WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/20.500.14365/5

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1,25-Dihydroxyvitamin D3 Induces N-Myc Downstream Regulated Gene-2 Expression in Papillary Thyroid Carcinoma Cells
(Dokuz Eylul Univ Inst Health Sciences, 2020) Sipahi, Murat; Bartik, Didem Keles; Doruk, Mehmet; Bayraktar, Firat; Oktay, Gulgun
Purpose: In addition to its role in serum calcium homeostasis, the anti-tumor function of 1,25-dihydroxyvitamin D-3 (calcitriol) in cancer development is well established. N-myc Downstream Regulated Gene 2 which functions as a tumor suppressor gene has recently been shown to be downregulated in various cancer leading to increased tumor incidence, progression and metastasis. The goal of this study was to investigate the possible effects of calcitriol treatment on NDRG2 expression in BCPAP papillary thyroid carcinoma cells. Methods: The experiments were carried on human primary thyroid follicular epithelial cells (Nthy-ori-3-1), and human papillary thyroid carcinoma cells (BCPAP). The half maximal inhibitory concentration (IC 50) of calcitriol on BCPAP cells was determined by WST-1 assay. BCPAP cells were treated with 15 and 30 mu M calcitriol for 24, 48, and 72 hours, respectively. Basal NDGR2 expression in Nthy-ori-3-1 and BCPAP cells as well as the alterations on NDRG2 expression in calcitriol treated BCPAP cells were evaluated with western blot. Results: A significant downregulation of NDRG2 was observed in BCPAP cells when compared to Nthy-ori-3-1 cells (p<0.01). IC50 dose of calcitriol was found to be 64, 54 and 43 mu M for 24, 48 and 72 hours, respectively. NDRG2 protein expression levels were significantly increased in 30 mu M calcitriol treated BCPAP cells after 48 hours (p<0.05). Conclusions: Calcitriol induced NDRG2 protein expression in BCPAP cells. We predict that calcitriol increased NDRG2 protein levels in BCPAP cells via c-Myc repression, which is upregulated by aberrant Wnt/beta-catenin signaling. Further investigation is required to enlighten the possible effect mechanisms of calcitriol in BCPAP cells.
Citation - WoS: 238
1-D Convolutional Neural Networks for Signal Processing Applications
(IEEE, 2019) Kiranyaz, Serkan; İnce, Türker; Abdeljaber, Osama; Avcı, Onur; Gabbouj, Moncef
1D Convolutional Neural Networks (CNNs) have recently become the state-of-the-art technique for crucial signal processing applications such as patient-specific ECG classification, structural health monitoring, anomaly detection in power electronics circuitry and motor-fault detection. This is an expected outcome as there are numerous advantages of using an adaptive and compact 1D CNN instead of a conventional (2D) deep counterparts. First of all, compact 1D CNNs can be efficiently trained with a limited dataset of 1D signals while the 2D deep CNNs, besides requiring 1D to 2D data transformation, usually need datasets with massive size, e.g., in the Big Data scale in order to prevent the well-known overfitting problem. 1D CNNs can directly be applied to the raw signal (e.g., current, voltage, vibration, etc.) without requiring any pre-or postprocessing such as feature extraction, selection, dimension reduction, denoising, etc. Furthermore, due to the simple and compact configuration of such adaptive 1D CNNs that perform only linear 1D convolutions (scalar multiplications and additions), a real-time and low-cost hardware implementation is feasible. This paper reviews the major signal processing applications of compact 1D CNNs with a brief theoretical background. We will present their state-of-the-art performances and conclude with focusing on some major properties.
A 2-Hop Coloring-Based Collision Free Infrastructure Design for Wireless Sensor Networks
(Institute of Electrical and Electronics Engineers Inc., 2016) Korkmaz I.; Dagdeviren O.; Dalkilic M.E.
This paper mainly proposes a design for a communication infrastructure for Wireless Sensor Networks. The proposed design prevents message collisions by arranging the time schedules to send, receive, forward and overhear packets of the nodes considering 2-hop graph coloring mechanism. The system aims to exclude the compromised nodes in the network using the overhearing mechanism, and copes with recovering the paths of the legitimate nodes using multipath redundancy. The proposed scheduling-based and overhearing supported infrastructure brings the advantage of providing the Sensor Networks with both reliable communication using backup paths and energy conservation by preventing the collisions. © 2016 IEEE.
