Search results for: Additive White Gaussian Noise

Authors: Novia Liza Rahmawaty, Wilson Novarino, Muhammad Nazri Janra

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Indonesian people love to keep songbird in cage to be competed, such as White-rumped Shama (Copsychus malabaricus). Each individual White-rumped Shama will be pitted their song and try to imitate the rhythm of the enemy with its songs. This study was conducted to see the natural song characters of White-rumped Shama and song character from birds that had been trained and comparison in three different places in West Sumatra. Individuals were recorded totaling 30 individuals in three areas in West Sumatra namely Padang, Solok and Pariaman and sound recordings of White-rumped Shama in nature were taken in HBW and Xenocanto website. Research has done conducted from June to October 2016 at place group practice of birdsongs and recorded at 16:00 to 18:00 pm. These voices were analyzed by Avisoft SAS-Lab Lite inform of oscillogram and sonogram. Measured parameters included: the length of voice, repertoire size, number of syllable type, syllable repertoire, and song repertoire. The results showed that repertoire composition of White-rumped Shama in nature less than the sound which was trained and has repeat songs composed by the same type of repertoire composition. Comparison of song character White-rumped Shama in three different places in West Sumatra, those birds in Solok had the best quality of voice or song than Padang and Pariaman. It showed by higher repertoire composition in Solok.

Keywords: repertoire composition, song characters, songbird, white-rumped shama

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Authors: John Lorenzo Bautista, Yoon-Joong Kim

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This paper presents the development of a Filipino speech recognition tool using the HTK System. The system was trained from a subset of the Filipino Speech Corpus developed by the DSP Laboratory of the University of the Philippines-Diliman. The speech corpus was both used in training and testing the system by estimating the parameters for phonetic HMM-based (Hidden-Markov Model) acoustic models. Experiments on different mixture-weights were incorporated in the study. The phoneme-level word-based recognition of a 5-state HMM resulted in an average accuracy rate of 80.13 for a single-Gaussian mixture model, 81.13 after implementing a phoneme-alignment, and 87.19 for the increased Gaussian-mixture weight model. The highest accuracy rate of 88.70% was obtained from a 5-state model with 6 Gaussian mixtures.

Keywords: Filipino language, Hidden Markov Model, HTK system, speech recognition

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Authors: Jian-Heng Wu, Bor-Shen Lin

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The temperature-salinity relationship is one of the most important characteristics used for identifying water masses in marine research. Temperature-salinity characteristics, however, may change dynamically with respect to the geographic location and is quite sensitive to the depth at the same location. When depth is taken into consideration, however, it is not easy to compare the characteristics of different water masses efficiently for a wide range of areas of the ocean. In this paper, the Gaussian mixture model was proposed to analyze the temperature-salinity-depth characteristics of water masses, based on which comparison between water masses may be conducted. Gaussian mixture model could model the distribution of a random vector and is formulated as the weighting sum for a set of multivariate normal distributions. The temperature-salinity-depth data for different locations are first used to train a set of Gaussian mixture models individually. The distance between two Gaussian mixture models can then be defined as the weighting sum of pairwise Bhattacharyya distances among the Gaussian distributions. Consequently, the distance between two water masses may be measured fast, which allows the automatic and efficient comparison of the water masses for a wide range area. The proposed approach not only can approximate the distribution of temperature, salinity, and depth directly without the prior knowledge for assuming the regression family, but may restrict the complexity by controlling the number of mixtures when the amounts of samples are unevenly distributed. In addition, it is critical for knowledge discovery in marine research to represent, manage and share the temperature-salinity-depth characteristics flexibly and responsively. The proposed approach has been applied to a real-time visualization system of ocean data, which may facilitate the comparison of water masses by aggregating the data without degrading the discriminating capabilities. This system provides an interface for querying geographic locations with similar temperature-salinity-depth characteristics interactively and for tracking specific patterns of water masses, such as the Kuroshio near Taiwan or those in the South China Sea.

