Mühendislik Fakültesi, Mekatronik Mühendisliği Bölümü Koleksiyonu

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https://hdl.handle.net/11467/9349

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Dinamik tüketici talep yönetimi yapabilen blokzincir/kripto para tabanlı elektrik piyasası işletme modeli
(Osman SAĞDIÇ, 2020) Özpınar, Alper
Günümüzde e lektrik enerjisi piyasası en genel ve ideal tanımlaması ile tüketiciler ve üreticiler arasındaki arz talep dengesinin oluşturulması en uygun fiyatlamanın yapıl arak piyasaya sunulması ve tüketilmesi ve enerji kaynaklarının hem üretimde hem de tüketimde farklı kontrol ve denetim araçları ile kontrol edilmesiyle oluşmaktadır. Bu piyasalara ülkeler e göre serbest piyasa koşullarının oluşması için gerekli hukuki düzenlemeler yapılmaktadır. Bu düzenlemlerd e temel amaç elektrik enerjisi gibi insan yaşamındaki toplumsal yaşam zamanlarına bağlı tüketim ve sanayii elektrik kullanımı ile ilgili genel bir denge kurulmasının sağlanarak enerjinin en verimli şekilde tüketilmesini sağlamaktır. Özellikle fosil yakıtl ara dayalı enerji üretimi yerine yenilenebilir enerji kaynaklarına dayalı temiz enerji üretimi için tüketici tarafındaki enerji talebini kontrol edebilmek ve bu talebe yöne lik olarak en uygun üretim senaryolarını ve fiyatlandırma optimizasyonunu yapmak çok önemli bir konu haline gelmiştir. Özellikle 2020 yılı içerisinde tüm dünyayı etkileyen pandemi süreci ile birlikte geleneksel tüketici davranışları ev tipi ve sanayii tipi tüketim in trendlerinin değişmesine neden olmuştur. Bu makalede tüketic ilerin talepl erini bireysel ve tüketim senaryolarına göre segmente ederek dinamik fiyatlandırma yapan ama bunu toplu olarak merkezi sistemde düzenleyerek talep tarafındaki dalgalanmaları en az a indirerek Gün İçi, Gün Öncesi ve Dengeleme Güç Piyasalarına yönelik yeni ne sil piyasa işletme modeli ve bu modelin işletilmesinde kullanılacak olan blokzincir tabanlı teklif güvenliği ve tüketicilerin çif taraflı enerji kullanımlarına yönelik önerilen kripto para kWhCoin anlatılmaktadır.
The impacts of mental and physical fatigue of employees on the perception level and the risk of accident
(Osman SAĞDIÇ, 2020) Taşdelen, Ahmet; Özpınar, Alper
The sources of work accidents identified in the root cause analysis are dangerous behaviors and dangerous occurrences. Despite the studies, improvements, and arrangements made on this subject in recent years, the status of the matter has not been improved until today, and the rates of occurrences have almost remained the same. In the accident root cause studies conducted, the findings suggest that the human factor is the leading cause of accidents in the workplace. However, pointing out that the human factor alone is not enough to correctly examine the causes of these accidents. In the assessments performed, the physical and mental fatigue and psychological conditions of the workers are generally excluded from the studies. Despite this, the perceptual deficit that arises from fatigue and insomnia plays a significant role in the occurrence of accidents or near-miss incidents. These fluctuating changes in the mental and physical well-being of the worker overtime often go unnoticed by both the employee and the employer. By regularly monitoring the components of this state of well-being, within the scope of occupational health and safety, it must be aimed at proactive and preventive protection of the health and safety of employees in the workplace concerning the environment, equipment, and individual/team. In this study, a roadmap developed for the prevention of near-miss incidents or accidents that may occur due to changes in decision-making skills, risk-taking behaviors, and reaction time of employees due to deterioration in the perception levels of them, and a matching matrix regarding the Occupational Health and Safety (OHS) processes are presented.
Modelling and simulation of driving performance in a series hybrid electric vehicle
(International Automotive Technologies Congress, 2018) Özpınar, Mustafa Alper; Albayrak Serin, Dilara
Throughout the history, electric vehicles and hybrid electric vehicles have come to spotlight of researchers but interest in these concepts decreased from time to time. With the desire to decrease fuel consumption and emissions, studies on hybrid electric vehicles have risen throughout the years. There are several studies which focus on driving performance of a hybrid electric vehicle but few of these especially focus on effect of velocity over hybrid electric vehicle fuel consumption. Through this research, finding the effect of velocity on fuel consumption and total trip cost as well as vehicle performance is aimed. For this goal, a mid-size family sedan type of series hybrid electric vehicle including battery, range extender and velocity controller is modelled and simulated with the help of MATLAB/Simulink The modelled vehicle is tested with simulated route from Istanbul to Ankara. The properties of vehicle route are retrieved from Google Earth and the road is also simulated in MATLAB. Both modeling and simulation processes for several velocity values are carried out.
