Insider threats that occur within organizations cause more serious damage than external threats. However, there are many factors that are difficult to determine, such as the definition, classification, and severity of security breaches; hence, it is necessary to analyze system logs and user behavior-based scenarios within organizations. The reality is that qualitative judgment criteria are different for everyone to apply, and there is no detailed verification procedure to compare them objectively. In this study, realistic insider threats were examined through the definition, classification, and correlation/association analysis of various human–machine logs of acts associated with security breaches that occur in an organization. In addition, a quantitative process and decision-making tool were developed for insider threats by establishing various internal information leakage scenarios. As a result, insider threats were assessed quantitatively and a decision-making process was completed that enabled case analysis based on several insider threat scenarios. This study will enable precise modeling of insider threats that occur in real organizations and will support an objective process and a decision-making system to establish a range of required information for security protection measures. Full article

Millimeter-wave wireless networks of the new fifth generation (5G) have become a primary focus in the development of the information and telecommunication industries. It is expected that 5G wireless networks will increase the data rates and reduce network latencies by an order of magnitude, which will create new telecommunication services for all sectors of the economy. New electronic components such as 28 GHz (27.5 to 28.35 GHz) single-chip transmit radio frequency (RF) front-end monolithic microwave integrated circuits (MMICs) will be required for the performance and power consumption of millimeter-wave (mm-wave) 5G communication systems. This component includes a 6-bit digital phase shifter, a driver amplifier and a power amplifier. The output power P3dB and power-added efficiency (PAE) are 29 dBm and 19.2% at 28 GHz. The phase shifter root-mean-square (RMS) phase and gain errors are 3° and 0.6 dB at 28 GHz. The chip dimensions are 4.35 × 4.40 mm. Full article

For the first time, the paper considers in a unified work the possibility of the appearance of additional pulses in various structures based on modal filtration technology, which is used to improve protection against ultrashort pulses (USP). We analyzed meander lines (ML) with broad-side coupling, structures with modal reservation (MR), reflection symmetric MLs, and modal filters (MF) with a passive conductor in the reference plane cutout and obtained the following results. It was found that the main reason for the additional pulses to appear in these structures is the introduction of asymmetry (of the cross-section, boundary conditions, and excitation). It is theoretically and experimentally established that additional pulses are a new resource for increasing the efficiency of protective devices with modal decomposition, but the highest effectiveness could be achieved through careful optimization. Full article

One of the key performance requirements for different control systems is non-overshooting step response, so that the controllable value should not overcome the reference value within a transient process. The problem of providing a non-overshooting step response was examined in this paper. Despite much scientific research being dedicated to the overshoot elimination problem, there are little to no results regarding parametric uncertainty for the discussed problem. Consideration of parametric uncertainty, particularly in the form of interval-given parameters, is essential, since in many physical processes, electronic devices and control systems parameter values can be obtained with acceptable error, and they can vary under different conditions. The main result of our research is the development of a proportional-integral-derivative (PID)-controller tuning approach for systems with interval-given parameters that provides a non-overshooting step response for such classes of control systems. This paper investigates analytical conditions and constraints for linear time invariant (LTI) systems in order to have no overshoot, enhances them with respect to parametric uncertainty, and formulates rules for tuning choices of parameters. Full article

The authors investigated the changes in diffuse reflectance spectra (ρ_λ) within 0.32–2.1 μm and integral absorption coefficient (a_s) of solar irradiation for a zinc oxide powder-based coating. The latter was consequently irradiated with protons (E = 3 keV, F ≤ 1 × 10¹⁶ cm⁻²), solar spectrum quanta (5 eq. of solar irradiation, 1 h), electrons (E = 30 keV, F = 1 × 10¹⁶ cm⁻²), and—repetitively—solar spectrum quanta (5 eq. of solar irradiation, 1 h). Following the irradiation procedure, the decrease in absorption coefficient varied from 0.044 to 0.036 and from 0.062 to 0.04, respectively. Additionally, it was shown that the solar spectrum quanta did not significantly affect the coating pre-irradiated with protons or electrons and did not change the value of induced absorption in the visible region (the latter being caused by the absorption of intrinsic point defects of the zinc oxide crystal lattice). The absorption coefficient degradation decreased under solar spectrum quanta irradiation, which was determined by the decrease in the concentration of free electrons that absorbed in the near-infrared (near-IR) region. ρ_λ spectra were measured in high vacuum in situ. A post-irradiation transfer of a coating into the atmosphere leads not only to the complete recovery of its reflectance, but also to partial translucence in comparison with the non-irradiated state. Full article