Keywords: water mass, Gaussian mixture model, data visualization, system framework

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Authors: Wiyanti Fransisca Simanullang, Shinya Yamanaka

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Grinding method was used to control the active site and to improve the specific surface area (SSA) of calcium oxide (CaO) derived from scallop shell as a sustainable resource. The dry grinding of CaO with acetone and tertiary butanol as a liquid additive was carried out using a planetary ball mill with a laboratory scale. The experiments were operated by stepwise addition with time variations to determine the grinding limit. The active site of CaO was measured by X-Ray Diffraction and FT-IR. The SSA variations of products with grinding time were measured by BET method. The morphology structure of CaO was observed by SEM. The use of liquid additive was effective for increasing the SSA and controlling the active site of CaO. SSA of CaO was increased in proportion to the amount of the liquid additive and the grinding time. The performance of CaO as a solid base catalyst for biodiesel production was tested in the transesterification reaction of used cooking oil to produce fatty acid methyl ester (FAME).

Keywords: active site, calcium oxide, grinding, specific surface area

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Authors: Nihal Atif Salim

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To improve the quality of life in cities, a variety of interventions are used. Noise is a substantial and important sort of pollution that has a negative impact on the urban environment and human health. According to the complaint survey, it ranks second among environmental contamination complaints (conducted by EEAA in 2019). The most significant source of noise in the city is traffic noise. In order to improve the sound urban environment, many physical techniques are applied. In the local area, noise barriers are considered as one of the most appropriate physical techniques along existing traffic routes. Alexandria is Egypt's second-largest city after Cairo. It is located along the Mediterranean Sea, and El- Gish Road is one of the city's main arteries. It impacts the waterfront promenade that extends along with the city by a high level of traffic noise. The purpose of this paper is to clarify the design considerations for the most appropriate noise barrier type along with the promenade, with the goal of improving the Quality of Life (QOL) and the sonic urban environment specifically. The proposed methodology focuses on how noise affects human perception and the environment. Then it delves into the various physical noise control approaches. After that, the paper discusses sustainable design decisions making. Finally, look into the importance of incorporating sustainability into design decisions making. Three stages will be followed in the case study. The first stage involves doing a site inspection and using specific sound measurement equipment (a noise level meter) to measure the noise level along the promenade at many sites, and the findings will be shown on a noise map. The second step is to inquire about the site's user experience. The third step is to investigate the various types of noise barriers and their effects on QOL along existing routes in order to select the most appropriate type. The goal of this research is to evaluate the suitable design of noise barriers that fulfill environmental and social perceptions while maintaining a balanced approach to the noise issue in order to improve QOL along existing roadways in the local area.

Keywords: noise pollution, sonic urban environment, traffic noise, noise barrier, acoustic sustainability, noise reduction techniques

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Authors: Maryam Kiani

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The aim of this study was to investigate the influence of nanoparticles additive on the properties of fly ash-based geopolymer. The geopolymer samples were prepared using fly ash as the primary source material, along with an alkali activator solution and different concentrations of carbon black additive. The effects of nanoparticles flexural strength, water absorption, and micro-structural properties of the cured samples. The results revealed that the inclusion of nanoparticles additive significantly enhanced the mechanical and electrical properties of the geopolymer binder. Micro-structural analysis using scanning electron microscopy (SEM) revealed a more compact and homogeneous structure in the geopolymer samples with nanoparticles. The dispersion of nanoparticles particles within the geopolymer matrix was observed, suggesting improved inter-particle bonding and increased density. Overall, this study demonstrates the positive impact of nanoparticles additive on the qualities of fly ash-based geopolymer, emphasizing its potential as an effective enhancer for geopolymer binder applications for the development of construction and infrastructure for energy buildings.

