Search results for: frequency identification

Authors: Gangmin Li, Fan Yang

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Personalized recommendation is crucial for any recommendation system. One of the techniques for personalized recommendation is to identify the intention. Traditional user intention identification uses the user’s selection when facing multiple items. This modeling relies primarily on historical behaviour data resulting in challenges such as the cold start, unintended choice, and failure to capture intention when items are new. Motivated by recent advancements in Large Language Models (LLMs) like ChatGPT, we present an approach for user intention identification by embracing LLMs with Chain-of-Thought (CoT) prompting. We use the initial user profile as input to LLMs and design a collection of prompts to align the LLM's response through various recommendation tasks encompassing rating prediction, search and browse history, user clarification etc. Our tests on real-world datasets demonstrate the improvements in recommendation by explicit user intention identification and, with that intention, merged into a user model.

Keywords: personalized recommendation, generative user modelling, user intention identification, large language models, chain-of-thought prompting

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Authors: Ahmad H. Abdelgwad, Galal E. Nadim, Tarek M. Said, Amr M. Gody

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The prime objective of this manuscript is to provide intensive review of the techniques used for permittivity measurements. The measurement techniques, relevant for any desired application, rely on the nature of the measured dielectric material, both electrically and physically, the degree of accuracy required, and the frequency of interest. Regardless of the way that distinctive sorts of instruments can be utilized, measuring devices that provide reliable determinations of the required electrical properties including the obscure material in the frequency range of interest can be considered. The challenge in making precise dielectric property or permittivity measurements is in designing of the material specimen holder for those measurements (RF and MW frequency ranges) and adequately modeling the circuit for reliable computation of the permittivity from the electrical measurements. If the RF circuit parameters such as the impedance or admittance are estimated appropriately at a certain frequency, the material’s permittivity at this frequency can be estimated by the equations which relate the way in which the dielectric properties of the material affect on the parameters of the circuit.

Keywords: dielectric permittivity, free space measurement, waveguide techniques, coaxial probe, cavity resonator

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Authors: Yekta Ülgen, Fırat Matur

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Cole-Cole parameters of 40 post-menopausal women are compared with their DEXA bone mineral density measurements. Impedance characteristics of four extremities are compared; left and right extremities are statistically same, but lower extremities are statistically different than upper ones due to their different fat content. The correlation of Cole-Cole impedance parameters to bone mineral density (BMD) is observed to be higher for a dominant arm. With the post menopausal population, ANOVA tests of the dominant arm characteristic frequency, as a predictor for DEXA classified osteopenic and osteoporotic population around the lumbar spine, is statistically very significant. When used for total lumbar spine osteoporosis diagnosis, the area under the Receiver Operating Curve of the characteristic frequency is 0.875, suggesting that the Cole-Cole plot characteristic frequency could be a useful diagnostic parameter when integrated into standard screening methods for osteoporosis. Moreover, the characteristic frequency can be directly measured by monitoring frequency driven the angular behavior of the dominant arm without performing any complex calculation.

Keywords: bioimpedance spectroscopy, bone mineral density, osteoporosis, characteristic frequency, receiver operating curve

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Authors: S. Mohamed Rabeek, Mi Kyoung Park, M. Annamalai Arasu

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This paper presents a design of a wireless read out system for tracking the frequency shift of the polymer coated piezoelectric micro electromechanical resonator due to gas absorption. The measure of this frequency shift indicates the percentage of a particular gas the sensor is exposed to. It is measured using an oscillator and an FPGA based frequency counter by employing the resonator as a frequency determining element in the oscillator. This system consists of a Gas Sensing Wireless Readout (GSWR) and an USB Wireless Transceiver (UWT). GSWR consists of an oscillator based on a trans-impedance sustaining amplifier, an FPGA based frequency readout, a sub 1GHz wireless transceiver and a micro controller. UWT can be plugged into the computer via USB port and function as a wireless module to transfer gas sensor data from GSWR to the computer through its USB port. GUI program running on the computer periodically polls for sensor data through UWT - GSWR wireless link, the response from GSWR is logged in a file for post processing as well as displayed on screen.