Ev2c: extended vehicle–to–cloud model and conceptual implementation for big data
(IEEE, 2015) Özpınar, Alper; Boyacı, Ali; Yarkan, Serhan; Öztürk, Erdinç
Green transportation is an integral part of green environment concept. Next generation transportation systems are desired to achieve high performances with reduced fuel consumption and carbon emission. In this regard, vehicle maintenance status along with some other critical diagnostic data should steadily be checked and tracked. It is known that vehicles that are poorly maintained or not maintained in a timely manner lead to both emissions exceeding the standards and low performance. Vehicle telematics along with some other conveniences such as infotainment systems, location–based services and applications are expected to improve safety, availability, and reliability of next generation transportation systems. From this perspective, intelligent transport systems (ITS) seems to be a promising solution candidate which encompasses all of the aforementioned topics as well as vehicle–to–vehicle (V2V), vehicle–to–infrastructure (V2I), and vehicle–to–cloud (V2C) opportunities. Therefore, in this study, a conceptual model that links vehicle telematics to the cloud along with V2V communications facility is proposed and a prototype based on IEEE 802:11x protocol suite is implemented. Mobile data collection and measurements are obtained. Results are presented along with relevant discussions as well as the end point storage and usage of the data are introduced. In the proposed model, the mobile data are transferred to cloud computing platform to create the big data for further research opportunities for car manufacturers, policy makers, and researchers with the concern of ethics and security issues.
E-devlet hizmetlerine bütünleşik artırılmış gerçeklik uzman sistem modeli
(Akademik Bilişim Konferansı, 2015) Özpınar, Alper; Öz, Çağla; Özsoy, Dilara; Pederlioğlu, Kevser; Seyhan, Sedef
E-Devlet uygulamaları, yerel yönetimler ve devletin vermiş olduğu hizmetler ile ilgili olarak birçok farklı ve bağımsız uygulama bulunmaktadır. Ancak bu uygulamaların kent bilgi sistemleri, coğrafi bilgi sistemleri ve mobil uygulamalar üzerinde erişiminde genel sınırlar ve özellikle sunulan bilgilerin yol haritası kavramı üzerinde eksiklikler bulunmaktadır. Yapılan çalışmada E-Devlet hizmetlerine bütünleşik artırılmış gerçeklik uzman sistem modeli oluşturulmuş. Oluşturulan modelde; bireylerin tercihlerine, yaşadıkları çevrede alabilecekleri hizmetlere ve günlük yaşamlarında karşılaştıkları vatandaşlık hizmet, servis ve problemleri çözmelerine yarayacak, bulut bilişim destekli uzman bir destek sistemin katmanları ve ilgili teknolojiler ile bütünleşik mimarı yapısı tanımlanmıştır.
A comparison of long-range licensed and unlicensed lpwan technologies according to their geolocation services and commercial opportunities
(Mediterranean Microwave Symposium, 2018) Rama, Ylli; Özpınar, Alper
The era of the Internet of Things already started to be a part of daily lives. During these early years of development, the biggest barrier on the IoT solutions is the limited connection ranges and the desire for longer isolated working without connection to the grid. Low Power Wide Area Networks (LPWAN) is one of the most important key solutions for these two major issues due to its ability to connect very low power devices distributed in very large areas. This need does make the LP-WAN technologies become widely used in different fields of various applications of smart cities. In this paper, the current LP-WAN technologies are categorized into two groups, those unlicensed and licensed. Explored from both technical and non-technical requirements for applications, they are also compared to each other regarding their technological and commercial aspects. Also, as the need for technologies that would apply asset location is quickly becoming a requirement for the enterprise and industrial IoT, so the geolocation feature of LPWAN is also discussed as a major requirement.
Workforce optimization for bank operation centers: a machine learning approach
(Ijimai, 2017) Serengil, Şefik İlgin; Özpınar, Alper
Online Banking Systems evolved and improved in recent years with the use of mobile and online technologies, performing money transfer transactions on these channels can be done without delay and human interaction, however commercial customers still tend to transfer money on bank branches due to several concerns. Bank Operation Centers serve to reduce the operational workload of branches. Centralized management also offers personalized service by appointed expert employees in these centers. Inherently, workload volume of money transfer transactions changes dramatically in hours. Therefore, work-force should be planned instantly or early to save labor force and increase operational efficiency. This paper introduces a hybrid multi stage approach for workforce planning in bank operation centers by the application of supervised and unsu-pervised learning algorithms. Expected workload would be predicted as supervised learning whereas employees are clus-tered into different skill groups as unsupervised learning to match transactions and proper employees. Finally, workforce optimization is analyzed for proposed approach on production data.
