Ozan Erdinç - IEEE Xplore Author Profile
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Ozan Erdinç

Also published under: Ozan Erdinc, Ozan Erdin&#x00E7;, O. Erdinç, O. Erdinc, Ozan ErdıNç, Ozan Erdin

Publications
105
Citations
2,607
Publications by Year
20092024
Co-Authors:
Show All Co-Authors (111)
Image of author Ozan Erdinç

Ozan Erdinç

Also published under: Ozan Erdinc, Ozan Erdin&#x00E7;, O. Erdinç, O. Erdinc, Ozan ErdıNç, Ozan Erdin

Affiliation

Department of Electrical Engineering
Yildiz Technical University
Istanbul, Turkey

Publication Topics

Biography

Ozan Erdinç (Senior Member, IEEE) received the B.Sc., M.Sc., and Ph.D. degrees from Yıldız Technical University (YTU), Istanbul, Türkiye, in 2007, 2009, and 2012, respectively. Until May 2013, he was with private sector in different positions, including electrical installations, renewable energy investments, and as a procurement expert. In June 2013, he became a Post-Doctoral Fellow in Portugal, under the EU-FP7 funded SINGULAR Project. Later, he joined the Department of Electrical Engineering, YTU, where he obtained the title of an Associate Professor in April 2016. In September 2021, he was appointed as a Full Professor with YTU. He was the IEEE Power and Energy Society (PES) Turkey Chapter Chair; the Head of Alternative Energy Based Elec...
Publications
105
Citations
2,607
Publications by Year
20092024
Co-Authors:
Show All Co-Authors (111)
Author's Published Works

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Robust Joint Graph Learning for Multi-View Clustering

Yanfang He;Umi Kalsom Yusof

IEEE Transactions on Big Data
Year: 2025 | Volume: 11, Issue: 2 | Journal Article |
Cited by: Papers (1)
In real-world applications, multi-view datasets often comprise diverse data sources or views, inevitably accompanied by noise. However, most existing graph-based multi-view clustering methods utilize fixed graph similarity matrices to handle noisy multi-view data, necessitating additional clustering steps for obtaining the final clustering. This paper proposes a Robust Joint Graph learning for Mul...Show More

Robust Joint Graph Learning for Multi-View Clustering

Yanfang He;Umi Kalsom Yusof

Year: 2025 | Volume: 11, Issue: 2 | Journal Article |

Simulation of Crowd Evacuation in Asymmetrical Exit Layout Based on Improved Dynamic Parameters Model

Omar Alidmat;Hamza Abu Owida;Umi Kalsom Yusof;Ahmed Almaghthawi;Askar Altalidi;Rami S. Alkhawaldeh;Suhaila Abuowaida;Nawaf Alshdaifat;Jamil AlShaqsi

IEEE Access
Year: 2025 | Volume: 13 | Journal Article |
Cited by: Papers (7)
Evacuation systems are crucial for minimizing casualties and property losses during emergencies. Understanding evacuee behavior in overcrowded situations is essential for developing effective evacuation strategies. However, evacuating large crowds from buildings with multiple exits is a challenging problem, especially when the exits are asymmetrical and the crowds are dense. This paper proposes a ...Show More

Simulation of Crowd Evacuation in Asymmetrical Exit Layout Based on Improved Dynamic Parameters Model

Omar Alidmat;Hamza Abu Owida;Umi Kalsom Yusof;Ahmed Almaghthawi;Askar Altalidi;Rami S. Alkhawaldeh;Suhaila Abuowaida;Nawaf Alshdaifat;Jamil AlShaqsi

Year: 2025 | Volume: 13 | Journal Article |

Dynamic Exit Selection and Counting Area Adjustment for Efficient Crowd Evacuation in Asymmetrical Layouts

Omar Khair Alla Alidmat;Raed Alazaidah;Mohammad Arabiat;Hayel Khafajeh;Mohammad Aljaidi;Umi Kalsom Yusof;Ali Elrashidi

