Various Types Of Interference Research Articles

Method for increasing the dynamic range of digital images based on modular arithmetic

The article proposes a new method of synthesis of digital images from several digital images to increase the dynamic range of intensity. The method is based on modular arithmetic. The increased range is divided into several residual classes. The full value of the intensity is calculated as the solution of the system of comparisons of residues for given modules. An analysis is made of the stability of the proposed method to the nonlinearity of the transfer characteristic and digital image recording devices under various types of interference. To this end, the maximum range for changing the brightness of a digital image is limited. By selecting the magnitude of the modules and the maximum brightness value, the distance between the diagonals in the decision table is selected so that this distance is greater than the level of distortion and (or) interference. Experimental validation of the method has been performed.

Stable descriptors in image recognition tasks

Objective. The objective of the study is to determine various stable characteristics of images (semi-invariants and invariants) as descriptors necessary for the formation of a feature space of standards intended for recognizing images of different nature belonging to different classes of objects. Methods. The authors propose metrics for evaluating the proximity of the recognized image to a given standard in the space of covariance matrices, based on the obtained descriptors as a methodological basis for constructing image recognition methods. Results. The content of the main stages of selecting descriptors for a given class of objects is developed, taking into account the different illumination of the recognized images. The effectiveness of the results obtained is confirmed by experimental studies related to the solution of the problem of recognition of special images - facies. Conclusions. The definition of stable image descriptors as invariants or semi-invariants to zoom and brightness transformations allows solving the problems of facies classification in conditions of the unstable shooting of recognized images. The images can be rotated and shifted in any way. In general, the proposed approach allows developing an effective image recognition system in the presence of various types of interference on the recognized images.

Resource Allocation for IRS-Assisted Full-Duplex Cognitive Radio Systems

In this article, we investigate the resource allocation design for intelligent reflecting surface (IRS)-assisted full-duplex (FD) cognitive radio systems. In particular, a secondary network employs an FD base station (BS) for serving multiple half-duplex downlink (DL) and uplink (UL) users simultaneously. An IRS is deployed to enhance the performance of the secondary network while helping to mitigate the interference caused to the primary users (PUs). The DL transmit beamforming vectors and the UL receive beamforming vectors at the FD BS, the transmit power of the UL users, and the phase shift matrix at the IRS are jointly optimized for maximization of the total spectral efficiency of the secondary system. The design task is formulated as a non-convex optimization problem taking into account the imperfect knowledge of the PUs’ channel state information (CSI) and their maximum interference tolerance. Since the maximum interference tolerance constraint is intractable, we apply a safe approximation to transform it into a convex constraint. To efficiently handle the resulting approximated optimization problem, which is still non-convex, we develop an iterative block coordinate descent (BCD)-based algorithm. This algorithm exploits semidefinite relaxation, a penalty method, and successive convex approximation and is guaranteed to converge to a stationary point of the approximated optimization problem. Our simulation results do not only reveal that the proposed scheme yields a substantially higher system spectral efficiency for the secondary system than several baseline schemes, but also confirm its robustness against CSI uncertainty. Besides, our results illustrate the tremendous potential of IRS for managing the various types of interference arising in FD cognitive radio networks.

Quieting an environmental magnetic field without shielding.

We construct an active magnetic compensation device and propose an efficient magnetic compensation method that suppresses a wider range of frequencies and amplitudes of time-varying magnetic fields than conventional methods. This system can compensate for all frequencies in the bandwidth of the sensors used by analyzing and extracting the spectral characteristics of the ambient field. We compensate simultaneously for various types of interference in rotation and achieve a reduction of the 50-Hz power-frequency field noise by 36 dB. Meanwhile, the real-time compensation of the field gradient is also investigated. Due to the effectiveness and extensive applicability of this method, it holds great promise for applications in atomic magnetometers, electron microscopes, and atomic clocks.

Analysis and Research on the fault disposal process of the electric energy metering devices

With the wide application of electronic equipment, the electric energy metering device of site operation is often subject to various types of interference. Due to the complex operation environment, various kinds of fault problems often occur in the electric energy metering devices. However, the actual failure disposal methods were not unified and standardized, which often results in the waste of electric energy metering device assets. In view of the above problems, the faults disposal methods of the electric energy metering devices were studied, the work flow of standardized fault disposal of electric energy metering devices was sorted out and the disposal requirements of each link were identified, which provides a good foundation for standardizing the unified and efficient disposal of the failed electric energy metering devices, deepening the quality management of the whole life cycle of the electric energy metering devices, and realizing the effective reuse of the electric energy metering devices.

