Yönetim Bilişim Sistemleri Bölümü Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12469/68

Browse

Now showing 1 - 10 of 10

Citation - WoS: 18
Citation - Scopus: 23
Applying a Behavioural and Operational Diagnostic Typology of Competitive Intelligence Practice: Empirical Evidence From the Sme Sector in Turkey
(Taylor and Francis Group, 2012) Wright, Sheila; Bisson, Christophe; Duffy, Alistair P.
This paper reports on an empirical study conducted within the SME sector in the city of Istanbul Turkey. The findings from this study enabled the creation of a behavioural and operational typology of competitive intelligence practice one developed from the work of S. Wright D.W. Pickton and J. Callow (2002. Competitive intelligence in UK firms: A typology. Marketing Intelligence & Planning 20 349-360). Using responses to questions which indicated a type of behaviour or operational stance towards the various strands of CI practice under review it has been possible to identify areas where improvements could be made to reach an ideal situation which could garner significant competitive advantage for the SMEs surveyed. © 2012 Copyright Taylor and Francis Group LLC.
Citation - WoS: 12
Citation - Scopus: 12
Assessment of Chromite Liberation Spectrum on Microscopic Images by Means of a Supervised Image Classification
(Elsevier Science Bv, 2017) Camalan, Mahmut; Çavur, Mahmut; Hosten, Cetin
Assessment of mineral liberation spectrum with all its aspects is essential for plant control and optimization. This paper aims to estimate 2D mineral map and its associated liberation spectrum of a particular chromite sample from optical micrographs by using Random Forest Classification a powerful machine-learning algorithm implemented on a user-friendly and an open-source software. This supervised classification method can be used to accurately generate 2D mineral map of this chromite sample. The variation of the measured spectra with the sample size is studied showing that images of 200 particles randomly selected from the optical micrographs are sufficient to reproduce liberation spectrum of this sample. In addition the 2D spectrum obtained with this classification method is compared with the one obtained from the Mineral Liberation Analyzer (MLA). Although 2D mineralogical compositions obtained by the two methods are quite similar microscopic analysis estimates poorer liberation than MLA due to the residual noise (misclassified gangue) generated by the classification. Nevertheless we cannot compare the reliabilities of the two methods as there is not a standard produce yet to quantify the accuracy of MLA analysis. (C) 2017 Elsevier B.V. All rights reserved.
Citation - WoS: 6
Citation - Scopus: 10
A Competitive Intelligence Practices Typology in an Airline Company in Turkey
(Springer, 2020) Şahin, Murat; Bisson, Christophe
Oil prices, political instabilities, travel legislations, and many other competitive factors make it essential for any international airline with the instinct to survive to be on constant watch in such a fiercely competitive environment. To meet this need, it is vital for international airline companies to integrate competitive intelligence (CI) into their strategy building process. In this study, we create for the first time a typology of competitive intelligence practices of an international airline company (in Turkey), based on the model developed by (Wright et al.Journal of Strategic Marketing, 20(1), 19-33,2012), and it is one of the very first to investigate Competitive intelligence in this sector. Furthermore, we made a two-step cluster analysis to uncover hidden clusters that change the way of thinking within the company. Our findings show where the company would need to make improvements on the 6 strands of the model which are attitude, gathering, use, location, technological support, and IT support. Yet, that could lead towards stronger business performance. It might also inspire other companies of the airline sector and beyond.
Citation - WoS: 2
Citation - Scopus: 2
Determination of a Diffusion Coefficient in a Quasilinear Parabolic Equation
(De Gruyter Open Ltd, 2017) Kanca, Fatma
This paper investigates the inverse problem of finding the time-dependent diffusion coefficient in a quasilinear parabolic equation with the nonlocal boundary and integral overdetermination conditions. Under some natural regularity and consistency conditions on the input data the existence uniqueness and continuously dependence upon the data of the solution are shown. Finally some numerical experiments are presented.
A Generic Framework for Building Heterogeneous Simulations of Parallel and Distributed Computing Systems
(Springer Heidelberg, 2017) Dursun, Taner; Dağ, Hasan
There have been many systems available for parallel and distributed computing (PDC) applications such as grids clusters super-computers clouds peer-to-peer and volunteer computing systems. High-performance computing (HPC) has been an obvious candidate domain to take advantage of PDC systems. Most of the research on HPC has been conducted with simulations and has been generally focused on a specific type of PDC system. This paper however introduces a general purpose simulation model that can be easily enlarged for constructing simulations of many of the most well-known PDC system types. Although it might create a new vision for research activities in the simulation community current simulation tools do not provide proper support for cooperation between software working in real-time and simulation time. In this paper thus we also present a promising approach for constructing hybrid simulations that offers great potential for many research areas. As a proof of concept we implemented a prototype for our simulation model. Then we are able to rely on this prototype to build simulations of various PDC systems. Thanks to hybrid simulation support of our model we are able to combine and manage the simulated PDC systems with our previously developed policy-based management framework in simulation runs.
Citation - WoS: 4
Citation - Scopus: 6
Harmony Search Algorithm Based Management of Distributed Energy Resources and Storage Systems in Microgrids
(MDPI, 2020) Ceylan, Oğuzhan; Sezgin, Mustafa Erdem; Goel, Murat; Verga, Maurizio; Lazzari, Riccardo; Kwaye, Marcel Pendieu; Sandroni, Carlo