2024 25th International Arab Conference on Information Technology (ACIT)
Year: 2024 | Conference Paper |
This research introduces an innovative methodology to address the significant challenge of evacuating large crowds from buildings with multiple exits, particularly in scenarios with asymmetrical exit configurations and high population densities. The proposed model incorporates dynamic counting areas that adjust according to evacuee density, alongside a probabilistic exit selection mechanism influe...Show More

Dynamic Exit Selection and Counting Area Adjustment for Efficient Crowd Evacuation in Asymmetrical Layouts

Omar Khair Alla Alidmat;Raed Alazaidah;Mohammad Arabiat;Hayel Khafajeh;Mohammad Aljaidi;Umi Kalsom Yusof;Ali Elrashidi

Year: 2024 | Conference Paper |

A Novel Cellular Automaton Model for Optimized Multi-Exit Crowd Evacuation in High-Density Environments

Omar Khair Alla Alidmat;Suhaila Abuowaida;Esraa Alhenawi;Hebatullah Khattab Awwad;Adai Al-Momani;Umi Kalsom Yusof;Ali Elrashidi

2024 25th International Arab Conference on Information Technology (ACIT)
Year: 2024 | Conference Paper |
Evacuation systems play a critical role in mitigating casualties and property damage during emergency situations. Comprehending evacuee behavior in overcrowded scenarios is vital for developing effective evacuation strategies. Nonetheless, evacuating large crowds from buildings with multiple exits presents a significant challenge, particularly when exits are asymmetrical and crowds are dense. This...Show More

A Novel Cellular Automaton Model for Optimized Multi-Exit Crowd Evacuation in High-Density Environments

Omar Khair Alla Alidmat;Suhaila Abuowaida;Esraa Alhenawi;Hebatullah Khattab Awwad;Adai Al-Momani;Umi Kalsom Yusof;Ali Elrashidi

Year: 2024 | Conference Paper |

ASFE Feature Selection Technique Integrated with SMOTE-ENN for Handling High-Dimensional and Highly Imbalanced Wafer Defect Classification Data

Yi Wei Tye;Umi Kalsom Yusof;Xin Ying Chew;Samat Tulpar

2024 17th International Conference on Advanced Computer Theory and Engineering (ICACTE)
Year: 2024 | Conference Paper |
In semiconductor manufacturing, the advancement of high-throughput sensors leads to the generation of high-dimensional and highly imbalanced data, presenting challenges like feature redundancy, increased computational costs, and bias in the classification models towards the majority class. These challenges complicate wafer defect classification, necessitating the integration of advanced feature se...Show More

ASFE Feature Selection Technique Integrated with SMOTE-ENN for Handling High-Dimensional and Highly Imbalanced Wafer Defect Classification Data

Yi Wei Tye;Umi Kalsom Yusof;Xin Ying Chew;Samat Tulpar

Year: 2024 | Conference Paper |

Multi-Domain Long-Tailed Learning: Challenges, Progress, and Prospects

Panpan Fu;Umi Kalsom Yusof

IEEE Access
Year: 2024 | Volume: 12 | Journal Article |
In practical applications, the issue of data imbalance inevitably rises. In most studies, the predominant focus regarding long-tailed class imbalance pertains to a setting within a single domain in which the training and test samples are presumed to originate from the same feature space and possess identical data distributions. However, natural datasets can be derived from distinct domains in whic...Show More

Multi-Domain Long-Tailed Learning: Challenges, Progress, and Prospects

Panpan Fu;Umi Kalsom Yusof

Year: 2024 | Volume: 12 | Journal Article |

Study on the Correlation of Trainable Parameters and Hyperparameters with the Performance of Deep Learning Models

Song-Quan Ong;Pradeep Isawasan;Gomesh Nair;Khairulliza Ahmad Salleh;Umi Kalsom Yusof

