Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395

Browse

Search Results

Now showing 1 - 8 of 8
  • Article
    Process Optimization of Buckwheat Starch Myristic Acid Complex Film
    (John Wiley and Sons Inc, 2026-02) Koca, E.; Oskaybaş-Emlek, B.; Kahraman, K.; Özbey, A.; Aydemir, L.Y.; Oskaybas Emlek, Betul
    In this study, it was aimed to develop an edible film from an amylose-lipid complex with better mechanical properties and water vapor barrier. For this purpose, the buckwheat starch (BS) is modified with myristic acid (MA) and the edible film production process was optimized by using central composite design with 4 center points where film forming solution's glycerol concentration, pH, and the temperature of as dependent variable and tensile strength (TS), elongation at break (EAB) value and Young's modulus (YM) as response. The models were significant for TS and YM, and the glycerol concentration and temperature had a significant effect on the TS of the films. The edible film produced in validated optimized conditions had better EAB (149%) and TS (1.064 MPa), and lower water solubility (44.7%) and water vapor permeability (0.39 g × mm/m2 × h × kPa) than control film (p < 0.05). There was no significant change in color values, but an increase in opacity (2.14). With the formation of the BS-MA complex, increased surface roughness and more hydrophilic (contact angle = 92.4°) films were obtained. These findings demonstrate that the BS-MA complex film has significant potential for practical applications as an edible film. © 2026 Wiley-VCH GmbH.
  • Book Part
    A Systematic Review of Optimization Studies Used in Renewable Energy Systems
    (Springer Science and Business Media Deutschland GmbH, 2026) Söylemez, İ.; Erdoğan, A.
    This study presents a literature review of recent studies on renewable energy systems. Due to the large number of studies, this study has been limited to some keywords. When only the word “renewable energy systems” is searched, there are more than 14,343 studies in the literature between 2017 and 2024. A systematic search was conducted for the studies in which “optimization” or “mathematical model” was mentioned as a solution methodology. A total of 755 studies were identified in the “Scopus database” and analyzed for these studies. A detailed examination was carried out for the type of studies (research article, review, conference paper, etc.), countries where the studies were carried out, authors who carried out the studies and their statistics with each other, and so on. With this study, an overview of the literature will be provided and it will be a guiding study for researchers on the direction of the studies. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
  • Conference Object
    Citation - WoS: 8
    Citation - Scopus: 12
    SVM-RCE-R Optimization of Scoring Function for SVM-RCE
    (Springer International Publishing AG, 2021) Yousef, Malik; Jabeer, Amhar; Bakir-Gungor, Burcu
    Gene expression data classification provides a challenge in classification due to it having high dimensionality and a relatively small sample size. Different feature selection approaches have been used to overcome this issue and SVM-RCE being one of the more successful approach. This study is a continuation of two previous research studies SVM-RCE and SVM-RCE-R. SVM-RCE-R suggests a new approach in the scoring function for the clusters, showing that for some different combination of weights the performance was improved. The aim of this study is to find the optimal weights for the scoring function suggested in the study of SVM-RCE-R using optimization approaches. We have discovered that finding the optimal weights for the scoring function would improve the performance of the SVM-RCE-in most cases. We have shown that in some cases the performance is increased dramatically by 10% in terms of accuracy and AUC. By increasing the performance of the algorithm, it is more likely that we can extract subset genes relating to the class association of a microarray sample.
  • Conference Object
    Citation - WoS: 7
    Citation - Scopus: 10
    PI-Controlled ANN-Based Energy Consumption Forecasting for Smart Grids
    (SciTePress, 2015) Gezer, Gülsüm; Tuna, Gürkan; Κogias, DImitrios G.; Gülez, Kayhan; Güngör, Vehbi Çağrı; Kogias, Dimitris
    Although Smart Grid (SG) transformation brings many advantages to electric utilities, the longstanding challenge for all them is to supply electricity at the lowest cost. In addition, currently, the electric utilities must comply with new expectations for their operations, and address new challenges such as energy efficiency regulations and guidelines, possibility of economic recessions, volatility of fuel prices, new user profiles and demands of regulators. In order to meet all these emerging economic and regulatory realities, the electric utilities operating SGs must be able to determine and meet load, implement new technologies that can effect energy sales and interact with their customers for their purchases of electricity. In this respect, load forecasting which has traditionally been done mostly at city or country level can address such issues vital to the electric utilities. In this paper, an artificial neural network based energy consumption forecasting system is proposed and the efficiency of the proposed system is shown with the results of a set of simulation studies. The proposed system can provide valuable inputs to smart grid applications. © 2022 Elsevier B.V., All rights reserved.
  • Conference Object
    Citation - WoS: 18
    Citation - Scopus: 19
    Optimal Energy Management and Scheduling of a Microgrid in Grid-Connected and Islanded Modes
    (IEEE, 2019-09) Zacharia, L.; Tziovani, L.; Savva, M.; Hadjidemetriou, L.; Kyriakides, E.; Bintoudi, A. D.; Al-Agtash, S.
