Application Of Computer Control Research Articles

EyeMo: A Solution for Individuals with Disabilities to Use a Computer Through Eye Movements

The maintenance of an upright posture and the execution of desired movements by individuals necessitate the seamless and harmonious functioning of the muscular and skeletal systems. Neuromuscular diseases, spinal cord injuries, and related conditions can adversely impact individuals' motor functions, leading to a loss of muscle strength and, in severe cases, paralysis. Such health challenges may result in social isolation and detachment from one's social life. This study is focused on the development of a computer control application utilizing eye movements to aid users in navigating and interacting with computers. The system utilizes a lightweight eyeglass frame and a mini-USB camera to accurately capture images of the user's pupil. Pupil detection is achieved through a combination of traditional image processing and deep learning techniques, ensuring high accuracy under diverse conditions. Users have the ability to interactively calibrate the application to accommodate varying screen sizes, thereby enhancing system responsiveness. The user interface incorporates functionalities such as left-click, right-click, double-click, and scrolling, empowering users to perform tasks ranging from internet browsing to video watching. 
 After the development of the application, a request for research permission was submitted to the local institution to allow volunteers to test the application, adhering to ethical standards. Following the approval of ethical clearance, the application was made available for use by volunteers, and feedback was systematically collected. Volunteers generally reported that the application was beneficial, indicating its potential use by disadvantaged individuals. The upcoming versions of the application have the potential for integration with smart home systems. Additionally, the developed application can be used in games and for educational purposes.

Brain-computer interfaces in digital mindfulness training for metacognitive, emotional and attention regulation skills: a literature review

Brain–Computer Interfaces (BCIs) are specialized systems that allow users to control computer applications using their brain waves. With the arrival of consumer-grade electroencephalography (EEG) equipment, brain-controlled systems began to find fertile ground in mental training. One particular area that is gradually gaining attention is that of mindfulness training. In this paper, the results of a literature review of BCI-assisted mindfulness training using BCI’s are presented. The specific aim is to review the effects of BCIs embedded in mindfulness interventions on training metacognitive, emotional, and attention regulation skills. Papers published the last 10 years were reviewed. The results showed that the use of BCIs provides subjects the unique opportunity to self-regulate mental and emotional functions using the feedback derived from their own brain activity. Subjects were found to raise better awareness about the ways non-conscious operations influence mental and emotional states. It was observed that subjects by learning to deal with the neurofeedback within immersive worlds or with the aid of mobile devices can better develop awareness and self-regulation skills including inhibition and flexibility. Learning environments have been undergoing rapid change driven by the evolution and availability of digital technologies. In that vein, BCIs combined with mobiles and immersive technologies could support mindfulness as an innovative practice for cognitive, emotional, and metacognitive development. This study aims to contribute to the debate about the use of BCI-assisted mindfulness practices as proactive methods and training strategies for various target groups such as students, teachers, and workers to achieve well-being and peak performance.

Applying Brain Computer Interface Technology for Playing Games

Brain Computer Interfaces are specialized systems that allows users to control computer applications using their brain waves. Initially, BCI were mostly used in medical field. But after some research and thanks to consumer-grade electroencephalography (EEG) devices, many applications and research opportunities were opened outside of the medical field. One particular area that is gaining more evidence due to the arrival consumer-grade devices is that of computer games, as it allows more user-friendly applications of BCI technology for the general public. In this report, we are going to talk about one of those games, Maze game. It will be a 2D maze, path known to the user. Using the EEG device named Neurosky Brain Wave Kit user will be able to move the avatar in order to reach the goal from the starting position.

Optimization of the Bi-Axial Tracking System for a Photovoltaic Platform

The article deals with the optimization of the azimuthal tracking mechanism for a photovoltaic (PV) platform, which uses linear actuators as actuation elements for both movements (diurnal and elevation). In the case of diurnal movement, where the platform’s angular field of orientation is large, a mechanism with a relatively simple structure is used for amplifying the actuator’s stroke and avoiding the risk of the system locking itself (by limiting the values of the transmission angle). The optimization study targets the mechanical device, the control device, and the bi-axial tracking program (embodied by the laws of motion in time for the platform’s diurnal and elevation angles) with the purpose of obtaining a high input of solar radiation, with a minimal energy consumption to achieve tracking. The study is carried out by using a virtual prototyping platform, which includes Computer Aided Design (CAD), Multi-Body Systems (MBS), and Design for Control (DFC) computer applications. The mechanical and control devices of the solar tracker are integrated and tested in mechatronic concept. The simulations’ results, which were performed for a set of representative days throughout the year, prove the effectiveness of the proposed design.

