The increasing adoption of digital technologies, robotic systems, and IoT applications in sectors such as medicine, agriculture, and industry drives a surge in data generation and necessitates secure and efficient encryption. For resource-constrained systems, lightweight yet robust cryptographic algorithms are critical. This study addresses the security demands of IoRT systems by proposing an enhanced chaos-based encryption method. The approach integrates the lightweight structure of NIST-standardized Ascon-AEAD128 with the randomness of the Zaslavsky map. Ascon-AEAD128 is widely used on many hardware platforms; therefore, it must robustly resist both passive and active attacks. To overcome these challenges and enhance Ascon’s security, we integrate into Ascon the keys and nonces generated by the Zaslavsky chaotic map, which is deterministic, nonperiodic, and highly sensitive to initial conditions and parameter variations.This integration yields a chaos-based Ascon variant with a higher encryption security relative to the standard Ascon. In addition, we introduce exploratory variants that inject non-repeating chaotic values into the initialization vectors (IVs), the round constants (RCs), and the linear diffusion constants (LCs), while preserving the core permutation. Real-time tests are conducted using Raspberry Pi 3B devices and ROS 2–based IoRT robots. The algorithm’s performance is evaluated over 100 encryption runs on 12 grayscale/color images and variable-length text transmitted via MQTT. Statistical and differential analyses—including histogram, entropy, correlation, chi-square, NPCR, UACI, MSE, MAE, PSNR, and NIST SP 800-22 randomness tests—assess the encryption strength. The results indicate that the proposed method delivers consistent improvements in randomness and uniformity over standard Ascon-AEAD128, while remaining comparable to state-of-the-art chaotic encryption schemes across standard security metrics. These findings suggest that the algorithm is a promising option for resource-constrained IoRT applications.

This study presents the design, modeling, and prototyping of an external rotor permanent magnet synchronous motor (ER-PMSM) specifically for elevator traction systems. The external rotor design aims to surpass the efficiency of conventional inner rotor gearless elevator traction motors. A commercially available 4 kW inner rotor permanent magnet synchronous motor (IR-PMSM) was selected for comparative analysis. Critical parameters, including stator tooth tip thickness, slot tip radius, slot height, stator yoke height, stator tooth thickness, and the number of turns per phase, were optimized to enhance efficiency. The artificial bee colony (ABC) algorithm was utilized for the first time to determine the optimal configuration of an external rotor PMSM. The prototype was fabricated and subjected to rigorous testing using a dedicated electrical motor test setup. Comparative results demonstrated a significant improvement in efficiency for the ER-PMSM over the IR-PMSM, with the efficiency increasing from 72.5% to 84.67% at nominal operating conditions.

This paper proposes a 2 kW in-wheel brushless direct current (BLDC) motor design for a light electric vehicle (EV). The EV is designed for a predefined route in electric vehicle races. The BLDC motor was directly mounted into the vehicle's wheel rim. Initially, dynamic model of EV was calculated according to vehicle characteristics. The motor's slot/pole ratio was selected as 36/32. The designs for the stator, rotor, and magnets were subsequently developed based on the motor's boundary dimensions, aiming for low cogging torque and high efficiency. To achieve this, the distance between stator tooth tips was optimized. The design was validated through 2D finite element analyses, followed by the motor's production. Performance tests conducted with the experimental setup confirmed that the design matches the experimental results.

There has been a global increase in the number of vehicles in use, resulting in a higher occurrence of traffic accidents. Advancements in computer vision and deep learning enable vehicles to independently perceive and navigate their environment, making decisions that enhance road safety and reduce traffic accidents. Worldwide accidents can be prevented in both driver-operated and autonomous vehicles by detecting living and inanimate objects such as vehicles, pedestrians, animals, and traffic signs in the environment, as well as identifying lanes and obstacles. In our proposed system, road images are captured using a camera positioned behind the front windshield of the vehicle. Computer vision techniques are employed to detect straight or curved lanes in the captured images. The right and left lanes within the driving area of the vehicle are identified, and the drivable area of the vehicle is highlighted with a different color. To detect traffic signs, pedestrians, cars, and bicycles around the vehicle, we utilize the YOLOv5 model, which is based on Convolutional Neural Networks. We use a combination of study-specific images and the GRAZ dataset in our research. In the object detection study, which involves 10 different objects, we evaluate the performance of five different versions of the YOLOv5 model. Our evaluation metrics include precision, recall, precision-recall curves, F1 score, and mean average precision. The experimental results clearly demonstrate the effectiveness of our proposed lane detection and object detection method.