As an emerging technique of wireless communication, visible light communication is experiencing a boom in the global communications field, and the dream of accessing the Internet with light is fast becoming a reality. Multiple input multiple output, which is a key technique in radio frequency communication, can multiply channel capacity. However, it suffers the trouble of too large channel correlation when directly applied to visible light communication. The aims of this paper were to investigate spatial modulation and cooperative communication, then put forward a cooperative strategy based on space–time labeling diversity for indoor visible light communication systems to achieve high reliability. This scheme was conceived in two steps: (1) a cooperative indoor visible light communication system with a source luminaire, a relay luminaire, and a destination receiver was set up by employing the idea of cooperative transmission. Relative to the destination receiver, these two luminaires can be symmetric or asymmetric in geographical distribution. (2) Space–time labeling diversity of the constellations at the source luminaire was re-adjusted at the relay luminaire to enlarge the product of the distance of corresponding points on both constellations and was introduced on the basis of spatial modulation. Furthermore, total bit error ratio of the proposed cooperative indoor visible light communication system was derived. This scheme was implemented through Monte Carlo simulation. Evaluations of performance demonstrated the superiority of the cooperative strategy based on space–time labeling diversity over conventional optical transmission schemes. The presented approach in this paper could be of some value and interest to those who are working on visible light communication devices. Full article

Due to the serious impact of falls on the quality of life of the elderly and on the economical sustainability of health systems, the study of new monitoring systems capable of automatically alerting about falls has gained much research interest during the last decade. In the field of Human Activity Recognition, Fall Detection Systems (FDSs) can be contemplated as pattern recognition architectures able to discriminate falls from ordinary Activities of Daily Living (ADLs). In this regard, the combined application of cellular communications and wearable devices that integrate inertial sensors offers a cost-efficient solution to track the user mobility almost ubiquitously. Inertial Measurement Units (IMUs) typically utilized for these architectures, embed an accelerometer and a gyroscope. This paper investigates if the use of the angular velocity (captured by the gyroscope) as an input feature of the movement classifier introduces any benefit with respect to the most common case in which the classification decision is uniquely based on the accelerometry signals. For this purpose, the work assesses the performance of a deep learning architecture (a convolutional neural network) which is optimized to differentiate falls from ADLs as a function of the raw data measured by the two inertial sensors (gyroscope and accelerometer). The system is evaluated against on a well-known public dataset with a high number of mobility traces (falls and ADL) measured from the movements of a wide group of experimental users. Full article

A coherent optical (CO) orthogonal frequency division multiplexing (OFDM) scheme gives a scalable and flexible solution for increasing the transmission rate, being extremely robust to chromatic dispersion as well as polarization mode dispersion. Nevertheless, as any coherent-detection OFDM system, the overall system performance is limited by laser phase noises. On the other hand, extreme learning machines (ELMs) have gained a lot of attention from the machine learning community owing to good generalization performance, negligible learning speed, and minimum human intervention. In this manuscript, a phase-error mitigation method based on the single-hidden layer feedforward network prone to the improved ELM algorithm for CO-OFDM systems is introduced for the first time. In the training step, two steps are distinguished. Firstly, pilots are used, which is very common in OFDM-based systems, to diminish laser phase noises as well as to correct frequency-selective impairments and, therefore, the bandwidth efficiency can be maximized. Secondly, the regularization parameter is included in the ELM to balance the empirical and structural risks, namely to minimize the root mean square error in the test stage and, consequently, the bit error rate (BER) metric. The operational principle of the real-complex (RC) ELM is analytically explained, and then, its sub-parameters (number of hidden neurons, regularization parameter, and activation function) are numerically found in order to enhance the system performance. For binary and quadrature phase-shift keying modulations, the RC-ELM outperforms the benchmark pilot-assisted equalizer as well as the fully-real ELM, and almost matches the common phase error (CPE) compensation and the ELM defined in the complex domain (C-ELM) in terms of the BER over an additive white Gaussian noise channel and different laser oscillators. However, both techniques are characterized by the following disadvantages: the CPE compensator reduces the transmission rate since an additional preamble is mandatory for channel estimation purposes, while the C-ELM requires a bounded and differentiable activation function in the complex domain and can not follow semi-supervised training. In the same context, the novel ELM algorithm can not compete with the CPE compensator and C-ELM for the 16-ary quadrature amplitude modulation. On the other hand, the novel ELM exposes a negligible computational cost with respect to the C-ELM and PAE methods. Full article