3D dendritic spine segmentation using nonparametric shape priors
(Institute of Electrical and Electronics Engineers Inc., 2017) Bocugoz E.; Erdil E.; Argunsah A.O.; Unay D.; Cetin M.
Analyzing morphological and structural changes of dendritic spines in 2-photon microscopy images in time is important for neuroscience researchers. Correct segmentation of dendritic spines is an important step of developing robust and reliable automatic tools for such analysis. In this paper, we propose an approach for segmentation of 3D dendritic spines using nonparametric shape priors. The proposed method learns the prior distribution of shapes through Parzen density estimation on the training set of shapes. Then, the posterior distribution of shapes is obtained by combining the learned prior distribution with a data term in a Bayesian framework. Finally, the segmentation result that maximizes the posterior is found using active contours. Experimental results demonstrate that using nonparametric shape priors leads to better 3D dendritic spine segmentation results. © 2017 IEEE.
Citation - WoS: 9
Citation - Scopus: 17
Abnormal Ecg Beat Detection Based on Convolutional Neural Networks
(Institute of Electrical and Electronics Engineers Inc., 2020) Ozdemir M.A.; Guren O.; Cura O.K.; Akan A.; Onan A.
The heart is the most critical organ for the sustainability of life. Arrhythmia is any irregularity of heart rate that causes an abnormality in your heart rhythm. Clinical analysis of Electrocardiogram (ECG) signals is not enough to quickly identify abnormalities in the heart rhythm. This paper proposes a deep learning method for the accurate detection of abnormal and normal heartbeats based on 2-D Convolutional Neural Network (CNN) architecture. Two channels of ECG signals were obtained from the MIT-BIH arrhythmia dataset. Each ECG signal is segmented into heartbeats, and each heartbeat is transformed into a 2-D grayscale heartbeat image as an input for CNN structure. Due to the success of image recognition, CNN architecture is utilized for binary classification of the 2-D image matrix. In this study, the effect of different CNN architectures is compared based on the classification rate. The accuracies of training and test data are found as 100.00% and 99.10%, respectively for the best CNN model. Experimental results demonstrate that CNN with ECG image representation yields the highest success rate for the binary classification of ECG beats compared to the traditional machine learning methods, and one-dimensional deep learning classifiers. © 2020 IEEE.
Citation - WoS: 1
Citation - Scopus: 1
Abstinence-Related Motivational Engagement Scale: Validity and Reliability in Turkish People
(Bilimsel Tip Publishing House, 2018) Yavan, Tulay; Gulesen, Asli; Bebis, Hatice
OBJECTIVES: This research aimed to conduct a validity and reliability study of the Turkish version of the abstinence-related motivational engagement (ARME) scale. MATERIALS AND METHODS: This study included 122 people and was administered in a smoking cessation clinic. The sociodemographic-smoking status characteristics questionnaire and the ARME scale were used for data collection. A psycholinguistic language adaptation was performed. In the validity, analyses, content, construct, and criterion-related validities were used. For content validity, expert evaluation was performed. For construct validity, principal component analyses (exploratory factor analyses) were performed. Orthogonal (Varimax) rotation was used to explore multiple factors. The Kaiser-Meyer-Olkin test was used to assess the adequacy of the sample size. For criterion-related validity, we compared the ARME scale points of people who were abstinent and had relapse for smoking at the end of the sixth month. In the reliability analysis, standard deviation (SD) and item analysis, internal consistency, and test-retest methods were used. RESULTS: The four factors explain 58% of the total variance. Items have factor loading between 0.409 and 0.805. When the factor structure of the scale was assessed, the items in each factor group have a factor load of at least 0.40. Due to one-dimensional use of the original scale, it has been decided to maintain this scale in its original form. The ARME scale points of people who quit smoking were statistically higher than the points of people who had relapse at the end of the sixth month. Cronbach's alpha coefficients were between 0.846 and 0.763. Significant and positive correlation was found between the test-retest scale scores. CONCLUSION: The Turkish adaptation of the ARME scale, which was developed for adults who quitted smoking, is an adequately valid and reliable measurement instrument. It is considered that the scale might be used reliably in different cultures as well.