Design and simulation of quantum-dot cellular automata serial decimal pipelined processor based on Turing machine model

The quantum-dot cellular automata (QCA) nanoscale computer technology is promising to overcome the limits of the microelectronic CMOS technology. Because the leading role of QCA wires, the serial data transfer/processing is preferable. The financial, Internet of Things, and control computer applications require direct processing of decimal information without representation and conversion errors. Because a QCA wire can be considered as a virtual tape with written binary symbols, a special version of Turing machine model can be used for a QCA computer implementation. Design of a novel QCA serial decimal pipelined processor based on the Turing machine model is presented. The processor uses the run-time tape reconfiguration for arithmetic processing of decimal operands encoded in the 5-bit Johnson-Mobius code. The proposed design demonstrates significant hardware simplification.

Computer Control System Application for Electrical Engineering and Electrical Automation

Electrical engineering has gradually entered the era of automation technology along with the development of high technology. In computer control systems, the application of automation technology and electrical engineering has gradually improved. The paper mainly discusses the basic concepts of intelligent technology and electrical automation, and focuses on the specific application of intelligent computer control in electrical automation, and analyzes the application prospect and development trend of this technology in electrical engineering in the future.

SSVEP-based brain-computer interface for computer control application using SVM classifier

In this research, a Brain Computer Interface (BCI) based on Steady State Visually Evoked Potential (SSVEP) for computer control applications using Support Vector Machine (SVM) is presented. For many years, people have speculated that electroencephalographic activities or other electrophysiological measures of brain function might provide a new non-muscular channel that can be used for sending messages or commands to the external world. BCI is a fast-growing emergent technology in which researchers aim to build a direct channel between the human brain and the computer. BCI systems provide a new communication channel for disabled people. Among many different types of the BCI systems, the SSVEP based has attracted more attention due to its ease of use and signal processing. SSVEPs are usually detected from the occipital lobe of the brain when the subject is looking at a twinkling light source. In this paper, SVM is used to classify SSVEP based on electroencephalogram data with proper features. Based on the experiment utilizing a 14-channel Electroencephalography (EEG) device, 80 percent of accuracy can be reached by our SSVEP-based BCI system using Linear SVM Kernel as classification engine.

Quantum-dot cellular automata serial decimal processing-in-wire: Run-time reconfigurable wiring approach

The quantum-dot cellular automata (QCA) technology is promising to overcome the limits of CMOS technology for perspective computers. A chain of QCA is used as a wire. Logic gates are simply implemented by a cross pattern of QCA. Because the leading role of QCA wires, the serial data transfer/processing is preferable. The growing market of financial, Internet-based, and automatic control computer applications requires a binary-coded decimal data encoding for direct processing of decimal information without representation and conversion errors. The 5-bit decimal Johnson–Mobius encoding and radical departure from Boolean logic allow using a delay element, implemented by short length of QCA wire, as a function element. The previous published by author serial decimal QCA arithmetic designs demonstrate hardware simplification in comparison with traditional designs. The paper presents novel serial decimal adder and adder/subtractor designs used the run-time reconfigurable wiring approach, which results in further significant QCA hardware simplification.

Flow-Based Specification of Time Design Requirements

This paper focuses on design requirements in real-time systems where information is processed to produce a response within a specified time. Nowadays, computer control applications embedded in chips have grown in significance in many aspects of human life. These systems need a high level of reliability to gain the trust of users. Ensuring correctness in the early stages of the design process is especially a major challenge in these systems. Faulty requirements lead to errors in the final product that have to be fixed later, often at a high cost. A crucial step in this process is modeling the intended system. This paper explores the potential of flow-based modeling in expressing design requirements in real-time systems that include time constraints and synchronization. The main emphasized problem is how to represent time. The objective is to assist real-time system requirement engineers, in an early state of the development, to express the timing behavior of the developed system. Several known examples are modeled and the results point to the viability of the flow-based representation in comparison with such time specifications as state-based and line-based modeling.