Chaotic systems are identified as nonlinear, deterministic dynamic systems that are exhibit sensitive to initial values. Some chaotic equations modeled from daily events involve time information and generate chaotic time series that are sequential data. Through successful prediction studies conducted on the generated chaotic time series, forecasts can be made about events displaying unpredictable behavior in nature, which have not yet been modeled. This enables preparation for both favorable and unfavorable situations that may arise. In this study, chaotic time series were generated using Lorenz, Chen, and Rikitake multivariate chaotic systems. To enhance prediction accuracy on the generated data, GRU, LSTM and RNN models were trained with different hyperparameters. Subsequently, comprehensive test studies were conducted to evaluate their performance. Predictions were calculated using evaluation metrics, including MSE, RMSE, MAE, MAPE, and R2. In the experimental study, each chaotic system was trained with different hyperparameter combinations on six network models. The experimental results indicate that the utilized models exhibited greater success in predicting chaotic time series compared to some other models in the literature.

The design of an external rotor gearless elevator machine (ERGEM) with a flanged shaft for elevator traction systems is presented in this paper. The machine is designed with two distinct shafts. The fixed shaft with stator is one, and the flanged shaft turns with the rotor is the other. The ERGEM's rotational movement has been reduced to a flanged shaft, and a novel motor design has been obtained that fits the market's traction pulleys and brake mechanisms. The flanged shaft provides traction by rotating with the pulley. Instead of making grooves on the rotor surface, an external pulley is used. The loads on the pulley have a negligible effect on the rotor because it is located between two fixing plates. With the plates on the right and left sides of the pulley, a symmetrical load distribution has been achieved. Finite element analyses (FEA) were performed using the maximum static load values. After the final design was approved, the prototype was built and experimental tests were conducted.

Rehabilitation at home is a growing need worldwide. Previous studies have suggested different devices in terms of motion and force transmission. In this study, we present design and development process of a novel hand exercise exoskeleton. The main advantages of our device that are portable, wearable, light weight (345 grams) and suitable for home use. The greatest feature of the device is the force transmitting mechanism. The spring mechanism manufactured by using commercial compression springs has some advantages in terms of size and weight. In design studies of the device, we have made use of the systematic approach. In this way, the best of three possible design solutions has been determined. Then the best design solution was selected. A few prototypes of the device were manufactured. The device has been tested clinically on both unimpaired individuals and hemiplegic hand patients for a short time. It was reported that the exoskeleton was suited to passive exercises. The result section gives an evaluation of the device in terms of exercises, ergonomics and the market. Additionally, a patent registration certificate was issued to our device for our country.

Rehabilitation at home is rapidly increasing. Although successful results are achieved with treatment methods applied in rehabilitation clinics, there are also some disadvantages in this process, such as dependence on an expert and high costs. Developments in mechatronic technologies have accelerated the development of assistive devices which are designed for use at home. One of the rehabilitation applications is on a hemiplegic hand. In previous studies, some useful devices have been developed for hand rehabilitation. In this study, we suggest a new, low-cost and wearable robotic glove for hand rehabilitation. The specific component of this device is the spring and cable driven system proposed for transmission of motion and force. The device was tested on both unimpaired participants and patients with the hemiplegic hand, and it was proven to be beneficial for hand rehabilitation. As a result of trials with unimpaired participants, the muscle activation of the extensor digitorum and the flexor carpi radialis were increased by 184.1 and 197.8% respectively. The weight of the device was less than 400 g, thanks to 3D printed parts.