Citation - Scopus: 1
Academic Performance Management Policy for Changing Roles of Universities in Innovation Systems
(Institute of Electrical and Electronics Engineers Inc., 2017) Ozcan S.; Ozyazici M.S.; Ozerdem M.B.
The purpose of this study is to establish a new performance measurement method for academic actors for their changing roles in innovation systems. The widely accepted triple helix and systems of innovation models show changing and overlapping roles of academic, industrial and governmental actors. In previous innovation systems, universities were not focused on applied research and technology transfer as much as they are now. Current literature shows a changing role of universities and importance of their involvement in innovation systems. Although academic organizations' roles have changed in innovation systems, academic performance measurement systems (APMS) are not adapted to examine innovation related performance factors. Many APMS focus on key performance indicators (KPIs) such as; publications, research projects and patents. However, the new APMS needs to assess the activities and processes that are related to innovation, such as; technology transfer processes, collaborative innovation activities, consultancies and academic spin-offs. For this study a new APMS is applied according to the needs of universities by using a synthetic data based on an engineering department's KPIs. APMS scores are calculated based on the cumulative metric of all research and innovation activities and, weighted according to the needs and considerations of the university. The results of this study show that many of those academicians who have great performance in publications and academic research do not necessarily have high-level performance in innovative activities. In fact the results show that those who had high points in some measurements have very low performance in others. For the management point of view, it may be more effective to position academicians for different roles and assess their performance accordingly as innovation-targeted, teaching-targeted and research-targeted academicians. © 2016 Portland International Conference on Management of Engineering and Technology, Inc.
Accounting Conservatism in the Post-Ifrs Period: Do Provisions Matter?
(Bilgesel Yayincilik San & Tic Ltd, 2013) Ozkan, Serdar; Karai̇brahi̇moğlu, Yasemin; Acar, Ece Erdener
Accounting conservatism is an important aspect of financial reporting quality. Considering the tradeoff between relevance and reliability of the accounting information, it is argued that the level of conservatism of financial reports is increased by provision items, which are mainly future oriented estimations. Using a sample of 1,225 firm-year observations from Istanbul Stock Exchange (ISE) between the years 2005-2010, this paper examines the relationship between provisions and conservatism. Overall findings show a positive association between provisions reported under IAS-37 Provisions, Contingent Liabilities and Contingent Assets and both earnings and balance sheet conservatism. This study makes significant contribution to the accounting literature by providing empirical evidence on such associations referring the use of provisions as a proxy for accounting conservatism.
Accurate Dictionary Matching for Mr Fingerprinting Using Neural Networks and Feature Extraction
(Institute of Electrical and Electronics Engineers Inc., 2020) Soyak R.; Ersoy E.O.; Navruz E.; Fakultesi M.; Unay D.; Oksuz I.
Magnetic Resonance Fingerprinting is a recent technique which aims at providing simultaneous measurements of multiple parameters. MRF works by varying acquisition parameters in a pseudorandom manner so as to get unique, uncorrelated signal evolutions from each tissue. MRF is a dictionary based approach, and thus requires a database. This database can be created by simulating the signal evolutions from first principles using different physical models for a wide variety of tissue parameter combinations. Having this dictionary, a pattern recognition algorithm is used to match the acquired signal evolutions from each voxel with each signal evolution in the dictionary. In this paper, we compare the efficiency of deep learning based feature extraction method and neural network architectures in order to achieve state-of-the-art accuracy in dictionary matching for MRF. Our results showcase successful dictionary matching with high accuracy both quantitatively and qualitatively. © 2020 IEEE.
Achieving Sustainable Learning Through Erp Based Supply Chain in Vitro Laboratory
(Elsevier Science Bv, 2011) Gocer, Aysu; Saatcioglu, Omur Yasar; Demir, Muhittin H.; Tuna, Okan; Baltacioglu, Tuncdan; Adali, Erman
In order to enable sustainable learning, practical motivation behind every theory in consideration needs to be experienced extensively. The purpose of this study is to enhance sustainable learning on logistics and supply chain management through an in vitro laboratory environment in which real life supply chain structure is simulated over actual physical flows, and also through enterprise resource planning (ERP) systems, and then to measure the level of sustainability achieved. Research is conducted by including a group of students to a hands-on implementation through both physical and computerized applications in this representative business environment. To support the findings, surveys and focus groups are conducted. (C) 2011 Published by Elsevier Ltd.
