based on the binding ability of analyte with the MIPs have been given. The review ends with describing scope and limitations of the above electrochemical based MIP sensors.

Molecularly Imprinted Electrochemical Sensors

Determination and classification of white blood cells are very important for diagnosing many diseases. The number of white blood cells and morphological changes or blasts of them provide valuable information for the positive results of the diseases such as Acute Lymphocytic Leucomia (ALL). Recognition and classification of white cells as basophils, lymphocytes, neutrophils, monocytes and eosinophils also give additional information for the diagnosis of many diseases. We are developing an automatic process for counting, size determination and classification of white blood cells. In this paper, we give the results of the classification process for which we experienced a study with hundreds of images of white blood cells. This process will help to diagnose especially ALL disease in a fast and automatic way. Three methods are used for classification of five types of white blood cells. The first one is a new algorithm utilizing image matching for classification that is called the Speed-Up Robust Feature detector (SURF). The second one is the PCA that gives the advantage of dimension reduction. The third is the classification tree called dendrogram following the PCA. Satisfactory results are obtained by two techniques.

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White Blood Cells Classifications by SURF Image Matching, PCA and Dendrogram

Internet kullanımının insanlar arasındaki iletişimi, bilgi paylaşımını ve karşılıklı etkileşimi arttırarak günlük hayatımızı önemli ölçüde değiştirdiği artık kaçınılmaz bir gerçektir. “Nesnelerin Interneti (IoT: Internet of Things)” olarak adlandırılan yeni teknolojik kavram akıllı cihazların, birbirlerini algılayan ve iletişime geçebilen nesneler aracılığıyla akıllı bağlantısı şeklinde tanımlanmaktadır. Bu teknoloji ile çok sayıda, küçük boyutlu, kablosuz teknoloji kullanabilen algılayıcı (sensor) cihazlar ile yaşadığımız çevredeki (ev, okul, işyeri, fabrika, şehir vb.) hemen hemen bütün olayları izlemek ve bilgi toplamak mümkündür. Aynı şekilde üretim/imalat ile ilgili endüstriyel sistemlerden aktarılabilecek gerekli verileri de Bilgi Sistemi içinde kullanabilmek Endüstriyel IoT (IIoT) olarak isimlendirilen bir diğer kavramı ortaya çıkarmıştır. Ortamdaki algılayıcı cihazlardan ve üretimdeki veri terminallerinden gelen, gerçek zamanlı sürekli veri akışı, internet ortamında Bulut Servis Sağlayıcılar tarafından verilen depolama, veritabanı, uygulama hizmetleri ile Bilgi Sistemleri tarafından kullanılmaya hazır hale getirilmektedir. Böyle bir IIoT bilgi akışı günlük yaşantımızı, iş hayatını ve endüstriyel üretim sistemlerini olumlu yönde etkileyebilecek değişikliklere neden olacaktır. Endüstri ve IoT’nin birleştirilmesi ile üretimde kullanılan akıllı cihazlar, insan hatasını en aza indirerek, gerçek zamanlı bilginin karar destek sistemleri tarafından değerlendirilmesini sağlayacaktır. Bu da üretimde kalitenin arttırılması, maliyetlerin azaltılması, rekabetçi ürünler yaratılması gibi birçok olumlu etki yaratacaktır. Bu çalışmada Nesnelerin İnterneti’nin endüstriyel üretime uyarlanması ile ilgili çalışmalar incelenmiş, otomatik depolama, önleyici bakım, madencilik, akıllı çevre düzenlemeleri gibi farklı uygulama örneklerinde IoT’nin yarattığı olumlu katkılar tartışılmış ve gelişmeye açık hususlar hakkında bilgi verilmiştir.

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Internet of Things (IoT) Applications in Industry

• Software scrum development. • Software cost estimation is still a complex task. • Effort estimation techniques in scrum still has some flaws that need to be resolve. Scrum methodology is the most useful and adopted part of the agile methodology. Many organizations are adopting Scrum for the last decade to meet their software requirements. It is facilitating the software industries to develop software applications according to the user's requirements. Scrum helps to fulfill the customer's requirements by interacting with the client and developer. Instead of this, scrum still has some challenges that influence the cost of a scrum. These challenging factors include coordination, team size, change request, complexity, and issues in daily meeting sessions. Due to these factors mostly the cost and time exceed scrum-based projects. To overcome these issues from the accurate and precise estimation in the scrum project we have developed a web-based software system to estimate the effort of a user story as well as the budget. There are some sophisticated cost estimation techniques for scrum-based projects. But all estimation techniques have some limitations that make them less useful for estimation and overcoming the effects of these factors in the scrum. We have surveyed the multiple software industries to get the static findings of the survey. We have designed the 30 hypotheses that main aim to reveal how much the proposed estimation technique is valuable for the accuracy of estimation. For the inclusion of participants, we have set the age criteria to get the opinions of the most experienced programmers. The main aim of this paper is to provide knowledge about key challenging factors in Scrum that cause exceed in cost and time, and also briefly explain why existing scrum cost estimation techniques are not pertinent for projects. In the last, we propose a framework as a solution to manage these factors and control cost and time from exceeding. We also adopted this estimation technique in different case studies in software industries for findings and results. The technique calculates the efforts autonomously. We design a software-based estimation technique that collects inputs from team/s and estimates the cost and time of a project. In outcomes, we found that our cost estimation approach reduced the issues from scrum software project development and make it more proficient for estimation of projects. Our proposed estimation technique introduced the new concept of estimation that facilitate the client, software industry, and developers as well to meet the requirements of the client, fulfill the changes during the sprints/s development and deliver the project within the time and cost. 

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A software-based cost estimation technique in scrum using a developer's expertise

The report describes the type of improved uninformed or heuristic search algorithms that are well-suited for non-procedural implementation in Control network programming, and how this can be achieved using the tools for dynamic computation control

Non-procedural implementation of local heuristic search in control network programming

The report describes the means for dynamic control of the computation process that are available in Spider - a language for Control Network Programming.

Tuncay Ercan

Papers

White Blood Cells Classifications by SURF Image Matching, PCA and Dendrogram

Internet of Things (IoT) Applications in Industry

A software-based cost estimation technique in scrum using a developer's expertise

Non-procedural implementation of local heuristic search in control network programming

Control network programming with SPIDER: dynamic search control