One-step modification of nano-polyaniline/glucose oxidase on double-side printed flexible electrode for continuous glucose monitoring: Characterization, cytotoxicity evaluation and in vivo experiment

The single-step modification of the nanostructured polyaniline (PANI)/glucose oxidase (GOD) enzyme on double-sided, screen-printed, flexible electrodes doped with Prussian blue (PB), has been achieved and successfully applied in continuous glucose monitoring in vivo, and its biocompatibility has been evaluated systematically. The proposed fabrication procedure is simple, low cost, and suitable for large-scale production. PB doped with carbon ink catalyzes the reduction of hydrogen peroxide (H2O2) in low-voltage conditions, which could help eliminate interferences. And the PANI/GOD nanostructure makes the GOD enzyme more stable for long-term, in vivo monitoring. More importantly, a polyurethane (PU) layer is deposited on the electrode's surface as a diffusion limiting membrane that enhanced the linear range and biocompatibility. In tests in vitro, the proposed biosensor achieved a linear range of 0–12 mM and a good sensitivity of 16.66 μA·mM−1·cm−2(correlation coefficient R2 = 0.9962) with an excellent specificity to glucose. The biosensor exhibits long-term stability, with a maximum lifespan of 14 days when stored in phosphate buffer solution at 4 °C, and achieves a sensitivity of 120%. The biocompatibilities of the electrode materials have also been systematically evaluated in cytotoxicity and cell adhesion tests to ensure the safety of implantation. In experiments in vivo, the biosensor can successfully monitor the glucose level fluctuation of rats after 24 h following implantation. Overall, the biosensor fabricated with the double-side, screen-printing process, satisfies the glucose monitoring range in vivo and eliminates various types of interference, thus establishing a new, large-scale production procedure for flexible in vivo biosensors.

On the evaluation of noise immunity of different classes of wideband signals

The current stage of the development of the society is characterized by a continuous increase in remote interaction between subscribers and user requests for various types of multiservice services, with the required quality regardless of their location. This is mainly implemented on the basis of wireless communication systems (SBS) at the current time. A large number of various SBSs existing at the present leads to an increase in the level of various types of interference, which makes it necessary to increase the noise immunity of these systems. To improve the reliability of receiving information in the conditions of various types of interference, as is known, it is necessary to implement the information exchange by using channel signals with a large base, which primarily depends on the bandwidth they occupy. In this regard, in the present article, a comparative assessment of the noise immunity is carried out based on the obtained quantitative values of frequency characteristics of a number of modern classes of broadband channel signals, including a new class of broadband channel signals, and the use of eigenvectors of sub-band matrices.

Theoretical bases of synthesis of quasi-orthogonal systems of complex signals

Functioning of a number of modern infocommunication systems (ICS) is carried out under external and internal influences, caused, on the one hand, by natural interference, interference from other radio systems operating at close frequencies or in a common part of the frequency range, on the other hand, intentional interference created by counteraction stations with the aim of electronic suppression of existing systems. Possible strategies of the counter station are as follows: determining the content of messages when legal subscribers use cryptographic data protection algorithms; falsification of messages; violation of data integrity; staging of various types of interference, etc. Therefore, more stringent requirements are imposed on the ICS, especially for critical purposes, to ensure the effectiveness of their functioning: reliability and speed of information transfer, survivability, noise immunity, information security. In such conditions, the presence and use of protected ICS is of particular importance. Under the security systems one should understand, first of all, their ability to provide the necessary indicators for noise immunity, information, energy and structural secrecy, information transfer speed, frequency and energy efficiency. The need for the use of secure systems makes researchers take a fresh look at both the modes of operation of secure radio channels and the aspects of formation and use of complex signals – physical data carriers for such systems. In this paper, based on the study of the algebraic structure of systems of non-linear parametric irregularities, the problems of synthesis of a number of classes of quasi-optimal uniform, non-uniform, complex discrete signals with specified correlation, ensemble and structural properties, including such signal systems that have the properties “blur" by correlation properties. This property means that an increase or decrease in the duration of a discrete sequence does not change the correlation properties of the signal, on the basis of which the signal is synthesized. It is shown that the use of many of the indicated signal systems in modern information and communication systems will improve such indicators of the functioning of such systems as noise immunity, operational secrecy, information security, noise immunity of signal reception.

