The article describes and compares two OFDM based communications schemes for reducing the effects of the combination of Narrowband Interference (NBI) and Impulsive Noise (IN), which are noise types typical in Power Line Communication (PLC). The two schemes are Modified BPSK-OFDM (called MBPSK, for brevity) and QFSK-OFDM (called QFSK, for brevity), which are non-conventional OFDM schemes. We give a description of the two schemes, showing how they are derived and also show their similarities and eventually compare their performances. Performance simulation results, in terms of bit error rate, are given to compare the systems under the effect of IN and NBI. The popular Middleton Class A model is used for modelling IN. The results show that MBPSK scheme outperforms the QFSK scheme in terms of minimum distance, and hence in terms of bit error probability when no preprocessing is performed. However, under clipping/nulling, both schemes eventually reach the bit error rate floor.
In this paper the biofeedback therapy application is presented. The application is implemented in desired biofeedback system based on RaspberyPI. The EEG signal is taken using popular headset with forehead probe and ear reference one. A patient is trying to focus on desired task and should keep attention level above threshold, the threshold is given and monitor by therapist. The success factor during one therapy session should be more than about 80%, so therapist have to control the threshold. The application consists algorithm for automatic threshold correction based on interview with experienced therapist.
In this paper, we proposed a novel design of U-slotted SIW antenna. Our antenna design is aimed to cover upper K-band and lower Ka-band spectrums, specifically from 24 GHz to 32 GHz. It has a compact square size of 5.2 x 5.2 mm2. We use a rectangular truncated corner to optimize the square radiator. The optimized rectangular truncated corner size of 2 x 0.8 mm2 gives an impedance bandwidth of 7.87 GHz. SIW cavity is constructed by using multiple metallic via-holes which are drilled in a dielectric substrate establishing. Next optimization, applying the U-shaped slot and SIW structure yield a wider impedance bandwidth of 8.89 GHz, there is about 1.02 GHz of impedance bandwidth enhancement. In addition, the SIW structure gives a higher gain of 7.63 dB and decreases the sidelobe level of -12.1 dB. Implementation of the SIW structure significantly decreases the size of antenna while keeping the antenna parameter’s performances.
The Distributed Ledger Technology (DLT) is a peer-to-peer model of sharing data among collaborating parties in a decentralized manner. An example of DLT is a blockchain where data form blocks in an append-only chain. Software architecture description usually comprises multiple views. The paper concentrates on the Deployment view of the DLT solution within the 1+5 architectural views model. The authors have proposed Unified Modeling Language (UML) extensibility mechanisms to describe the needed additional semantic notation to model deployment details. The paper covers both the network and node levels. The proposed stereotypes and tagged values have enriched UML Deployment diagram. We have gathered those modeling elements in dedicated UML Profile for Distributed Ledger Deployment. We have applied the profile to model Deployment view of a renewable energy management system that uses R3 Corda framework. The system records information about inbound and outbound energy to/from renewable energy grid.
Providing Privacy and security for aggregated data in wireless sensor networks has drawn the attention of practicing engineers and researchers globally. Several cryptographic methods have been already proposed to solve security and data integrity problems for aggregated data. Matrix cryptography is a better option for creating secure encryption/decryption algorithms to counter quantum attack. However, these algorithms have higher computational cost and increased communication overhead. Hence, a new technique of loss-less secure data aggregation in Clustered Wireless Sensor Networks is presented. The proposed method uses integer matrices as keys for data security and data integrity. Matrix operations are carried out in finite field Zp. Loss-less secure data aggregation is extended for homomorphic summation while the cipher text expansion ratio is kept substantially low. The proposed algorithm has inbuilt fast and efficient signature verification facility. The execution time of our signature verification mechanism is found to be approximately 50 percent less compared to a couple of standard existing signature verification schemes.
Currently, the Republic of Kazakhstan is developing a new standard for symmetric data encryption. One of the candidates for the role of the standard is the Qamal encryption algorithm developed by the Institute of Information and Computer Technologies (Almaty, Republic of Kazakhstan). The article describes the algorithm. Differential properties of the main operations that make up the Qamal cypher are considered in the questions of stability. We have shown that for a version with a 128-bit data block and the same secret key size for three rounds of encryption it is difficult to find the right pairs of texts with a probability of 2–120, which makes differential cryptanalysis not applicable to the Qamal cypher.
