System In Terms Of Speed Research Articles

Research on the center extraction algorithm of structured light fringe based on an improved gray gravity center method

Abstract In this study, we proposed a fast line-structured light stripe center extraction algorithm based on an improved barycenter algorithm to address the problem that the conventional strip center extraction algorithm cannot meet the requirements of a structured light 3D measurement system in terms of speed and accuracy. First, the algorithm performs pretreatment of the structured light image and obtains the approximate position of the stripe center through skeleton extraction. Next, the normal direction of each pixel on the skeleton is solved using the gray gradient method. Then, the weighted gray center of the gravity method is used to solve the stripe center coordinates along the normal direction. Finally, a smooth strip centerline is fitted using the least squares method. The experimental results show that the improved algorithm achieved significant improvement in speed, sub-pixel level accuracy, and a good structured light stripe center extraction effect, as well as the repeated measurement accuracy of the improved algorithm is within 0.01 mm, and the algorithm has good repeatability.

Development of control charts to monitor image data using the contourlet transform method

AbstractIn recent years, researchers and practitioners have been exploring new methods for quality control, including image processing. The effective use of high‐volume image data can significantly improve the monitoring of production and service systems in terms of speed, accuracy, and cost. Adopting an image‐based approach is better than relying on operator‐based solutions, and it offers new perspectives for process monitoring. Image processing can involve extracting features to identify, classify, detect, and cluster. Although there are several transformations to extract features from images, the Fourier method cannot consider the concurrency of frequency and time data, and the wavelet method only considers two specific directions. In multidimensional transforms, the optimal method can provide more information using fewer coefficients. The contourlet transform has advantages such as multiresolution, localization, critical sampling, directionality, and anisotropy. This research investigates the advantages of applying the contourlet transform to images and using data in a generalized likelihood ratio control chart. The results show that this method is more accurate than others because it can examine various directions in images. The proposed methodology algorithm is also presented in this study.

Deep Learning Based Cross-View Human Detection System

Human detection is an important research branch in the field of computer vision, and it is widely used in vehicle-assisted driving, intelligent monitoring, intelligent transportation and other aspects. In order to solve the problems of poor real-time performance, low detection accuracy and inability to detect under occlusion in traditional human detection methods. This paper proposes a deep learning based trainable cross-view human detection system, where the encoder-decoder network focuses on solving the feature association problem after perspective transformation. Then, the system was tested on the WildTrack dataset. The results show that our cross-view human detection system outperforms conventional systems in terms of speed and accuracy across the board, achieving a satisfactory performance rate of 0.71 MODA in the presence of extensive occlusion.

심전도 기반의 심장 질환 분류를 위한 신호 특징 추출 시스템 개발

In this paper, we propose a signal-based feature detection system for the early diagnosis of heart disease. The purpose of this study is to develop a compact healthcare system that extracts features from ECG signals. Therefore, the performance of the Tompkins algorithm, which is widely known as a signal-based feature detection algorithm, and the deep learning model of prior research are compared. In addition, by verifying the performance of the deep learning model by applying the Haar wavelet transform to the preprocessing, we determine the optimal feature detection model applicable to the healthcare system in terms of speed and accuracy. All algorithms and models were developed using Matlab on Window, and performance was compared on Jetson nano and Raspberry pi embedded boards. As a result, the best model in terms of speed and accuracy is the Haar wavelet bidirectional long short-term memory model, which quickly performs classification prediction with almost 97% accuracy. The advantage of this study is that it quickly performs classification prediction with high accuracy compared to existing healthcare systems that use algorithms that cause signal distortion. Therefore, cardiovascular diseases can be predicted and monitored based on the feature regions detected in this study. The data used are the MIT-BIH Arrhythmia Database and the Normal Sinus Rhythm Database. If additional patient data are established and verified in the future, it will be possible to use them not only in real life but also in clinical settings.