Solid-state drive (SSD) with flash memory as the storage medium are being widely used in various data storage systems. SSD data compression means that data is compressed before it is written to Not-And (NAND) Flash. Data compression can reduce the amount of data written in NAND Flash and improve the performance and reliability of SSDs. At present, the main problem facing data compression of SSD is how to improve the efficiency of data compression and decompression. In order to improve the performance of data compression and decompression, this study proposes a method of SSD data deduplication based on zone division. First, this study divides the storage space of the SSD into zones and divides them into one hot zone and multiple cold zones according to the different erasing frequency. Second, the data in each zone is divided into hot data and cold data according to the number of erasures. At the same time, the address mapping table in the hot zone is loaded into the cache. Finally, when there is a write or read request, the SSD will selectively compress or decompress the data according to the type of different zones. Through simulation tests, the correctness and effectiveness of this study are verified. The research results show that the data compression rate of this research result can reach 70–95%. Compared with SSD without data compression, write amplification is reduced by 5 to 30%, and write latency is reduced by 5 to 25%. The research results have certain reference value for improving the performance and reliability of SSD. Full article

Symmetries play very important roles in the dynamics of electrical systems. The relevant electronic circuits with fault diagnostics, including the optimized neural network algorithm model, are designed on the basis of symmetry principles. In order to improve the efficiency of the circuit pressure test, a circuit pressure function equivalent compression test method based on the parallel neural network algorithm is proposed. For the implementation stage of the circuit pressure test, the improved modified node algorithm (MNA) is used to build an optimization model, and the circuit network is converted into an ordinary differential equation for the circuit pressure function equivalent compression test. The test aims to minimize flux. Then, backpropagation (BP) neural network algorithm data fusion is introduced to optimize the minimum flux model of the cyclic pressure functional equivalent compression test. Finally, a simulation experiment is carried out to verify the effectiveness of the algorithm in the accuracy and efficiency of the pressure test. The results show that the improved BP neural network improves the data fusion accuracy and shortens the sample training time; compared with the uncompressed algorithm, the running time of the proposed algorithm is greatly reduced and the execution efficiency is high; compared with the vascular pressure test method, there is no significant difference in the convergence accuracy and it is at a level of 10⁻⁵. Since the parallel computing problem is not considered in either of the two-pulse tube pressure test methods, the convergence time of the algorithm increases exponentially with the increase in the number of parallel threads. However, the algorithm in this research considers the problem of parallel execution and uses a quad-core processor, with no significant change in computing time and high computing efficiency. Therefore, BP neural network data fusion can be used for the fault diagnosis of electronic circuits, with a high operating efficiency and good development prospects. Full article

The design and development of a compact square-wave pulse generator for the electroporation of biological cells is presented. This electroporator can generate square-wave pulses with durations from 3 μs up to 10 ms, voltage amplitudes up to 3500 V, and currents up to 250 A. The quantity of the accumulated energy is optimized by means of a variable capacitor bank. The pulse forming unit design uses a crowbar circuit, which gives better control of the pulse form and its duration, independent of the load impedance. In such cases, the square-wave pulse form ensures better control of electroporation efficiency by choosing parameters determined in advance. The device has an integrated graphic LCD screen and measurement modules for the visualization of the current pulse, allowing for express control of the electroporation quality and does not require an external oscilloscope for current pulse recording. This electroporator was tested on suspensions of Saccharomyces cerevisiae yeast cells, during which, it was demonstrated that the application of such square-wave pulses ensured better control of the electroporation efficiency and cell viability after treatment using the pulsed electric field (PEF). Full article