Keywords: gas sensor, GSWR, micromechanical system, UWT, volatile emissions

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Authors: Jagroop Singh Sidhu, Buta Singh

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A low computational deblocking filter including three frequency related modes (smooth mode, intermediate mode, and non-smooth mode for low-frequency, mid-frequency, and high frequency regions, respectively) is proposed. The suggested approach requires zero additions, zero subtractions, zero multiplications (for intermediate region), no divisions (for non-smooth region) and no comparison. The suggested method thus keeps the computation lower and thus suitable for image coding systems based on blocks. Comparison of average number of operations for smooth, non-smooth, intermediate (per pixel vector for each block) using filter suggested by Chen and the proposed method filter suggests that the proposed filter keeps the computation lower and is thus suitable for fast processing algorithms.

Keywords: blocking artifacts, computational complexity, non-smooth, intermediate, smooth

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Authors: Chad Goldsworthy, B. Rajeswari Matam

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The use of deep learning for species identification in camera trap images has revolutionised our ability to study, conserve and monitor species in a highly efficient and unobtrusive manner, with state-of-the-art models achieving accuracies surpassing the accuracy of manual human classification. The high imbalance of camera trap datasets, however, results in poor accuracies for minority (rare or endangered) species due to their relative insignificance to the overall model accuracy. This paper investigates the use of Focal Loss, in comparison to the traditional Cross Entropy Loss function, to improve the identification of minority species in the “255 Bird Species” dataset from Kaggle. The results show that, although Focal Loss slightly decreased the accuracy of the majority species, it was able to increase the F1-score by 0.06 and improve the identification of the bottom two, five and ten (minority) species by 37.5%, 15.7% and 10.8%, respectively, as well as resulting in an improved overall accuracy of 2.96%.

Keywords: convolutional neural networks, data imbalance, deep learning, focal loss, species classification, wildlife conservation

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Authors: Cai-Wan Chang-Jian, Han-Ting Tsai

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In the processing industry of metal forming, rolling is the most used method of processing. In a cold rolling factory of stainless steel, there occurs a product defect on temper rolling process within cold rolling. It is called 'roll marks', which is a phenomenon of undesirable flatness problem. In this research, we performed a series of experimental measurements on the roll marks, and we used optical sensors to measure it and compared the vibration frequency of roll marks with the vibration frequency of key components in the skin pass mill. We found there is less correlation between the above mentioned data. Finally, we took measurement on the motor driver in rolling mill. We found that the undulation frequency of motor could match with the frequency of roll marks, and then we have confirmed that the motor’s undulation caused roll marks.

Keywords: roll mark, plane strain, rolling mill, stainless steel

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Authors: Waddah Abdelbagi Talha, Mohammed Abdullah Elmaleeh, John Ojur Dennis

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This paper focuses on the simulation and implementation of a resonator micro-sensor for low magnetic field sensing based on a U-shaped cantilever and piezoresistive configuration, which works based on Lorentz force physical phenomena. The resonance frequency is an important parameter that depends upon the highest response and sensitivity through the frequency domain (frequency response) of any vibrated micro-scale of an electromechanical system (MEMS) device. And it is important to determine the direction of the detected magnetic field. The deflection of the cantilever is considered for vibrated mode with different frequencies in the range of (0 Hz to 7000 Hz); for the purpose of observing the frequency response. A simple electronic circuit-based polysilicon piezoresistors in Wheatstone's bridge configuration are used to transduce the response of the cantilever to electrical measurements at various voltages. Microcontroller-based Arduino program and PROTEUS electronic software are used to analyze the output signals from the sensor. The highest output voltage amplitude of about 4.7 mV is spotted at about 3 kHz of the frequency domain, indicating the highest sensitivity, which can be called resonant sensitivity. Based on the resonant frequency value, the mode of vibration is determined (up-down vibration), and based on that, the vector of the magnetic field is also determined.