Microgrids are composed of distributed energy resources (DERs), storage devices, electric vehicles, flexible loads and so on. They may either operate connected to the main electricity grid (on-grid operation) or separated from the grid (islanded operation). The outputs of the renewable energy sources may fluctuate and thus can cause deviations in the voltage magnitudes especially at islanded mode. This may affect the stability of the microgrids. This paper proposes an optimization model to efficiently manage controllable devices in microgrids aiming to minimize the voltage deviations both in on-grid and islanded operation modes. RSE Distributed Energy Resources Test Facility (DER-TF), which is a low voltage microgrid system in Italy, is used to verify the algorithm. The test system's data is taken through an online software system (REDIS) and a harmony search based optimization algorithm is applied to control the device parameters. The experimental results show that the harmony search based optimization approach successfully finds the control parameters, and can help the system to obtain a better voltage profile.
Citation - WoS: 33
Citation - Scopus: 44
Semantic and Syntactic Interoperability for Agricultural Open-Data Platforms in the Context of Iot Using Crop-Specific Trait Ontologies
(MDPI AG, 2020) Aydın, Şahin; Aydın, Mehmet Nafiz
In recent years, Internet-of-Things (IoT)-based applications have been used in various domains such as health, industry and agriculture. Considerable amounts of data in diverse formats are collected from wireless sensor networks (WSNs) integrated into IoT devices. Semantic interoperability of data gathered from IoT devices is generally being carried out using existing sensor ontologies. However, crop-specific trait ontologies-which include site-specific parameters concerning hazelnut as a particular agricultural product-can be used to make links between domain-specific variables and sensor measurement values as well. This research seeks to address how to use crop-specific trait ontologies for linking site-specific parameters to sensor measurement values. A data-integration approach for semantic and syntactic interoperability is proposed to achieve this objective. An open-data platform is developed and its usability is evaluated to justify the viability of the proposed approach. Furthermore, this research shows how to use web services and APIs to carry out the syntactic interoperability of sensor data in agriculture domain.
Citation - WoS: 10
Citation - Scopus: 10
Two-Dimensional Inverse Quasilinear Parabolic Problem With Periodic Boundary Condition
(Taylor & Francis Ltd, 2019) Baglan, İrem Sakınç; Kanca, Fatma
In this study we consider a coefficient problem of a quasi-linear two-dimensional parabolic inverse problem with periodic boundary and integral over determination conditions. We prove the existence uniqueness and continuously dependence upon the data of the solution by iteration method. Also we consider numerical solution for this inverse problem by using linearization and the implicit finite-difference scheme.
Citation - WoS: 26
Citation - Scopus: 44
Unsupervised Anomaly Detection in Multivariate Spatio-Temporal Data Using Deep Learning: Early Detection of Covid-19 Outbreak in Italy
(Ieee-Inst Electrıcal Electronıcs Engıneers Inc, 2020) Karadayı, Yıldız; Aydın, Mehmet Nafiz; Öğrenci, Arif Selçuk
Unsupervised anomaly detection for spatio-temporal data has extensive use in a wide variety of applications such as earth science, traffic monitoring, fraud and disease outbreak detection. Most real-world time series data have a spatial dimension as an additional context which is often expressed in terms of coordinates of the region of interest (such as latitude - longitude information). However, existing techniques are limited to handle spatial and temporal contextual attributes in an integrated and meaningful way considering both spatial and temporal dependency between observations. In this paper, a hybrid deep learning framework is proposed to solve the unsupervised anomaly detection problem in multivariate spatio-temporal data. The proposed framework works with unlabeled data and no prior knowledge about anomalies are assumed. As a case study, we use the public COVID-19 data provided by the Italian Department of Civil Protection. Northern Italy regions' COVID-19 data are used to train the framework; and then any abnormal trends or upswings in COVID-19 data of central and southern Italian regions are detected. The proposed framework detects early signals of the COVID-19 outbreak in test regions based on the reconstruction error. For performance comparison, we perform a detailed evaluation of 15 algorithms on the COVID-19 Italy dataset including the state-of-the-art deep learning architectures. Experimental results show that our framework shows significant improvement on unsupervised anomaly detection performance even in data scarce and high contamination ratio scenarios (where the ratio of anomalies in the data set is more than 5%). It achieves the earliest detection of COVID-19 outbreak and shows better performance on tracking the peaks of the COVID-19 pandemic in test regions. As the timeliness of detection is quite important in the fight against any outbreak, our framework provides useful insight to suppress the resurgence of local novel coronavirus outbreaks as early as possible.
Citation - WoS: 1
Citation - Scopus: 3
When Sharing Less Means More: How Gender Moderates the Impact of Quantity of Information Shared in a Social Network Profile on Profile Viewers' Intentions About Socialization
(Routledge, 2014) Baruh, Lemi; Chisik, Yoram; Bisson, Christophe; Şenova, Başak
This study summarizes the results from a 2 (low vs. high information) × 2 (female vs. male profile) experiment that investigates the impact of quantity of information shared on a Social Network Site (SNS) profile on viewers' intentions to pursue further interactions with the profile owner. Quantity of information had no statistically significant effect on intentions to further socialize online. The two-way interaction between information quantity and profile gender was such that for male profiles more information increased profile viewers' intentions to further socialize with the profile owner whereas for female profiles the opposite was the case. The three-way interactions among quantity of information profile gender and profile viewer's gender underline a tendency for male profile viewers to respond more positively to higher information shared by profiles from their own gender. For female viewers this effect although in the same direction was smaller. © 2014 Copyright Eastern Communication Association.

Browse

Browsing Yönetim Bilişim Sistemleri Bölümü Koleksiyonu by WoS Q "Q2"