Spectrum classification using convolutional neural networks for a mini-camera detection system.

A mini-camera is one of several emerging cat-eye devices featuring tiny lenses with diffracted retro-reflections. It is hard for traditional active laser detection systems to identify a mini-camera because of their weak reflection. This paper proposes an anti-camera system with a spectrum-based convolutional neural network algorithm to recognize the profile features of the retro-reflection images captured by the system. The network was trained with the spatial spectra of local datasets and uploaded onto the embedded device. The results of several indoor experiments demonstrate that the system reached high accuracy in real-time detection, even with various types of interference.

ANALISA KEGAGALAN LIGHTNING ARRESTER PADA PENYULANG SULAHAN BANGLI

In the process of electrical power distribution, various types of interference can occur so that a protection system is needed to maintain the continuity and stability of electrical power distribution. Arrester is one of the main protection systems used to protect electrical equipment against overvoltages caused by lightning strikes. Penyulang Sulahan is a 20kV medium voltage distribution system that gets power supplies from Gianyar Substation 1/60 MVA and is located on a plateau that is prone to natural phenomena such as lightning. During 2016 there were three times the failure of conventional arresters. Based on these data, it is necessary to analyze the failure of arresters at Penyulang Sulahan so that the continuity of electricity can be better. The method used in this study is to collect data in the form of single line diagrams, disturbance data, and large grounding resistance on Sulahan Feeders. Next, compare Metal Oxide Arrester with Multi Chamber Arrester. The results obtained were grounding in the Feeder over 5 ohms which caused conventional arrester to not work properly. Multi Chamber Arrester is an arrester that has no effect on the value of grounding resistance. After installing the Multi Chamber Arrester, failure of arresters has decreased to one failure during 2017

Discrete time information diffusion in online social networks: micro and macro perspectives

Opinions shared publicly in online social networks spread broadly and at an extremely high speed. However, modelling information diffusion in online social networks is still a challenge that is intriguing to many researchers. To monitor public opinions online, it is necessary to model the process of information dissemination. In this paper, we first study information diffusion based on the network structure and time occupation. By taking into consideration the availability of a user, e.g., his online or offline state, we present the discrete-time bi-probability independent cascade model. We next analyse the information diffusion from a macro perspective. A diffusion model is established by merging the interferences from other events and the cumulative effect that occurs over time. Finally, we observe the factors in online social networks that impact a message’s diffusion from a micro perspective and discuss more complex user behaviour and various types of interferences with their effects from a macro perspective. Experiments are conducted with real world data, and the experimental results justify our models.

Anomaly detection of hot components in gas turbine based on frequent pattern extraction

Hot components operate in a high-temperature and high-pressure environment. The occurrence of a fault in hot components leads to high economic losses. In general, exhaust gas temperature (EGT) is used to monitor the performance of hot components. However, during the early stages of a failure, the fault information is weak, and is simultaneously affected by various types of interference, such as the complex working conditions, ambient conditions, gradual performance degradation of the compressors and turbines, and noise. Additionally, inadequate effective information of the gas turbine also restricts the establishment of the detection model. To solve the above problems, this paper proposes an anomaly detection method based on frequent pattern extraction. A frequent pattern model (FPM) is applied to indicate the inherent regularity of change in EGT occurring from different types of interference. In this study, based on a genetic algorithm and support vector machine regression, the relationship model between the EGT and interference was tentatively built. The modeling accuracy was then further improved through the selection of the kernel function and training data. Experiments indicate that the optimal kernel function is linear and that the optimal training data should be balanced in addition to covering the appropriate range of operating conditions and ambient temperature. Furthermore, the thresholds based on the Pauta criterion that is automatically obtained during the modeling process, are used to determine whether hot components are operating abnormally. Moreover, the FPM is compared with the similarity theory, which demonstrates that the FPM can better suppress the effect of the component performance degradation and fuel heat value fluctuation. Finally, the effectiveness of the proposed method is validated on seven months of actual data obtained from a Titan130 gas turbine on an offshore oil platform. The results indicate that the proposed method can sensitively detect malfunctions in hot components during the early stages of a fault, and is robust to various types of interference.