EEG Mouse:A Machine Learning-Based Brain Computer Interface

The main idea of the current work is to use a wireless Electroencephalography (EEG) headset as a remote control for the mouse cursor of a personal computer. The proposed system uses EEG signals as a communication link between brains and computers. Signal records obtained from the PhysioNet EEG dataset were analyzed using the Coif lets wavelets and many features were extracted using different amplitude estimators for the wavelet coefficients. The extracted features were inputted into machine learning algorithms to generate the decision rules required for our application. The suggested real time implementation of the system was tested and very good performance was achieved. This system could be helpful for disabled people as they can control computer applications via the imagination of fists and feet movements in addition to closing eyes for a short period of time.

Predictive Control Algorithm in the Application of Computer Control

According to the error between the model predictive output and the future expected output, ILPC carries out an iterative learning and amending process on the current and the future control input vector, namely performs forecast, iterative amendment, forecast again, iterative amendment again repeatedly in the iterative domain. This paper gives a fast high-precision temperature control systems structure, characteristics and realization method. CARI model and the improved generalized predictive control method are used to improve the control precision of the system, and shorten the response time. The quick high precision temperature control systems structure and realization method are given, and according to the requirements of the task, the existing predictive control algorithm has been improved. Through the experiment, its temperature predictive control systems design scheme and realization method is proved to be reasonable and feasible. It can meet the demands for the expected temperature control.

Application of Computer Control in the Angular Distortion Measurement System

A new real-time angular distortion measurement system, composed of devices i.e. the photoelectrical auto-collimating collimator and the reflex light-tube installed on deck, is developed in this paper. Real-time measurement of vessels bi-dimensional angular distortion is achieved by using this computer control system. Two video signals of photoelectrical auto-collimating collimators are received by the computer control system, and real-time image processing is done to obtain the dynamic miss distance. Then relative distortion of vessel is calculated by overlying measuring results of these two-way images.

Robust control of depth of anesthesia based on H∞ design

Abstract This paper presents a case study on the design of a robust controller for the depth of anesthesia (DoA) induced by the drug propofol. This process is represented by a linear model together with a non-parametric uncertainty description that is evaluated using a patient model bank with 20 patients undergoing sedation. By using H∞ methods, the controller is aimed to comply with robust stability and performance specifications for the class of patient models considered. A minimization problem of sensitivity and complementary sensitivity is made to design the controller. The controller that results from this procedure is approximated by a controller with a lower order, that in turn is redesigned in discrete time for computer control application. The resulting controller is evaluated in simulations using a realistic nonlinear model of DoA.

Some Aspects of Voice User Interfaces Development for Internet And Computer Control Applications

This paper deals with some aspects of development voice user interfaces for several applications. The realistic scenario when developing VUI for such languages as Lithuanian is adaptation of foreign language speech recognizer. But not all voice commands could be recognized successfully enough using adapted recognizer. Hence the importance to implement hybrid recognizer arises. Several practical applications using Lithuanian voice command recognitions are presented. The experimental investigation showed that 90 percent recognition accuracy was achieved in average using adaptation of foreign language speech engine. Detailed analysis showed that most commands are recognized with very high accuracy. For those commands that aren’t recognized accurately enough hybrid recognition principle may be applied.DOI: http://dx.doi.org/10.5755/j01.eee.19.2.3469

Evaluation of Brain-computer Interfaces in Accessing Computer and other Devices by People with Severe Motor Impairments

A brain-computer interface (BCI) translates brain signals into commands that can be used to control computer applications or external devices. BCI provides a non-muscular communication channel and therefore it assumes a crucial importance for individuals with motor functions severely affected. The evaluation of BCI by individuals with severe disabilities is of utmost importance to understand the BCI feasibility as an assistive technology. This paper summarizes some of the results achieved in our research lab, with different BCIs tested by individuals with severe motor disabilities, focusing on some practical aspects of BCI evaluation, and on the target population.