2023 4th International Conference on Artificial Intelligence and Data Sciences (AiDAS)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
Trainable parameters and hyperparameters are critical to the development of a deep learning model. However, the components have typically been studied individually, and most studies have found it difficult to investigate the effects of their combination on model performance. We are interested in examining the correlation between the number of trainable parameters in a deep learning model and its p...Show More

Study on the Correlation of Trainable Parameters and Hyperparameters with the Performance of Deep Learning Models

Song-Quan Ong;Pradeep Isawasan;Gomesh Nair;Khairulliza Ahmad Salleh;Umi Kalsom Yusof

Year: 2023 | Conference Paper |

An Automated Blastocyst Grading System Using Convolutional Neural Network and Transfer Learning

Yusuf Abas Mohamed;Umi Kalsom Yusof;Iza Sazanita Isa;Murizah Mohd Zain

2023 IEEE 13th International Conference on Control System, Computing and Engineering (ICCSCE)
Year: 2023 | Conference Paper |
Cited by: Papers (2)
In vitro fertilization (IVF) involves collecting several mature egg samples fertilized with sperm in the IVF laboratory through a process of manual grading and selecting the healthiest blastocyst embryo through visual morphology assessment. Nevertheless, this manual process is highly subjective, prone to error and human bias, time-consuming, and can result in multiple pregnancies. Since the gradin...Show More

An Automated Blastocyst Grading System Using Convolutional Neural Network and Transfer Learning

Yusuf Abas Mohamed;Umi Kalsom Yusof;Iza Sazanita Isa;Murizah Mohd Zain

Year: 2023 | Conference Paper |

An Automated Day 3 Embryo Grading Based On Morphological Characteristics Using CNN with Transfer Learning Techniques

Faisal Kevin Alkindy;Umi Kalsom Yusof;Murizah Mohd Zain

2023 IEEE 13th International Conference on Control System, Computing and Engineering (ICCSCE)
Year: 2023 | Conference Paper |
Cited by: Papers (2)
In-Vitro fertilization (IVF) is the most successful form of assisted reproductive technology and one of the most used fertility treatments. According to a prior study, the day 3 embryo development stage is a crucial transitional time that significantly impacts the pregnancy and implantation rates of day 5 transfers. Most embryologists currently analyze the morphological characteristics of day 3 em...Show More

An Automated Day 3 Embryo Grading Based On Morphological Characteristics Using CNN with Transfer Learning Techniques

Faisal Kevin Alkindy;Umi Kalsom Yusof;Murizah Mohd Zain

Year: 2023 | Conference Paper |

Forecasting of Outpatient Hospital Visits using A Bidirectional Long Short-Term Memory Model

Nur Izzati Ab Kader;Umi Kalsom Yusof;Mohd Nor Akmal Khalid

2023 8th International Conference on Business and Industrial Research (ICBIR)
Year: 2023 | Conference Paper |
Recently, accurate predicting outpatient visits is crucial in healthcare for optimizing service delivery and resource allocation. Time series models, particularly Deep Learning (DL) methods, have gained popularity in predicting demand and can potentially be used to predict demand for medical services, including outpatient hospital visits. This study aims to assess the potential of Bidirectional Lo...Show More

Forecasting of Outpatient Hospital Visits using A Bidirectional Long Short-Term Memory Model

Nur Izzati Ab Kader;Umi Kalsom Yusof;Mohd Nor Akmal Khalid

Year: 2023 | Conference Paper |

Self-Weighted Graph-Based Framework for Multi-View Clustering

Yanfang He;Umi Kalsom Yusof

IEEE Access
Year: 2023 | Volume: 11 | Journal Article |
Cited by: Papers (3)
Multiple perspectives can be used to explore rich and complex datasets that are widely used in many applications. However, in real-world applications, the multi-view data are often noisy because of various environmental factors. The key challenge of graph-based multi-view clustering is obtaining a consistent clustering structure. Most graph-based methods learn independently in one view how similar...Show More

