Search

Badarneh and da Costa (IEEE Wirel Commun Lett, 2024. https://doi.org/10.1109/LWC.2024.3353620) introduced the fluctuating fading distribution by taking the signal envelope to be the ratio of two independent random variables, one having the Nakagami m distribution and the other a uniform random variable. The Nakagami m distribution corresponds to signals following the normal distribution which may not always hold in practice. In this paper, we derive twenty other fluctuating fading distributions. For each distribution, we give explicit expressions for the average channel capacity and the average bit error rate. Their correctness is checked numerically. [ABSTRACT FROM AUTHOR]

In many areas, such as speech processing, communication, and measurement systems, where the actual signal is not directly available, Wiener deconvolution is a widely used signal restoration technique. The accuracy of the estimated signal in Wiener deconvolution is determined by the unknown filter parameter. To compute this unknown parameter, complex and time-consuming numerical as well as iterative computation approaches were proposed in the literature, which also often compute an unoptimized unknown filter parameter. To address the computational problem and estimate a more accurate unknown filter parameter, the authors reported an analytical solution in a prior work for a given signal to noise ratio. However, it was revealed that the actual optimum parameter value also varies with noise also. In this paper, the authors propose a new analytical solution for optimum parameter estimation that includes noise as well. The authors compared the modified analytical solution to existing numerical computation methods for different values of Signal to Noise Ratio and demonstrated that the proposed methods' optimum parameter estimation is always close to the actual optimum value, which resulted in more accurate signal deconvolution. Proposed mathematical solutions are also verified with experimental signals, acquired in a laboratory. [ABSTRACT FROM AUTHOR]

This study aims to investigate, using patient studies, the impact of Injected Dose (ID), Body Mass Index (BMI), and image noise assessments in PET imaging. This study included 59 liver cancer patients weighing between 45 and 107 kg. After intravenously injecting 0.1 millicurie (mCi) of 18F-FDG per kilogram of body weight, PET scans were obtained for 1, 1.5, and 3 min/bed position based on the patient's weight. Weight, height, and body mass index were calculated using a spreadsheet. Five regions of interest (ROIs) were placed at the same site in the liver, which was considered to have a homogeneous metabolism, in five successive slices of PET/CT scans to determine the mean uptake (signal) values and their standard deviation (noise). The ratio of both gives the liver's Signal-to-Noise Ratio (SNR). Graphs were created to determine the relationship between these characteristics. The plots demonstrated that the dose injected increased when body weight and/or BMI increased, and that the SNR fell even as the dose administered increased. This is owing to the fact that heavier patients having a higher administered dose and, have a lower SNR even when greater 18F-FDG doses are delivered. These data indicate that the image quality, as measured by the SNR, is inferior in heavier persons compared to those who are thinner. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to investigate whether ABO and Rhesus (Rh) blood type systems are associated with distortion product otoacoustic emission (DPOAE) and transient otoacoustic emission (TEOAE) amplitudes, with the hypothesis that blood types affect hearing thresholds. Methods: Seventy participants with normal hearing, aged 18-26 years, with normal tympanometry and otoscopic examination findings, were included in the study. TEOAE and DPOAE tests were conducted on all participants. Results: The Rh factor did not significantly affect the OAE results. It was found that the TEOAE amplitudes of blood type B at 1.4 kHz in the left ear were higher than those of blood types A and AB. The amplitude of AB blood was lower than that of O, A, and B blood types at 2 kHz. Conclusion: Our study results did not indicate a consistent pattern for a specific blood type, in contrast to previous findings. Additional research is required to investigate the potential correlation between hearing function and ABO and Rh blood types. [ABSTRACT FROM AUTHOR]

Background: The digit in the noise test is a simple hearing screening tool that can identify hearing loss at the early stage. This screening tool takes less time than traditional pure-tone audiometry. There is a scarcity of hearing health professionals with few resources for carrying out hearing screening on a large scale in India. Hence, a hearing screening tool for the Hindi-speaking population is needed. Aim and Objective: The study aimed to develop and validate the Digit in Noise test in Hindi (DIN-H). Methods: A native Hindi female speaker recorded single digits from 1 to 9 made into triplet combinations, which were binaurally presented to 20 normal hearing subjects having hearing thresholds less than 25 dBHL from 250 to 8000 Hz in the presence of broadband speech-shaped noise. The digit triplets were homogenized using speech intelligibility function for similar difficulty levels across stimuli. The homogenized stimuli were evaluated by obtaining the Speech Recognition Threshold (SRT) of 20 normal hearing subjects. Results: The Mean SRT was − 10.4 and − 11.3 dB before and after homogenization. A strong positive correlation existed between test and retest SRTs (0.78). Mean SRT and slope obtained before and after optimization were comparable to other languages like Korean and English. This test can act as a reliable screening tool for assessing individuals. The test was administered to 106 normal hearing participants. The 95th percentile of the SRT value obtained was − 5.6 dB, which was kept as a cut-off score for the screening test. Conclusion: DIN-H can be used as a screening tool for assessing the integrity of the auditory system on a large scale in less time for the Hindi-speaking population. [ABSTRACT FROM AUTHOR]