Adaptive reception of aggregate frequency signals in an underwater acoustic communications channel under different types of interference

The paper presents the results of experimental research on a multichannel underwater acoustic communications system that increases the digital information rate by aggregate frequency signals under deepsea conditions with multipath signal propagation. Quantitative estimates of information reception quality under various types of interference are given.

APPLICATION OF FOURIER TRANSFORM AND WAVELET DECOMPOSITION FOR DECODING THE CONTINUOUS AUTOMATIC LOCOMOTIVE SIGNALING CODE

Purpose. The existing system of automatic locomotive signaling (ALS) was developed at the end of the last century. This system uses the principle of a numerical code which is implemented on the basis of relay engineering, and therefore, it is exposed to various types of interferences. Over the years, the system has been upgraded several times, but the causes of faults and failures in its operation are still the subject of research. It is known that the frequency and the phase modulation of signal has a higher interference immunity as compared to the amplitude modulation. Therefore, the purpose of the article is to study the possibility of using the frequency methods such as Fourier series expansion and wavelet decomposition to extract the informational component of the received code from ALS signals under the action of various types of interferences. Methodology. One can extract the information unavailable in time representation of the signal using the signal studies in the frequency domain. The wavelet decomposition has been used for this purpose. This makes it possible to represent the local characteristics of the signal and to provide time-frequency decomposition in two spaces at the same time. Due to the high accuracy of the signal representation it is possible to analyze the time localization of spectral components and eliminate interference components even in the case of coincidence of interference frequency with the signal carrier frequency. Findings. To compare informativity of the methods of Fourier expansion and wavelet decomposition it was studied the reference and noisy signal of green fire code using the software package MATLAB. Detailed analysis of the obtained spectral characteristics showed that the wavelet decomposition provides a more correct decoding of the signal. Originality. Replacing the electromagnetic relays in the ALS system by microprocessor hardware involves the use of some mathematical tool for decoding, in order to obtain more information about the code. More often than not, as a mathematical tool, the classical Fourier decomposition is used. But because of a number of drawbacks in this method, it was suggested to use the wavelet decomposition, which has a number of advantages and accounts the disadvantages of the Fourier transform. Practical value. The presented method of code signal research can be the basis for developing dynamic model of the ALS receiver and decoder using digital processing module, which will enable to increase the reliability and accuracy of extraction of the code information component.

Analysis of the adaptive algorithms behaviour applied to the railway optimization problems

Abstract: In this article we will analyse the proposed adaptive algorithm used for the search of the best timetables and ensuring train loco- motives as the task of finding the global extremum of the objective function, taking into account various types of interference in the input data. The focus of this paper is on the convergence and speed, as well as the impact of noise on the results obtained.

Evalution of a RoF system using TSSB based SCM for multiplexing WCDMA based RF channels

In the advancing era of technology the need of fast, reliable and affordable data communication links are the threads weaving this huge world wide web. The biggest challenge for communication engineers is to handle a bulky traffic effectively so that the result is low cost communication. Till the second generation evolution of communication system the network was mostly RF based but with the evolution towards 3G the use of optical spectrum was also inherited. But, the after 3G technologies i.e. 4G onwards the communication network has adopted the optical networks along with the existing RF network to deliver fast and economical communication services with the efficient use of RoF (Radio over Fiber) systems. Through this paper we have studied the performance evaluation of as RoF (Radio of Fiber) system if we used WCDMA-RF signals to be sent over an optical fiber using a TSSB SCM technique. The results obtained shows the effects of various types of interferences on ENR (Energy per bit calculated under the effect of total interference to noise ratio) of the dedicated channel for traffic transmission in WCDMA-RoF systems.