Keywords: resonant frequency, sensitivity, Wheatstone bridge, UNO-microcontroller

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Authors: Matthew C. Best

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Linear Multi-Input Multi-Output (MIMO) dynamic models can be identified, with no a priori knowledge of model structure or order, using a new Generalised Identifying Filter (GIF). Based on an Extended Kalman Filter, the new filter identifies the model iteratively, in a continuous modal canonical form, using only input and output time histories. The filter’s self-propagating state error covariance matrix allows easy determination of convergence and conditioning, and by progressively increasing model order, the best fitting reduced-order model can be identified. The method is shown to be resistant to noise and can easily be extended to identification of smoothly nonlinear systems.

Keywords: system identification, Kalman filter, linear model, MIMO, model order reduction

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Authors: Jun Wang, Tingcun Wei

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The digital pulse width modulator (DPWM) is the crucial building block for digitally-controlled DC-DC switching converter, which converts the digital duty ratio signal into its analog counterpart to control the power MOSFET transistors on or off. With the increase of switching frequency of digitally-controlled DC-DC converter, the DPWM with higher time resolution is required. In this paper, a 15-bits DPWM with three-level hybrid structure is presented; the first level is composed of a7-bits counter and a comparator, the second one is a 5-bits delay line, and the third one is a 3-bits digital dither. The presented DPWM is designed and implemented using the PLL megafunction of FPGA (Field Programmable Gate Arrays), and the required frequency of clock signal is 128 times of switching frequency. The simulation results show that, for the switching frequency of 2 MHz, a DPWM which has the time resolution of 15 ps is achieved using a maximum clock frequency of 256MHz. The designed DPWM in this paper is especially useful for high-frequency digitally-controlled DC-DC switching converters.

Keywords: DPWM, digitally-controlled DC-DC switching converter, FPGA, PLL megafunction, time resolution

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Authors: M. H. Aissa, Amar Bouzid Dj

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As known, many countries are now planning to build new wind farms with high capacity up to 5MW. Consequently, the size of the foundation increase. These kinds of structures are subject to fatigue damage from environmental loading mainly due to wind and waves as well as from cyclic loading imposed through the rotational frequency (1P) through mass and aerodynamic imbalances and from the blade passing frequency (3P) of the wind turbine which make them behavior dynamically very sensitive. That is why natural frequency must be determined with accuracy from the existing data of the soil and the foundation stiffness sources of uncertainties, to avoid the resonance of the system. This paper presents analytical expressions of stiffness foundation with large diameter in linear soil behavior in different soil stiffness profile. To check the accuracy of the proposed formulas, a mathematical model approach based on non-dimensional parameters is used to calculate the natural frequency taking into account the soil structure interaction (SSI) compared with the p-y method and measured frequency in the North Sea Wind farms.

Keywords: offshore wind turbines, semi analytical FE analysis, p-y curves, piles foundations

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Authors: D. Liu, D. M. Donskoy

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The vibroacoustic modulation method is based on the modulation effect of high-frequency ultrasonic wave (carrier) by low-frequency vibration in the presence of various defects, primarily contact-type such as cracks, delamination, etc. The presence and severity of the defect are measured by the ratio of the spectral sidebands and the carrier in the spectrum of the modulated signal. This approach, however, does not differentiate between amplitude and frequency modulations, AM and FM, respectfully. It was experimentally shown that both modulations could be present in the spectrum, yet each modulation may be associated with different physical mechanisms. AM mechanisms are quite well understood and widely covered in the literature. This paper is a first attempt to explain the generation mechanisms of FM and its correlation with the flaw properties. Here we proposed two possible mechanisms leading to FM modulation based on nonlinear local defect resonance and dynamic acousto-elastic models.

Keywords: non-destructive testing, nonlinear acoustics, structural health monitoring, acousto-elasticity, local defect resonance

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Authors: Ezzat Mohamed El-Amin

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Mapping the earthquake-size distribution in various tectonic regimes on a local to regional scale reveals statistically significant variations in the range of at least 0.4 to 2.0 for the b-value in the frequency-magnitude distribution. We map the earthquake frequency–magnitude distribution (b value) as a function of depth in the Reservoir Triggered Seismicity (RTS) region in Kalabsha region, in south Egypt. About 1680 well-located events recorded during 1981–2014 in the Kalabsha region are selected for the analysis. The earthquake data sets are separated in 5 km zones from 0 to 25 km depth. The result shows a systematic decrease in b value up to 12 km followed by an increase. The increase in b value is interpreted to be caused by the presence of fluids. We also investigate the spatial distribution of b value with depth. Significant variations in the b value are detected, with b ranging from b 0.7 to 1.19. Low b value areas at 5 km depth indicate localized high stresses which are favorable for future rupture.