Fifth-generation (5G) communications system is commercially introduced by several mobile operators where sub-6 GHz bands are the backbone of the 5G networks. A large-scale multiple-input multiple-output (MIMO), or massive MIMO (mMIMO), technology has a major impact to secure high data rate, high spectral efficiency, and quality of service (QoS). It could also have a major role in the beyond-5G systems. A massive number of antennas seek advanced signal processing to detect and equalize the signal. However, optimal detectors, such as the maximum likelihood (ML) and maximum posterior (MAP), are not desirable in implementation due to extremely high complexity. Therefore, sub-optimum solutions have been introduced to obtain and guarantee enough balance between the performance and the computational complexity. In this paper, a robust and joint low complexity detection algorithm is proposed based on the Jacobi (JA) and Gauss–Seidel (GS) methods. In such iterative methods, the performance, complexity, and convergence rate are highly dependent on the initial vector. In this paper, initial solution is proposed by exploiting the benefits of a stair matrix to obtain a fast convergence rate, high performance, and low complexity. Numerical results show that proposed algorithm achieves high accuracy and relieve the computational complexity even when the BS-to-user-antenna ratio (BUAR) is small. Full article

The roaming service enables a remote user to get desired services, while roaming in a foreign network through the help of his home network. The authentication is a pre-requisite for secure communication between a foreign network and the roaming user, which enables the user to share a secret key with foreign network for subsequent private communication of data. Sharing a secret key is a tedious task due to underneath open and insecure channel. Recently, a number of such schemes have been proposed to provide authentication between roaming user and the foreign networks. Very recently, Lu et al. claimed that the seminal Gopi-Hwang scheme fails to resist a session-specific temporary information leakage attack. Lu et al. then proposed an improved scheme based on Elliptic Curve Cryptography (ECC) for roaming user. However, contrary to their claim, the paper provides an in-depth cryptanalysis of Lu et al.’s scheme to show the weaknesses of their scheme against Stolen Verifier and Traceability attacks. Moreover, the analysis also affirms that the scheme of Lu et al. entails incorrect login and authentication phases and is prone to scalability issues. An improved scheme is then proposed. The scheme not only overcomes the weaknesses Lu et al.’s scheme but also incurs low computation time. The security of the scheme is analyzed through formal and informal methods; moreover, the automated tool ProVerif also verifies the security features claimed by the proposed scheme. Full article

In massive multiple-input multiple-output (M-MIMO) systems, a detector based on maximum likelihood (ML) algorithm attains optimum performance, but it exhaustively searches all possible solutions, hence, it has a very high complexity and realization is denied. Linear detectors are an alternative solution because of low complexity and simplicity in implementation. Unfortunately, they culminate in a matrix inversion that increases the computational complexity in high loaded systems. Therefore, several iterative methods have been proposed to approximate or avoid the matrix inversion, such as the Neuamnn series (NS), Newton iterations (NI), successive overrelaxation (SOR), Gauss–Siedel (GS), Jacobi (JA), and Richardson (RI) methods. However, a detector based on iterative methods requires a pre-processing and initialization where good initialization impresses the convergence, the performance, and the complexity. Most of the existing iterative linear detectors are using a diagonal matrix ( $\mathbf{D}$ ) in initialization because the equalization matrix is almost diagonal. This paper studies the impact of utilizing a stair matrix ( $\mathbf{S}$ ) instead of $\mathbf{D}$ in initializing the linear M-MIMO uplink (UL) detector. A comparison between iterative linear M-MIMO UL detectors with $\mathbf{D}$ and $\mathbf{S}$ is presented in performance and computational complexity. Numerical Results show that utilization of $\mathbf{S}$ achieves the target performance within few iterations, and, hence, the computational complexity is reduced. A detector based on the GS and $\mathbf{S}$ achieved a satisfactory bit-error-rate (BER) with the lowest complexity. Full article

Nowadays, eyeglassesare used for vision correction as well as in the fashion industry. Eyeglasses have become more expensive and the eyewear industry has grown rapidly, thereby requiring the development of advanced coating technologies. However, defect detection by visual inspection in the manufacturing process of eyeglass coatings is difficult. To solve this problem, we propose the coated eyeglass defect detection system framework based on machine vision for real-time inspection. First, we locate and extract regions of interest (ROI) ofthe coated eyeglass by adopting cross-projection based on symmetrizedenergy analysis. Next, we propose an efficient method based on the symmetrized energy analysis of color channelsto enhance defectsin each color channel of the ROI of the coated eyeglass. Then, we adoptsymmetrized cross-projection energy analysis for locating defective areas inside the ROI of the coated eyeglass. Finally, we compare the defect detection resultsfor the coated eyeglass with the standard manufacturingquality. An experiment is conducted using real data collected froma Taiwanese eyeglass factory to validate the performance of the proposed framework. This framework achieves a 100% defect detection rate, demonstrating that it is valid and useful for inspecting coated eyeglasses in industries. Full article

