Nihat Yilmaz

Feature Selection Method Based on Artificial Bee Colony Algorithm and Support Vector Machines for Medical Datasets Classification

This paper offers a hybrid approach that uses the artificial bee colony (ABC) algorithm for feature selection and support vector machines for classification. The purpose of this paper is to test the effect of elimination of the unimportant and obsolete features of the datasets on the success of the classification, using the SVM classifier. The developed approach conventionally used in liver diseases and diabetes diagnostics, which are commonly observed and reduce the quality of life, is developed. For the diagnosis of these diseases, hepatitis, liver disorders and diabetes datasets from the UCI database were used, and the proposed system reached a classification accuracies of 94.92%, 74.81%, and 79.29%, respectively. For these datasets, the classification accuracies were obtained by the help of the 10-fold cross-validation method. The results show that the performance of the method is highly successful compared to other results attained and seems very promising for pattern recognition applications.

Design and Actuator Selection of a Lower Extremity Exoskeleton

Lower extremity exoskeletons are wearable robots that integrate human intelligence with the strength of legged robots. Recently, lower extremity exoskeletons have been specifically developed for transportation of disabled individuals. This paper summarizes the anthropomorphic design of a lower extremity exoskeleton named “walking supporting exoskeleton (WSE).” WSE has been developed to support some fundamental motions (walking, sitting, standing, etc.) of disabled individuals who lost leg muscular activities completely or partially. WSE has two degrees of freedom per leg which are powered by electrical actuators. This paper discusses critical design criteria considered in mechanical design and actuator selection of WSE.

Web-based mobile robot platform for real-time exercises

This paper introduces a new vision-based and web-based mobile robot platform. The platform consists of control and communication centers, a mobile robot and real-time support libraries. All activities in the platform are achieved by only computer vision techniques. The platform provides monitoring, tele-controlling and programming for real-time educational exercises and helps to the users to achieve these exercises through a standard web browser without any need for additional support software. The results have shown that the proposed, designed and implemented platform provide amazing new facilities and features to the users (students and researchers) in applying their real-time exercises on web.

Web Robot Learning Powered by Bluetooth Communication System

This paper presents a web robot web-robot learning powered by Bluetooth communication system. The web-robot system is used as the virtual robot laboratory integrating a number of disciplines in engineering. This virtual laboratory is a valuable teaching tool for engineering education used at any time and from any location through Internet. The mobile robot was controlled with robot server named as control center. The server can be connected to mobile robot via Bluetooth adapter. The mobile robot system focuses on vision sensing. Real time image processing techniques are realized by the web robot system. This system can also realize monitoring, tele-controlling, parameter adjusting and reprogramming through Internet exclusively with a standard Web browser without the need of any additional software

Real-time line tracking based on web robot vision

This study presents a real‐time line tracking application based on web robot vision. The application is implemented with the help of Web‐SUN robot platform specially designed for research and development. Real‐time images were processed with the support libraries. The processes such as monitoring, tele‐control, parameter adjustment, and remote‐reprogramming were implemented on the designed platform through standard Internet browser without any additional software. A projection‐based line tracking algorithm and conventional PID control algorithm are used in study. Line tracking experiments are performed on a test track drawn by red tape on floor which includes curves and corners in laboratory environment. In this study, our real‐time line tracking experiments was completed smoothly in 10 tours on the test track with a maximum deviation of 12 cm.

A fault-tolerant multicast routing algorithm based on cube algebra for hypercube multicomputers

In this study a broadcast routing algorithm has been developed for a faulty hypercube parallel processing system using cube algebra. Without any restriction to the number of the faulty nodes, the routing from the source node to the destination node is implemented minimally. The developed routing algorithm has been visually simulated via the prepared data routing simulator program. It has been observed that this algorithm can be applied to various routing problems.

A multicast routing algorithm based on parallel branching method for faulty hypercubes

In this study, a multicast routing algorithm based on a parallel branching method has been developed for a faulty hypercube parallel processing system. The routing from the source to the destination nodes is guaranteed in the shortest time with this algorithm. Going through to the destinations from the source is a parallel process at each step. The superiority of the developed algorithm over previous studies is that the routing from the source to the destination is achieved in minimal steps without restriction to the number of faulty nodes. This means that the algorithm is running independently from the number of faulty nodes. The algorithm is simulated with a hypercube routing simulator.

Force Feedback Control of Lower Extremity Exoskeleton Assisting of Load Carrying Human

Lower extremity exoskeletons are wearable robot manipulators that integrate human intelligence with the strength of legged robots. Recently, lower extremity exoskeletons have been specifically developed for rehabilitation, military, industrial applications and rescuing, heavy-weight lifting and civil defense applications. This paper presents controller design of a lower-extremity exoskeleton for a load carrying human to provide force feedback control against to external load carried by user during walking, sitting, and standing motions. Proposed exoskeleton system has two legs which are powered and controlled by two servo-hydraulic actuators. Proportional and Integral (PI) controller is designed for force control of system. Six flexible force sensors are placed in exoskeleton shoe and two load cells are mounted between the end of the piston rod and lower leg joint. Force feedback control is realized by comparing ground reaction force and applied force of hydraulic cylinder. This paper discusses control simulations and experimental tests of lower extremity exoskeleton system.

Mechanical Design of Lower Extremity Exoskeleton Assisting Walking of Load Carrying Human

Exoskeletons are used in rehabilitation, military, industrial applications and rescuing, heavy-weight lifting and civil defense applications as well. This paper presents to design of a lower-extremity exoskeleton assisting walking of a load carrying human. Proposed exoskeleton system is designed to be appropriate mechanism with human lower extremity and it operates synchronously with the human realizes. The aim of exoskeleton actuator system is to provide forces against to external load carried by user during walking, sitting, and standing motions. Thus, it supports human walking and significant portion of external load carrying by the user. Also it makes possible to user spend less energy, less stress and fatigue. Proposed work involves the following design steps: kinematic synthesis of the exoskeleton, mechanical and electro-hydraulic system design.

Web-based maze robot learning using fuzzy motion control system

In this study, a Web based maze robot system has been designed and implemented for solving different maze algorithms with the help of machine learning approaches. The robot system has a map-based heuristic maze solving algorithm. The algorithm used for solving the maze is based on map creation and produces a control signal for robot direction. Robot motions were controlled by a fuzzy motion control system running on a chip. The control algorithm can be easily changed with the help of an algorithm via web interface controlled by the control center. The control center program powered by MATLAB functions and special libraries (image and control) in DELPHI manage all robotic activities. These activities are: command interpreter, image capturing, processing and serving, machine learning techniques, Web serving, database management, communication with robot, and compiling microcontroller programs. The results have shown that the proposed, designed and implemented system provides amazing new features to the applicants doing their real-time programming exercises on Web.