As the present and future of the robotic world and automation, autonomous vehicles and Advanced Driver Assistance Systems (ADAS) that work in conjunction with autonomous vehicles are important technologies that can benefit drivers through current driving environments. Some elementary factors of these autonomous cars are recognizing surroundings, barriers, pedestrians, traffic signs and other vehicles. In this study, as one of the functions of an autonomous car, the operation of peripheral object recognition is carried out through the use of deep learning which has been mentioned with great accuracy and speed these years in the field of solving problems in machine learning. Signs and objects in various environments, different viewing angles and dimensions can be recognized through the video images taken from the vehicle. Application of object recognition is achieved through the use of 517 images of 10 objects consisting of pedestrians, cars, bicycles and 7 traffic signs, and of convolutional neural networks models including SSD Inception V2, Faster R-CNN Inception V2, Faster R-CNN Resnet 50 and Faster R-CNN Resnet 101, which are known as the basis of deep learning. The models previously trained on the COCO data set are retrained and evaluated on the new data set with the transfer learning method. The new data set is formed by part of the image from the GRAZ-01 and GRAZ-02 data sets and part of the image from the mobile phone camera. As a result of performance analyzes, Faster R-CNN Resnet 101 model is found to be successful in object detection on both images and videos with 85.1% accuracy.

In this study, a SCARA Prismatic-Revolute-Revolute-type (FRB) robot manipulator is designed and implemented. Firstly, the SCARA robot is designed in accordance with the mechanical calculations. Then, forward and inverse kinematic equations of the robot are derived by using D-H parameters and analytical methods. The software is developed according to the obtained Cartesian velocities from joint velocities and joint velocities from Cartesian velocities. The trajectory planning is designed using the calculated kinematic equations, and the simulation is performed in MATLAB VRML environment. A stepping motor is used for the prismatic joint of the robot, and servo motors are used for revolute joints. While most of the SCARA robot studies focus on the Revolute-Revolute-Prismatic -type (RRP) servo control strategy, this work focuses on PRR, type and both stepper and servo control structures. The objects in the desired points of the workspace are picked and placed to another desired point synchronously with the simulation. Therefore, the performance of the robot is examined experimentally. (C) 2020 Sharif University of Technology. All rights reserved.

In this paper, a 4 kW external rotor permanent magnet (PM) synchronous motor was designed. It is aimed to obtain minimum cogging torque and minimum torque ripples by optimum pole embrace ratio. Conceptual design was modeled and analyzed by 2D finite element analyses (FEA). Low order harmonics of the induced phase voltages and torque ripples are investigated. According to optimization results, an external rotor PMSM was obtained with low cogging torque and low torque ripple. The designed PMSM was compared with a commercial inner rotor PMSM and much better performance results are taken.

Determining the dynamic properties of the joints of human limbs is a control and design parameter for humanoid mechanism, rehabilitation robots and orthotic and prosthetic devices. In other researches, some methods have been suggested for estimating joint torques of the hand such as mathematical models and simulation models. A 16 degree of freedom (DOF) dynamic simulation model of an average human hand is suggested in this study. Dynamic model of a human hand has been created by SimMechanics on MATLAB. Abduction/adduction and flexion/extension motions of the wrist and the fingers can be analysed using SimMechanics model by changing joint rotation. The model has been analyzed by inverse dynamics method using the video record of five healthy subjects (31.2 +/- 9.57 years) and the joint torques of the wrist and fingers have been calculated. The greatest torque of index finger with 0.0149 Nm occurs at the MCP joint during the cylindrical grip. The greatest wrist torque has been calculated as 0.225 Nm during motion of flexion/extension. Our results are similar to previous works. This simulation model can be used for estimating the joint torques at different motions of the hand without external devices and mathematical techniques.