Keywords: seismicity, frequency-magnitude, b-value, earthquake

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Authors: Sergey Svita, Valeriy Astapenko

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The study is devoted to theoretical analysis of ultrashort electromagnetic pulses (USP) absorption on gold nanospheres. Dependencies of USP energy absorption on nanospheres placed in various matrix are compared. The results of calculation of absorbed energy on gold nanospheres as a function of ultrashort electromagnetic pulse carrier frequency and number of pulse cycles of carrier frequency show strong non-linear dependence of absorbed energy on number of cycles of carrier frequency, but for relatively large number of cycles on USP carrier frequency it goes to linear dependence.

Keywords: ultrashort electromagnetic pulses, absorption, nanospheres, theoretical research

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Authors: Sanjay M. Gulhane, Athar Ravish Khan, Umesh W. Kaware

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Orthogonal frequency and code division multiplexing (OFCDM) has received large attention as a modulation scheme to realize high data rate transmission. Multiband (MB) Orthogonal frequency division multiplexing (OFDM) Ultra Wide Band (UWB) system become promising technique for high data rate due to its large number of advantage over Singleband (UWB) system, but it suffer from coherent frequency diversity problem. In this paper we have proposed MB-OFCDM UWB system, in which two-dimensional (2D) spreading (time and frequency domain spreading), has been introduced, combining OFDM with 2D spreading, proposed system can provide frequency diversity. This paper presents the basic structure and main functions of the MB-OFCDM system, and evaluates the bit error rate BER performance of MB-OFDM and MB-OFCDM system under UWB indoor multi-path channel model. It is observe that BER curve of MB-OFCDM UWB improve its performance by 2dB as compare to MB-OFDM UWB system.

Keywords: MB-OFDM UWB system, MB-OFCDM UWB system, UWB IEEE channel model, BER

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Authors: Kenneth Larsen, Astrid Aasland, Synnve Schjølberg, Trond Diseth

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Autism Spectrum Disorders (ASD) are neurodevelopmental disorders emerging in early development characterized by impairment in social communication skills and a restricted, repetitive and stereotyped patterns of behavior and interests. Early identification and interventions potentially improve development and quality of life of children with ASD. Symptoms of ASD are apparent through the second year of life, yet diagnostic age are still around 4 years of age. This study explored whether symptoms associated with ASD are possible to identify in typical Norwegian day-care centers in the second year of life. Results of this study clearly indicates that most described symptoms also are identifiable by day-care staff, and that a short observation list of 5 symptoms clearly identify children with ASD from a sample of normal developing peers.

Keywords: autism, early identification, day-care, screening

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Authors: Danika Pieters

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Due to changing societal and economic demands, organizational change has become increasingly prevalent in work life. While a long time change research has focused on the effects of single discrete change events on different employee outcomes such as job satisfaction and organizational commitment, a nascent research stream has begun to look into the potential cumulative effects of change in the context of continuous intense reforms. This case study of a large Belgian public organization aims to add to this growing literature by examining how the frequency and diversity of past changes impact employees’ appraisals of a newly introduced change. Twelve hundred survey results were analyzed using standard ordinary least squares regression. Results showed a correlation between high past change frequency and diversity and a negative appraisal of the new change. Implications for practitioners and future research are discussed.

Keywords: change frequency, change diversity, organizational changes, change appraisal, change evaluation

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Authors: Hamidreza Saberkari, Mousa Shamsi, Hossein Ahmadi, Saeed Vaali, , MohammadHossein Sedaaghi

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In the recent years, using signal processing tools for accurate identification of the protein coding regions has become a challenge in bioinformatics. Most of the genomic signal processing methods is based on the period-3 characteristics of the nucleoids in DNA strands and consequently, spectral analysis is applied to the numerical sequences of DNA to find the location of periodical components. In this paper, a novel ensemble algorithm for gene selection in DNA sequences has been presented which is based on the combination of Goertzel algorithm and anti-notch filter (ANF). The proposed algorithm has many advantages when compared to other conventional methods. Firstly, it leads to identify the coding protein regions more accurate due to using the Goertzel algorithm which is tuned at the desired frequency. Secondly, faster detection time is achieved. The proposed algorithm is applied on several genes, including genes available in databases BG570 and HMR195 and their results are compared to other methods based on the nucleotide level evaluation criteria. Implementation results show the excellent performance of the proposed algorithm in identifying protein coding regions, specifically in identification of small-scale gene areas.