Aconitine Impedes Cell Motility in Mda-Mb Breast Cancer Cells
(Dokuz Eylul Univ Inst Health Sciences, 2024) Keles, Didem; Sipahi, Murat; Surer, Seniz Inanc; Oktay, Gulgun
Purpose: Aconitine, a potent alkaloid from Aconitum plants, has shown promising anticancer properties. The aim of the study is to investigate the effects of aconitine on lateral migration, and matrix metalloproteinase (MMP) activity in MDA-MB-231 triple-negative breast cancer cells. Material and Methods: A WST-1 viability assay was conducted to determine the effect of aconitine on the viability of MDA-MB-231 cells. Following treatment with non-cytotoxic doses of aconitine, lateral migration was evaluated through wound healing assays. Additionally, gelatin zymography was conducted to analyze MMP-2 and MMP-9 activity and secretion levels. Results: Aconitine concentrations up to 200 mu M did not significantly affect cell viability for up to 72 hours, whereas higher doses (400-600 mu M) reduced viability in a time-dependent manner. Aconitine at 200 mu M showed a trend towards decreased lateral motility, with a significant reduction at 9 hours post-treatment. Gelatin zymography revealed no alterations in MMP-2 and MMP-9 activity or secretion levels following aconitine treatment. Conclusion: Aconitine demonstrates limited efficacy in modulating the migratory capacity of MDA-MB231 cells and does not affect gelatinase activity. Further investigation into underlying mechanisms is necessary, potentially leading to novel therapeutic strategies for triple-negative breast cancer.
Citation - WoS: 1
Citation - Scopus: 2
Adaptive Evolution of Finite State Machines for the Tartarus Problem
(Institute of Electrical and Electronics Engineers Inc., 2019) Oguz K.
Genetic algorithms can be used to evolve finite state machines for problems that require a large number of states and transitions. Tartarus problem is such a problem in which the purpose is to push the boxes towards the walls of a six by six grid using a bulldozer that can only sense its 8-neighbourhood. The bulldozer can rotate left, right, or move forward, each taking a single move out of its initial 80 moves. The result is scored by the number of boxes that are against a wall when the bulldozer is out of moves. Several approaches have been proposed, with genetic algorithms being the most common. We are proposing a representation of the problem using varying number of states and adaptive modification of the mutation parameter to decrease the probability of the population getting stuck at a local minima. Our results show improvement over the application of the genetic algorithm without parameter modification and dependency on the number states and the size of the population. © 2019 IEEE.
Citation - WoS: 1
Adaptive Video Streaming With H.264 Sp Frames
(Pamukkale Univ, 2012) Sayit, Muge; Tunali, E. Thrhan
In this work, SP frames of the extended profile of H.264 AVC video codec are utilized to obtain efficient switching for actual video streaming experiments on the Internet. An adaptive algorithm is developed and by using this algorithm, performance of SP frames is compared with that of standard I-frame switching. Detailed measurements of network conditions are given for each experiment to indicate that comparisons are carried out in fair conditions. It has been observed that, under certain conditions, SP frames can improve performance considerably whereas in the others, they may only introduce overhead. Based on this observation different GOP patterns are proposed for different video type-congestion level combinations.
Admission-Discharge-Transfer Gateway Interface: A Health Level 7 Application for Hospital Information Systems
(World Scientific And Engineering Acad And Soc, 2010) Atay, Coskun
[Abstract Not Available]
Citation - WoS: 1
Citation - Scopus: 1
Advances in the Formulation of Minimal Thermodynamically Consistent Models for Dispersion Force-Driven High-Accuracy Inertial Nano-Sensors
(IEEE, 2025) Pinto, Fabrizio
We present advances in the accurate multiphysics modeling of nano-accelerometers motivated by the specific navigational requirements of small spacecraft under low thrust in interplanetary missions. The process of energy transfer to the nanodevice via parametric coupling is analyzed from the thermodynamical standpoint. The system is based on simultaneous electrostatic excitation and on van der Waals forces modulated by laser radiation acting as a parametric pump. It is shown that the processes involved rigorously satisfy the First and Second Laws of Thermodynamics. This proof paves the way for the design of thermodynamically consistent models of this novel class of nano-accelerometers.