To improve power system reliability, a protection mechanism is highly needed. Early detection can be used to prevent failures in the power transmission line (TL). A classification system method is widely used to protect against false detection as well as assist the decision analysis. Each TL signal has a continuous pattern in which it can be detected and classified by the conventional methods, i.e., wavelet feature extraction and artificial neural network (ANN). However, the accuracy resulting from these mentioned models is relatively low. To overcome this issue, we propose a machine learning-based on Convolutional Neural Network (CNN) for the transmission line faults (TLFs) application. CNN is more suitable for pattern recognition compared to conventional ANN and ANN with Discrete Wavelet Transform (DWT) feature extraction. In this work, we first simulate our proposed model by using Simulink® and Matlab®. This simulation generates a fault signal dataset, which is divided into 45.738 data training and 4.752 data tests. Later, we design the number of machine learning classifiers. Each model classifier is trained by exposing it to the same dataset. The CNN design, with raw input, is determined as an optimal output model from the training process with 100% accuracy.
The paper addresses the issue of the Electromagnetic Environment Situational Awareness techniques. The main focus is put on sensing and the Radio Environment Map. These two dynamic techniques are described in detail. The Radio Environment Map is considered the essential part of the spectrum management system. It is described how the density and deployment of sensors affect the quality of maps and it is analyzed which methods are the most suitable for map construction. Additionally, the paper characterizes several sensing methods.
Steganography is a technique that allows hidden transfer of data using some media such as Image, Audio, Video, Network Protocol or a Document, without its existence getting noticed. Over the past few years, a lot of research has been done in the field of Image, Video and Audio Steganography but very little work has been done in Network Steganography. A Network Steganography technique hides data in a Network Data Unit, i.e., a Network Protocol Packet. In this paper we present an algorithm ARPNetSteg that implements Network Steganography using the Address resolution protocol. Our technique is a robust technique that can transfer 44 bits of covert data per ARP reply packet.
This article presents a consistent solution of Transmit Power Control in centralized (clustered) wireless network with and without jamming. Depending on the policy assumed, appropriate solutions are applied to minimize the power used in a system or to satisfy expected Quality of Service. Because of specific nature of the system there is no optimal solution which can be applied in practice. Correctness and effectiveness of four proposed Transmit Power Control algorithms was presented in the form of computer simulation results in which the system capacity, mean power used and the number of successful links were described.
The zero attraction affine projection algorithm (ZA-APA) achieves better performance in terms of convergence rate and steady state error than standard APA when the system is sparse. It uses l1 norm penalty to exploit sparsity of the channel. The performance of ZA-APA depends on the value of zero attractor controller. Moreover a fixed attractor controller is not suitable for varying sparsity environment. This paper proposes an optimal adaptive zero attractor controller based on Mean Square Deviation (MSD) error to work in variable sparsity environment. Experiments were conducted to prove the suitability of the proposed algorithm for identification of unknown variable sparse system.
In Polish coal mining, medium voltage power distribution networks operate with an insulated neutral point. Zero-sequence current transformers are the basic sensors that generate input signals for earth-fault protection relays. In the literature, the problem of frequency response analysis of various types of current transformers has been examined many times, e.g.  , but not for zero-sequence current transformers so far. As part of the work, two types of zero-sequence current transformers in the range from 0.1 Hz to 100 kHz were tested. Both the change of the current ratio and the angular shift between the transformer secondary current and the total primary current were analyzed.
Elastic optical networking is a potential candidate to support dynamic traffic with heterogeneous data rates and variable bandwidth requirements with the support of the optical orthogonal frequency division multiplexing technology (OOFDM). During the dynamic network operation, lightpath arrives and departs frequently and the network status updates accordingly. Fixed routing and alternate routing algorithms do not tune according to the current network status which are computed offline. Therefore, offline algorithms greedily use resources with an objective to compute shortest possible paths and results in high blocking probability during dynamic network operation. In this paper, adaptive routing algorithms are proposed for shortest path routing as well as alternate path routing which make routing decision based on the maximum idle frequency slots (FS) available on different paths. The proposed algorithms select an underutilized path between different choices with maximum idle FS and efficiently avoids utilizing a congested path. The proposed routing algorithms are compared with offline routing algorithms as well as an existing adaptive routing algorithm in different network scenarios. It has been shown that the proposed algorithms efficiently improve network performance in terms of FS utilization and blocking probability during dynamic network operation.
Establishing the proper values of controller parameters is the most important thing to design in active queue management (AQM) for achieving excellent performance in handling network congestion. For example, the first well known AQM, the random early detection (RED) method, has a lack of proper parameter values to perform under most the network conditions. This paper applies a Nelder-Mead simplex method based on the integral of time-weighted absolute error (ITAE) for a proportional integral (PI) controller using active queue management (AQM). A TCP flow and PI AQM system were analyzed with a control theory approach. A numerical optimization algorithm based on the ITAE index was run with Matlab/Simulink tools to find the controller parameters with PI tuned by Hollot (PI) as initial parameter input. Compared with PI and PI tuned by Ustebay (PIU) via experimental simulation in Network Simulator Version 2 (NS2) in five scenario network conditions, our proposed method was more robust. It provided stable performance to handle congestion in a dynamic network.
