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Image Processing Based Scrub Tester Design and Production
Get PDFcenter dot Determining how resistant paint, varnish or coating type materials, applied to wood-based panel surfaces, are to the effects of exposure to household chemicals is important in terms of developing products and providing durable surface coating to users. Every paint or coating type product coming off the production line needs to be tested quickly, and a new direction should be given to the work based on the positive or negative results obtained. Products without quality monitoring are returned by customers due to insufficient performance, resulting in loss of time, labor and materials. In this study, an Image Processing Based Scrub Tester (IPBST) was designed and produced in order to imitate the effect of paint, varnish and coating materials on the surfaces of furniture and decoration elements used in daily life against household chemicals. Unlike its counterparts, with IPBST, the image of each sample is digitally recorded before and after the scrubbing process, thanks to the compact photo booth integrated into the device. Wear, color and brightness change analyses of sample images can be performed with the Surface Flaw Analysis (SFA) method developed using the Matlab Graphical User Interface (GUI) image processing program on a computer integrated into the device. In this way, a 4-in-1 device that can do the job of 4 devices has been provided to the relevant scientific community and industry without the need for different types of industrial test devices.National New Ideas and Products Research Support Programme [221O551, TUBITAK-1005]Acknowledgements - Zahvala This research received support from project num-ber 221O551 under the TUBITAK-1005 National New Ideas and Products Research Support Programme
Fuzzy-Based Fitness-Distance Balance Snow Ablation Optimizer Algorithm for Optimal Generation Planning in Power Systems
Get PDFEconomic dispatch (ED) is one of the most important problems in terms of energy planning, management, and operation in power systems. This study presents a snow ablation optimizer (SAO) algorithm developed with the fuzzy-based fitness-distance balance (FFDB) method for solving ED problems in small-, medium- and large-scale electric power systems and determining the optimal operating values of fossil fuel thermal generation units. The FFDB-based SAO algorithm (FFDBSAO) controls early convergence problems through balancing exploration-exploitation and improves the solving of high-dimensional optimization problems. In the light of extensive experimental studies conducted on CEC2020, CEC2022, and classical benchmark test functions, the FFDBSAO2 algorithm has shown superior performance against its competitors. Wilcoxon and Friedman's statistical analysis results confirm the performance and efficiency of the algorithm. Moreover, the proposed algorithm significantly reduces total fuel cost by optimizing fossil fuel thermal generation units. According to the results, the scalability and robustness of the algorithm make it a valuable tool for solving large-scale optimization problems in the planning of electric power systems
Novel machine learning framework for high-resolution sorghum biomass estimation using multi-temporal UAV imagery
Get PDFAccurate assessment of crop health and yield potential facilitates precise estimation of above-ground biomass (AGB). Traditional AGB estimation methods are often limited by their destructive, labor-intensive nature. This study developed a rapid, non-destructive approach to estimate sorghum AGB using high-resolution unmanned aerial vehicle (UAV) data and machine learning (ML). A two-year field experiment tested four irrigation strategies: full irrigation at 100% of crop evapotranspiration (S1), partial deficits at 75% and 50% of S1, and a rain-fed (S4). This gradient assessed the ML model's robustness across diverse conditions, yielding 216 AGB measurements reflecting variable plant responses to water stress. Multispectral and canopy height data were derived from UAV imagery collected during the sorghum growing season. Three ML algorithms-Random Forest (RF), Support Vector Machine (SVM), and K-Nearest Neighbors (K-NN)-were applied. RF outperformed others with an R2 of 0.80, RMSE of 0.78 kg m(-)2, and MAE of 0.58 kg m(-)2, followed by SVM (R2 = 0.64, RMSE = 1.08 kg m(-)2, MAE = 0.77 kg m(-)2), while K-NN showed the lowest accuracy (R2 = 0.50, RMSE = 1.26 kg m(-)2, MAE = 0.96 kg m(-)2). Optimal RF hyperparameters were identified, and estimated AGB aligned closely with ground measurements, showing no significant differences. Spatial AGB maps effectively highlighted variability across treatments. This study demonstrates that UAV-based remote sensing combined with ML offers a reliable, non-destructive method for sorghum AGB estimation, enhancing precision agriculture applications such as irrigation management, crop monitoring, and yield prediction.Scientific and Technological Research Council of Turkey (TUBITAK)TUBITAKThe authors thank to TUBITAK for their supports
Vâkı’a Sûresi’nin 78-80. Âyetlerinin Anlamı: Abdestsiz Mushaf’a Dokunma ve Âdetli Kadınların Kur’an Okuması Meselesi
Get PDFAllah kelamı Kur’an-ı Kerîm, Tevrat’ın Hz. Musa’ya verildiği gibi Hz. Peygambere yazılı olarak değil, şifahi ola-rak vermiştir. Vahiy meleği Cebrâil, okuduğu zaman Hz. Muhammed (s.a.s) sûre ve âyetleri hafızasına almış oluyordu. Hz. Peygamber kendisine indirilen sûre ve âyetleri sahabeye okuyor, vahiy kâtiplerine de yazdırıyor-du. Sahabe, sûre ve âyetleri namazda ve sair zamanda okuyor, bazıları ezberliyordu
ALIGNING MIS UNDERGRADUATE PROGRAMS IN TURKEY WITH JOB MARKET SKILL DEMANDS
Get PDFBu çalışmanın temel amacı, Türkiye'de bulunan devlet üniversitelerindeki Yönetim Bilişim Sistemleri (YBS) bölümlerinde yürütülen eğitim programları ile iş piyasasında talep edilen yetkinliklerin ne ölçüde örtüştüğünü analiz etmektir. Çalışma aynı zamanda YBS mezunlarının mevcut iş piyasası koşullarına ve gelecekte meydana gelebilecek değişimlere uyum sağlayabilmesi için gerekli becerilerin geliştirilmesine katkı sağlamayı da amaçlamaktadır