Keywords: fly-ash, geopolymer, energy buildings, nanotechnology

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Authors: Kai Chen, Shuguang Cui, Feng Yin

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Gaussian process (GP) with spectral mixture (SM) kernel demonstrates flexible non-parametric Bayesian learning ability in modeling unknown function. In this work a novel time-varying and non-stationary convolution spectral mixture (TN-CSM) kernel with a significant enhancing of interpretability by using process convolution is introduced. A way decomposing the SM component into an auto-convolution of base SM component and parameterizing it to be input dependent is outlined. Smoothly, performing a convolution between two base SM component yields a novel structure of non-stationary SM component with much better generalized expression and interpretation. The TN-CSM perfectly allows compatibility with the stationary SM kernel in terms of kernel form and spectral base ignored and confused by previous non-stationary kernels. On synthetic and real-world datatsets, experiments show the time-varying characteristics of hyper-parameters in TN-CSM and compare the learning performance of TN-CSM with popular and representative non-stationary GP.

Keywords: Gaussian process, spectral mixture, non-stationary, convolution

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Authors: Muhammad Arif Jalil, Xaythavay Luangvilay, Montree Bunruangses, Somchat Sonasang, Preecha Yupapin

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Black and white holes form the entangled pair⟨BH│WH⟩, where a white hole occurs when the particle moves at the same speed as light. The entangled black-white hole pair is at the center with the radian between the gap. When the speed of particle motion is slower than light, the black hole is gravitational (positive gravity), where the white hole is smaller than the black hole. On the downstream side, the entangled pair appears to have a black hole outside the gap increases until the white holes disappear, which is the emptiness paradox. On the upstream side, when moving faster than light, white holes form times tunnels, with black holes becoming smaller. It will continue to move faster and further when the black hole disappears and becomes a wormhole (Singularity) that is only a white hole in emptiness (Emptiness). This research studies use of black and white holes generated by a two-level circuit for communication transmission carriers, in which high ability and capacity of data transmission can be obtained. The black and white hole pair can be generated by the two-level system circuit when the speech of a particle on the circuit is equal to the speed of light. The black hole forms when the particle speed has increased from slower to equal to the light speed, while the white hole is established when the particle comes down faster than light. They are bound by the entangled pair, signal and idler, ⟨Signal│Idler⟩, and the virtual ones for the white hole, which has an angular displacement of half of π radian. A two-level system is made from an electronic circuit to create black and white holes bound by the entangled bits that are immune or cloning-free from thieves. Start by creating a wave-particle behavior when its speed is equal to light black hole is in the middle of the entangled pair, which is the two bit gate. The required information can be input into the system and wrapped by the black hole carrier. A timeline (Tunnel) occurs when the wave-particle speed is faster than light, from which the entangle pair is collapsed. The transmitted information is safely in the time tunnel. The required time and space can be modulated via the input for the downlink operation. The downlink is established when the particle speed is given by a frequency(energy) form is down and entered into the entangled gap, where this time the white hole is established. The information with the required destination is wrapped by the white hole and retrieved by the clients at the destination. The black and white holes are disappeared, and the information can be recovered and used.

Keywords: cloning free, time machine, teleportation, two-level system

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Authors: Ji Xi, Cheng Song Chin, Ehsan Mesbahi

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Structure-borne noise is an important aspect of offshore platform sound field. It can be generated either directly by vibrating machineries induced mechanical force, indirectly by the excitation of structure or excitation by incident airborne noise. Therefore, limiting of the transmission of vibration energy throughout the offshore platform is the key to control the structure-borne noise. This is usually done by introducing damping treatment to the steel structures. Two types of damping treatment using on-board are presented. By conducting a statistical energy analysis (SEA) simulation on a jack-up rig, the noise level in the source room, the neighboring rooms, and remote living quarter cabins are compared before and after the damping treatments been applied. The results demonstrated that, in the source neighboring room and living quarter area, there is a significant noise reduction with the damping treatment applied, whereas in the source room where air-borne sound predominates that of structure-borne sound, the impact is not obvious. The subsequent optimization design of damping treatment in the offshore platform can be made which enable acoustic professionals to implement noise control during the design stage for offshore crews’ hearing protection and habitant comfortability.