INCREASING THE TIME OF USING THE ENERGY RESOURCE OF THE ON-BOARD ACCUMULATORY BATTERY BY IMPROVING THE QUALITY OF CONTROLLING THE ELECTRIC QUADCOPTER'S PROPELLER DRIVES

A review of the current state in quadcopters’ flight control systems showed that the electric drives of their propellers are performed according to single-circuit schemes with feedback on rotational speed in which the error in the results of monitoring the angles of roll, pitch, yaw is worked out by a control system with a PI or PID regulator. There is no astaticism load in such systems and the parameters of the current consumed from the on-board battery are not optimized. The consequence of this is a decrease of service life on-board battery and low quality flight control when the load changes. It is proposed to perform the electric drive system of the quadcopter’s screw according to a two-fold integrating structural scheme in which astaticism is provided during perturbations in control and load.
 A transient speed characteristic based on the optimization results of the double-integration scheme with speed and current circuits in accordance with a symmetrical optimum the parameters of which do not meet the requirements of quadcopter’s high-quality control flight mode was obtained and do not contribute to an increase in the time of using the energy resource of the on-board battery. It is proposed to include additional smoothing differentiating links at its input to eliminate the shortcomings of the obtained transient characteristic of the electric drive system in terms of speed. The parameters of these links were found using the compensation conditions. The obtained transient characteristics of the electric drive system of the quadcopter’s screws in terms of speed and current do not have sudden changes in the adjustable value and do not have overregulation. The result of such parameters in transient characteristics is high-quality control of the quadcopter’s flight mode and an increase in the time of using the energy resource of the on-board battery.

Project BIS-IG: Prototyping of Wireless Irrigation Control System Using Arduino Microcontroller with SMS Notification

Objectives: This study aims to: 1. Improve water sustainability using automated water control systems and 2. Determine exact water requirement to irrigate on fine, medium and coarse soil type using drip irrigation technique. Methods: To work effectively with the Wireless Irrigation System, a sensor module was developed to sense out the soil humidity and water content of the soil. The system is designed using drip irrigation technique as a model for testing irrigation control. It will focus on three soil types which include fine, medium and coarse in determining the need of soil humidity level in the system. The developed technology was compared to the existing irrigation control system in terms of speed of irrigation and amount of water used in the irrigation procedure. Findings : In the existing irrigation system, continuous distribution of water to farmlands takes place. The water sustainability was not controlled. The proposed irrigation control system analyzes the soil humidity level of the farmland, and only applies irrigation when a specific soil which needs irrigation based on humidity level; when the soil humidity is below normal, the reservoir will release water to plants. After a series of testing and comparing of the two-irrigation control system during testing, it is proven that the developed irrigation control system can be used to improve water sustainability in irrigation. An average of 52.777777775% of water from the reservoir was saved using the automatic irrigation control system. Novelty: The proposed system was used as a prototype material or model in testing lowland areas for a bigger wireless irrigation control system that can be used in automation of irrigating farmlands through drip irrigation technique. The developed system was tested in a farm land miniature where soil types are in different stations. The developed system can reduce the use of water in irrigation. Keywords: Arduino; drip irrigation; wireless communication; desktop application; embedded system

Optimal control of fluctuations of the “liquid substance - pipeline” system in terms of speed during transportation of a liquid substance

The process of transporting a liquid substance (oil, petroleum products, gas mixtures) the pipeline network and related engineering facilities, being a dynamically non-equilibrium physical system, are often carried out in extreme modes, which can form dangerous wave phenomena accompanied by various instabilities, generating undesirable consequences and even catastrophes. Similar phenomena can occur in technical devices and apparatuses containing in their design hydraulic networks for the transfer of continuous media (aircraft, energy objects). Eliminate (extinguish or reduce the intensity) such phenomena are possible in the shortest possible time by making additional structural changes to the pipeline network, which make it possible to use external devices for dynamic influence on the “liquid substance – pipeline” system and eliminate (or minimize) the possibility of negative wave effects. The paper is devoted to the problem of eliminating dangerous vibrations initiated by a liquid substance transported through a pipeline network, provided that time resources are spent minimally. A mathematical model of the wave process and the problem of optimal control over the speed of such a model are considered. The control effect on the “liquid substance-pipeline” system is carried out at the initial and final points of the pipeline network, while the necessary information about the state of the system is used in a finite number of points distributed along the entire length of the pipeline, which makes it possible to calculate external influences on the system. In order to simplify the presentation of the results, a linear carrier of a liquid substance is used (in applications, a pipeline without branches) and a one-dimensional wave equation – the length of the pipeline is much larger than its diameter.

Microscopy automation on a budget: capturing high-speed multi-labelled events with LED Illumination Systems.

Capturing fast cellular processes with widefield fluorescence microscopy and multiple fluorophores has historically required the addition of motorised components. The light source has often been overlooked as an affordable means of achieving multi-wavelength imaging, but LEDs have changed the game. Here we compare typical configurations for automated illumination systems in terms of speed, cost and signal-to-noise ratio (i.e. image contrast). We also explore how to transform a manual microscope into a powerful automated imaging system by capitalising on LED switching speeds, with lower cost filters and minimal requirement for expensive motorised components.