AI Threats in Cyber Security: Empowering Employee Awareness and Training for Cyber Security Culture
Get PDFWith the emergence of artificial intelligence, cyber threats have become increasingly complex. Traditional cyber security measures are insufficient to cope with new cyber threats. In order to defend against advanced threats, businesses are now obliged to adopt proactive defense strategies. One of the proactive defense strategies is the integration of Cyber Security Culture into security frameworks. The inclusion of artificial intelligence technologies in defense programs and the creation of a cyber security culture will provide strategic advantages to organizations. Although the creation of a strong security culture has been researched and discussed for a long time, many businesses still avoid this topic. A well-d eveloped cyber security culture will make it easier for organizations to take precautions against advanced cyber attacks. © 2025 Elsevier B.V., All rights reserved
New symmetric midpoint type inequalities for convex functions
Get PDFIn this study, we first develop symmetric quantum integral identity utilizing the derivatives and integrals of symmetric quantum types. Then, by using this identity, we establish modified versions of midpoint-type inequalities for differentiable convex functions. To obtain recent results, a few basic inequalities such as power mean and Holder's, have been utilized. We create links between our results and previous findings in the literature taking q -> 1. For a better understanding and validation of the results, we present numerical results and some graphs. Finally, we provide some examples to illustrate the validity of newly obtained symmetric quantum inequalities. The concepts and methods presented in this work can inspire more investigation
On multiplicative conformable fractional integrals: theory and applications
Get PDFIn this paper, we first introduce the multiplicative conformable left and right fractional integrals, followed by the derivation of key properties, such as integrability, boundedness, continuity, and the semi-group property, for the newly defined multiplicative conformable fractional integrals. Then, we establish the Hermite-Hadamard inequalities in three distinct senses for multiplicative conformable fractional integrals. Moreover, we present several corresponding midpoint and trapezoidal inequalities for the obtained Hermite-Hadamard inequalities including multiplicative conformable fractional integrals. By special cases, we present the relations between newly obtained inequalities for multiplicative conformable fractional integrals and existing results for multiplicative Riemann-Liouville fractional integrals and multiplicative integrals. Furthermore, we give some new Hermite-Hadamard type, trapezoid type and midpoint type inequalities or multiplicative Riemann-Liouville fractional integrals. Finally, we give several examples and 3D graphs to illustrate the main results
Evaluation of wooden chair designs through finite element analysis and interval-valued spherical fuzzy analytic hierarchy process weighted aggregated sum product assessment (IAHP-WASPAS)
Get PDFProduct design is a complex process that involves evaluating multiple design alternatives based on various criteria. The selection of an optimal design requires a structured decision-making approach capable of handling uncertainty and computational analysis. This study proposed a novel decision-making methodology that integrates finite element analysis (FEA) with the interval-valued spherical fuzzy analytic hierarchy process (IVSF-AHP) and the interval-valued spherical fuzzy weighted aggregated sum product assessment (IVSF-WASPAS) to enhance the accuracy and reliability of design selection. A case study was made at a furniture manufacturing company in Turkey, focusing on the development and optimization of a dining chair. FEA was employed to assess the structural integrity and manufacturability of each design under different loading conditions. IVSF-AHP was used to determine the importance of evaluation criteria, while IVSF-WASPAS was applied to rank alternative designs. Additionally, sensitivity and comparative analyses were conducted to support the model's results. The proposed methodology presents a systematic and practical framework for manufacturers, product designers, and engineers to improve the product design process
Cognitive Radio Sensor Network-Based Urgent Communication for Field Hospitals
Get PDFIn this study, a medical sensor network structure based on cognitive wireless regional area network (WRAN) technology is proposed for urgent communication in field hospitals. WRAN technology is based on cognitive radio network approach, which is exploited for opportunistic spectrum access in places without internet access. In cognitive radio-based WRAN technology, a consumer premises equipment (CPE) and a base station communicate opportunistically by sensing available radio channels. In our network structure, CPEs use the time-division multiple access (TDMA) technique with channel bonding to detect patient-related data and transmit it to the base station. With the help of our node placement approach, many sensor nodes were placed in the field hospital environment. Because urgent communication is important in field hospitals, a fuzzy logic-based relay selection approach is proposed to improve network sustainability. Sensor nodes are placed to cover the entire region to detect parameters around the field hospital. The values detected by the sensor nodes were collected by the collector station fixed in the center. The simulation model of our proposed approach was implemented using riverbed modeler software. Thanks to our proposed node placement and relay node selection approaches, the field hospital was monitored safely with a minimum number of wireless sensor nodes