Self-Weighted Graph-Based Framework for Multi-View Clustering

Yanfang He;Umi Kalsom Yusof

Year: 2023 | Volume: 11 | Journal Article |

Optimizing the Hyperparameter Tuning of YOLOv5 for Underwater Detection

Iza Sazanita Isa;Mohamed Syazwan Asyraf Rosli;Umi Kalsom Yusof;Mohd Ikmal Fitri Maruzuki;Siti Noraini Sulaiman

IEEE Access
Year: 2022 | Volume: 10 | Journal Article |
Cited by: Papers (39)
This study optimized the latest YOLOv5 framework, including its subset models, with training on different datasets that differed in image contrast and cloudiness to assess model performances based on quantitative metrics and image processing speed. The hyperparameter in the feature-extraction phase was configured based on the learning rate and momentum and further improved based on the adaptive mo...Show More

Optimizing the Hyperparameter Tuning of YOLOv5 for Underwater Detection

Iza Sazanita Isa;Mohamed Syazwan Asyraf Rosli;Umi Kalsom Yusof;Mohd Ikmal Fitri Maruzuki;Siti Noraini Sulaiman

Year: 2022 | Volume: 10 | Journal Article |

Leveraging Bio-Inspired Knowledge-Intensive Optimization Algorithm in the Assembly Line Balancing Problem

Mohd Nor Akmal Khalid;Umi Kalsom Yusof

IEEE Access
Year: 2021 | Volume: 9 | Journal Article |
Cited by: Papers (2)
With the increasing pressure from the market and the surge of “Industry 4.0,” staying competitive and relevant is becoming more and more difficult. The assembly line, which represents a long-term investment of the manufacturing industry, needs to be efficiently utilized. While assembly line balancing (ALB) problem had been studied for decades, oversights on the bottleneck resources could significa...Show More

Leveraging Bio-Inspired Knowledge-Intensive Optimization Algorithm in the Assembly Line Balancing Problem

Mohd Nor Akmal Khalid;Umi Kalsom Yusof

Year: 2021 | Volume: 9 | Journal Article |

Combining oversampling and undersampling techniques for imbalanced classification: A comparative study using credit card fraudulent transaction dataset

Haziqah Shamsudin;Umi Kalsom Yusof;Andal Jayalakshmi;Mohd Nor Akmal Khalid

2020 IEEE 16th International Conference on Control & Automation (ICCA)
Year: 2020 | Conference Paper |
Cited by: Papers (46)
Credit card fraud is a serious and growing problem. It is becoming more challenging with an issues of highly imbalanced class. In the field of data mining, prediction or typically known as data classification problem involved detecting events. Uncommon events are hard to identify on account of their inconsistency and casualness, however, misclassifying rare events can result in heavy costs. Thus, ...Show More

Combining oversampling and undersampling techniques for imbalanced classification: A comparative study using credit card fraudulent transaction dataset

Haziqah Shamsudin;Umi Kalsom Yusof;Andal Jayalakshmi;Mohd Nor Akmal Khalid

Year: 2020 | Conference Paper |

An Artificial Immune System Approach for Solving Type-E Assembly Line Balancing Problem with Problem-Specific Information

Mohd Nor Akmal Khalid;Umi Kalsom Yusof;Hiroyuki Iida

2020 IEEE 16th International Conference on Control & Automation (ICCA)
Year: 2020 | Conference Paper |
The advent of industrial 4.0 ushered a new era in the manufacturing industry where merely optimizing the available resources is not enough to fulfill the need of the growing market. Various approaches have addressed the assembly line balancing (ALB) problem for decades. Although solving the ALB problem is crucial, a bottleneck may still occur over the next operation stages. As such, two research d...Show More

An Artificial Immune System Approach for Solving Type-E Assembly Line Balancing Problem with Problem-Specific Information

Mohd Nor Akmal Khalid;Umi Kalsom Yusof;Hiroyuki Iida

Year: 2020 | Conference Paper |

Multi-objective Filter-based Feature Selection Using NSGAIII With Mutual Information and Entropy

