Altan Koçyiğit

Middle East Technical University | METU · Department of Information Systems

The Software Product Line (SPL) approach receives more attention due to the observed benefits, such as cost reduction, quality improvements, and reduced delivery time. Although organizations are aware of its potential benefits, they face some challenges while creating a clear road map to adopt this approach. Capability maturity models are developed...

In federated learning, each participant trains its local model with its own data and a global model is formed at a trusted server by aggregating model updates coming from these participants. Since the server has no effect and visibility on the training procedure of the participants to ensure privacy, the global model becomes vulnerable to attacks s...

Availability of large, diverse, and multi-national datasets is crucial for the development of effective and clinically applicable AI systems in the medical imaging domain. However, forming a global model by bringing these datasets together at a central location, comes along with various data privacy and ownership problems. To alleviate these proble...

Availability of large, diverse, and multi-national datasets is crucial for the development of effective and clinically applicable AI systems in the medical imaging domain. However, forming a global model by bringing these datasets together at a central location, comes along with various data privacy and ownership problems. To alleviate these proble...

Leveraging data science can enable businesses to exploit data for competitive advantage by generating valuable insights. However, many industries cannot effectively incorporate data science into their business processes, as there is no comprehensive approach that allows strategic planning for organization-wide data science efforts and data assets....

Today, data analytics plays a vital role in attaining competitive advantage, generating business value, and driving revenue streams for organizations. Thus, the organizations pay significant attention to improve their data analytics maturity. Nevertheless, the existing literature is dramatically limited in proposing a comprehensive roadmap to assis...

Today, data science presents immense opportunities by turning raw data into manufacturing intelligence in data-driven manufacturing that aims to improve operational efficiency and product quality together with reducing costs and risks. However, manufacturing firms face difficulties in managing their data science endeavors for reaping these potentia...

In federated learning, each participant trains its local model with its own data and a global model is formed at a trusted server by aggregating model updates coming from these participants. Since the server has no effect and visibility on the training procedure of the participants to ensure privacy, the global model becomes vulnerable to attacks s...

Purpose The purpose of this paper is to investigate social and technical drivers of data science practices and develop a standard model for assisting organizations in their digital transformation by providing data science capability/maturity level assessment, deriving a gap analysis, and creating a comprehensive roadmap for improvement in a standar...

With the recent advancements in heterogeneous networks, particularly following the improvements in the Internet of Things (IoT) supporting infrastructures, various machine learning applications which use distributed computing facilities such as cloud, fog, and edge computing have gained popularity. One way of performing computationally intensive le...

Decision-making in everyday life has an essential role in effectively completing personal tasks and processes. The complexity of these processes and the resulting cognitive load of managing them may vary significantly. To decrease the cognitive load created by such decision-making efforts and to obtain better outcomes, recommendation systems carry...

Today, business success is essentially powered by data-centric software. Big data analytics (BDA) grasp the potential of generating valuable insights and empowering businesses to support their strategic decision-making. However, although organizations are aware of BDAs’ potential opportunities, they face challenges to satisfy the BDA-specific proce...

Today, data science presents immense opportunities by turning raw data into manufacturing intelligence in data-driven manufacturing that aims to improve operational efficiency and product quality together with reducing costs and risks. However, manufacturing firms face difficulties in managing their data science endeavors for reaping these potentia...

The ability to leverage data analytics can enhance the decision-making process in organizations by generating valuable insights. However, there is a limited understanding of how organizations can adopt data analytics as part of their business processes due to a lack of comprehensive roadmap with a structural approach like a Process Capability Matur...

There are few studies conducted on personal processes within the Business Process Management (BPM) domain. Personal processes are looser and more context- and person-dependent compared to the clearly defined business processes. This makes it more challenging to create solutions in this domain. In this study, a taxonomy is developed for personal pro...

Decision making in everyday life is one of the key activities that has significant effect in shaping the flow of living, the quality of life, and the effectiveness of completing daily life tasks. Recommendation systems are widespread, being used via various mediums to decrease the cognitive load of these decision-making activities. Personal process...