Hand gesture recognition supported by fuzzy rules and Kalman filters

The paper presents a system based on camera and multimedia projector enabling a user to control computer applications by dynamic hand gestures. Gesture recognition methodology based on representing hand movement trajectory by motion vectors analysed using fuzzy rule-based inference is first given. For effective hand position tracking Kalman filters are employed. The system engineered is developed using J2SE and C++/OpenCV technology. In addition, OpenCV is used for image processing and J2SE with jFuzzyLogic package is employed for gesture interpretation. Results of fuzzy rule-based and fixed threshold-based gesture recognition effectiveness are provided. Additionally, for fuzzy rule-based gesture recognition the system efficacy after utilising Kalman filters is examined. The so-called interactive whiteboard application is given as an example of the system usage.

Artificial intelligence in the colour and textile industry

The use of computers in the colour and textile industry dates back to 1960s 111. A significant number of papers have been published over the years describing the application of computer control in various fields of textiles (21, including fibre production [3,4], yarn formation 151, fabric formation [6-8], and dyeing processes and machinery [9-211. Although the term ’artificial intelligence’ was coined in 1956 1221, it was during the last decade of the 20th century that textile researchers actively investigated its application in various fields. Some earlier developments in artificial intelligence have been reported for the textiles industry [23], textile finishing 124,251 and the colour industry [26]. One of the earlier applications of artificial intelligence in textile coloration was robotics, which was explored in the quest for automation and control. However, more recently, artificial neural networks (ANN) 127,281, fuzzy logic and some expert or knowledge-based systems have attracted the attention of researchers in different sectors of the colour and textile industry. The aim of this paper is to review some recent applications of artificial intelligence in finding better solutions to various problems in different areas of the colour and textile industry. The intention is to describe the applications rather briefly and to give a more thorough account of specific technologies that are being used or have a huge potential for use in the foreseeable future.

Robotic excavation in construction automation

This article presents some results of the autonomous excavation project conducted at the Australian Centre for Field Robotics (ACFR) with a focus on construction automation. The application of robotic technology and computer control is one key to construction industry automation. Excavation automation is a multidisciplinary task, encompassing a broad area of research and development. The ultimate goal of the ACFR excavation project is to demonstrate fully autonomous execution of excavation tasks in common construction, such as loading a truck or digging a trench. A number of difficult theoretical and practical problems must be solved to achieve this objective. The problems fall into three main groups: excavation planning, sensing and estimation, and control.

Computer Control Applications in Combined Waste Water Treatment Plants

During the past years one amplified research topic of the University of Applied Sciences in Hamburg was the purification of high nitrogen and methanol loaded waste water with simultaneous nitrification and denitrification processes. These include modern methods of bioprocess and automation technology as well as analytical techniques and simulation tools. The apparent processing was used to establish an advanced controlled waste water treatment process.

A dynamic-zone strategy for vehicle-collision prevention and load balancing in an AGV system with a single-loop guide path

One of the advances in computer-aided production is the application of computer control to automated material handling systems. Computer control is especially important to Automated Guide Vehicles (AGVs) since their control problems are more complicated than those of traditional automated material handling systems, e.g., conveyors. Of the many design and control issues of AGVs, an important one is the prevention of vehicle collision. Many traditional vehicle-collision prevention strategies are the so-called zone strategies that divide guide paths into several non-overlapping zones, and restrict the presence of at most one vehicle in any zone at any time. In this paper, the concept of a new vehicle-collision prevention strategy called “dynamic-zone strategy” will be introduced. Detailed procedures based on this new strategy will be proposed for an AGV system with a single-loop guide path. Traditional zone strategies are fixed-zone strategies in which the zone assigned to each vehicle cannot be changed and vehicles are not allowed to help each other. As a result, fixed-zone strategies often have the disadvantage of not being able to satisfy the transportation demand whenever there is a load imbalance between vehicles. The objective of this paper is to develop a strategy that not only can prevent the collision of vehicles but also can avoid the disadvantage of fixed-zone strategies. To accomplish this, the proposed strategy relies on two procedures — Zone Adjustment Procedure and Zone Assistance Procedure. With Zone Adjustment Procedure, the area of each zone will be changed according to the current production demand. On the other hand, with Zone Assistance Procedure, vehicles are allowed to help each other so that the workload of every vehicle is balanced all the time. The methods of these two procedures will be developed in this paper. In addition, a Simulated Annealing (SA)-based zone-division design method that can find near-optimal zone-division designs will also be proposed in this paper. Experiments are then conducted to show that the proposed dynamic-zone strategy and the proposed zone-division design method are indeed beneficial to the throughput performance of production systems.