Advertising Adaptations Between Globalization and Locality: Case of Snickers
(Ankara Univ, Fac Communication, 2015) Kaptan, Yesim
By comparing the American and the Turkish versions of television commercials arising from the Snickers' global advertising campaign You are not you when you are hungry, this article examines how commercials are adapted to appeal to a sense of locality through the strategies of locality. To explore how locality is represented in advertising, three localization strategies (national language, culture, humor) employed in advertising adaptation are analyzed. Using interviews with focus groups and an advertising practitioner, the author argues that advertising plays an important role for construction and reproduction of locality in everyday life. The author asks which values and codes are employed in advertising adaptations and how they are articulated to discourse of consumer culture in the media materials. The article also discusses the significance of advertising adaptations within the overlapping contexts of global formats, national media, and local identities.
Ageless Wisdom: a Cross-Cultural Study on Enhancing Life Satisfaction Through Skills Promotion Among Older Adults
(2024) Adele Gaia De Stefani; Burçin Önder; Kaygın, Hüseyin; Ulus, İhsan Çağatay; Ratkowska-Pasikowska, Justyna; Ertürk, Nesrin Oruç
This article explores the pervasive issue of ageism and its detrimental effects on the elderly population. Ageism or the prejudice and discrimination against older adults based on their age, can have significant impact on their well-being and life satisfaction. However, the article also delves into the potential positive effects of continuous learning on reducing ageism and enhancing the life satisfaction of the elderly. As a proactive approach, lifelong learning presents an opportunity for the elderly to challenge stereotypes, remain engaged in society, and foster personal growth. This study highlights how training and educational programs can empower older adults, instilling a sense of purpose and accomplishment, leading to a more fulfilled and satisfying life in their later years. The main purpose was to investigate how continuous learning affects the lives and life satisfaction perception of elderly people over the age of 65 from Greece, Hungary, Italy, Poland and Turkey after one week and 25 hours of technology, art and psychotherapy trainings that are believed to support them in every aspect of life.
An Agent Based Modeling Approach To the Check Payments Among Smes in Turkey
(Bilgesel Yayincilik San & Tic Ltd, 2013) Arslan, İlker; Duman, Alper
Systemic risk and fragility became more important especially after the crisis of 2008. However, the burgeoning literature especially focuses on interbank and bank-firm credit networks. On the other hand, in developing countries, deferred check payments also compose another kind of credit networks and complement for the bank-firm credit lines. Check payments among SMEs even substitute for bank credits. Recent developments in Turkey offer an interesting setting in which we examine the fragility of check payment system. In this paper, we investigate whether the dramatic increase in nonpayments of checks have been due to the decline in growth or loosening of the legal sanctions. We analyze check payments using an agent based model. We can view check payments as a network structure where firms are nodes and check obligations are directed links. Firms' decision on whether paying their checks or not, depend on behavior of their neighbors and probable payoffs to their decisions. Our main finding is that lack of strict punishment can cause default cascades in check payment systems.
The 'Alevi Opening' of The Justice and Development Party
(Edinburgh Univ Press, 2022) Borovali, Murat; Boyraz, Cemil
Alternative E-Assessment in Language Classes: Recent Experiences and Future Directions
(2024) Çağlayan, Esin
This study aimed to explore English as a Foreign Language (EFL) teachers' perceptions regarding alternative e-assessments in the Turkish tertiary level context. The study utilized semi-structured interviews with a sample of EFL instructors from 17 higher education institutions in Türkiye. The data were analyzed using thematic analysis to identify emerging themes. The results revealed varying perceptions about alternative e-assessments, with six primary themes emerging: impact on learning, workload, academic integrity, digital technology, grading and feedback, and assessment competence. Overall, this qualitative study provides valuable insights into the perceptions of EFL teachers regarding alternative e-assessments, highlighting key areas of concern. The study emphasizes the need to address these concerns in professional development programs that provide teachers with the necessary knowledge and skills to effectively implement alternative e-assessments. The results also have implications for the development of effective assessment policies and procedures, optimizing educational practices in the digital age.

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