Advances in medical technology is not sufficient alone to satisfy the growing and emerging needs such as improving quality of life, providing healthcare services tailored to each individual, ensuring efficient management of care and creating sustainable social healthcare. There is a potential for substantially enhancing healthcare services by integ...

İçinde bulunduğumuz büyük veri çağında bilgi teknolojisi servislerinden ve nesnelerin interneti kaynaklarından üretilen veri miktarındaki üstel artış ile birlikte şirketlerin veriden elde edebileceği fayda da her geçen gün hızla artmaktadır. Ancak bu mevcut verileri etkin şekilde kullanmak, stratejik üstünlük elde etmek ve kendi iş süreçlerini iyil...

The proliferation of mobile technologies has paved the way for the widespread use of mobile health (mHealth) devices. This in turn generates a large amount of data, which is essentially big data, that can be used for various purposes. In order to obtain the maximum benefit from mHealth data, emerging big data technologies can be employed. In this c...

Complex Event Processing (CEP) is a promising approach for real-time processing of big-data streams originating from Internet of Things (IoT) devices. Even though scalability and flexibility are key issues for IoT applications, current studies are mostly based on centralized solutions and restrictive query languages. Moreover, development, deployme...

Purpose Predicting customers’ purchase behaviors is a challenging task. The literature has introduced the individual-level and the segment-based predictive modeling approaches for this purpose. Each method has its own advantages and drawbacks, and performs in certain cases. The purpose of this paper is to propose a hybrid approach which predicts cu...

The amount of data created in various sources over the Web is tremendously increasing. Trying to keep track of relevant sources is an increasingly time-consuming task. The traditional way of accessing information over the Web is pull-based. Users need to query data sources in certain time intervals where an important piece of information can be lat...

This paper analyzes the correlations between the problem domain measures such as the number of distinct nouns and distinct verbs in the requirements artifacts and the solution domain measures such as the number of software classes and methods in the corresponding object-oriented software. For this purpose, 14 completed software development projects...

Purpose The purpose of this paper is to propose a new RFM model called length, recency, frequency, monetary and periodicity (LRFMP) for classifying customers in the grocery retail industry; and to identify different customer segments in this industry based on the proposed model. Design/methodology/approach This study combines the LRFMP model and c...

Exponential growth in data volume originating from Internet of Things sources and information services drives the industry to develop new models and distributed tools to handle big data. In order to achieve strategic advantages, effective use of these tools and integrating results to their business processes are critical for enterprises. While ther...

Exponential growth in data volume originating from Internet of Things sources and information services drives the industry to develop new models and distributed tools to handle big data. In order to achieve strategic advantages, effective use of these tools and integrating results to their business processes are critical for enterprises. While ther...

This paper describes the design and implementation of a novel approach to dynamically adjust the recommendation list size for multiple preferences of a user. By considering users’ earlier preferences, machine learning techniques are employed to estimate the optimal recommendation list size according to current conditions of users. The proposed appr...

Average reciprocal hit rank (ARHR) is a commonly used metric for ranking evaluation of top-n recommender systems. However, it suffers from an important shortcoming that it cannot be applied when the user has multiple preferences at a time. In order to overcome this problem, a modified version of ARHR metric is introduced and applied to grocery shop...

Detailed requirements is the primary input of software size measurement and effort estimation methodologies and a significant amount of time and expertise is needed for size measurement. In order to streamline size measurement and effort estimation, this study exploits the correlations between the problem domain measures such as the number of disti...

The use of mobile applications and their functionality are increasing day by day but mobile devices are still inferior to ordinary computers in terms of memory and processor capacity. Furthermore, the rapid depletion of the mobile devices’ energy is still a major problem. Performance and energy shortcomings of mobile devices can be improved by usin...

Various types of wireless networks have been developed and deployed including 3G, WLAN, WiMAX, LTE and LTE Advanced. User connectivity and network performance can be improved using vertical handover techniques which involve switching between available networks in heterogeneous environments. In this respect, recently there has been an increased inte...

In recent years, there has been an increased interest in the integration of different technologies in heterogeneous environments. Modelling heterogeneous systems is a complex task and handover schemes should consider issues such as network coverage, mobility, and Quality of Service (QoS). Analytical models are useful to deal with this complexity. T...