Spectrum is a natural resource and is utilized in various applications. The proposed method addresses the necessity of spectrum sensing and shows improvement in detection probability. The proposed hybrid sensing technique includes two different spectrum sensing techniques for detecting the unused spectrum. Based on the signal-to-noise ratio (SNR) of the received signals, the proposed hybrid sensing techniques either energy based spectrum sensing or eigenvalue-based spectrum sensing are chosen based on the SNR computation. For low SNR ranges, Eigenvalue-based spectrum sensing is used, and for high SNR energy based spectrum sensing is used to identify the unused spectrum depending on the presence or absence of the primary users (PUs). The proposed model is simulated, implemented, and tested in a cognitive radio test bed and its performance is analyzed. Under high SNR region, the proposed system shows a 93% improvement in the probability of detection while energy detection provides 88% improvement. Comparing the performance of the proposed hybrid sensing technique with Eigenvalue-based spectrum sensing, the proposed model shows an improvement of 97% probability of detection. Under low SNR region, the proposed model shows a 90% improvement in the probability of detection while energy based spectrum sensing and Eigenvalue based spectrum sensing provide 50% and 85%, respectively. [ABSTRACT FROM AUTHOR]

Due to the complex and variable nature of the atmospheric conditions, traditional multi-wavelength differential absorption lidar (DIAL) methods often suffer from significant errors when inverting ozone concentrations. As the detection range increases, there is a higher demand for Signal to Noise Ratio (SNR) in lidar signals. Based on this, the paper discusses the impact of different atmospheric factors on the accuracy of ozone concentration inversion. It also compares the advantages and disadvantages of the two-wavelength differential method and the three-wavelength dual-differential method under both noisy and noise-free conditions. Firstly, the errors caused by air molecular extinction, aerosol extinction, and backscatter terms in the inversion using the two-wavelength differential method were simulated. Secondly, the corrected inversion errors were obtained through direct correction and the introduction of a three-wavelength dual differential correction. Finally, addressing the issue of insufficient SNR in practical inversions, the inversion errors of the two correction methods were simulated by constructing lidar parameters and incorporating appropriate noise. The results indicate that the traditional two-wavelength differential algorithm is significantly affected by aerosols, making it more sensitive to aerosol concentration and structural changes. On the other hand, the three-wavelength dual differential algorithm requires a higher SNR in lidar signals. Therefore, we propose a novel strategy for inverting atmospheric ozone concentration, which prioritizes the use of the three-wavelength dual-differential method in regions with high SNR and high aerosol concentration. Conversely, the direct correction method utilizing the two-wavelength differential approach is used. This approach holds the potential for high-precision ozone concentration profile inversion under different atmospheric conditions. [ABSTRACT FROM AUTHOR]

In the present examination it was attempted to analyse the influence of jatropha methyl ester along with butanol and operating parameters of a three-cylinder automotive passenger car common rail direct injection (CRDI) engine on its performance and emission features. Design of experiments methodology was adopted to design the experiments for the present work. NOx, smoke and brake thermal efficiency were the responses and torque, speed, percentage biodiesel in the diesel/biodiesel blend and percentage of higher alcohol blend were the factors for the work. Percentage influence of each factor on the responses and the optimum combination levels of factors was obtained through Taguchi parametric design. From the analysis it was observed that among the torque and speed, the influence of torque is more in the performance and emission features of the tested engine. Also, addition of butanol influences the engine characteristics when compared with that of biodiesel. Among the operating and fuel parameters tested, operating parameters of the engine show their dominant role in lowering the NOx and smoke emission with better BTE with a percentage contribution of 76 when compared to the fuel parameters contribution of 24% [ABSTRACT FROM AUTHOR]

This research paper conducts a thorough comparison of four prominent transmission technologies suitable for mobile robots operating in challenging environments. Emphasizing key factors such as signal strength, noise resistance, and data transfer efficiency, the study aims to identify the optimal communication solution in hostile conditions. The exploration delves into the intricacies of received signal strength indication (RSSI) and signal-tonoise ratio (SNR), revealing distinctive traits and trade-offs among the technologies. Navigating through the complexities of frequency bands, modulation types, and communication topologies, the paper examines the impact of obstacles, energy consumption dynamics, and potential real-world applications. Beyond contributing to the fields of robotics and communication, the study offers practical insights for stakeholders seeking resilient and efficient transmission methods for mobile robotic applications. Advocating for long range (LoRa) as the preferred transmission technology in hostile environments, the paper highlights its unmatched immunity to noise, stability, and minimal energy consumption. These findings provide valuable guidance for technology choices in collaborative mobile robot operations under challenging conditions. This research sets the stage for future developments in robotic communication, underscoring the crucial role of selecting the right transmission means for mission-critical applications in hostile environments. [ABSTRACT FROM AUTHOR]

