Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article A Hybrid Actuation System for Enhancing the Performance Metrics Related to Kinesthetic-Type Haptic Devices(IEEE-Inst Electrical Electronics Engineers Inc, 2025) Kucukoglu, Sefa Furkan; Can Dede, Mehmet ismetHigh torque to volume ratio, fast response, and high dynamic range are some of the desired performance metrics for kinesthetic-type haptic device actuation systems. In this article, we present a hybrid actuation system consisting of an active actuator and a magnetorheological fluid-based brake (MRF brake). MRF brake's tradeoffs, namely, off-state torque and slow response (compared to an electric motor), are investigated and resolved by this hybrid actuation system. First, the transient behavior of the MRF brake is investigated and an mathematical model is proposed to mimic its transient response behavior. It is found that the performance of the proposed model performs better than the conventionally used first-order transfer function. Second, hybrid actuation system is constructed. The active actuator is used for compensating for the speed of the response and the off-state torque based on the proposed mathematical model of the MRF brake. It is measured that the off-state torque is largely eliminated from 0.178 to 0.008 N center dot m, the dynamic range is enlarged from 15 to 42.4 dB, and its time constant is improved from 69.6 to 4.4 ms when the hybrid actuation system is used instead of just an MRF brake.Article FW-S3KIFCM: Feature Weighted Safe-Semi Kernel-Based Intuitionistic Fuzzy C-Means Clustering Method(Tsinghua Univ Press, 2025) Khezri, Shirin; Aghazadeh, Nasser; Hashemzadeh, Mahdi; Oskouei, Amin GolzariSemi-supervised clustering (SSC) methods have emerged as a notable research area in machine learning. These methods integrate prior knowledge of class distribution into their clustering process. Despite their efficiency and straightforwardness, SSCs encounter some fundamental issues. Generally, the proportion of unlabeled data surpasses that of labeled data. Consequently, handling the uncertainty of unlabeled data becomes difficult. This issue is frequently related to numerous real-world problems. On the other hand, existing SSC techniques fail to differentiate between the varied attributes within the feature space. When forming clusters, they presume uniform significance for all attributes, disregarding potential variations in feature importance. This presumption hinders the creation of optimal clusters. Furthermore, all existing approaches employ the Euclidean distance metric, susceptible to noise and outliers. This paper proposes a robust safe-semi-supervised clustering algorithm to mitigate these shortcomings. For the first time, this approach combines two concepts of Intuitionistic Fuzzy C-Means (IFCM) clustering and Safe-Semi-Supervised Fuzzy C-Means (S3FCM) clustering to address the uncertainty problem in unlabeled data. Also, it uses a kernel function as a distance metric to tackle noise and outliers. Additionally, incorporating a feature weighting parameter in the objective function highlights the importance of significant features in creating optimal clusters. The effectiveness of the proposed method is thoroughly evaluated on various benchmark datasets, and its performance is compared with state-of-the-art methods. The results show the superiority of the proposed method over its competitors.Conference Object Citation - Scopus: 1Integration of Stm32 Microcontroller With Arm Cortex Architecture Into the 8-Bit Measurement Circuit Customized for Real-Time Data Acquisition on Propeller Shaft To Increase Data Speed and Accuracy(ISRES Publishing, 2023) Aldemir,O.; Tarakci,S.; Ozdemir,S.; Isik,E.Propeller shafts transmit torque and high-speed rotational movement from the engine to related equipment. Expected propeller shaft functions are calculated and designed by using an analytical and numerical approaches. The verification tests are significant in that they provide feedback to the design and development processes. Therefore, acquiring accurate data from power transmission equipment is becoming even more important. This paper focuses on the study of circuit boards customized for use in the validation tests of the propeller shafts. It should be noted that these measurement circuits were integrated on the propeller shafts. These measurement circuits were used to acquire data such as torque, temperature, etc. in real time. Especially with instantaneous signals such as torque, data loss can occur due to low microcontroller resolution. Therefore, it was aimed to develop to the microcontroller to 32-bit resolution from 8-bit resolution to increase data speed and accuracy. As the first step, an INA125P operational amplifier was installed to amplify the low voltage values gathered from the gages and the sensors. The gain value of the amplifier was calculated in order to provide the highest data resolution and sensitivity. And then, ADS1115 analog to digital converter circuit with a rate of 860 samples per second and 16-bit resolution was used to interpret the analog data. A low pass filter was installed to remove noise from the output signal. Embedded code was also locally developed for the hardware installed. The system was calibrated on a validated test rig. Real-time torque and temperature data were acquired from the propeller shaft. It is observed that compared to the previous 8-bit system, the data accuracy and integrity from the new 32-bit board has increased by a factor of 5 to 100 Hz. The collected data was found to be 99.4% compatible with the validated test rig data. © 2023 Published by ISRES.Article Citation - WoS: 32Citation - Scopus: 49Measurement of the tt‾bb‾ Production Cross Section in the All-Jet Final State in pp Collisions at S=13 TeV(Elsevier B.V., 2020) Sirunyan, A.M.; Tumasyan, A.; Adam, W.; Ambrogi, F.; Bergauer, T.; Brandstetter, J.; Moraes, A.A measurement of the production cross section of top quark pairs in association with two b jets (tt‾bb‾) is presented using data collected in proton-proton collisions at s=13 TeV by the CMS detector at the LHC corresponding to an integrated luminosity of 35.9 fb−1. The cross section is measured in the all-jet decay channel of the top quark pair by selecting events containing at least eight jets, of which at least two are identified as originating from the hadronization of b quarks. A combination of multivariate analysis techniques is used to reduce the large background from multijet events not containing a top quark pair, and to help discriminate between jets originating from top quark decays and other additional jets. The cross section is determined for the total phase space to be 5.5±0.3(stat)<inf>−1.3</inf> +1.6(syst)pb and also measured for two fiducial tt‾bb‾ definitions. The measured cross sections are found to be larger than theoretical predictions by a factor of 1.5–2.4, corresponding to 1–2 standard deviations. © 2020 The Author