Credit risk evaluation as a service (creaas) based on ann and machine learning
(Auricle Technologies, 2016) Özpınar, Alper; Birol, Aysun
Credit risk evaluation is the major concern of the banks and financial institutions since there is a huge competition between them to find the minimum risk and maximum amount of credits supplied. Comparing with the other services of the banks like credit cards, value added financial services, account management and money transfers, the majority of their capitals has been used for various types of credits. Even there is a competition among them for finding and serving the low risk customers, these institution shares limited information about the risk and risk related information for the common usage. The purpose of this paper is to explain the service oriented architecture and the decision model for those banks which shares the information about their customers and makes potential customer analysis. Credit Risk Evaluation as a Service system, provides a novel service based information retrieval system submitted by the banks and institutions. The system itself has a sustainable, supervised learning with continuous improvement with the new data submitted. As a main concern of conflict of interest between the institutions trade and privacy information secured for internal usage and full encrypted data gathering and as well as storing architecture with encryption. Proposed system architecture and model is designed mainly for the commercial credits for SME’s due to the complexity and variety of other credits.
Planning workforce management for bank operation centers with neural networks
(Wseas, 2016) Serengil, Şefik İlgin; Özpınar, Alper
A bank operation center provides a revolutionary efficiency to reduce operational workload of branches. In this way, offering faster, more accurate and high quality service is aimed to increase service quality. Service quality is also based on predicting transactions counts before time to make employee planning properly. In this paper, transactions of bank operation centers are considered as time series problem and a model is proposed for forecasting the transaction counts for different operation types with artificial neural networks. This model was simulated for forecasting Money Order and EFT operations which are the most active transactions of operation centers
A balancing demand response clustering approach of domestic electricity for day-ahead markets
(Auricle Technologies, 2018) Özpınar, Alper; Işık, Burak
This paper introduces a new clustering approach for multi-customer intelligent demand response for customers living in the same or closer smart grid locations using real electricity consumption data from smart meters. Most of the demand side management or customer tariffs focused on a single customer to optimize their usage discarding the others connected to the same grid. The proposed balancing clustering focus on the customers connected to the same or closest grid to optimize the smooth operating of the energy producers. This approach offers a triple win-win-win model for peak and low consumption customers as well as the balancing for the producer/ distributor utility companies for planning the day ahead markets. This paper uses the most widely used clustering method of k-means for finding similar customers on the opposing side peak, low consumption profiles and combines the most distinguished customers forming more uniform consumption for day-ahead market. This customer balancing and grouping them provides a better way toaggregate residential load data for power buy and sell for all sides and results in better load scheduling.
The classification of workforce requirement planning for service oriented operations
(Auricle Technologies, 2016) Özpınar, Alper; Serengil, Şefik İlgin
In today’s world of competitive international economy sectors, service industry or service sector oriented businesses, the key point is to maximize the efficiency and sustainability of the business directly related with optimal planning of the workload and distributing them among the employees. Helpdesks and operation centers are one of the fastest developing service area of this sector. This paper compares the machine learning algorithms that can be used for the classification of workforce requirements for a bank operation center which provides support to reduce operational workload of bank branches. Classification of the workload based on the quantity of Money Order and EFT operations within time zones aids in the management of workforce teams and distribution of jobs between team members.