This article highlights the issue of identifying information security threats to computer networks. The aim of the study is to increase the number of identified threats. Firstly, it was carried out the analysis of computer network models used to identify threats, as well as in approaches to building computer network threat models. The shortcomings that need to be corrected are highlighted. On the basis of the mathematical apparatus of attributive metagraphs, a computer network model is developed that allows to describe the software components of computer networks and all possible connections between them. On the basis of elementary operations on metagraphs, a model of threats to the security of computer network software is developed, which allows compiling lists of threats to the integrity and confidentiality of computer network software. These lists include more threats in comparison with the considered analogues. Full article

The investigation of size effects appearing in the dependence of AlGaN/GaN HEMT high-frequency characteristics on channel width d and number of sections n is conducted using the notions of measure, metric and normed functional (linear) spaces. In accordance with the results obtained, in local approximation the phenomenon of similarity can exist, not only in metric spaces of heteroepitaxial structures, but also in the defined on them functional spaces of the measures of these structures’ additive electrophysical characteristics. This provides means to associate size effects of the HEMTs with their structure material fractal geometry. The approach proposed in the work gives an opportunity, not only to predict the size of the structural elements (e.g., channel width and number of sections) of the transistor with the desired characteristics, but also to reconstruct its compact model parameters, which significantly speeds up the development and optimization of the HEMTs with the desired device characteristics. At transferring to the global approximation, when the topological and fractal dimensions of the structure coincide, its electrophysical characteristics, and subsequently, the values of the compact model equivalent circuit parameters, as well as HEMT high frequency characteristics, follow the classic (linear) laws peculiar to the spaces of integer topological dimensions D_T. Full article

The presence of imbalance in data significantly complicates the classification task, including fuzzy systems. Due to a large number of instances of bigger classes, instances of smaller classes are not recognized correctly. Therefore, additional tools for improving the quality of classification are required. The most common methods for handling imbalanced data have several disadvantages. For example, methods for generating additional instances of minority classes can worsen classification if there is a strong overlap of instances from different classes. Methods that directly modify the fuzzy classification algorithm lead to a decline in the interpretability of the model. In this paper, we study the efficiency of the gravitational search algorithm in the tasks of selecting the features and tuning the term parameters for fuzzy classifiers of imbalanced data. We consider only data with two classes and apply the algorithm based on extreme values of classes to construct models with a minimum number of rules. In addition, we propose a new quality metric based on the sum of the overall accuracy and the geometric mean with the presence of a priority coefficient between them. Full article

The design, simulation and experimental results of the integrated optical and electronic components for 25 Gb/s microwave photonic link based on a 0.25 µm SiGe:C BiCMOS technology process are presented. A symmetrical depletion-type Mach-Zehnder modulator (MZM) and driver amplifier are intended for electro-optical (E/O) integrated transmitters. The optical divider and combiner of MZM are designed based on the self-imaging theory and then simulated with EM software. In order to verify the correctness of the theory and material properties used in the simulation, a short test (prototype) MZM of 1.9 mm length is produced and measured. It shows an extinction ratio of 19 dB and half-wave voltage-length product of V_{π ∙} L = ~1.5 V·cm. Based on these results, the construction of the segmented modulator with several driver amplifier units is defined. The designed driver amplifier unit provides a bandwidth of more than 30 GHz, saturated output power of 6 dBm (output voltage of V_pp = 1.26 V), and matching better than −15 dB up to 35 GHz; it dissipates 170 mW of power and occupies an area of 0.4 × 0.38 mm². The optical-electrical (O/E) receiver consists of a Ge-photodiode, transimpedance amplifier (TIA), and passive optical structures that are integrated on a single chip. The measured O/E 3 dB analog bandwidth of the integrated receiver is 22 GHz, and output matching is better than −15 dB up to 30 GHz, which makes the receiver suitable for 25 Gb/s links with intensity modulation. The receiver operates at 1.55 μm wavelength, uses 2.5 V and 3.3 V power supplies, dissipates 160 mW of power, and occupies an area of 1.46 × 0.85 mm². Full article