Keywords: statistical energy analysis, damping treatment, noise control, offshore platform

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Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

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In this paper, we present the human action recognition method using the variational Bayesian HMM with the Dirichlet process mixture (DPM) of the Gaussian-Wishart emission model (GWEM). First, we define the Bayesian HMM based on the Dirichlet process, which allows an infinite number of Gaussian-Wishart components to support continuous emission observations. Second, we have considered an efficient variational Bayesian inference method that can be applied to drive the posterior distribution of hidden variables and model parameters for the proposed model based on training data. And then we have derived the predictive distribution that may be used to classify new action. Third, the paper proposes a process of extracting appropriate spatial-temporal feature vectors that can be used to recognize a wide range of human behaviors from input video image. Finally, we have conducted experiments that can evaluate the performance of the proposed method. The experimental results show that the method presented is more efficient with human action recognition than existing methods.

Keywords: human action recognition, Bayesian HMM, Dirichlet process mixture model, Gaussian-Wishart emission model, Variational Bayesian inference, prior distribution and approximate posterior distribution, KTH dataset

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Authors: Mohammadreza Judaki, Hosein Mohammadnezhad Shourkaei

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Usually, noise generated by industrial units, is a pollution and disturbs people and causes problems for human health and sometimes these units will be closed because they cannot eliminate this pollution. Small-scale power plants usually are built close to residential areas, and noise generated by these power plants is an important factor in choosing their location and their design. Materials used to reduce noise are studied by measuring their absorption and reflection index numerically and experimentally. We can use MIKI model (Yasushi Miki, 1990) to simulate absorption index by using software like Ansys or Soundflow and compare calculation results with experimental simulation data. We consider high frequency sounds of power plant engines octave band diagram because dB value of high frequency noise is more noticeable for human ears. To prove this, in this study we first will study calculating octave band of engines exhausts and then we will study acoustic behavior of materials that we will use in high frequencies and this will give us our optimum noise reduction plan.

Keywords: acoustic materials, eliminating engine noise, octave level diagram, power plant noise

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Authors: Rafael Felipe Guatura da Silva, José Luis Gomes da Silva, Luiz Antonio, Ferreira Perrone de Brito

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Noise can cause serious damage to human health, such as hearing loss, stress, irritability, fatigue, and others. Aviation is a place where your entire process should be work out with the utmost attention and commitment of human resources, thus the need to study the effects of noise in this sector, as aeronautical noise levels are high. This study aimed to evaluate the impact of noise pollution on the performance of professionals regarding the fatigue generated by aeronautical noise and time to noise exposure. The methodology used consists of measurements of sound pressure levels at 42 points of the aerodrome. The selected points are located inside the hangars and outside the airfield hangars. All points chosen are close to the professionals' work areas, seeking to identify the sound pressure levels to which they submitted. The other part of the research used the principle on the application of a self-report questionnaire to a sample of 207 people working inside the aerodrome. The 207 professionals surveyed consist of aircraft mechanics, pilots, maintenance managers, and administrative professionals. The questionnaire was intended to evaluate the knowledge that professionals have about health risks caused by sound exposure as well as to identify diseases that professionals have, and that may be associated with exposure to high levels of sound pressure. Preliminary results identify points with sound pressure levels of up to 91.7 dB, thus highlighting the need for the use of personal protective equipment that reduces noise exposure. It was also identified a large number of professionals who are bothered by the sound exposure and approximately 25% of professionals interviewed reported having a hearing disorder.