An Efficient Implementation and Analysis of Tail-Biting Convolution Coding Algorithm for OFDM Based System in Terms of Speed, Memory and Peak-to-Average Power Ratio Using DSP

Fourth Generation (4G) mobile communication system uses Orthogonal Frequency Division Multiplexing (OFDM). With this technique, high data rate demands are achieved. Tail biting Convolution Coding (TBCC) avoids the data rate loss, hence it is widely used error control coding algorithm in OFDM and other various wireless communication technologies. But, OFDM has increased Peak to Average Power Ratio (PAPR). High PAPR signal consumes more power and makes system power inefficient. To gain supercomputing performance in terms of Speed, Memory and Power on mobile devices, an efficient implementation of algorithms on Digital Signal Processing (DSP) processor is an essential requirement. This requirement becomes more stringent for Fifth Generation (5G) mobile devices. For this, wide scope of knowledge as well as skills are required to understand the algorithm, DSP architecture, instruction set, optimization and performance measurement. In this article, we have implemented TBCC algorithm using Bit by Bit (BYB) and Look Up Table (LUT) approaches on Freescale StarCore SC140 based DSP platform and proposed an efficient algorithm implementation methodology by comparing the machine cycles and memory requirement. We have used coding rate (R) = 1/2, 1/3, 1/4 and constraint length (K) = 5 and K = 9 for implementation of TBCC. Using our proposed LUT approach, we have achieved average 45.82% Computational Complexity Reduction Ratio (CCRR) in machine cycles compared to BYB approach. Proposed LUT approach increases the TBCC execution speed. Our developed fixed point routines can be used for any K ≤ 9. TBCC is also analyzed for PAPR to get an overall profiling results and three dimensional optimization of TBCC algorithm in terms of Speed, Memory and Power.

Human Occupancy Detection via Passive Cognitive Radio.

Human occupancy detection (HOD) in an enclosed space, such as indoors or inside of a vehicle, via passive cognitive radio (CR) is a new and challenging research area. Part of the difficulty arises from the fact that a human subject cannot easily be detected due to spectrum variation. In this paper, we present an advanced HOD system that dynamically reconfigures a CR to collect passive radio frequency (RF) signals at different places of interest. Principal component analysis (PCA) and recursive feature elimination with logistic regression (RFE-LR) algorithms are applied to find the frequency bands sensitive to human occupancy when the baseline spectrum changes with locations. With the dynamically collected passive RF signals, four machine learning (ML) classifiers are applied to detect human occupancy, including support vector machine (SVM), k-nearest neighbors (KNN), decision tree (DT), and linear SVM with stochastic gradient descent (SGD) training. The experimental results show that the proposed system can accurately detect human subjects—not only in residential rooms—but also in commercial vehicles, demonstrating that passive CR is a viable technique for HOD. More specifically, the RFE-LR with SGD achieves the best results with a limited number of frequency bands. The proposed adaptive spectrum sensing method has not only enabled robust detection performance in various environments, but also improved the efficiency of the CR system in terms of speed and power consumption.

A Hybrid Intelligent Decision-Making System for Navigation with Optimized Performance

A moving vehicle comes across some permanent components like roads and some variable components like other vehicles etc. Keeping these components at forefront, an automated vehicle needs to take astute and speedy decisions about its next move. In this research paper, we have proposed a hybrid model based on two soft computing techniques that is Neural Networks and Fuzzy Systems to optimize the performance of Navigation Systems in terms of speed and accuracy. The proposed model is an extension of authors previous work [ 1] in which the Best Feature Selection model was created to extract the most paramount features of navigation images. In that, it was observed that extracted feature set had direct impact on speed and accuracy of the working model as no resources were required to be spent on impertinent features. Our hybrid model performs three steps afore taking final decision that is either to move or stop the automated vehicle. The first step involves passing the outputs of Best Feature Selection Model and PCA as inputs through Convolutional Neural Network (CNN) deep learning model and obtaining the response in form of move or stop. Principal Component Analysis (PCA) technique was performed on the extracted feature set to improve our knowledge about input feature set by procreating new features. In our previous work [2], it was justified that Principal Component Analysis (PCA) when used in conjunction with Convolutional Neural Networks (CNN) yields better results as compared to standalone performance of PCA and CNN. It was withal analysed that PCA-CNN is going to give nearly same precision either we give ten percent training or we give high order training. The second step involves using one other variant of Neural Networks that is Re-current Neural Networks (RNN) for ascertaining out the bestest feature from all eleven features of Best Feature Selection Model. The factor with least Mean Square Error is used to calculate the decision in form of move or stop. The last step involves passing the outputs of CNN model and RNN model through Fuzzy Module. Here the Fuzzy rules are generated to take final decision for moving vehicle. The accuracy of this hybrid model came out be 89.28 percent which is far better than individual accuracies that is 72 percent and 60 percent of CNN model and RNN model respectively

Hard Limits and Performance Tradeoffs in a Class of Antithetic Integral Feedback Networks.

