Örnek, Mustafa Nevzat

Profile URL
https://hdl.handle.net/20.500.13091/11781
Name Variants
Ornek, Mustafa N. Ornek, Mustafa Nevzat Örnek, Mustafa N. Örnek, M. Nevzat Ornek, M. Nevzat Örnek, M. N. Ornek, M. N.
Job Title
Email Address
mnornek@ktun.edu.tr
Main Affiliation
07. 16. Department of Machinery and Metal Technologies
Status
Current Staff
Website
ORCID ID
0000-0002-7478-3728
Scopus Author ID
56031369800
Turkish CoHE Profile ID
5D4A3F1C12054E2F
Google Scholar ID
rIisQfAAAAAJ
WoS Researcher ID
ABF-7736-2021

Research Topics

Domains
Life SciencesPhysical Sciences
Fields
Agricultural and Biological SciencesChemistryEngineeringComputer Science
Subfields
Plant ScienceAnalytical ChemistryMechanical EngineeringMechanics of MaterialsInformation Systems
Specific Research Areas
Smart Agriculture and AI
Spectroscopy and Chemometric Analyses
Agricultural Engineering and Mechanization
Forest Biomass Utilization and Management
Web Application Security Vulnerabilities

Sustainable Development Goals

NO POVERTY1
NO POVERTY
0
Research Products
ZERO HUNGER2
ZERO HUNGER
0
Research Products
GOOD HEALTH AND WELL-BEING3
GOOD HEALTH AND WELL-BEING
0
Research Products
QUALITY EDUCATION4
QUALITY EDUCATION
0
Research Products
GENDER EQUALITY5
GENDER EQUALITY
0
Research Products
CLEAN WATER AND SANITATION6
CLEAN WATER AND SANITATION
0
Research Products
AFFORDABLE AND CLEAN ENERGY7
AFFORDABLE AND CLEAN ENERGY
0
Research Products
DECENT WORK AND ECONOMIC GROWTH8
DECENT WORK AND ECONOMIC GROWTH
0
Research Products
INDUSTRY, INNOVATION AND INFRASTRUCTURE9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
1
Research Products
REDUCED INEQUALITIES10
REDUCED INEQUALITIES
0
Research Products
SUSTAINABLE CITIES AND COMMUNITIES11
SUSTAINABLE CITIES AND COMMUNITIES
0
Research Products
RESPONSIBLE CONSUMPTION AND PRODUCTION12
RESPONSIBLE CONSUMPTION AND PRODUCTION
0
Research Products
CLIMATE ACTION13
CLIMATE ACTION
0
Research Products
LIFE BELOW WATER14
LIFE BELOW WATER
0
Research Products
LIFE ON LAND15
LIFE ON LAND
0
Research Products
PEACE, JUSTICE AND STRONG INSTITUTIONS16
PEACE, JUSTICE AND STRONG INSTITUTIONS
0
Research Products
PARTNERSHIPS FOR THE GOALS17
PARTNERSHIPS FOR THE GOALS
0
Research Products
Documents

5

Citations

37

h-index

3

Go to Scopus profile
Documents

3

Citations

28

Go to WoS profile

Publication Collaboration

Affiliation Name Count
Selçuk University 9
Konya Technical University 5
Konya Food and Agriculture University 1
1 / 1
Data obtained from OpenAlex
Scholarly Output

5

Articles

5

Views / Downloads

13/26

Supervised MSc Theses

0

Supervised PhD Theses

0

WoS Citation Count

28

Scopus Citation Count

33

Patents

0

Projects

0

WoS Citations per Publication

5.60

Scopus Citations per Publication

6.60

Open Access Source

3

Supervised Theses

0

JournalCount
ACADEMIC PLATFORM-JOURNAL OF ENGINEERING AND SCIENCE1
ERWERBS-OBSTBAU1
JOURNAL OF FOOD MEASUREMENT AND CHARACTERIZATION1
Selçuk Üniversitesi Mühendislik Bilim ve Teknoloji Dergisi1
Yuzuncu Yil University Journal of Agricultural Sciences1
Current Page: 1 / 1

Scopus Quartile Distribution

Competency Cloud

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Filters

2018 - 201922020 - 20213

Settings

Author of Publication: search.filters.isAuthorOfPublication.95886cf4-de54-4cad-8d2d-ffffe2b05074