Energy and latency are the significant Quality of Service parameters of ad hoc networks. Lower latency and limited energy expenditure of nodes in the ad hoc network contributes to a prolonged lifetime of the network. Reactive protocols determine the route to the destination using a route discovery process which results in increased delay and increased energy expenditure. This paper proposes a new technique of route discovery, Dynamic Blocking Expanded Ring Search (DBERS) which minimizes time delay and energy required for route discovery process. DBERS reduces energy expenditure and time delay occurring in the existing route discovery techniques of reactive protocols. The performance of DBERS is simulated with various network topologies by considering a different number of hop lengths. The analytical results of DBERS are validated through conduction of extensive experiments by simulations that consider topologies with varying hop lengths. The analytical and simulated results of DBERS are evaluated and compared with widely used route discovery techniques such as BERS, BERS+. The comparison of results demonstrates that DBERS provides substantial improvement in time efficiency and also minimizes energy consumption.
This paper models the downlink Fifth Generation (5G) network that supports a flexible frame structure and a shorter Round-Trip Time (RTT) for Hybrid Automatic Repeat Request (HARQ). Moreover, the design of the renowned Time Division Multiple Access (TDMA) packet scheduling algorithms is revised to allow these algorithms to support packet scheduling in the downlink 5G. Simulation results demonstrate that the Proportional Fair provides a comparable performance to the delay–aware Maximum-Largest Weighted Delay First for simultaneously providing the desired transmission reliability of the Guaranteed Bit Rate (GBR) and Non-Guaranteed Bit Rate (Non- GBR) healthcare contents whilst maximizing the downlink 5G performance.
The proportional-integral-derivative (PID) controller is widely used in various industrial applications such as process control, motor drives, magnetic and optical memory, automotive, flight control and instrumentation. PID tuning refers to the generation of PID parameters (Kp, Ki, Kd) to obtain the optimum fitness value for any system. The determination of the PID parameters is essential for any system that relies on it to function in a stable mode. This paper proposes a method in designing a predictive PID controller system using particle swarm optimization (PSO) algorithm for direct current (DC) motor application. Extensive numerical simulations have been done using the Mathwork’s Matlab simulation environment. In order to gain full benefits from the PSO algorithm, the PSO parameters such as inertia weight, iteration number, acceleration constant and particle number need to be carefully adjusted and determined. Therefore, the first investigation of this study is to present a comparative analysis between two important PSO parameters; inertia weight and number of iteration, to assist the predictive PID controller design. Simulation results show that inertia weight of 0.9 and iteration number 100 provide a good fitness achievement with low overshoot and fast rise and settling time. Next, a comparison between the performance of the DC motor with PID-PSO, with PID of gain 1, and without PID were also discussed. From the analysis, it can be concluded that by tuning the PID parameters using PSO method, the best gain in performance may be found. Finally, when comparing between the PID-PSO and its counterpart, the PI-PSO, the PID-PSO controller gives better performance in terms of robustness, low overshoot (0.005%), low minimum rise time (0.2806 seconds) and low settling time (0.4326 seconds).
The cold start of the space GPS receiver, i.e. the start without any information about the receiver position, satellite constellation, and time, is complicated by a large Doppler shift of a navigation signal caused by the satellite movement on the Earth orbit. That increases about five times the search space of the navigation signals compared to the standard GPS receiver. The paper investigates a method of the acceleration of the GPS receiver cold start time designed for the pico- and femto-satellites. The proposed method is based on a combination of the parallel search in Doppler frequency and PRN codes and the serial search in code phase delay. It can shorten the cold start time of the GPS receiver operating on LEO orbit from about 300 to 60 seconds while keeping the simplicity of FPGA signal processor and low power consumption. The developed algorithm was successfully implemented and tested in the piNAV GPS receiver. The energy required for the obtaining of the position fix was reduced five times from 36 on to 7.7 Joules. This improvement enables applications of such receiver for the position determination in smaller satellites like Pocket Cube or femto-satellites with a lower energy budget than the Cube Satellite.
The behavioural model of a graphene field-effect transistor (GFET) is proposed. In this approach the GFET element is treated as a “black box” with only external terminals available and without considering the physical phenomena directly. The presented circuit model was constructed to reflect steady-state characteristics taking also into account GFET capacitances. The authors’ model is defined by a relatively small number of equations which are not nested and all the parameters can be easily extracted. It was demonstrated that the proposed model allows to simulate the steady-state characteristics with the accuracy approximately as high as in the case of the physical model. The presented compact GFET model can be used for circuit or system-level simulations in the future.