Feedback regulation is pervasive in biology at both the organismal and cellular level. In this article, we explore the properties of a particular biomolecular feedback mechanism called antithetic integral feedback, which can be implemented using the binding of two molecules. Our work develops an analytic framework for understanding the hard limits, performance tradeoffs, and architectural properties of this simple model of biological feedback control. Using tools from control theory, we show that there are simple parametric relationships that determine both the stability and the performance of these systems in terms of speed, robustness, steady-state error, and leakiness. These findings yield a holistic understanding of the behavior of antithetic integral feedback and contribute to a more general theory of biological control systems.

CamType: assistive text entry using gaze with an off-the-shelf webcam

As modern assistive technology advances, eye-based text entry systems have been developed to help a subset of physically challenged people to improve their communication ability. However, speed of text entry in early eye-typing system tends to be relatively slow due to dwell time. Recently, dwell-free methods have been proposed which outperform the dwell-based systems in terms of speed and resilience, but the extra eye-tracking device is still an indispensable equipment. In this article, we propose a prototype of eye-typing system using an off-the-shelf webcam without the extra eye tracker, in which the appearance-based method is proposed to estimate people’s gaze coordinates on the screen based on the frontal face images captured by the webcam. We also investigate some critical issues of the appearance-based method, which helps to improve the estimation accuracy and reduce computing complexity in practice. The performance evaluation shows that eye typing with webcam using the proposed method is comparable to the eye tracker under a small degree of head movement.

A smooth contact-state transition in a dynamic model of rolling-element bearings

We present a new formulation to calculate the response of a system containing rolling-element bearings operating under a radial clearance and a dominant radial load. The nonlinear bearing force- and stiffness-displacement characteristics in combination with the bearing clearance necessitate an advanced numerical analysis. The response of a shaft-bearing-housing assembly can be unstable in the transient regions, e.g., at the start of a system run-up or when passing the critical speed of a system. This can lead to long computational times or even to non-converged solutions. In this paper, a new analytical bearing-stiffness model is presented that is capable of overcoming these problems by smoothing the nonlinear bearing force- and stiffness-displacement characteristics in the discontinuous regions. The smoothing is implemented on the deformation scale. The proposed model is modular, allowing us to define a specific value of the smoothing to each rolling element that comes into contact. A simple case study that involves two bearings of different types (ball and cylindrical roller) is presented. They support an unbalanced rotor, subjected to a constant angular acceleration. We show that a small smoothing value can significantly enhance the numerical calculation of the chosen system in terms of speed and stability.

Face Liveness Detection Based on Joint Analysis of RGB and Near-Infrared Image of Faces

We have witnessed the huge evolution of face recognition technology from the first pioneering works to the current state-of-the-art highly accurate systems in the past few decades. The ability to resist spoofing attacks has not been addressed until recently. While a number of researchers has thrown themselves into the challenging mission of developing effective liveness detection methods against this kind of threat, the existing algorithms are usually affected by limitations such as light conditions, response speed and interactivity. In this paper, a novel and appealing approach is introduced based on the joint analysis of visible image and near-infrared image of faces, three different features (bright pupil, HOG in nose area, reflectance ratio) are extracted to form the final BPNGR feature vector. A SVM classifier with RBF kernel is trained to distinguish between genuine (live) and spoof faces. Experiment results on the self-collected database with 605 samples clearly demonstrate the superiority of our method over previous systems in terms of speed and accuracy.