Poly-?-caprolactone electrospun nanofiber mesh as a gene delivery tool
(Aims Press, 2016) Jiang, Jianhao; Ceylan, Muhammet; Zheng, Yi; Yao, Li; Asmatulu, Ramazan; Yang, Shang-You
Poly-?-caprolactone (PCL) is a biodegradable aliphatic polyester which plays critical roles in tissue engineering, such as scaffolds, drug and protein delivery vehicles. PCL nanofiber meshes fabricated by electrospinning technology have been widely used in recent decade. The objective of this study intends to develop a gene-tethering PCL-nanofiber mesh that can be used as a wrapping material during surgical removal of primary bone tumors, and as a gene delivery tool to provide therapeutic means for tumor recurrence. Non-viral plasmid vector encoding green fluorescent protein (eGFP) was incorporated into PCL nanofibers by electron-spinning technique to form multilayer nano-meshes. Our data demonstrated that PCL nanofiber mesh possessed benign biocompatibility in vitro. More importantly, pCMVb-GFP plasmid-linked electrospun nanofiber mesh successfully released the GFP marker gene and incorporated into the co-cultured fibroblast cells, and consequently expressed the transgene product at transcriptional and translational levels. Further investigation is warranted to characterize the therapeutic influence and long-term safety issue of the PCL nanofiber mesh as a gene delivery tool and therapeutic device in orthopedic oncology
Effects of gentamicin-loaded PCL nanofibers on growth of Gram positive and Gram negative bacteria
(Blue Pen, 2017) Ceylan, Muhammet; Yang, Shang-You; Asmatulu, Ramazan
Poly-?-caprolactones (PCLs) incorporated with gentamicin of different concentrations (0, 2.5, 5 and 10 wt.%) were electrospun under various conditions, and the resultant nanofibers of different thicknesses (1, 2 and 4 layers) were used against the growth of Gram-negative and Gram-positive bacteria, such as Escherichia coli, Salmonella sp. and Staphylococcus epidermidis. PCL polymer was selected mainly because of its biodegradable aliphatic polyester characteristics and also, it plays a critical role in tissue engineering and pharmaceuticals. Scanning electron microscopy (SEM) images showed that the resultant fibers were in the range of 50 to 200 nm with an average diameter of 100 nm. Bacterial test results revealed that the gentamicin molecules in the nanofibers were gradually released from the PCL nanofibers during the in vitro tests and prevented bacterial growth at different inhibition zones and kinetics. Overall, this work provides a detailed explanation of how to improve the antibacterial properties of new drug delivery systems for many biomedical fields, such as scaffolding; drug, DNA, and protein delivery; and wound healing.
Synthesis and characterization of platinum nanocomposites
(Eskişehir Teknik Üniversitesi, 2018) Ceylan, Muhammet; Tepekıran, Beyza Nur
This work related to fabrication of platinum nano particles, reveals considerably outstanding catalytic and electrical properties and preparation of Pt- PS nano composite. For this study Pt nano particles were synthesized by wet chemical method. Pt particles with 0.25%, 0.5%, 1% and 2% concentration amounts were added into the polystyrene solution, acquired by recycled PS. Three different composites which possess a distinct percentage of platinum were produced. Fibers were fabricated by electro spinning method afterward. Pt particles which were produced by wet chemical method and fibers were analyzed by SEM-EDS. There were various test and measurement methods performed to determine the characteristics of the platinum nano composite.
ATM cash flow prediction and replenishment optimization with ANN
(Kırıkkale Üniversitesi, 2019) Özpınar, Alper; Serengil, Sefik Ilkin
ATMs are physical interaction points between financial institutions and real customers. Storing physical cash causes renouncing to get interested. On the other hand, customer satisfaction requires to store the necessary cash amount. This concern becomes even more critical for countries having high-interest rate and overnight interest rates are higher. In this paper, we will show that daily cash withdrawals are predictable and we will propose a cost function for replenishment optimization. Experiments show that proposed model decrease idle balance dramatically.
E-Ticarette Müşteri İlişkileri Yönetiminde Tedarik Zinciri Etkisinin İncelenmesi
(İstanbul Ticaret Üniversitesi, 2011) Özpınar, Alper; Ağbulut, Eda; Öner, Oya
Son yıllarda arz-talep dengesindeki değişimler ve yeni ekonomik koşullar, firmaların müşterine 360° bir bakış açısı değerlendirmelerini gerektiğini ortaya koymuştur. Genellikle yanlış anlaşılan müşteri ilişkileri yönetimi uygulamalarında firmalar dış kaynaklı bir çağrı merkezi ile anlaşmakta ve paket bir MİY yazılımı uygulamaya almaktadırlar. İç süreçlerden bağımsız ve altyapı desteği olmayan bu sistemler genellikle müşteri ve firma açısından başarısız bir deneyim olmaktan öteye gidememektedir. Çalışmada insan, süreç ve teknoloji çevriminde; e-ticaret firmaların tedarik zinciri yönetimlerinin müşteri ilişkilerine olan etkisi ve başlıca etki faktörleri belirlenmiş. Belirlenen faktörlere göre müşteriler ve tedarikçisi olan işletmeleri kapsayan bir anket çalışması yapılmış ve anket sonuçları değerlendirilmiştir. Sonuçlara göre teknoloji ve süreçler açısından uygun veri akışı ve etkili bir kullanım için yol haritası ortaya konulmuştur.

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