Ali Muhammad Usman;Umi Kalsom Yusof;Sybirah Naim;Nehemiah Musa;Haruna Chiroma

2020 2nd International Conference on Computer and Information Sciences (ICCIS)
Year: 2020 | Conference Paper |
Cited by: Papers (3)
Feature selection (FS) aims to select the subsets of the most informative features by ignoring the redundant ones and consequently, improving the classification performance. Hence, consider as a two objective optimisation problem. Moreover, most of the existing work treats FS as single-objective by combining the two aims into a single fitness function. As such, there is a trade-off between the num...Show More

Multi-objective Filter-based Feature Selection Using NSGAIII With Mutual Information and Entropy

Ali Muhammad Usman;Umi Kalsom Yusof;Sybirah Naim;Nehemiah Musa;Haruna Chiroma

Year: 2020 | Conference Paper |

Filter-Based Multi-Objective Feature Selection Using NSGA III and Cuckoo Optimization Algorithm

Ali Muhammad Usman;Umi Kalsom Yusof;Syibrah Naim

IEEE Access
Year: 2020 | Volume: 8 | Journal Article |
Cited by: Papers (23)
Feature selection aims to confiscate inappropriate features and yet improve classification performance. These aims are conflicting with one another, and a choice must be made in the presence of the trade-off between them. Numerous researches deal with feature selection problem but, they are mostly single-objective based. Nowadays, multi-objective optimisation approaches are becoming the most suita...Show More

Filter-Based Multi-Objective Feature Selection Using NSGA III and Cuckoo Optimization Algorithm

Ali Muhammad Usman;Umi Kalsom Yusof;Syibrah Naim

Year: 2020 | Volume: 8 | Journal Article |

Literature Survey: Statistical Characteristics of Google Cluster Trace

Norfazlin Rashid;Umi Kalsom Yusof

2018 Fourth International Conference on Advances in Computing, Communication & Automation (ICACCA)
Year: 2018 | Conference Paper |
Cited by: Papers (1)
Usually, data sets used in computer network research are not widely shared because of the risk of security breach. However, with the release of Google Cluster trace (GCT), academics are able to validate their work with a common set of data. Furthermore, it helps researchers to understand the real nature of huge workload in cloud data centres. This paper aims to collect and summarize the characteri...Show More

Literature Survey: Statistical Characteristics of Google Cluster Trace

Norfazlin Rashid;Umi Kalsom Yusof

Year: 2018 | Conference Paper |

Model student selection using fuzzy logic reasoning approach

Mohd Nor Akmal Khalid;Umi Kalsom Yusof;Looi Guo Xiang

2016 International Conference On Advanced Informatics: Concepts, Theory And Application (ICAICTA)
Year: 2016 | Conference Paper |
Cited by: Papers (3)
In an educational institution, various students criteria contributed to the main reason the student is nominated as a model student. This includes cumulative grade point average (CGPA) of academic courses taken, co-curriculum involvement, soft skills, hard work, leadership, attitude, time management, attendance, attire, and technical skill in order to make the selection decision. The distinctive s...Show More

Model student selection using fuzzy logic reasoning approach

Mohd Nor Akmal Khalid;Umi Kalsom Yusof;Looi Guo Xiang

Year: 2016 | Conference Paper |

Modelling crowd behaviour during emergency evacuation: A proposed framework

Wahida Zakaria;Umi Kalsom Yusof

2016 International Conference On Advanced Informatics: Concepts, Theory And Application (ICAICTA)
Year: 2016 | Conference Paper |
Cited by: Papers (7)
Emergency often create panic and stress in crowd. The human emotional transition between normal to panic state is due to extreme event which is beyond control. In the past, crowd behavior models for emergency evacuation being studied are aircraft emergency evacuation, emotional ant based, behavior based real time evacuation and many more which is related to the behavior and life like. They are dif...Show More