Stroke affects millions of people every year. Most of them need rehabilitation to recover their mobility. Although a lot of robotic based devices have been suggested for rehabilitation of the hand muscles, these devices still need some improvements. Methods using for transmitting movement and force in previous devices have some disadvantages. One of them is misalignment on the centre of rotation between joints used in devices and joints of the hand and the wrist. This situation causes a shear force on the joints of human limbs. To resolve these problems new approaches should be proposed. In this study a novel device is suggested to perform the wrist exercises. The device has a cable and spring-driven system for transmitting movement and force. Thus, it does not cause the alignment problem on the centre of rotation. The device allows both passive (assistive) and active exercises. It is aimed that the device is suitable for home use, portable and low cost. The proposed new device expected to reduces the rehabilitation cost and therapy period. The device can be used for other situations such as nerve injury, nerve compression, tendon injury, fracture and sport injury besides stroke rehabilitation. If this low cost device can be commercialized, it is clear that, it may contribute to Turkey competitiveness capacity on the global medical markets.

İnme, her yıl milyonlarca kişiyi etkilemektedir. Bu kişilerin çoğu, hareket kabiliyetlerini geri kazanabilmek için rehabilitasyona ihtiyaç duymaktadırlar. El kaslarının robotik temelli rehabilitasyonuna yönelik çok sayıda cihaz önerilmiş olmasına rağmen bu cihazların hala geliştirilmesi gereken yönleri vardır. Önceki cihazlarda kuvvet ve hareket aktarımı için kullanılan yöntemlerin bir takım olumsuz yönleri bulunmaktadır. Bunlardan biri, cihazlarda kullanılan mafsallar ile el ve el bileği eklemlerinin dönme merkezlerinin tam olarak hizalanamamasıdır. Bu durum, vücut eklemleri üzerinde kesme kuvvetleri oluşturmaktadır. Dönme merkezlerini hizalamak için uygulanan yöntemlerin bazı dezavantajları bulunduğundan yeni uygulamalara ihtiyaç vardır. Bu çalışmada, el bileği egzersizlerini gerçekleştirmek amacıyla yeni bir cihaz önerilmektedir. Cihaz, hareket ve kuvvet aktarımını kablo ve yay tahriki ile yapmaktadır. Böylece dönme merkezlerinin hizalanması sorunu yaşanmamaktadır. Cihaz, pasif ve aktif egzersizlere olanak sağlamaktadır. Cihazın ev ortamında kullanıma uygun, taşınabilir ve düşük maliyetli olması amaçlanmıştır. Geliştirilen cihazın, rehabilitasyon maliyetlerini azaltması ve tedavi sürecini kısaltması beklenmektedir. Cihaz, inme rehabilitasyonun yanı sıra sinir yaralanması, sinir sıkışması, tendon yaralanması, kırıklar ve spor yaralanmaları gibi durumlarda da kullanılabilir. Düşük maliyetli olması beklenen cihazın, ticarileştirilmesi durumunda tıbbi cihazlar alanında dış pazarlara bağımlı ülkemizin rekabet gücüne katkı yapması beklenmektedir .

In this study, it was aimed to investigate the effects of an exercise glove developed by our research team on hand muscles. Within this scope, clinical investigations were carried out on volunteer healthy subjects. Subjects performed the exercises both wearing the glove and without glove. EMG was measured on extensor and flexor muscles during the exercises. Muscle activations were compared by the amplitude analysis during exercises with and without the glove. It is understood that exercises with the glove increase extensor and flexor muscle activations. This glove can be adapted to rehabilitation devices by integrating with different actuators. In addition, this glove can also be used in order to strengthen the hand muscles.

Determining the joint torques of the hand is a useful design parameter for humanoid mechanism, rehabilitation robots and orthotic and prosthetic devices. In previous studies, different methods have been suggested for estimating joint torques of the hand such as mathematical models and simulation models. This paper presents a 16 DOF hand kinematic model and its simulation. Kinematic structure of an average human hand was created by SimMechanics and Simulink on MATLAB. The model was simulated by inverse dynamics method using the video record of a healthy subject (male, 29 years, 71 kg and 174 cm) and the joint torques of the index finger and wrist were calculated. The maximum torque at index finger with 0.015 Nm occurs at the MCP joint during the cylindrical grip. The maximum wrist torque was calculated as 0.225 Nm during movement of flexion/extension. Flexion/extension and abduction/adduction movements of the fingers and the wrist can be analyzed with this model changing joint rotation axis easily. This MATLAB model can be used in order to calculate the joint torques at different movements of the hand without complex equations and external devices.