In conventional magnetic flux leakage (MFL) detection research, the surface of the workpiece is usually assumed to be smooth. However, the actual roughness will have an impact on the detection. To solve the problem of crack detection on rough surfaces, a method using ferromagnetic lift-off media instead of air lift-off was proposed. Firstly, the smooth surface and the rough surface model were established, and the difference of the leakage magnetic field signal was compared through the simulations. Secondly, the air lift-off media was replaced with ferromagnetic lift-off media, and the enhancement effect of the ferromagnetic lift-off media on the SNR(signal-to-noise ratio,SNR) of the magnetic flux leakage signal of microcrack was analyzed. Then, by changing the ferromagnetic media layer thickness and permeability, the improvement of the these parameters on SNR of the magnetic leakage signal of microcracks was analyzed. Finally, it was verified by experiments that the method can improve SNR of magnetic flux leakage signal of microcrack on the rough workpiece surface to a certain extent. The SNR enhancement method provides a certain application reference for the practice of magnetic flux leakage detection of rough surface workpieces. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Geodesy & Geodynamics (1671-5942) is the property of Editorial Board Journal of Geodesy & Geodynamics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract Communication services that are dependable are crucial, particularly during emergencies when the regular infrastructure for communication may be disrupted or nonexistent. In such situations, device-to-device (D2D) communication can be a helpful choice since it allows user equipment (UE) that is close to one another to connect directly, bypassing the cellular network infrastructure. The primary focus of this thesis is the application of D2D communication in a decentralized emergency scenario with a damaged eNodeB. The main objective is to find an appropriate strategy for finding and selecting D2D couples by simulating several methods in MATLAB. This study compares three D2D pair selection algorithms: distance-based, Signal-to-Interference and Noise Ratio (SINR)-based, and data rate-based distance-based. The simulation results show that the data rate-based strategy is the most effective method for selecting D2D couples in emergency scenarios. In contrast to algorithms that rely on distance and SINR, this one reduces the chance of an outage by 20%. Bit error rate (BER), capacity, spectral efficiency, and energy efficiency are the three types of links that are assessed: direct links, relay links, and UE relay links. The results show that, with the lowest BER and maximum data throughput, the direct link is the most reliable and efficient communication option. However, the relay connection and the UE relay link show better overall spectral efficiency in comparison to the direct link, indicating their ability to transport more data per unit of bandwidth. The option that consumes the least energy among the three is the direct link. The study demonstrates the great potential of D2D communication in emergency scenarios where conventional communication infrastructure may not be available. The direct link is the most dependable and effective alternative for communication, according to the data, although the UE link can still function effectively in the event that the direct link is compromised. The data rate-based method is a useful strategy for finding and choosing D2D partners. The results of this study can direct the development of D2D emergency communication solutions in 5G networks.

ABSTRACTThis research examines screening of the factors affecting cotton-sized yarn gain strength, elongation, stretch, size pick-up, and yarn abrasion resistance. The factors considered in this research are sizing machine parameters like sizing machine speed, squeezing roller pressure, warp yarn tension of various sizing machine zones, warp yarn twist, and viscosity of the size paste. Taguchi design with Minitab software has been used to design and analyze the results of the experiments. The study revealed that viscosity, yarn twist, sizing machine speed, and wet tension affected sized yarn gain strength significantly. Viscosity has maximum contribution to gain strength (34.57%) compared to other factors and has a positive effect on the gain strength of the sized yarn. For stretch percentage and the loss elongation of sized yarn, the wet tension is the most significant factor with 50.30% and 52.13% contribution respectively. Moreover, for the size pick-up and yarn abrasion resistance of sized yarn, the speed of the sizing machine is the most effective parameter with 44.45% and 56.29% contribution, respectively. The screening experimental result revealed the most significant factor that must be further optimized using response surface methods of experimental design.