    Microgrids are becoming one of the main components of future smart grids. Ensuring their optimal and stable operation is of crucial importance and can be a challenging task. In this paper, two optimization algorithms are implemented for scheduling the microgrid operation in grid-connected and islanded modes, according to the priorities and objectives in each mode. For achieving an optimal operation at each mode, the proposed scheme is able to shed loads, define the generation level of the photovoltaics and regulate the charging/ discharging level of the Energy Storage System (ESS). The effectiveness of the proposed scheduling is demonstrated through an analytical real-time simulation, where various transitions between the grid-connected and islanded modes are considered. The results indicate that the proposed scheme is able to regulate successfully the energy flows of the microgrid even under various transitions.
  • Book Part
    Hosting Capacity Calculation Methods
    (Elsevier, 2025) Oguzhan, Ceylan; Alper, Savasci
    In this chapter, we focus on hosting capacity (HC) calculations, by giving the methods to determine the maximum amount of distributed energy resources (DER) that can be integrated into power distribution network(s) without compromising reliability or performance. We detail methodologies such as power flow-based approaches, probabilistic techniques, and machine learning algorithms, with sample applications of HC calculations. Initially, we focus on power flow-based methods based on simulating power distribution network(s) to assess system voltage, current flow, and stability impacts from DER installations. Then, we will give the probabilistic approaches that use uncertainties in renewable generation and consumer demand, based on statistical techniques and Monte Carlo simulations aiming to reflect these variability. Machine learning (ML) techniques will also be given based on analyzing large data sets, detecting patterns, and predicting system responses. These kinds of methods include regression analysis and neural networks trained on historical data for optimized HC predictions. It should be stated that HC is impacted by several factors, such as network topology, load profiles, and DER characteristics, and these as well will be discussed. We will provide a practical example of an HC calculation on a 141-node distribution network using a step-by-step algorithm in Matpower, with simulation results based on an iterative deterministic method. Then, we will give the broader implications of HC assessments for grid modernization and energy policy, highlighting how accurate calculations support a more decentralized, sustainable, and resilient energy future. © 2025 Elsevier B.V., All rights reserved.
  • Article
    Citation - WoS: 5
    Citation - Scopus: 5
    Development of Buckwheat Starch-Capric Acid Complex-Based Film: Process Optimization and Film Characterization
    (Wiley-VCH Verlag GmbH, 2025-02-26) Koca, Esra; Kahraman, Kevser; Oskaybas-Emlek, Betul; Ozbey, Ayse; Aydemir, Levent Yurdaer
    To overcome the limitations of starch usage alone, the film formation ability of the buckwheat starch-capric acid complex (BS-CA) was optimized, and the films were characterized. Significant models were obtained for tensile strength (TS) and Young's modulus (YM) of BS-CA film (p < 0.0001). The glycerol/starch ratio, temperature, and their interactions were significant in the YM model (R-2 is 0.9851). The BS-CA film had a better water vapor barrier (0.463 +/- 0.02 g mm/m(2) h kPa), with lower water solubility (WS) (34.18 +/- 1.70%) and moisture content (MC) (16.87 +/- 0.09%) than the buckwheat starch (BS) film (p < 0.05). It had lower thickness (0.073 +/- 0.00 mm) and TS (0.624 +/- 0.04 MPa) but higher elasticity (114.60 +/- 3.12%). The non-covalent interactions were determined between BS and CA, since new peaks were not observed in the film's FTIR spectrum. BS-CA film had a typical V-type crystalline structure and had slightly lower decomposition temperatures than the BS film. Contact angle measurements (55.19 degrees +/- 1.7), and images of AFM topography and SEM showed that the BS-CA film surface was hydrophilic; height and average roughness values were 1014 and 276 nm, respectively, which were quite higher than those of BS film. The results reveal that starch modification with fatty acid is a promising way to develop starch-based films to be used in practical applications.
  • Conference Object
    Citation - Scopus: 5
    Enerji Hasadı ve Sıkıştırmalı Algılama Yapan Gizlilik Odaklı Sualtı Kablosuz Ağlarında Ömür Analizi
    (Institute of Electrical and Electronics Engineers Inc., 2019-04) Uyan, Osman Gokhan; Güngör, Vehbi Çağrı
    Underwater sensor networks (UWSN) are a division of classical wireless sensor networks (WSN), which are designed to accomplish both military and civil operations, such as invasion detection and underwater life monitoring. Underwater sensor nodes operate using the energy provided by integrated limited batteries, and it is a serious challenge to replace the battery under the water especially in harsh conditions with a high number of sensor nodes. Here, energy efficiency confronts as a very important issue. Besides energy efficiency, data privacy is another essential topic since UWSN typically generate delicate sensing data. UWSN can be vulnerable to silent positioning and listening, which is injecting similar adversary nodes into close locations to the network to sniff transmitted data. In this paper, we discuss the usage of compressive sensing (CS) and energy harvesting (EH) to improve the lifetime of the network whilst we suggest a novel encryption decision method to maintain privacy of UWSN. We also deploy a Mixed Integer Programming (MIP) model to optimize the encryption decision cases which leads to an improved network lifetime. © 2020 Elsevier B.V., All rights reserved.