Keywords: protein coding regions, period-3, anti-notch filter, Goertzel algorithm

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Authors: Joon-Hoon Park

Abstract:

In this paper the rationalized Haar transform is applied for distributed parameter system identification and estimation. A distributed parameter system is a dynamical and mathematical model described by a partial differential equation. And system identification concerns the problem of determining mathematical models from observed data. The Haar function has some disadvantages of calculation because it contains irrational numbers, for these reasons the rationalized Haar function that has only rational numbers. The algorithm adopted in this paper is based on the transform and operational matrix of the rationalized Haar function. This approach provides more convenient and efficient computational results.

Keywords: distributed parameter system, rationalized Haar transform, operational matrix, system identification

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Authors: Yen-Po Wang, Ming-Chih Huang, Ming-Lian Chang

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A scheme integrated with deterministic–stochastic subspace system identification and the method of damage localization vector is proposed in this study for damage detection of structures based on seismic response data. A series of shaking table tests using a five-storey steel frame has been conducted in National Center for Research on Earthquake Engineering (NCREE), Taiwan. Damage condition is simulated by reducing the cross-sectional area of some of the columns at the bottom. Both single and combinations of multiple damage conditions at various locations have been considered. In the system identification analysis, either full or partial observation conditions have been taken into account. It has been shown that the damaged stories can be identified from global responses of the structure to earthquakes if sufficiently observed. In addition to detecting damage(s) with respect to the intact structure, identification of new or extended damages of the as-damaged (ill-conditioned) counterpart has also been studied. The proposed scheme proves to be effective.

Keywords: damage locating vectors, deterministic-stochastic subspace system, shaking table tests, system identification

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Authors: Abdolreza Esmaeilzadeh, Maryam Erfanmanesh, Sousan Ghasemi, Farzaneh Mohammadi

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Background: Hepatitis C Virus (HCV), a public health problem, is an enveloped, single-stranded RNA virus and a member of the Hepacivirus genus of the Flaviviridae family. Liver cancer, cirrhosis, and end-stage liver are the outcomes of chronic infection with HCV. HCV isolates show significant heterogeneity in genetics around the world. Therefore, determining HCV genotypes is a vital step in determining prognosis and planning therapeutic strategies. Materials and Methods: Serum samples of 136 patients were collected and analyzed for anti-HCV antibodies using ELISA (The enzyme-linked immunosorbent assay) method. Then, positive samples were exposed to RT-PCR, which was performed under standard condition. Afterwards, they investigated for genotyping using allele-specific PCR (AS-PCR), and HCV genotype 2.0 line probe assay (LiPA). Results: Samples indicated 216 bp bands on 2% agarose gel. Analyses of the results demonstrated that the most dominant subtype was 3a with frequency of 38.26% in Zanjan Province followed by subtypes of 1b, 1a, 2, and 4 with frequencies of 25.73%, 22.05%, 5.14%, and 4.41%, respectively. The frequency of unknown HCV genotypes was 4.41%. Conclusions: According to the results, it was found that HCV high prevalent genotype in Zanjan is subtype 3a. Analysis of the results provides identification of certain HCV genotypes, and these valuable findings could affect the type and duration of the treatment.

Keywords: anti-HCV antibody, Hepatitis C Virus (HCV), genotype, RT-PCR, AS-PCR

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Authors: Keunhong Chae, Seokho Yoon

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In this paper, frequency offset (FO) estimation schemes robust to the non-Gaussian noise environments are proposed for orthogonal frequency division multiplexing (OFDM) systems. First, a maximum-likelihood (ML) estimation scheme in non-Gaussian noise environments is proposed, and then, the complexity of the ML estimation scheme is reduced by employing a reduced set of candidate values. In numerical results, it is demonstrated that the proposed schemes provide a significant performance improvement over the conventional estimation scheme in non-Gaussian noise environments while maintaining the performance similar to the estimation performance in Gaussian noise environments.