In recent years, a significant development of technologies related to the control and communication of mobile robots, including Unmanned Aerial Vehicles, has been noticeable. Developing these technologies requires having the necessary hardware and software to enable prototyping and simulation of control algorithms in laboratory conditions. The article presents the Laboratory of Intelligent Mobile Robots equipped with the latest solutions. The laboratory equipment consists of four quadcopter drones (QDrone) and two wheeled robots (QBot), equipped with rich sensor sets, a ground control station with Matlab-Simulink software, OptiTRACK object tracking system, and the necessary infrastructure for communication and security. The paper presents the results of measurements from sensors of robots monitoring various quantities during work. The measurements concerned, among others, the quantities of robots registered by IMU sensors of the tested robots (i.e., accelerometers, magnetometers, gyroscopes and others).
One of the ways to improve calculations related to determining the position of a node in the IoT measurement system is to use artificial neural networks (ANN) to calculate coordinates. The method described in the article is based on the measurement of the RSSI (Received Signal Strength Indicator), which value is then processed by the neural network. Hence, the proposed system works in two stages. In the first stage, RSSI coefficient samples are taken, and then the node location is determined on an ongoing basis. Coordinates anchor nodes (i.e. sensors with fixed and previously known positions) and the matrix of RSSI coefficients are used in the learning process of the neural network. Then the RSSI matrix determined for the system in which the nodes with unknown positions are located is fed into the neural network inputs. The result of the work is a system and algorithm that allows determining the location of the object without processing data separately in nodes with low computational performance.
Power quality (PQ) monitoring is important for both the utilities and also the users of electric power. The most widespread measurement instrument used for PQ monitoring is the PQM (Power Quality Monitor) or PQA (Power Quality Analyzer). In this paper we propose the usage of PMU data for PQ parameters monitoring. We present a new methodology of PQ parameters monitoring and classification based on PMU data. The proposed methodology is tested with real measurements performed in distribution system using dedicated PMU system.
In the paper, the research on the process of optimizing the carbon footprint to obtain the low-carbon products is presented. The optimization process and limits were analyzed based on the CFOOD project co-financed by the Polish Research and Development Agency. In the article, the carbon footprint (CF) testing methods with particular emphasis on product life cycle assessment (LCA) are discussed. The main problem is that the energy received from the energy-meters per the production stage is not directly represented in the raw data set obtained from the factory because many production line machines are connected to a single measurement point. In the paper, we show that in some energy-demanding production stages connected with cooling processes the energy used for the same stage and similar production can differ even 25-40%. That is why the energy optimization in the production can be very demanding.
The paper presents the analysis of the magnetic sensor’s applicability to the energy harvesting operations. The general scheme and technical advancement of the energy extraction from the electric vehicle (such as a tram or a train) is presented. The proposed methodology of applying the magnetic sensor to the energy harvesting is provided. The experimental scheme for the sensor characteristics and measurement results is discussed. Conclusions and future prospects regarding the practical implementation of the energy harvesting system are provided.
In the paper, we demonstrate the feasibility of interdigital electrodes fabrication with the usage of inkjet printing technology. The emphasis was put to obtain better shape quality and lower spacing between electrodes with respect to typical printing process. The paper presents an analysis of the main factors that have an influence on the dimension and quality of printed structures and proposes two methods that allow eliminating the main problems. The first proposed method is based on controlling the time between patterning of successive drops. While the second method is based on changing the design methods considering printing orientation. Both methods do not require any additional technological processes or the use of any special surface preparation methods. Finally, the obtained results and conclusions were presented and discussed.
The aim of the study was to find out the experiences of academics working at The Maria Grzegorzewska University, related to crisis remote education (remote teaching and distance learning in conditions of forced social isolation caused by SARSCoV- 2 pandemic). A case study was used. The research was limited to one institution and the method of a diagnostic survey based on the questionnaire technique was used. Recommendations for further development were made, based on disclosed advantages, disadvantages, problems and opportunities connected with crisis remote education conclusions reported by academic teachers.
The aim of the study was to find out the experiences of students of The Maria Grzegorzewska University, related to crisis remote education (remote teaching and distance learning in conditions of forced social isolation caused by SARS-CoV-2 pandemic). A case study was used. The research was limited to one institution and the method of a diagnostic survey based on the questionnaire technique was used. Recommendations for further development were made, based on disclosed advantages, disadvantages, problems and opportunities connected with crisis remote education conclusions reported by students.
The process of designing and creating an integrated distributed information system for storing digitized works of scientists of research institutes of the Almaty academic city is analyzed. The requirements for the storage of digital objects are defined; a comparative analysis of the open source software used for these purposes is carried out. The system fully provides the necessary computing resources for ongoing research and educational processes, simplifying the prospect of its further development, and allows to build an advanced IT infrastructure for managing intellectual capital, an electronic library that is intended to store all books and scientific works of the Kazakhstan Engineering Technological University and research institutes of the Almaty academic city.
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