This paper discusses an approach for assessing the quality of speech while undergoing speech rehabilitation. One of the main reasons for speech quality decrease during the surgical treatment of vocal tract diseases is the loss of the vocal tractˈs parts and the disruption of its symmetry. In particular, one of the most common oncological diseases of the oral cavity is cancer of the tongue. During surgical treatment, a glossectomy is performed, which leads to the need for speech rehabilitation to eliminate the occurring speech defects, leading to a decrease in speech intelligibility. In this paper, we present an automated approach for conducting the speech quality evaluation. The approach relies on a convolutional neural network (CNN). The main idea of the approach is to train an individual neural network for a patient before having an operation to recognize typical sounding of phonemes for their speech. The neural network will thereby be able to evaluate the similarity between the patientˈs speech before and after the surgery. The recognition based on the full phoneme set and the recognition by groups of phonemes were considered. The correspondence of assessments obtained through the autorecognition approach with those from the human-based approach is shown. The automated approach is principally applicable to defining boundaries between phonemes. The paper shows that iterative training of the neural network and continuous updating of the training dataset gradually improve the ability of the CNN to define boundaries between different phonemes. Full article

Wireless networks employing millimeter-wave (mmWave) and Massive Multiple-Input Multiple-Output (MIMO) technologies are a key approach to boost network capacity, coverage, and quality of service (QoS) for future communications. They deploy symmetric antennas on a large scale in order to enhance the system throughput and data rate. However, increasing the number of antennas and Radio Frequency (RF) chains results in high computational complexity and more energy requirements. Therefore, to solve these problems, this paper proposes a low-complexity hybrid beamforming scheme for mmWave Massive-MIMO 5G wireless networks. The proposed algorithm is on the basis of alternating the minimum mean square error (Alt-MMSE) hybrid beamforming technique in which the orthogonal properties of the digital matrix were designed, and then the MSE of the transmitted and received signal was reduced. The phase of the analog matrix was obtained from the updated digital matrix. Simulation results showed that the proposed hybrid beamforming algorithm had better performance than existing state-of-the-art algorithms, and similar performance with the optimal digital precoding algorithm. Full article

This paper concerns several important topics of the Symmetry journal, namely, pattern recognition, computer-aided design, diversity and similarity. We also take advantage of the symmetric structure of a membership function. Searching for the (sub) optimal subset of features is an NP-hard problem. In this paper, a binary swallow swarm optimization (BSSO) algorithm for feature selection is proposed. To solve the classification problem, we use a fuzzy rule-based classifier. To evaluate the feature selection performance of our method, BSSO is compared to induction without feature selection and some similar algorithms on well-known benchmark datasets. Experimental results show the promising behavior of the proposed method in the optimal selection of features. Full article

In recent years, compression steganography technology has attracted the attention of many scholars. Among all image compression method, absolute moment block truncation coding (AMBTC) is a simple and effective compression method. Most AMBTC-based reversible data hiding (RDH) schemes do not guarantee that the stego AMBTC compression codes can be translated by the conventional AMBTC decoder. In other words, they do not belong to Type I AMBTC-based RDH scheme and easily attract malicious users’ attention. To solve this problem and enhance the hiding capacity, we used (7,4) hamming code to design a Type I AMBTC-based RDH scheme in this paper. To provide the reversibility feature, we designed a prediction method and judgement mechanism to successfully select the embeddable blocks during the data embedding phase and data extraction and recovery phase. In comparing our approach with other BTC-based schemes, it is confirmed that our hiding capacity is increased while maintaining the limited size of the compression codes and acceptable image quality of the stego AMBTC-compressed images. Full article

Food safety event detection is a technique used to discover food safety events by monitoring online news. In general, a set of keywords are extracted as features to represent news, and then the news is clustered to generate events. The most popular method for news feature extraction is Term Frequency-Inverse Document Frequency (TF-IDF), however, it has some defects such as being prone to the “dimension disaster”, low computational efficiency, and a lack of semantic information. In addition, Latent Dirichlet Allocation (LDA) is also widely used in news representation. Despite its low dimension, it still suffers from some drawbacks such as the need to set a predefined number of clusters and has difficulty recognizing new events. In this paper, a method based on multi-feature fusion is proposed, which combines the TF-IDF features, the named entity features, and the headline features to represent the news. Based on the representations, the incremental clustering method is used to cluster the news documents and to detect food safety events. Compared with the traditional methods, the proposed method achieved higher Precision, Recall, and F1 scores. The proposed method can help regulatory authorities to make decisions and improve the reputation of the government, whilst reducing social anxiety and economic losses. Full article