Recently, superposition coding (SC), Stanford University Interim (SUI) fading channel, user clustering, successive interference cancellation (SIC) mechanism has been incorporated into the power allocation design for attaining good performance. Nonetheless, the existing model works with cluster size up to 4 user per cluster and induce higher control channel overhead. In addressing this paper introduce an effective resource allocation (ERA) design for power domain non-orthogonal multiple access (PDNOMA) system. The ERA, first employ Zadoff Chu (ZC) coding, then power is allocated according to the distance considering 5 user per cluster. Finally, multi-level SIC is done at the receiver end. The ERA performance is studied by varying signal-to-noise ratio (SNR) in terms of bit error rate (BER) considering a maximum of five users per cluster. Further, the ERA performance in terms of BER is tested under different scenario defined in SUI propagation scenario such as higher pathloss, moderate path loss, and low path loss. The throughput performance under varied density and speed is also studied; the ERA achieves much better performance in terms of ERA, SNR and throughput than standard multi-user downlink resource allocation (MUDRA) model. [ABSTRACT FROM AUTHOR]

Communication services that are dependable are crucial, particularly during emergencies when the regular infrastructure for communication may be disrupted or nonexistent. In such situations, device-to-device (D2D) communication can be a helpful choice since it allows user equipment (UE) that is close to one another to connect directly, bypassing the cellular network infrastructure. The primary focus of this thesis is the application of D2D communication in a decentralized emergency scenario with a damaged eNodeB. The main objective is to find an appropriate strategy for finding and selecting D2D couples by simulating several methods in MATLAB. This study compares three D2D pair selection algorithms: distance-based, Signal-to-Interference and Noise Ratio (SINR)-based, and data rate-based distance-based. The simulation results show that the data rate-based strategy is the most effective method for selecting D2D couples in emergency scenarios. In contrast to algorithms that rely on distance and SINR, this one reduces the chance of an outage by 20%. Bit error rate (BER), capacity, spectral efficiency, and energy efficiency are the three types of links that are assessed: direct links, relay links, and UE relay links. The results show that, with the lowest BER and maximum data throughput, the direct link is the most reliable and efficient communication option. However, the relay connection and the UE relay link show better overall spectral efficiency in comparison to the direct link, indicating their ability to transport more data per unit of bandwidth. The option that consumes the least energy among the three is the direct link. The study demonstrates the great potential of D2D communication in emergency scenarios where conventional communication infrastructure may not be available. The direct link is the most dependable and effective alternative for communication, according to the data, although the UE link can still function effectively in the event that the direct link is compromised. The data rate-based method is a useful strategy for finding and choosing D2D partners. The results of this study can direct the development of D2D emergency communication solutions in 5G networks. [ABSTRACT FROM AUTHOR]

Purpose: The extraction of information from images provided by medical imaging systems may be employed to obtain the specific objectives in the various fields. The quantity of signal to noise ratio (SNR) plays a crucial role in displaying the image details. The higher the SNR value, the more the information is available. Methods: In this study, a new function has been formulated using the appropriate suggestions on convolutional combination of the longitudinal and transverse magnetization components related to the relaxation times of T1 and T2 in MRI, where by introducing the distinct index on the maximum value of this function, the new maps are constructed toward the best SNR. Proposed functions were analytically simulated using Matlab software and evaluated with respect to various relaxation times. This proposed method can be applied to any medical images. For instance, the T1- and T2-weighted images of the breast indicated in the reference [35] were selected for modelling and construction of the full width at x maximum (FWxM) map at the different values of x-parameter from 0.01 to 0.955 at 0.035 and 0.015 intervals. The range of x-parameter is between zero and one. To determine the maximum value of the derived SNR, these intervals have been first chosen arbitrarily. However, the smaller this interval, the more precise the value of the x-parameter at which the signal to noise is maximum. Results: The results showed that at an index value of x = 0.325, the new map of FWxM (0.325) will be constructed with a maximum derived SNR of 22.7 compared to the SNR values of T1- and T2-maps by 14.53 and 17.47, respectively. Conclusion: By convolving two orthogonal magnetization vectors, the qualified images with higher new SNR were created, which included the image with the best SNR. In other words, to optimize the adoption of MRI technique and enable the possibility of wider use, an optimal and cost-effective examination has been suggested. Our proposal aims to shorten the MRI examination to further reduce interpretation times while maintaining primary sensitivity. Significance: Our findings may help to quantitatively identify the primary sources of each type of solid and sequential cancer. A new index was defined as full width in a fraction (x) of the maximum value (FWxM) of the MNormalized function that was computed for creating new maps. The derived SNR has been improved at the values of x from 0.185 to 0.430 (red segment). The maximum-SNR of 22.7 was at the distinct x-parameter index of 0.325. [ABSTRACT FROM AUTHOR]