Millions of people suffer a stroke each year. One of the problems after stroke is hemiplegic hand. In previous studies a lot of robotic based devices has been suggested for rehabilitation of hemiplegic hand. Actuators using for force transmitting in previous devices have some disadvantages. One of them is misalignment on the centre of rotation between joints used in devices and joints of the hand. In this study a novel device is suggested to perform the finger exercises. The device has a cable and spring driven mechanism with an electrical linear actuator. The device allows both passive and active exercises. It is aimed that the device is suitable for at home use, wearable, portable and low cost. It is expected from the new device that it will reduces the rehabilitation cost and therapy period. The device can be used for other rehabilitation treatments such as nerve injury, nerve compression, tendon injury, fracture and sport injury besides stroke rehabilitation.

OBJECTIVE:The aim of this study was to determine the joint torques on the lower extremity during the daily physical activity movements of sit-to-stand, crouch down-stand up, and stair climbing without using an external device. METHODS:The study subject was a healthy 26-year-old male without any physical problems. A link-segment model was prepared according to the subject's individual anthropometric characteristics and transferred to the MATLAB(®) program. Joint torques were calculated using SimMechanics™ software. Motions were recorded by one digital video camera as the subject performed the movements (sit-to-stand from 20 cm and 40 cm height, crouch down-stand up, and climbing 10 cm and 20 cm high step) and the joint's position data was obtained using a digitization process. In addition, the vertical ground reaction forces were measured using a force plate in order to test the accuracy of the link-segment model. Lower extremity joint torques were calculated. RESULTS:Maximum joint torques occurred in the knee joint. The knee and the ankle joints were the most loaded joint during the high step movement. The highest torques of the knee and ankle joint were 157.2 Nm and 146 Nm, respectively, during the movements. Knee joint torque and the ankle joint torque increased when the sitting height increased. The hip joint experienced the least amount of load during the movements. CONCLUSION:The knee joint has enough strength against high torques during extension and flexion movement. Joint torques can be successfully calculated using a simulation process involving an inverse dynamics method without an external device mounted on the limbs. The obtained data can be used in the design of prosthetics and orthotics and for structural analysis of the bones.

Cardiac arrhythmias are common heart diseases. Electrocardiography (ECG) is an important measure for diagnosing arrhythmias. Researchers use the ECG signals in order to train artificial neural networks (ANN). In previous studies the ECG signals of males and females were analysed together. We know that there are some differences between male and female ECG signals. This paper suggests that classifying the arrhythmias according to gender differences gives more accurate results. In this study we classify the subjects as normal and right bundle branch block (RBBB) using cascade forward back algorithm in MATLAB. The accuracy of network simulations are as follow: 81.25% only male, 80% only female, 40% male and female together.

The hand has an important role in our lives. Some injuries and diseases influence the hand motor activities and so the hand could not perform its functions. There are different rehabilitation and therapy methods for neuromusculoskeletal system. One of these is the use of orthotic devices. In this paper, we have designed a single degree of freedom dynamic and active orthosis in order to rehabilitate hand muscles by moving the wrist. Firstly, we have modelled the hand as a solid bar with a single degree of freedom in the sagittal plane, and then anthropometric characteristics of an average human hand were determined. Second, flexion and extension movement of hand is recorded by a video camera to detect the movement range of the hand and wrist joint torque has been calculated using the hand movement data on SimMechanics software. As a result of the study, a new hand orthosis is designed for adult people according to the movement range of the hand and the joint torque. Keywords: dynamic orthosis, hand, wrist, rehabilitation.