Authors:Derviş Emre AYDIN; Yilmaz AR Abstract: Eyewitness misidentifications are one of the leading factors in wrongful convictions. This study focuses on the structure of the lineups, which is one of the factors that cause misidentification, and the use of artificial intelligence (AI) technologies in the selection of fillers to be included in the lineups. In the study, AI-based face recognition systems are used to determine the level of similarity of fillers to the suspect. Using two different face recognition models with a Convolutional Neural Network (CNN) structure, similarity threshold values close to human performance were calculated (VGG Face and Cosine similarity = 0.383, FaceNet and Euclidean l2 = 1.16). In the second part of the study, the problems that are likely to be caused by facial recognition systems used in the selection of fillers are examined. The results of the study reveal that models responsible for facial recognition may not suffice alone in the selection of fillers and, an advanced structure using CNN models trained to recognize other attributes (race, gender, age, etc.) associated with similarity along with face recognition models would produce more accurate results. In the last part of the study, a Line-up application that can analyze attributes such as facial similarity, race, gender, age, and facial expression, is introduced. PubDate: Fri, 30 Dec 2022 00:00:00 +030
Authors:Gizem Eda SAĞIR; Selçuk TAŞCIOĞLU Abstract: Quadrature mixing is widely used in wireless communication receivers since it provides a solution for image signal problem with low-cost implementations. Image signal is caused by phase and amplitude mismatches between in-phase (I) and quadrature (Q) paths of the receiver. This problem is known as I/Q imbalance and degrades the communication performance if not compensated. In this study, the impact of I/Q imbalance compensation on wireless communication performance is evaluated through experiments and simulations. Simulation results demonstrate that significant communication performance improvement can be achieved in terms of bit error rate (BER) and symbol error rate (SER) by compensating the I/Q imbalance properly. In the experiments, compensation is applied to the signals captured using a software defined radio with zero-IF architecture. Experimental results demonstrate that wireless transmission success rate for the zero-IF receiver is increased by compensating I/Q imbalance. PubDate: Fri, 30 Dec 2022 00:00:00 +030
Authors:Sümeye Nur KARAHAN; Aykut KALAYCIOĞLU Abstract: Applications of deep learning in communications systems are becoming popular today with their powerful solutions to complex problems. This study considers the utilization of deep learning detectors for small-scale multiple-input multiple-output systems. Deep neural network, long short-term memory, and one-dimenisonal convolutional neural network architectures are discussed and the bit error rate performances of these deep learning based detectors are compared with the optimal maximum likelihood and sub-optimal minimum mean square error detectors. Simulation results show that the deep neural network architecture has the best detection performance among the discussed deep learning detectors and may outperform the sub-optimal minimum mean square error detector. For small-scale multiple-input multiple-output systems, the performance of the deep learning based detector is close to that of the optimal detector. PubDate: Fri, 30 Dec 2022 00:00:00 +030
Authors:Kürşad ERDOĞAN; Fikret ARI Abstract: Soil erosion, mainly occurring in agricultural areas, is an economic and ecological problem that can happen anywhere. Swelling and transport of soil particles reduce the productivity of agricultural lands. Soil surface analysis and soil-water interaction are essential topics in agricultural research and engineering as they affect the risk of soil erosion. Erosion affects the upper soil layers rich in organic matter. After the transport of this topsoil, the subsoil with a more compact structure emerges. In this case, the cultivation of the soil becomes complex, and agricultural productivity is adversely affected. Different techniques have been used to analyze the effects of erosion. In this study, we focused on rill erosion, one of the types. An electronic imaging system has been designed using the Microsoft Kinect Sensor and Raspberry Pi, which can be found quickly and at a low cost during operation. The software has been developed to extract the surface topography by analyzing the depth images of rill erosion obtained with this system. Measurements were taken using eight types of flow rates on four soil types. As a result of the experimental findings, it has been seen that volume changes of 1.3812 mm3 can be detected as a unit with the Kinect Sensor placed at a distance of 70 cm. PubDate: Fri, 30 Dec 2022 00:00:00 +030
Authors:Oğuzhan TİMUR; Ahmet TEKE Abstract: Different methods should be developed to work on energy efficiency in the electrical systems that do not allow outside intervention in the control part. In this study, the command and control of split air conditioners is carried out through hardware and software designed using the embedded system board. Infrared signals in the remote control device of the air conditioner were read with the developed circuit and recorded in the internal memory of the card, and these codes were used for energy efficiency studies. The obtained codes were used in 2 different applications. Thermal camera technology has been used instead of the traditional presence and motion sensors, which cannot achieve the desired success in asset detection in the absence of motion in the implemented applications. In this way, the presence of living things in the areas where the application is made has been detected with a much higher sensitivity regardless of the movement. As a result of the realized studies on the existing systems, 30% energy saving potential is determined approximately. PubDate: Fri, 30 Dec 2022 00:00:00 +030
Authors:Levent ÖZBEK Abstract: The study aims to determine a mathematical model that can be used to describe the growth of the Adana pigeon. Since pigeons have only one breeding season, just one or two pairs of baby pigeons are raised per year. Hatchlings sometimes die before reaching adulthood. For this reason, measurements can be taken for 10, 15 and 60 days periods. Related with this issue, only 43-days measurements of 68 pigeons are used over a 6-year period. The study is modelled by taking the day-to-day average of the data (43 days) of 68 pigeons. The study was conducted on 68 Adana pigeons in the interval between the age of 1 and 43 days. The growth of pigeon cub was measured by daily live weight until 1 to 43 days. The estimation is carried out by writing the specific Matlab codes. Classical growth functions used in animals are in nonlinear form. Various numerical methods have been developed to estimate parameters in nonlinear functions. Special program routines have been developed to implement these methods. In these nonlinear models, there are more than one parameter to be estimated. Therefore, the number of mathematical operations in estimating the parameters is large. The most used models in the literature are Brody, Bertalanffy, Logistic, Generalized Logistic, Gompertz, Richards, Negative Exponential, Stevens, and Tanaka. However, as far as is known, there is no published article for Adana pigeons that uses all of these models and compares which one is better. These models are Brody, Bertalanffy, Logistic, Generalized Logistic, Gompertz, Richards, Negative Exponential, Stevens, and Tanaka. The best analysis was done by the Richards model in terms of both the Mean Squared Error (MSE), mean absolute percentage error (MAPE) and (Coefficient of Determination) R2 . PubDate: Fri, 30 Dec 2022 00:00:00 +030
Open Access journal