Medical imaging plays an important role in modern healthcare, with Computed Tomography (CT) being essential for high-resolution cross-sectional imaging. However, Gaussian noise often occurs within the CT scan images and makes it difficult for image interpretation and reduces the diagnostic accuracy, creating a significant obstacle to fully utilizing CT scanning technology. Existing denoising techniques have a hard time balance between noise reduction and preserving the important image details, failing to enable the optimal diagnostic precision. This study introduces Adaptive Gaussian Wiener Filter (AGWF), a novel filter aims to denoise CT scan images that have been corrupted with various Gaussian noise variance without compromising the image details. The AGWF combines the Gaussian filter for initial noise reduction, followed by the implementation of Wiener filter, which can adaptively estimate noise variance and signal power in localized regions. This approach not only outperforms other existing techniques but also showcases a remarkable balance between noise reduction and image detail preservation. The experiment evaluates 300 images from the dataset and each image is corrupted with Gaussian noise variance to ensure a comprehensive evaluation of the AGWF's performance. The evaluation indicated that AGWF can improve the Signal-to-Noise Ratio (SNR) value and reduce the Root Mean Square Error (RMSE) and Mean Square Error (MSE) value, showing a qualitative improvement in CT scan imagery. The proposed method holds promising potential for advancing medical imaging technology with the implementation of deep learning. [ABSTRACT FROM AUTHOR]

Speech enhancement algorithms are applied in multiple levels of enhancement to improve the quality of speech signals under noisy environments known as multi-channel speech enhancement (MCSE) systems. Numerous existing algorithms are used to filter noise in speech enhancement systems, which are typically employed as a pre-processor to reduce noise and improve speech quality. They may, however, be limited in performing well under low signal-to-noise ratio (SNR) situations. The speech devices are exposed to all kinds of environmental noises which may go up to a high-level frequency of noises. The objective of this research is to conduct a noise reduction experiment for a multi-channel speech enhancement (MCSE) system in stationary and non-stationary environmental noisy situations with varying speech signal SNR levels. The experiments examined the performance of the existing and the proposed MCSE systems for environmental noises in filtering low to high SNRs environmental noises (-10 dB to 20 dB). The experiments were conducted using the AURORA and LibriSpeech datasets, which consist of different types of environmental noises. The existing MCSE (BAV-MCSE) makes use of beamforming, adaptive noise reduction and voice activity detection algorithms (BAV) to filter the noises from speech signals. The proposed MCSE (DWT-CNN-MCSE) system was developed based on discrete wavelet transform (DWT) preprocessing and convolution neural network (CNN) for denoising the input noisy speech signals to improve the performance accuracy. The performance of the existing BAV-MCSE and the proposed DWT-CNN-MCSE were measured using spectrogram analysis and word recognition rate (WRR). It was identified that the existing BAV-MCSE reported the highest WRR at 93.77% for a high SNR (at 20 dB) and 5.64% on average for a low SNR (at -10 dB) for different noises. The proposed DWT-CNN-MCSE system has proven to perform well at a low SNR with WRR of 70.55% and the highest improvement (64.91% WRR) at -10 dB SNR. [ABSTRACT FROM AUTHOR]

This paper presents a successful implementation of the Six Sigma methodology for analyzing the effluents of plastic manufacturing industries. The proposed Complex Fuzzy Analytic Hierarchy Process with Octagonal Fuzzy Number (CFAHP-OFN) is superior because of the advantage of increasing the fuzzy scale during the production process. The current study aims to construct and progress a project using weight assessment criteria and ranking by using an complex fuzzy analytic hierarchy process so that the global efficiency, profitability and quality of the organization can be improved to a greater extent. This study tracks the application of integrating the DMAIC procedure with CFAHP-OFN and also analyzing industrial effluents and delivering results that could concurrently fulfill operational quality conditions. Concentrating on energy consumption, the experts in the production industry decided (i) to find an optimum setting during the machining process using design of experiments and (ii) to analyze the industrial effluents of the recycling process. An empirical case study was conducted to demonstrate the project’s effectiveness. The results obtained during the production process were checked using quadratic fuzzy regression control charts. This study also focused on recycling plastic; hence, water samples were collected from industrial effluents and heavy metals were analyzed in a laboratory. Principal component analysis and factor loadings were used to study heavy metal content concentrations. This paper emphasizes the entire plastic production process starting from the manufacturing process until the recycling process, to help the organization create an eco-friendly environment.

In recent development and improvement of wireless communication system, the cognitive radio (CR) is a potential approach to utilize spectrum efficiently. Spectrum sensing technique arguably is the most significant component of cognitive radio. Cooperative spectrum sensing (CSS) is utilized to improve the detection performance of the system. Several fusion strategies of decision making are presented for sensing the primary user but they do not perform well under low signal to noise ratio (SNR) conditions. This paper proposes artificial neural network (ANN) based CSS under Rayleigh multipath fading channel in IEEE 802.22 wireless regional area network (WRAN). We implemented an ANN in the fusion centre. First, the energy of the received signal is calculated using discrete wavelet packet transform (DWPT). Then, calculated energy, SNR and false alarm probability are used jointly to make a data set of 2048 samples and are used to train Levenberg-Marquardt back propagation training algorithm-based feed-forward neural network (FFNN). Using this trained neural network, CSS in WRAN is simulated under Rayleigh multipath fading channel and results demonstrate the superiority of the proposed approach over traditional CSS with DWPT and Fast fourier transform (FFT) based energy detection schemes in low SNR environment.