Scholarly Output Search Results

Now showing 1 - 5 of 5
  • Article
    Evaluation of Most Visited Web Sites in Turkey in Aspects of Structure and Security
    (2018-12-01) Daşdemir, Atakan; Örnek, Mustafa Nevzat; Örnek, Humar Kahramanlı
    Applications on World Wide Web have made our daily lives easier with their basic and fast access, neglecting time and place, they have become indispensable. It made Web applications a popular target for malevolent users and increased web security risk. In this study web penetration test which is indispensable for web security and threating risks for web security are mentioned. In Turkey, 60 of the most visited sites were identified in five different categories scanned as an ordinary user to consider a safety assessment of the general situation of the websites. For the review, large sites in news sites, e-commerce, government, universities and other categories have been selected that are thought to have strong security infrastructure. The knowledge about these sites such as used technologies and infrastructure which considers as vulnerability of sites and can be obtained by the ordinal person who uses penetration tests has been investigated in this study. As a result of the research, operating system information and web server information from 62% and 87% of the reviewed sites were identified respectively. Medium and low degree vulnerabilities were found in all scanned websites. With the vulnerability screening tests, weakness map revealed and information about the most identified weaknesses was given
  • Article
    Havucun Boy ve Çap Verileri Kullanılarak Hacminin Hesaplanması için Matematiksel Model Geliştirilmesi
    (2019-01-01) Örnek, Mustafa Nevzat; Kahramanlı Örnek, Humar; Örnek, Humar Kahramanli
    Havuç, dünyada patatesten sonra en çok üretimi yapılan sebzedir. Türkiye’de havucun en çok yetiştirildiği bölge Konya iline bağlı Kaşınhanı’dır. Bu nedenle çalışmada uygulama amacı ile Kaşınhanı’nda üretilen havuçlar seçilmiştir. Toplam 464 adet Nantes türü havuç kullanılmıştır. Havuçların boyu, 5 santimetre ara ile çapları ve hacimleri ölçülmüştür. Daha sonra sunulan yöntem ile havuçların hacimleri hesaplanmış ve gerçek hacimlerle karşılaştırılmıştır. Tüm havuçlar için hesaplanan hacim ile ölçülen hacim arasındaki R2 değeri 0,9 olarak bulunmuştur. Ölçülen ve hesaplanan değerler arasında korelasyon doğrusunun eğimi 1,06 olmuştur ki, bu da ideal değere çok yakındır.
  • Article
    Citation - WoS: 15
    Citation - Scopus: 15
    Developing a Deep Neural Network Model for Predicting Carrots Volume
    (SPRINGER, 2021-04-23) Örnek, Mustafa Nevzat; Örnek, Humar Kahramanlı
    In this paper, a deep learning approach to predict carrots volume according to the physical properties was designed. A total of 464 carrots were used for volume prediction. The used carrots were taken from Kasinhani, Konya. First, the data was produced. For this, the length, the diameters with 5 cm intervals, and the volume of each carrot were measured and recorded. The measurements were done using a steel ruler, a vernier caliper, and a glass graduated cylinder. Two deep learning methods: DFN and LSTM were developed to predict carrot volume. The developed systems were implemented with the Keras library for Python. Statistical measures such as Root Mean Squared Error, Mean Absolute Error, and R-2 were used to determine the predicting accuracy of the system. Both methods produced very close values. DFN and LSTM networks achieved 0.9765 and 0.9766 R-2, respectively. RMSE values were 0.0312 for both models. The results obtained showed that both DFN and LSTM are successful and applicable to this task.
  • Article
    Citation - WoS: 13
    Citation - Scopus: 15
    Determination of Some Physical and Chemical Properties of Common Hawthorn (crataegus Monogyna Jacq. Var. Monogyna)
    (SPRINGER, 2021-02-01) Dokumacı, Keziban Yalçın; Uslu, Nurhan; Hacıseferoğulları, Haydar; Örnek, M. Nevzat; Yalcin Dokumaci, Keziban
    Hawthorn as a wild plant is an important fruit for human health. In this study, it was aimed to determine some physical and chemical properties of common hawthorn which is native plant of middle Anatolia in Turkey. According to chemical analysis results, crude protein, crude oil, ash, pH, acidity, total phenol contents and antioxidant activity values were found to be 3.03%, 1.22%, 2.77%, 4.08, 1.56%, 9.35 mg g(-1) and 67.62% respectively. Some mineral matter contents as K, P, Ca, Mg, Fe, Na and B values were found to be 16,273.88 mg kg(-1), 1316.92 mg kg(-1), 1263.86 mg kg(-1), 934.87 mg kg(-1), 62.20 mg kg(-1), 57.06 mg kg(-1) and 42.28 mg kg(-1) respectively. The values of mass, diameter, length, geometric mean diameter and sphericity of Common hawthorn fruit were determined as 0.93 g, 11.37 mm, 12.25 mm, 11.65 mm and 0.95 at 68.98% (db) humidity respectively. In addition, fruit hardness, chroma (C*), hue angle (h*) of hawthorn was found as 1.21 N, 28.94 ve 16.19 under same humidity respectively. According to study results, it can be concluded that the hawthorn fruits are admirable natural food for human nutrition, and it can be considered as reference for the future researches.
  • Article
    Citation - Scopus: 3
    Design of Real Time Image Processing Machine for Carrot Classification
    (Centenary University, 2020-06-30) Örnek, Mustafa Nevzat; Hacıseferoğullari, H.
    Kasınhanı district of Konya province has the greatest carrot production in Turkey. By the year 2017, Konya Province has approximately 46.5% of carrot production areas and 59.7% of total production. There are several washing and packing facilities in the region. These facilities show totally similar features and fully satisfy the needs of the region. Carrots coming from the washing pools come firstly to the mechanical grading machines and then to the packing department or directly to the packing department in some facilities. Grading and packing processes are carried out manually in these facilities. The classification efficiency of mechanical classification machines is known to be insufficient. In this study, mechanical, electronic and software sections of the real-time image processing machine are explained. The system was composed of a belt conveyor, cameras and closed chamber to receive images, image processing and control computer and routing covers attached to servo motors. As a result of the experiments, carrot classification rates ranged from 80.14 to 100% in real-time image processing machine. © 2020, Centenary University. All rights reserved.