Security Improvement in Elliptic Curve Cryptography

This paper proposed different approaches to enhance the performance of the Elliptic Curve Cryptography (ECC) algorithm. ECC is vulnerable to attacks by exploiting the public parameters of ECC to solve Discrete Logarithm Problem (DLP). Therefore, these public parameters should be selected safely to obviate all recognized attacks. This paper presents a new generator function to produce the domain parameters for creating the elliptic curve; a secure mechanism is used in the proposed function to avoid all possible known attacks that attempts to solve the Elliptic Curve Discrete Logarithm Problem (ECDLP). Moreover, an efficient algorithm has been proposed for choosing two base points from the curve in order to generate two subgroups in a secure manner. The purpose of the aforementioned algorithm is to offer more confidence for the user since it is not built upon a hidden impairment that it could be subsequently utilized to retrieve user’s private key. The Elliptic Curve Diffie Hellman (ECDH) algorithm is implemented to exchange a session key between the communicating parties in a secure manner. Beside, a preprocessing operation is performed on the message to enhance the diffusion property and consequently leads to increase the strength against cryptanalysis attack. Finally, the dual encryption/decryption algorithm is implemented using different session keys in each stage of the encryption to boost immunity against any attack on the digital audio transmission. The gained results show the positive effect of the dual elliptic curve system in terms of speed and confidentiality without needing any extra time for encryption.

DESIGN OF BLUETOOTH LOW ENERGY BASED INDOOR POSITIONING SYSTEM

Nowadays, there is an increasing demand for indoor positioning systems as services based on location are very important in mobile applications. Since Global Positioning System (GPS) makes only outdoor positioning successful, there is a need of new approaches for indoor positioning systems. Some techniques on indoor positioning systems have been proposed in this scope, but they have not reached to the success of outdoor systems in terms of speed, consistency and power management. The aim of this study is to develop an indoor positioning system using latest Bluetooth Low Energy (BLE) technology. This system consists of BLE sensor nodes, a mobile device and a mobile application that calculates indoor position by measuring the signal levels of the sensor nodes designed. BLE sensor nodes have low power consumption and can be powered by a coin battery. Since most consumers have a mobile phone today, the system can be used easily by installing a mobile application.

Increased wavelength VCSELs reach out

Work from Sweden and the US is extending the reach of low-cost laser and fibre technology to meet the growing needs of optical interconnects in the massive data centres that underpin our Internet-enabled world. Team member Ewa Simpanen holding up a set of VCSEL chips in the cleanroom at Chalmers University of Technology. VCSELs (Vertical-cavity surface-emitting lasers) are power efficient semiconductor lasers that can be produced in high volumes at low cost. They can also be directly modulated at high speed when biased at low currents. All of this makes them the preferred light source for the short-reach optical interconnects used in data centres and high-performance computing systems. In these applications, VCSELs are used with high modal bandwidth multimode fibre (MMF) to relax the laser-to-fibre alignment tolerance, which also reduces costs associated with assembly and packaging. With the development of cloud-based applications and Internet-delivered services, data centres operated by service providers like Facebook and Google are developing into very large facilities. These ‘mega’ data centres need optical interconnects that can reach beyond 1 km. This cannot be supported by current VCSEL-MMF technology owing to the large chromatic dispersion and attenuation in MMF at the standard wavelength – 850 nm. At longer wavelengths, dispersion and attenuation are much lower, allowing greater reach. This is the need that the team, from Chalmers University of Technology in Sweden, and Hewlett Packard Enterprise (HPE) in the US, are working to meet. Team member Ewa Simpanen told us, “The purpose of this work is to develop high-speed, longer wavelength those while still using the GaAs-based material systems as it enables the fabrication of VCSELs which are superior to those based on other material systems in terms of speed, efficiency, manufacturability, and cost.” Currently, large-scale data centres use single-mode fibres and long-wavelength silicon photonic transceivers to cover the needed distances. With longer wavelength GaAs-based VCSELs, it would be possible to build transmitters for long-range interconnects that are as power and cost efficient as those used for shorter reach interconnects. In this issue of Electronics Letters, the Chalmers and HPE team present a VCSEL design operating at 1060 nm. This high-speed, single-mode, low-resistance VCSEL can support bit-rates up to 50 Gbit/s while dissipating no more than 100 fJ of energy per bit; making it very energy efficient – on par with the state-of-the-art at 850 nm. “We have limited the wavelength extension to 1060 nm since the long-term reliability of GaAs-based VCSELs may be compromised if extending the wavelength beyond ∼1100 nm,” explained Simpanen. At 1060 nm, the fibre chromatic dispersion is reduced by 70% and attenuation by 50% compared to 850 nm. Using a single-mode VCSEL the narrow spectral width of the laser further reduces the impact of chromatic dispersion. With the single-mode VCSEL properly aligned to the MMF, only the fundamental mode of the fibre, or the lowest order mode group, is excited, which also reduces the impact of modal dispersion. “In these conditions, the fibre ideally acts as a pure attenuator without degrading the signal quality. All this together should enable data transmission distances compatible with what is required in mega data centres,” said Simpanen. The results reported in this issue deal with the modulation capacity of the VCSEL itself. Since then, the team have started investigating the data transmission capacity of optical interconnects using the VCSEL together with MMF designed for high modal bandwidth at 1060 nm and so far the results are very promising, according to Simpanen. “This prototype fibre is fabricated at and provided by Corning. In a first preliminary experiment, we have transmitted data at 25 Gbit/s over 1 km with some margin. We believe that higher data rates and/or longer transmission distances are possible with further optimisations. We will also investigate the alignment tolerances under mode selective launch as they are of utmost importance for practical implementations.” A microscope image of an array of VCSEL devices on chip; newly fabricated and ready for characterisation. Looking further ahead, the team think that continued engineering of conventional VCSEL designs and the implementation of more exotic VCSEL concepts for further significant speed improvements will play a big part in developing much higher capacity interconnects. Combined with electronic compensation techniques, such as equalisation and digital signal processing, higher order modulation formats, and more advanced forms of spatial and wavelength division multiplexing, they believe such lasers could eventually achieve aggregate interconnect capacities approaching 100 Tbit/s.