Keywords: frequency offset estimation, maximum-likelihood, non-Gaussian noise environment, OFDM, training symbol

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Authors: Sami M. Alshareef

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In the rapidly evolving energy landscape, the integration of renewable energy sources and the electrification of transportation are essential steps toward achieving sustainability goals. However, these advancements introduce new challenges, particularly in maintaining frequency stability due to variable photovoltaic (PV) generation and the growing demand for fast charging stations. The variability of photovoltaic (PV) generation due to weather conditions can disrupt the balance between generation and load, resulting in frequency deviations. To ensure the stability of power systems, it is imperative to develop effective under frequency load-shedding schemes. This research proposal presents an adaptive under-frequency load shedding scheme based on the power swing equation, designed explicitly for the IEEE-9 Bus Test System, that includes PV generation and fast charging stations. This research aims to address these challenges by developing an advanced scheme that dynamically disconnects fast charging stations based on power imbalances. The scheme prioritizes the disconnection of stations near affected areas to expedite system frequency stabilization. To achieve these goals, the research project will leverage the power swing equation, a widely recognized model for analyzing system dynamics during under-frequency events. By utilizing this equation, the proposed scheme will adaptively adjust the load-shedding process in real-time to maintain frequency stability and prevent power blackouts. The research findings will support the transition towards sustainable energy systems by ensuring a reliable and uninterrupted electricity supply while enhancing the resilience and stability of power systems during under-frequency events.

Keywords: load shedding, fast charging stations, pv generation, power system resilience

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Authors: Varsha Singh, Shraddha Prajapati, M. B. Kiran

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Texture identification is useful in predicting the functionality of a component. Many of the existing texture identification methods are of contact in nature, which limits its measuring speed. These contact measurement techniques use a diamond stylus and the diamond stylus being sharp going to damage the surface under inspection and hence these techniques can be used in statistical sampling. Though these contact methods are very accurate, they do not give complete information for full characterization of surface. In this context, the presented method assumes special significance. The method uses a relatively low cost vision system for image acquisition. Software is developed based on wavelet transform, for analyzing texture images. Specimens are made using different manufacturing process (shaping, grinding, milling etc.) During experimentation, the specimens are illuminated using proper lighting and texture images a capture using CCD camera connected to the vision system. The software installed in the vision system processes these images and subsequently identify the texture of manufacturing processes.

Keywords: diamond stylus, manufacturing process, texture identification, vision system

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Authors: P. Zamani, A. Taleshi Anbouhi, M. R. Ashory, S. Mohajerzadeh, M. M. Khatibi

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Modal analysis is a developing science in the experimental evaluation of dynamic properties of the structures. Mechanical devices such as accelerometers are one of the sources of lack of quality in measuring modal testing parameters. In this paper, eliminating the accelerometer’s mass effect of the frequency response of the structure is studied. So, a strategy is used for eliminating the mass effect by using sensitivity analysis. In this method, the amount of mass change and the place to measure the structure’s response with least error in frequency correction is chosen. Experimental modal testing is carried out on a steel plate and the effect of accelerometer’s mass is omitted using this strategy. Finally, a good agreement is achieved between numerical and experimental results.

Keywords: accelerometer mass, frequency response function, modal analysis, sensitivity analysis

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Authors: Abdelaziz Rabehi

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The current–voltage (I–V) characteristics of Au/GaN Schottky diodes were measured at room temperature. In addition, capacitance–voltage–frequency (C–V–f) characteristics are investigated by considering the interface states (Nss) at frequency range 100 kHz to 1 MHz. From the I–V characteristics of the Schottky diode, ideality factor (n) and barrier height (Φb) values of 1.22 and 0.56 eV, respectively, were obtained from a forward bias I–V plot. In addition, the interface states distribution profile as a function of (Ess − Ev) was extracted from the forward bias I–V measurements by taking into account the bias dependence of the effective barrier height (Φe) for the Schottky diode. The C–V curves gave a barrier height value higher than those obtained from I–V measurements. This discrepancy is due to the different nature of the I–V and C–V measurement techniques.