Keywords: aeronautical noise, fatigue, noise and health, noise management

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Authors: Sylvain Amailland, Jean-Hugh Thomas, Charles Pézerat, Romuald Boucheron, Jean-Claude Pascal

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The noise requirements for naval and research vessels have seen an increasing demand for quieter ships in order to fulfil current regulations and to reduce the effects on marine life. Hence, new methods dedicated to the characterization of propeller noise, which is the main source of noise in the far-field, are needed. The study of cavitating propellers in closed-section is interesting for analyzing hydrodynamic performance but could involve significant difficulties for hydroacoustic study, especially due to reverberation and boundary layer noise in the tunnel. The aim of this paper is to present a numerical methodology for the identification of hydroacoustic sources on marine propellers using hydrophone arrays in a large hydrodynamic tunnel. The main difficulties are linked to the reverberation of the tunnel and the boundary layer noise that strongly reduce the signal-to-noise ratio. In this paper it is proposed to estimate the reflection coefficients using an inverse method and some reference transfer functions measured in the tunnel. This approach allows to reduce the uncertainties of the propagation model used in the inverse problem. In order to reduce the boundary layer noise, a cleaning algorithm taking advantage of the low rank and sparse structure of the cross-spectrum matrices of the acoustic and the boundary layer noise is presented. This approach allows to recover the acoustic signal even well under the boundary layer noise. The improvement brought by this method is visible on acoustic maps resulting from beamforming and DAMAS algorithms.

Keywords: acoustic imaging, boundary layer noise denoising, inverse problems, model adaptation

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Authors: Ravindra B. Patil, P. Krishnamoorthy, Shriram Sethuraman

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This work proposes a novel Gaussian Mixture Model (GMM) based approach for accurate tracking of the arterial wall and subsequent computation of the distension waveform using Radio Frequency (RF) ultrasound signal. The approach was evaluated on ultrasound RF data acquired using a prototype ultrasound system from an artery mimicking flow phantom. The effectiveness of the proposed algorithm is demonstrated by comparing with existing wall tracking algorithms. The experimental results show that the proposed method provides 20% reduction in the error margin compared to the existing approaches in tracking the arterial wall movement. This approach coupled with ultrasound system can be used to estimate the arterial compliance parameters required for screening of cardiovascular related disorders.

Keywords: distension waveform, Gaussian Mixture Model, RF ultrasound, arterial wall movement

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Authors: Donatella Giuliani

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In this research, we propose an unsupervised grayscale image segmentation method based on a combination of the Firefly Algorithm and the Gaussian Mixture Model. Firstly, the Firefly Algorithm has been applied in a histogram-based research of cluster means. The Firefly Algorithm is a stochastic global optimization technique, centered on the flashing characteristics of fireflies. In this context it has been performed to determine the number of clusters and the related cluster means in a histogram-based segmentation approach. Successively these means are used in the initialization step for the parameter estimation of a Gaussian Mixture Model. The parametric probability density function of a Gaussian Mixture Model is represented as a weighted sum of Gaussian component densities, whose parameters are evaluated applying the iterative Expectation-Maximization technique. The coefficients of the linear super-position of Gaussians can be thought as prior probabilities of each component. Applying the Bayes rule, the posterior probabilities of the grayscale intensities have been evaluated, therefore their maxima are used to assign each pixel to the clusters, according to their gray-level values. The proposed approach appears fairly solid and reliable when applied even to complex grayscale images. The validation has been performed by using different standard measures, more precisely: the Root Mean Square Error (RMSE), the Structural Content (SC), the Normalized Correlation Coefficient (NK) and the Davies-Bouldin (DB) index. The achieved results have strongly confirmed the robustness of this gray scale segmentation method based on a metaheuristic algorithm. Another noteworthy advantage of this methodology is due to the use of maxima of responsibilities for the pixel assignment that implies a consistent reduction of the computational costs.

Keywords: clustering images, firefly algorithm, Gaussian mixture model, meta heuristic algorithm, image segmentation

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Authors: Efrain Rodriguez, Sergio Pertuz, Cristhian Riano

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Tool-path generation is an essential step in the FFF (Fused Filament Fabrication)-based Additive Manufacturing (AM) process planning. In the manufacture of a mechanical part by using additive processes, high resource consumption and prolonged production times are inherent drawbacks of these processes mainly due to non-optimized tool-path generation. In this work, we propose a heuristic-search intelligent algorithm-based approach for optimized tool-path generation for FFF-based AM. The main benefit of this approach is a significant reduction of travels without material deposition when the AM machine performs moves without any extrusion. The optimization method used reduces the number of travels without extrusion in comparison with commercial software as Slic3r or Cura Engine, which means a reduction of production time.