(The relationship between electronic accounting information systems and the degree of bank credit risk (Field study on specialized Sudanese banks: العلاقة بين انظمة المعلومات المحاسبية الإلكترونية ودرجة مخاطر الائتمان المصرفي (دراسة ميدانية على البنوك السودانية المتخصصة )

The study examined the role of accounting information systems to reduce the risk of electronic credit bank. The problem with the study is that the banks are exposed to the failures , in the event of failed management in the recruitment of accounting information systems , electronic tapped to serve and support its own operations in making investment decisions in general, and the decisions of the granting of credit in the banks , in particular the most part due failures in the field of credit to the problems in the measurement of risk credit , which represents state banks face at the present time which makes it tough in the granting of credit . This study is important from the importance of accounting information systems electronic as a strategy has become a strategic resource dependent upon the banks to deal with the market conditions when making decisions to grant credit, as banks must stand on the degree of credit risk for credit operations that have been granted to customers, so before making a decision to grant loans new in order to stand on the truth and put . The study aimed to identify the characteristics of the electronic accounting information systems in terms of speed in providing information and in terms of the accuracy of information and reflection on the measurement of credit risk in banks, the formulation of the theoretical aspects of the accounting information systems and electronic use them to improve the process of measuring credit risk. The study relied on deductive approach and inductive and historical approach descriptive and concluded several results, most important , study results indicated accounting information systems electronic affect the credit risk of the bank, confirmed the findings of the study and a relationship with a significance between rehabilitation personnel information systems, accounting and reduce the credit risk of the bank, results indicated study indicated that the accounting information systems electronic increase the credibility of accounting information . The study recommended a number of recommendations, including the need to make sure the loan guarantee granted by the credit risk faced by the bank through electronic accounting information system, focusing on the importance of the information system of accounting -mail addresses for being immediate loans when due.

A Novel Hybrid Mental Spelling Application Based on Eye Tracking and SSVEP-Based BCI.

Steady state visual evoked potentials (SSVEPs)-based Brain-Computer interfaces (BCIs), as well as eyetracking devices, provide a pathway for re-establishing communication for people with severe disabilities. We fused these control techniques into a novel eyetracking/SSVEP hybrid system, which utilizes eye tracking for initial rough selection and the SSVEP technology for fine target activation. Based on our previous studies, only four stimuli were used for the SSVEP aspect, granting sufficient control for most BCI users. As Eye tracking data is not used for activation of letters, false positives due to inappropriate dwell times are avoided. This novel approach combines the high speed of eye tracking systems and the high classification accuracies of low target SSVEP-based BCIs, leading to an optimal combination of both methods. We evaluated accuracy and speed of the proposed hybrid system with a 30-target spelling application implementing all three control approaches (pure eye tracking, SSVEP and the hybrid system) with 32 participants. Although the highest information transfer rates (ITRs) were achieved with pure eye tracking, a considerable amount of subjects was not able to gain sufficient control over the stand-alone eye-tracking device or the pure SSVEP system (78.13% and 75% of the participants reached reliable control, respectively). In this respect, the proposed hybrid was most universal (over 90% of users achieved reliable control), and outperformed the pure SSVEP system in terms of speed and user friendliness. The presented hybrid system might offer communication to a wider range of users in comparison to the standard techniques.