A new hybrid optical fiber communication (OFC) and free space optics (FSO) communication systems are proposed for enhancing the transmission capacity. It is based on using subcarrier modulation (SCM) with spectral amplitude coding based optical code division multiple access (SAC-OCDMA) technique using three different codes. Permutation vector (PV) code, zero cross correlation (ZCC) code, and fixed right shift (FRS) code are used. The performance is evaluated for various numbers of users, data rate, effective power levels, number of subcarriers, and number of carrier channels. Additionally, the effects under different fog conditions including light fog (LF), medium fog (MF), and heavy fog (HF) are evaluated. Moreover, the proposed FSO system achieves ranges of 1.8 km, 1.05 km, and 0.8 km under LF, MF, and HF conditions respectively. Our results show that the proposed OFC system supports 7, 6, and 5 simultaneous users with PV, ZCC, and FRS codes respectively. Similarly, each user carries 5 channels, and each channel carries 14 subcarriers with 1 Gbps information per subcarrier when PV code is adopted. As for FSO transmission, the proposed hybrid system can support up to 22, 18, and 14 users under LF, MF, and HF respectively. Each user also carries information from 5 channels. All results are obtained at BER less than $3\times {10}^{-3}$ .

This paper proposes the Modified Light GBM to classify the Malicious Users (MUs) and legitimate Secondary Users (SUs) in the cognitive-radio network. The proposed method is to avoid the consequences of malicious users in Cooperative Spectrum Sensing (CSS) without the detection of MUs. The method is tested against the occurrence of Always No Malicious User (ANMU), always yes malicious user (AYMU), the Random Malicious User (RMU), and Opposite Malicious User (OMU) transmitting spectrum sensing data to the Fusion Center (FC) by normal secondary users. The efficiency of the proposed method is expressed via simulations and compared with other existing methods. [ABSTRACT FROM AUTHOR]

Small‐signal stability is an important task and key research in electrical engineering for networks. This research article focuses on the implementation of a multi‐objective approach for choosing an optimal location for Phasor Measurement Units (PMUs) to quantify a power system's small‐signal stability by maximizing the signal‐to‐noise ratio (SNR) in the system. The novelty of this research lies in the implementation of Dingo Optimization (DOX) technique along with the Prony Analysis (PA) approach for the assessment of small‐signal stability in standard grid networks. The voltage angle, amplitude and the range of frequencies are measured by the optimal placement of PMUs, which primarily focus on the multi‐signal PA. To achieve the objective of this research, DOX integrated with the multi‐signal PA approach is used to determine the ideal position for PMU placement by considering maximum redundancy and optimizing the signal to noise ratio to a maximum level. The effectiveness of the DOX strategy is established with improved accuracy and fewer disturbances by optimizing the electromechanical oscillations of the system. The implementation of the DOX approach for attaining the best value of the maximized SNR is obtained by analyzing a wide set of conditions, perturbations, and additive noise, which provides an accurate assessment of damping ratio (DR) and frequency (f) of electromechanical oscillations. Numerical results obtained from the standard IEEE test systems (14, 39, 57, 118, and 300 bus systems) are compared with the existing methods in the literature. The statistical indices demonstrate that under the highly limited optimization context selected, the intended optimizer functions satisfactorily. [ABSTRACT FROM AUTHOR]

The Six Sigma approach is utilized in this research to improve the quality of process outputs while machining Galvanized Iron in turning process. The main objective of the present work is to improve the output characterization of MRR (Material Removal Rate) by optimizing the turning process parameters. Taguchi's parameter design is a method for optimizing control settings in Design of Experiments (DOE) to achieve the best results. An orthogonal array offers a framework of equal minimal experiments for prediction and diagnosis of optimal outcomes. The Material Removal Rate (MRR) is evaluated for each experiment. The response fluctuation was investigated using the Signal to Noise (S/N) ratio. In Miniutab 19 software, Taguchi technique reduces quality characteristic variation owing to uncontrollable parameters. Furthermore, statistical analysis reveals that the standard deviation and mean value of confirmatory trial results were lower than it was before Taguchi design run data. [ABSTRACT FROM AUTHOR]

A new composite model called shadowed Beaulieu-Xie (BX) is used in terahertz and millimeter-wave wireless communication systems. This model characterizes an environment with an arbitrary number of non-line-of-sight and line-of-sight signals. In this paper, an analysis of the average bit error rate (ABER) is done. The analysis is carried out for different coherent and non-coherent modulation techniques. The mathematical expressions of ABER are obtained using the probability density function of the output signal to noise ratio of the shadowed BX fading channel. A new closed-form ABER expression for gray-coded rectangular quadrature amplitude modulation over the shadowed BX channel is also evaluated. The effects of fading and shadowing parameters on the modulation techniques are analyzed and compared. [ABSTRACT FROM AUTHOR]