Wireless sensor networks (WSNs) are resource-scarce networks and the optimization of the resources is challenging. As far as random deployment is concerned, the optimization of these resources becomes even more difficult In this paper, a novel framework is proposed for solving optimal deployment problems for randomly deployed and clustered WSNs. In...

Wireless sensor networks (WSNs) are resource-scarce networks and the optimization of the resources is challenging. As far as random deployment is concerned, the optimization of these resources becomes even more difficult. In this paper, a novel framework is proposed for solving optimal deployment problems for randomly deployed and clustered WSNs. I...

Predicting how much effort will be required to complete a software project as early as possible is a very important factor in the success of software development projects. Including function points and its variants, there are several size measures and corresponding measurement methods that can be used for effort estimation. However, in most of the...

It is an important issue in the software industry to predict how much effort will be required for a software project as early as possible. Software size is one of the commonly used attributes in effort estimation. In this paper, we propose an early software size and effort estimation method based on conceptual model of the problem domain. Our metho...

Smart phones are not capable of competing against their desktop counterparts or servers in terms of CPU speed, battery, memory and storage. However, a mobile device can transparently use cloud resources by employing an offloading mechanism. Offloading enables mobile devices to run computation intensive applications such as object recognition, Optic...

Two stage open queuing networks are used for modeling the subsystem-behaviour in computers and communication networks, mass storage devices, memory servers, and queuing analysis of wireless mobile cellular networks. The queuing analysis of wireless systems is essential in order to quantify the impact of different factors on quality of service (QoS)...

Clustering is considered a common and an effective method to prolong the lifetime of a wireless sensor network. This paper provides a new insight into the cluster formation process based on uniformly quantizing the residual energy of the sensor nodes. The unified simulation framework provided herein, not only aids to reveal an optimum number of clu...

In this paper, a novel method is proposed to dimension a randomly deployed heterogeneous wireless sensor network (WSN) of minimum monetary cost satisfying minimum coverage and minimum lifetime requirements. We consider WSNs consisting of two different types of nodes clusterheads and ordinary sensor nodes, randomly deployed over a sensing field. All...

Analytical solutions for two-dimensional Markov processes suffer from the state space explosion problem. Two stage tandem networks are effectively used for analytical modelling of various communication and computer systems which have tandem system behaviour. Performance evaluation of tandem systems with feedbacks can be handled with these models. H...

Fault-tolerant systems with repair-upon-failure strategy can become expensive in terms of labour and time. Postponing non essential repairs can reduce these costs. Of course, while postponing these repairs, it is essential to keep the whole system capable to deal with user requests. For this purpose, usually, a threshold value is defined which repr...

Clustering is an efficient method to solve scalability problems and energy consumption challenges. For this reason it is widely exploited in Wireless Sensor Network (WSN) applications. It is very critical to determine the number of required clusterheads and thus the overall cost of WSNs while satisfying the desired level of coverage. Our objective...

Fault-tolerant systems with repair-upon-failure strategy can become expensive in terms of labour and time. Especially for homogeneous multi-server systems, if no control hierarchy exists, postponing non essential repairs can reduce these costs without affecting the availability of the whole system significantly. Of course, while postponing these re...

Fault tolerant, large scale multi-server systems require an optimum number of repairmen for maximising performability. However, performability evaluation of such systems is difficult due to the state space explosion problem. In this paper, a simple and flexible approximate technique capable of overcoming state space explosion problem in computing t...

In order to be context-aware, a system or application should adapt its behaviour according to current context, acquired by various context provision mechanisms. After acquiring current context, this information should be matched against the previously defined context sets. In this paper, a granular best match algorithm dealing with the subjective,...

In this paper, a novel routing and wavelength assignment algorithm for optical wavelength routing networks is introduced and its performance is evaluated by using simulations. The algorithm is based on statistically predictive minimization of path reconfiguration probability. In this approach, the path reconfiguration probability, that is the proba...

A survey of recent literature on all optical networking is presented. Starting from multiplexing techniques and topological features, network design and performance issues are reviewed. Particular attention is devoted to Wavelength Division Multiplexing (WDM) networks. Static and dynamic solutions of the routing and wavelength assignment (RWA) prob...