This study highlights the importance of detecting and localizing useful and interference signal extreme points in multiconductor transmission lines (MCTL) by developing a new approach for detecting and localizing signal extreme points in MCTL networks of arbitrary complexity. A radio-electronic component is presented as a network consisting of a number of connected MCTL sections. Each MCTL section is divided into segments and the number of segments is set by the user. The approach is based on a quasi-static calculation of signal waveforms at any point (segment) along each conductor of an MCTL. The block diagrams of the developed algorithms are presented. Using the approach, a number of investigations have been done which include the following: the signal maximum detection and localization in the meander lines with one and two turns, the influence of ultrashort pulse duration on localization of its extreme points in the printed circuit board (PCB) bus of a spacecraft autonomous navigation system, the influence of ultrashort pulse duration on localization of crosstalk extreme points in the PCB bus, and the simulation of electrostatic discharge effects on the PCB bus. There are also some investigations with optimization methods presented. A genetic algorithm (GA) was used to optimize the influence of ultrashort pulse duration on localization of the pulse and crosstalk extreme points in the PCB bus. Furthermore, the GA was used to optimize the PCB bus loads by criteria of the peak voltage minimization. A similar investigation was carried out with the evolution strategy. The obtained results help us to argue that the signal extreme points can be detected both in structures with different configurations and applying different excitations. Full article

Statistical analysis of the results of minisodar measurements of vertical profiles of wind velocity components in a 5–200 m layer of the atmosphere shows that this problem belongs to the class of robust nonparametric problems of mathematical statistics. In this work, a new consecutive nonparametric method of adaptive pendular truncation is suggested for outlier detection and selection in sodar data. The method is implemented in a censoring algorithm. The efficiency of the suggested algorithm is tested in numerical experiments. The algorithm has been used to calculate statistical characteristics of wind velocity components, including vertical profiles of the first four moments, the correlation coefficient, and the autocorrelation and structure functions of wind velocity components. The results obtained are compared with classical sample estimates. Full article

Many works have been conducted relevant to rainfall measurements, while the first relevant ones were based on the power loss estimation function from wireless links located back to the early 1940s. It is notable, though, that this innovative idea conduced to many theoretical models correlating the signal attenuation to the rainfall intensity. This type of parameter strongly contributes to the mechanism of frequency attenuation above 10 GHz. Consequently, in the last twenty years, there has been a significant boost to this research topic. Researchers all around the world have worked thoroughly on the issue of estimating rain with the use of earth-to-earth microwave signal attenuation. Nevertheless, the issue remains intriguing and challenging. This paper presents a literature survey, of the last decade, on this challenging issue focusing on measurements from backhaul cellular microwave links and experimental setups. Research challenges and future trends are also presented. Full article

Power-consuming entities such as high performance computing (HPC) sites and large data centers are growing with the advance in information technology. In business, HPC is used to enhance the product delivery time, reduce the production cost, and decrease the time it takes to develop a new product. Today’s high level of computing power from supercomputers comes at the expense of consuming large amounts of electric power. It is necessary to consider reducing the energy required by the computing systems and the resources needed to operate these computing systems to minimize the energy utilized by HPC entities. The database could improve system energy efficiency by sampling all the components’ power consumption at regular intervals and the information contained in a database. The information stored in the database will serve as input data for energy-efficiency optimization. More so, device workload information and different usage metrics are stored in the database. There has been strong momentum in the area of artificial intelligence (AI) as a tool for optimizing and processing automation by leveraging on already existing information. This paper discusses ideas for improving energy efficiency for HPC using AI. Full article

The standardization activities of the fifth generation communications are clearly over and deployment has commenced globally. To sustain the competitive edge of wireless networks, industrial and academia synergy have begun to conceptualize the next generation of wireless communication systems (namely, sixth generation, (6G)) aimed at laying the foundation for the stratification of the communication needs of the 2030s. In support of this vision, this study highlights the most promising lines of research from the recent literature in common directions for the 6G project. Its core contribution involves exploring the critical issues and key potential features of 6G communications, including: (i) vision and key features; (ii) challenges and potential solutions; and (iii) research activities. These controversial research topics were profoundly examined in relation to the motivation of their various sub-domains to achieve a precise, concrete, and concise conclusion. Thus, this article will contribute significantly to opening new horizons for future research directions. Full article