Purpose: A 128‐channel receive‐only array for brain imaging at 7 T was simulated, designed, constructed, and tested within a high‐performance head gradient designed for high‐resolution functional imaging. Methods: The coil used a tight‐fitting helmet geometry populated with 128 loop elements and preamplifiers to fit into a 39 cm diameter space inside a built‐in gradient. The signal‐to‐noise ratio (SNR) and parallel imaging performance (1/g) were measured in vivo and simulated using electromagnetic modeling. The histogram of 1/g factors was analyzed to assess the range of performance. The array's performance was compared to the industry‐standard 32‐channel receive array and a 64‐channel research array. Results: It was possible to construct the 128‐channel array with body noise–dominated loops producing an average noise correlation of 5.4%. Measurements showed increased sensitivity compared with the 32‐channel and 64‐channel array through a combination of higher intrinsic SNR and g‐factor improvements. For unaccelerated imaging, the 128‐channel array showed SNR gains of 17.6% and 9.3% compared to the 32‐channel and 64‐channel array, respectively, at the center of the brain and 42% and 18% higher SNR in the peripheral brain regions including the cortex. For R = 5 accelerated imaging, these gains were 44.2% and 24.3% at the brain center and 86.7% and 48.7% in the cortex. The 1/g‐factor histograms show both an improved mean and a tighter distribution by increasing the channel count, with both effects becoming more pronounced at higher accelerations. Conclusion: The experimental results confirm that increasing the channel count to 128 channels is beneficial for 7T brain imaging, both for increasing SNR in peripheral brain regions and for accelerated imaging. [ABSTRACT FROM AUTHOR]

In recent days, extensive digital communication process has been performed. Due to this phenomenon, a proper maintenance of authentication, communication without any overhead such as signal attenuation code rate fluctuations during digital communication process can be minimized and optimized by adopting parallel encoder and decoder operations. To overcome the above-mentioned drawbacks by using proposed reconfigurable code rate cooperative (RCRC) and low-density parity check (LDPC) method. The proposed RCRC-LDPC is capable to operate over gigabits/sec data and it effectively performs linear encoding, dual diagonal form, widens the range of code rate and optimal degree distribution of LDPC mother code. The proposed method optimize the transmission rate and it is capable to operate on 0.98 code rate. It is the highest upper bounded code rate as compared to the existing methods. The proposed method optimizes the transmission rate and is capable to operate on a 0.98 code rate. It is the highest upper bounded code rate as compared to the existing methods. the proposed method's implementation has been carried out using MATLAB and as per the simulation result, the proposed method is capable of reaching a throughput efficiency greater than 8.2 (1.9) gigabits per second with a clock frequency of 160 MHz. [ABSTRACT FROM AUTHOR]

Deep-learning based speech enhancement included many applications like improving speech intelligibility and perceptual quality. There are many methods which focus on amplitude spectrum enhancement. In the existing models, computation of the complex layer is huge which leads to a very big challenge to the device. DFT data is complex valued, so computation is difficult since we need to deal with the both real and imaginary parts of the signal at the same time. To reduce the computation, some researchers use the variants of STFT as input, such as amplitude/energy spectrum, Log-Mel spectrum, etc. They all enhance amplitude spectrum without estimating clean phase, this would limit the enhancement performance. In the proposed method DCT is used which is real-valued transformation without information lost and contains implicit phase. This avoids the problem of manually design a complex network to estimate the explicit phase and it will improve the enhancement performance. More research have done on phase spectrum estimation directly and indirectly, but it is not ideal. Recently, complex valued models are proposed like deep complex convolution recurrent network (DCCRN). The computation of the model is very huge. So a Deep Cosine transform convolutional Gated recurrent Unit (DCTCGRU) is proposed to reduce the complexity and improve further performance. GRU can well model the correlation between adjacent frames of noisy speech. The results from the experiment show that DCTCGRU achieves better results in terms of SNR, PESQ and STOI compared with the state-of-the-art algorithms. [ABSTRACT FROM AUTHOR]

We are developing a 70-dB SNR 1,000 frame-per-second absorption imaging system, and it enables us to visualize gas concentration distribution in a vacuum chamber for semiconductor manufacturing. This article presents the measurement and analysis of temporal and steady-state NO2 gas concentration distribution using this system. In the steady-state gas flow condition which supplied from a shower plate, the spectrometry of NO2 gas shows a good linear relationship between the absorbance and the partial pressure with the system. The system enables the visualization of steady-state of NO2 gas concentration distribution which supplied from one hole of shower plate, and the results are compared with simulation to discuss the reasonability of the measurement. The system also enables to visualize the temporal NO2 gas concentration distribution supplied from a single nozzle, and the advantages of the system’s features of 70-dB and 1,000 fps are discussed. [ABSTRACT FROM AUTHOR]