Modelling crowd behaviour during emergency evacuation: A proposed framework

Wahida Zakaria;Umi Kalsom Yusof

Year: 2016 | Conference Paper |

Survey on crowd behaviour evacuation modelling during emergency event

Wahida Zakaria;Umi Kalsom Yusof

2015 9th Malaysian Software Engineering Conference (MySEC)
Year: 2015 | Conference Paper |
In the event of natural disasters, catastrophes or war, efficient tools are needed to produce evacuation plans to evacuate the crowd safely. Disaster is an unplanned situation that can happen anywhere and anytime. The worst case is when disasters happen on large gatherings which can increase risk of death during egress evacuation. When an emergency arises, crowds will evacuate to the nearest exit ...Show More

Survey on crowd behaviour evacuation modelling during emergency event

Wahida Zakaria;Umi Kalsom Yusof

Year: 2015 | Conference Paper |

Incorporating dynamism in emergency route planning problem using immune-based approach

Mohd Nor Akmal Khalid;Umi Kalsom Yusof

2015 4th International Conference on Software Engineering and Computer Systems (ICSECS)
Year: 2015 | Conference Paper |
The occurrence of emergency events tends to spark a very chaotic reaction, inducing a large surge of demand (number of evacuees) which exceeds the available resources (pathway/network). Planning a suitable evacuation route and identifying the shortest evacuation route before the occurrence of extreme events are crucial for an effective evacuation process. Although evacuation plans can be orchestra...Show More

Incorporating dynamism in emergency route planning problem using immune-based approach

Mohd Nor Akmal Khalid;Umi Kalsom Yusof

Year: 2015 | Conference Paper |

Content-based filtering algorithm for mobile recipe application

Teh Lee Cheng;Umi Kalsom Yusof;Mohd Nor Akmal Khalid

2014 8th. Malaysian Software Engineering Conference (MySEC)
Year: 2014 | Conference Paper |
Cited by: Papers (6)
In general, people like to cook but they have no idea on what to cook and how to cook. Furthermore, they also wish to know certain recipes that suit to their preference. There are many cooking recipe websites but most of them do not provide suggestions for the user based on user's food preferences. Current recipe suggestions developed by some researchers are mainly based on the collective interest...Show More

Content-based filtering algorithm for mobile recipe application

Teh Lee Cheng;Umi Kalsom Yusof;Mohd Nor Akmal Khalid

Year: 2014 | Conference Paper |

Preventive maintenance scheduling optimization in semiconductor assembly industry using harmony search algorithm

Nur Izzah Azhar;Umi Kalsom Yusof;Mohd Nor Akmal Khalid

2013 IEEE Student Conference on Research and Developement
Year: 2013 | Conference Paper |
Highly competitive markets and rapidly changing customer demands have increased the importance of proper resource utilization in the semiconductor industry. Utilizing resources (i.e. machines) is vital in order to maintain continuous flow of manufacturing as well as their efficiency and productivity. However, machine maintenance is being overlooked in most cases of the semiconductor assembly proce...Show More

Preventive maintenance scheduling optimization in semiconductor assembly industry using harmony search algorithm

Nur Izzah Azhar;Umi Kalsom Yusof;Mohd Nor Akmal Khalid

Year: 2013 | Conference Paper |

An artificial immune system algorithm for optimizing the distributed production scheduling in the semiconductor assembly industry

Nur Ifwah Mohd Anuar;Umi Kalsom Yusof;Mohd Nor Akmal Khalid

2013 13th International Conference on Intellient Systems Design and Applications
Year: 2013 | Conference Paper |
Cited by: Papers (2)
The semiconductor industry faces one of the most challenging and rapidly evolving problem in each passing time. The importance of satisfying customer demands and achieving higher profits have increased the attention towards production scheduling in semiconductor assembly areas. Combination of productivity and flexibility provided by semiconductor assembly areas have attracted many research efforts...Show More

An artificial immune system algorithm for optimizing the distributed production scheduling in the semiconductor assembly industry

Nur Ifwah Mohd Anuar;Umi Kalsom Yusof;Mohd Nor Akmal Khalid

Year: 2013 | Conference Paper |

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