Keywords: Schottky diodes, frequency dependence, barrier height, interface states

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Authors: Ashok Kalagura

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This paper presents a data-mining model for fault-zone identification of flexible AC transmission systems (FACTS)-based transmission line including a thyristor-controlled series compensator (TCSC) and unified power-flow controller (UPFC), using ensemble decision trees. Given the randomness in the ensemble of decision trees stacked inside the random forests model, it provides an effective decision on the fault-zone identification. Half-cycle post-fault current and voltage samples from the fault inception are used as an input vector against target output ‘1’ for the fault after TCSC/UPFC and ‘1’ for the fault before TCSC/UPFC for fault-zone identification. The algorithm is tested on simulated fault data with wide variations in operating parameters of the power system network, including noisy environment providing a reliability measure of 99% with faster response time (3/4th cycle from fault inception). The results of the presented approach using the RF model indicate the reliable identification of the fault zone in FACTS-based transmission lines.

Keywords: distance relaying, fault-zone identification, random forests, RFs, support vector machine, SVM, thyristor-controlled series compensator, TCSC, unified power-flow controller, UPFC

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Authors: Y. Wang

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The Traveling salesman problem (TSP) is NP-hard in combinatorial optimization. The research shows the algorithms for TSP on the sparse graphs have the shorter computation time than those for TSP according to the complete graphs. We present an improved iterative algorithm to compute the sparse graphs for TSP by frequency graphs computed with frequency quadrilaterals. The iterative algorithm is enhanced by adjusting two parameters of the algorithm. The computation time of the algorithm is O(CN_maxn²) where C is the iterations, N_max is the maximum number of frequency quadrilaterals containing each edge and n is the scale of TSP. The experimental results showed the computed sparse graphs generally have less than 5n edges for most of these Euclidean instances. Moreover, the maximum degree and minimum degree of the vertices in the sparse graphs do not have much difference. Thus, the computation time of the methods to resolve the TSP on these sparse graphs will be greatly reduced.

Keywords: frequency quadrilateral, iterative algorithm, sparse graph, traveling salesman problem

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Authors: Michel Kulhandjian, Dimitris A. Pados

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The objective of this work is to develop a theoretical framework for reliable digital recording system identification from digital audio files alone, for forensic purposes. A digital recording system consists of a microphone and a digital sound processing card. We view the cascade as a system of unknown transfer function. We expect same manufacturer and model microphone-sound card combinations to have very similar/near identical transfer functions, bar any unique manufacturing defect. Input voice (or other) signals are modeled as non-stationary processes. The technical problem under consideration becomes blind deconvolution with non-stationary inputs as it manifests itself in the specific application of digital audio recording equipment classification.

Keywords: blind system identification, audio fingerprinting, blind deconvolution, blind dereverberation

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Authors: Mirza Mohibulla Baig, Imil Hamda Imran, Tri Bagus Susilo, Sami El Ferik

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The paper deals with system identification and control a nonlinear model of semi-autonomous underwater vehicle (UUV). The input-output data is first generated using the experimental values of the model parameters and then this data is used to compute the estimated parameter values. In this study, we use the semi-autonomous UUV LAURS model, which is developed by the Sensors and Actuators Laboratory in University of Sao Paolo. We applied three methods to identify the parameters: integral method, which is a classical least square method, recursive least square, and weighted recursive least square. In this paper, we also apply three different inputs (step input, sine wave input and random input) to each identification method. After the identification stage, we investigate the control performance of yaw motion of nonlinear semi-autonomous Unmanned Underwater Vehicle (UUV) using feedback linearization-based controller. In addition, we compare the performance of the control with an integral and a non-integral part along with state feedback. Finally, disturbance rejection and resilience of the controller is tested. The results demonstrate the ability of the system to recover from such fault.

Keywords: system identification, underwater vehicle, integral method, recursive least square, weighted recursive least square, feedback linearization, integral error

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