In the context of side-channel attacks, the Signal to Noise Ratio (SNR) is a widely used metric for characterizing the information leaked by a device when handling sensitive variables. In this paper, we derive the probability density function (p.d.f.) of the signal to noise ratio (SNR) for the byte value and Hamming Weight (HW) models, when the number of traces per class is large and the target SNR is small. These findings are subsequently employed to establish an SNR threshold, guaranteeing minimal occurrences of false positives. Then, these results are used to derive the theoretical number of traces that are required to remain below pre-defined false negative and false positive rates. The sampling complexity of the T-test, ρ-test and SNR is evaluated for the byte value and HW leakage model by simulations and compared to the theoretical predictions. This allows to establish the most pertinent strategy to make use of each of these detection techniques.

Speech enhancement algorithms are applied in multiple levels of enhancement to improve the quality of speech signals under noisy environments known as multi-channel speech enhancement (MCSE) systems. Numerous existing algorithms are used to filter noise in speech enhancement systems, which are typically employed as a pre-processor to reduce noise and improve speech quality. They may, however, be limited in performing well under low signal-to-noise ratio (SNR) situations. The speech devices are exposed to all kinds of environmental noises which may go up to a high-level frequency of noises. The objective of this research is to conduct a noise reduction experiment for a multi-channel speech enhancement (MCSE) system in stationary and non-stationary environmental noisy situations with varying speech signal SNR levels. The experiments examined the performance of the existing and the proposed MCSE systems for environmental noises in filtering low to high SNRs environmental noises (−10 dB to 20 dB). The experiments were conducted using the AURORA and LibriSpeech datasets, which consist of different types of environmental noises. The existing MCSE (BAV-MCSE) makes use of beamforming, adaptive noise reduction and voice activity detection algorithms (BAV) to filter the noises from speech signals. The proposed MCSE (DWT-CNN-MCSE) system was developed based on discrete wavelet transform (DWT) preprocessing and convolution neural network (CNN) for denoising the input noisy speech signals to improve the performance accuracy. The performance of the existing BAV-MCSE and the proposed DWT-CNN-MCSE were measured using spectrogram analysis and word recognition rate (WRR). It was identified that the existing BAV-MCSE reported the highest WRR at 93.77% for a high SNR (at 20 dB) and 5.64% on average for a low SNR (at −10 dB) for different noises. The proposed DWT-CNN-MCSE system has proven to perform well at a low SNR with WRR of 70.55% and the highest improvement (64.91% WRR) at −10 dB SNR.

In this paper, the dry sliding wear behaviour of the polyester composite reinforced with iron slag as filler was studied experimentally. The Taguchi method-based experiments were carried on pin-on-disk wear test set-up. The control factors considered for studying wear rate were sliding velocity, slag percentage and normal load applied on the member with constant sliding distance. The output performance parameters considered were coefficient of friction and weight loss. From the analysis of variance (ANOVA), it was observed that coefficient of friction is significantly affected by normal load then followed by slag content and sliding velocity. Sliding velocity plays a vital role on the weight loss then followed by slag content and normal load. The optimal factor combination obtained was sliding velocity = 50 cm/s, slag percentage = 30 % and normal load = 4 kg. The model was validated using the set of optimal factor combinations to conduct a confirmation experiment.

Due to the complex and variable nature of the atmospheric conditions, traditional multi-wavelength differential absorption lidar (DIAL) methods often suffer from significant errors when inverting ozone concentrations. As the detection range increases, there is a higher demand for Signal to Noise Ratio (SNR) in lidar signals. Based on this, the paper discusses the impact of different atmospheric factors on the accuracy of ozone concentration inversion. It also compares the advantages and disadvantages of the two-wavelength differential method and the three-wavelength dual-differential method under both noisy and noise-free conditions. Firstly, the errors caused by air molecular extinction, aerosol extinction, and backscatter terms in the inversion using the two-wavelength differential method were simulated. Secondly, the corrected inversion errors were obtained through direct correction and the introduction of a three-wavelength dual differential correction. Finally, addressing the issue of insufficient SNR in practical inversions, the inversion errors of the two correction methods were simulated by constructing lidar parameters and incorporating appropriate noise. The results indicate that the traditional two-wavelength differential algorithm is significantly affected by aerosols, making it more sensitive to aerosol concentration and structural changes. On the other hand, the three-wavelength dual differential algorithm requires a higher SNR in lidar signals. Therefore, we propose a novel strategy for inverting atmospheric ozone concentration, which prioritizes the use of the three-wavelength dual-differential method in regions with high SNR and high aerosol concentration. Conversely, the direct correction method utilizing the two-wavelength differential approach is used. This approach holds the potential for high-precision ozone concentration profile inversion under different atmospheric conditions.