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Çevrimiçi Deneyler

Demirtaş, Burak Kağan (Akademisyen Kitabevi, 2021)

Ekonomi bilimi deneysel metotların gün geçtikçe daha da fazla kullanıldığı birbilim dalı haline gelmiştir. Gelişen teknoloji ile birlikte deneysel çalışmalar içinkullanılan araçlar da gün geçtikçe artmaktadır. Literatürde ...

Çok işçili montaj hatlarında istasyon ve kaynak yatırımı maliyetinin enküçüklenmesine yönelik tavlama benzetimi ve tam sayılı doğrusal programlamaya dayalı yeni bir algoritma

Şahin, Murat; Kellegöz, Talip; Söylemez, İsmet (Dicle Üniversitesi, 2018)

Standardize edilmiş ürünlerin üretiminde yaygın olarak kullanılan montaj hatları önemli bir akış tipi üretim şeklidir. Buhatların dengelenme problemleri üretim ve kaynak yatırımı maliyetlerinin enküçüklenmesi açısından ...

Çok Ölçekli Malzeme Modellemesi Yoluyla Talaşlı İmalat Çıktılarının Daha Kapsamlı Ve Doğru Analizi

Bal, Burak; LAYEGH KHAVIDAKI, SEYD EHSAN (TUBİTAK, 2020)

İnconel 718 savunma sanayi, uzay-havacılık ve otomotiv için kullanılan ve ileride kullanım alanı daha da genişleyebilecek olan süper alaşımdır. Bu projede Inconel 718 süper alaşımının talaşlı imalat sonucunda yüzeyinde ...

A Data Mining Method For Refining Groups In Data Using Dynamic Model Based Clustering

Servi, Tayfun; Erol, Hamza (IEEE, 2013)

A new data mining method is proposed for determining the number and structure of clusters, and refining groups in multivariate heterogeneous data set including groups, partly and completely overlapped group structures ...

Data Mining Techniques in Direct Marketing on Imbalanced Data using Tomek Link Combined with Random Under-sampling

Ümit Yilmaz; Zafer Aydin; V. Çağri Güngör; Cengiz Gezer (Association for Computing Machinery, 2021)

Determining the potential customers is very important in direct marketing. Data mining techniques are one of the most important methods for companies to determine potential customers. However, since the number of potential ...

Data-driven discovery and DFT modeling of Fe4H on the atomistic level

Zagorac, Dejan; Zagorac, Jelena; Djukic, Milos B.; Bal, Burak; Schön, J. Christian (ELSEVIER, 2024)

Since their discovery, iron and hydrogen have been two of the most interesting elements in scientific research, with a variety of known and postulated compounds and applications. Of special interest in materials engineering ...

Dayım: Bir İnsanoğlunun Portresi

Donmez, Rasim Ozgur (TURKISH LIBRARIANS ASSOC, YENISEHIR, NECATIBEY CAD, ELGIN SOK, PO BOX 175, ANKARA, 06440, TURKEY, 2019)

This is a memoir written by his nephew about our colleague Ali Can, who passed away in last July.

Debris flow modelling and hazard assessment for a glacier area: a case study in Barsem, Tajikistan

Yılmaz, Kutay; Dincer, Ali Ersin; Kalpakcı, Volkan; Öztürk, Şevki (SPRINGER, 2023)

This study analyses a previous debris fow hazard as a consequence of emerging risks related to climate and regional physical changes. In addition to the increasing food frequencies, there is an increasing risk of mud or ...

A decision support system for the prediction of mortality in patients with acute kidney injury admitted in intensive care unit

Kayaalti, Selda; Kayaalti, Omer; Aksebzeci, Bekir Hakan (UNIV SOUTH BOHEMIA, FAC HEALTH & SOCIAL STUD, JIROVCOVA, CESKA BUDEJOVICE, 370 04, CZECH REPUBLIC, 2020)

Intensive care unit (ICU) is a very special unit of a hospital, where healthcare professionals provide treatment and, later, close followup to the patients. It is crucial to estimate mortality in ICU patients from many ...

A Deep Ensemble Approach for Long-Term Traffic Flow Prediction

Cini, Nevin; Aydin, Zafer (SPRINGER, 2024)

In the last 50 years, with the growth of cities and increase in the number of vehicles and mobility, traffic has become troublesome. As a result, traffic flow prediction started to attract attention as an important research ...

A deep learning approach with Bayesian optimization and ensemble classifiers for detecting denial of service attacks

Gormez, Yasin; Aydin, Zafer; Karademir, Ramazan; Gungor, Vehbi C. (WILEY, 111 RIVER ST, HOBOKEN 07030-5774, NJ USA, 2020)

Detecting malicious behavior is important for preventing security threats in a computer network. Denial of Service (DoS) is among the popular cyber attacks targeted at web sites of high-profile organizations and can ...

Deep learning approaches for vehicle type classification with 3-D magnetic sensor

Kolukisa, Burak; Yildirim, Veli Can; Elmas, Bahadir; Ayyildiz, Cem; Gungor, Vehbi Cagri (ELSEVIER, 2022)

In the Intelligent Transportation Systems, it is crucial to determine the type of vehicles to improve traffic management, increase human comfort, and enable future development of transport infrastructures. This paper presents ...

Deep Learning Based Formation Control of Drones

Kabore, Kader M.; Güler, Samet (Springer Science and Business Media Deutschland GmbH, 2021)

Robot swarms can accomplish demanding missions fast, efficiently, and accurately. For a robust operation, robot swarms need to be equipped with reliable localization algorithms. Usually, the global positioning system (GPS) ...

Deep learning based semantic segmentation and quantification for MRD biochip images

Çelebi, Fatma; Tasdemir, Kasim; Icoz, Kutay (ELSEVIER SCI LTD, 2022)

Microfluidic platforms offer prominent advantages for the early detection of cancer and monitoring the patient response to therapy. Numerous microfluidic platforms have been developed for capturing and quantifying the tumor ...

A deep neural network approach with hyper-parameter optimization for vehicle type classification using 3-D magnetic sensor

Kolukisa, Burak; Yildirim, Veli Can; Ayyildiz, Cem; Gungor, Vehbi Cagri (ELSEVIER, 2023)

The identification of vehicle types plays a critical role in Intelligent Transportation Systems. In this study, battery-operated, easy-to-install, low-cost 3-D magnetic traffic sensors have been developed for vehicle type ...

Deep-Red-Emitting Colloidal Quantum Well Light-Emitting Diodes Enabled through a Complex Design of Core/Crown/Double Shell Heterostructure

Shabani, Farzan; Dehghanpour Baruj, Hamed; Yurdakul, Iklim; Delikanli, Savas; Gheshlaghi, Negar; Isik, Furkan; Liu, Baiquan; Altintas, Yemliha; Canimkurbey, Betul; Demir, Hilmi Volkan (WILEY-V C H VERLAG GMBHPOSTFACH 101161, 69451 WEINHEIM, GERMANY, 2021)

Extending the emission peak wavelength of quasi-2D colloidal quantum wells has been an important quest to fully exploit the potential of these materials, which has not been possible due to the complications arising from ...