COMBINING METHODS OF FREQUENCY FILTERING AND NONLINEAR ANALYSIS FOR SOMNOLOGICAL STUDY OF EEG SIGNALS

Aim - combined use of frequency and nonlinear analysis methods for obtaining hypnograms by analyzing electroencephalographic (EEG) signals during somnological studies. Methods. Frequency filtering methods were used for preliminary treatment of EEG signals before the following nonlinear analysis. As non-linear methods of analysis we used fractal methods of deterministic chaos, such as Hurst’s method of the normalized amplitude, approximate entropy method, calculation of the correlation integral by Grassberger and Procaccia’s method. For the possibility of applying the last two methods we used quasi phase space recovery method according to the Taken’s theorem. As a result of non-linear analysis we obtained hypnograms reflecting the transition between the stages of sleep in patients undergoing somnological examination. To assess the reliability of the results, they were compared to the hypnograms obtained by the classical method based on the rules of Rehchaffen and Keyls. Also the problems associated with the occurrence of various types of interference were considered and methods for reducing their influence on the final results were suggested. Results. We can conclude that using these methods with appropriate selection of the parameters, employing the necessary normalization of raw data, and averaging the results allow us to obtain hypnogram having a full match of defined phases of sleep for about half of the periods recorded by EEG. To obtain these results it is sufficient to use only one channel of EEG recording.

Security Implications of Data Mining in Cloud Scheduling

Cloud providers host an increasing number of popular applications, on the premise of resource flexibility and cost efficiency . Most of these systems expose virtualized resources of different types and sizes. As instances share the same physical host to increase utilization, they contend on hardware resources, e.g., last-level cache, making them vulnerable to side-channel attacks from co-scheduled applications. In this work we show that using data mining techniques can help an adversarial user of the cloud determine the nature and characteristics of co-scheduled applications and negatively impact their performance through targeted contention injections. We design Bolt, a simple runtime that extracts the sensitivity of co-scheduled applications to various types of interference and uses this signal to determine the type of these applications by applying a set of data mining techniques. We validate the accuracy of Bolt on a 39-server cluster. Bolt correctly identifies the type and characteristics of 81 percent out of 108 victim applications, and constructs specialized contention signals that degrade their performance. We also use Bolt to find the most commonly-run applications on EC2. We hope that underlining such security vulnerabilities in modern cloud facilities will encourage cloud providers to introduce stronger resource isolation primitives in their systems.

Structure development of diagnostic providing and diagnostic model of axle boxes in modern railroad cars

The study of technical and informational characteristics of embedded control systems of axle boxes has allowed creating the overall structure of the diagnostic software for axle boxes for modern railroad cars and also apply a thermal model and the recognition of the technical condition of axle boxes for solving the problem of increasing the reliability of the control of the rolling stock when it moves, due to the recent increase in the speed of movement of the extended portion of non-stop movement, as well as an increase in the intensity of the operation of rolling stock. Based on these studies it was developed the overall structure of the diagnostic software for axle boxes of modern railroad cars. It offers the most informative diagnostic features of the technical condition of axle box, increasing the accuracy of control and reduces the impact of various types of interference in its results. It is built diagnostic model of axle box on the basis of the thermal model based on additional parameters, the measurement of which is technically feasible only embedded systems. The proposed structure of the diagnostic software for axle boxes will not only improve the reliability and efficiency of control, but also makes it possible to detect emerging defects in the early stages and to solve the actual problem of forecasting residual resource of axle box to reduce the number of uncoupling of defective railroad cars. Developed activities will help to improve traffic safety and stability of the transportation process.

An fMRI study of the functional mechanisms of Stroop/reverse-Stroop effects

Many previous behavioral inhibition studies have employed the classic Stroop and reverse-Stroop paradigm. Although an experimental dissociation has been demonstrated between Stroop interference (SI) and reverse-Stroop interference (RI), the mechanisms that underlie these phenomena remain unclear. In this study, we used functional magnetic resonance imaging (fMRI) to compare the functional mechanisms of SI and RI. We identified the brain regions activated by the Stroop word-color matching task using four tests: the Stroop control test (Test 1), Stroop test (Test 2), reverse-Stroop control test (Test 3), and reverse-Stroop test (Test 4). Neuroimaging results revealed that SI elicited activation in the bilateral middle frontal gyrus (BA9). In contrast, a number of other regions, including the bilateral middle frontal gyrus (BA 9 and BA10), medial frontal gyrus (BA 8), and cingulate gyrus (BA6 and BA 32) exhibited significant activation during RI. Our results indicate that there is a dissociation between the types of interference and brain activation. These findings suggest that SI and RI interference can be attributable to different neural mechanisms. It also suggests that the prefrontal cortex and the cingulate cortex are differentially sensitive to various types of interference, and that the reverse-Stroop task may be more useful than the Stroop task for evaluating interference control in psychiatric patients with frontal dysfunction.