Keywords: additive manufacturing, tool-path optimization, fused filament fabrication, process planning

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Authors: Thirsa Sherry, Utkarsh Shrivastav, Kannan B. T., Iynthezhuton K.

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The field of aerodynamics and aeroacoustics remains one of the most poignant and well-researched fields of today. The current paper aims to investigate the predominant problem concerning the effects of noise of varying frequencies and waveforms on airflow surrounding an airfoil. Using a single speaker beneath the airfoil at different positions, we wish to simulate the effects of sound directly impinging on an airfoil and study its direct effects on airflow. We wish to study the same using smoke visualization methods with incense as our smoke-generating material in a variable-speed subsonic wind tunnel. Using frequencies and wavelengths similar to those of common engine noise, we wish to simulate real-world conditions of engine noise interfering with airflow and document the arising trends. These results will allow us to look into the real-world effects of noise on airflow and how to minimize them and expand on the possible relation between waveforms and noise. The parameters used in the study include frequency, Reynolds number, waveforms, angle of attack, and the effects on airflow when varying these parameters.

Keywords: engine noise, aeroacoustics, acoustic excitation, low speed

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Authors: Noha Al Majid, Said Mazer, Moulhime El Bekkali, Catherine Algani, Mahmoud Mehdi

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A low noise figure (NF) and high linearity V-band Low Noise Amplifier (LNA) is reported in this article. The LNA compromises a three-stage cascode configuration. This LNA will be used as a part of a WPAN (Wireless Personal Area Network) receiver in the millimeter-wave band at 60 GHz. It is designed according to the MMIC technology (Monolithic Microwave Integrated Circuit) in PH 15 process from UMS foundry and uses a 0.15 μm GaAs PHEMT (Pseudomorphic High Electron Mobility Transistor). The particularity of this LNA compared to other LNAs in literature is its very low noise figure which is equal to 1 dB and its high linearity (IIP3 is about 22 dB). The LNA consumes 0.24 Watts, achieving a high gain which is about 23 dB, an input return loss better than -10 dB and an output return loss better than -8 dB.

Keywords: low noise amplifier, V-band, MMIC technology, LNA, amplifier, cascode, pseudomorphic high electron mobility transistor (PHEMT), high linearity

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Authors: Leonardo Herrera, Shield B. Lin, Stephen J. Montgomery-Smith, Ziraguen O. Williams

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Three control algorithms: Proportional-Integral-Derivative, Linear-Quadratic-Gaussian, and Linear-Quadratic-Gaussian with the shift, were applied to the computer simulation of a one-directional dynamic model of a Stewart Platform. The goal was to compare the dynamic system responses under the three control algorithms and to minimize the impact energy when simulating spacecraft docking operations. Equations were derived for the control algorithms and the input and output of the feedback control system. Using MATLAB, Simulink diagrams were created to represent the three control schemes. A switch selector was used for the convenience of changing among different controllers. The simulation demonstrated the controller using the algorithm of Linear-Quadratic-Gaussian with the shift resulting in the lowest impact energy.

Keywords: controller, Stewart platform, docking operation, spacecraft

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Authors: Yulu Zhang, Atushi Teramoto, Taka-Aki Ohkubo

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In this study, the effect of expansive additives on autogenous shrinkage and delayed expansion of ultra-high strength mortar was explored. The specimens made for the study were composed of ultra-high strength mortar, which was mixed with ettringite-lime composite type expansive additive. Two series of experiments were conducted with the specimens. The experimental results confirmed that the autogenous shrinkage of specimens was effectively decreased by increasing the proportion of the expansive additive. On the other hand, for the specimens, which had 7% expansive additive, and were cured for seven days at a constant temperature of 20°C, and then cured for a long time in either in an underwater, moist (Relative humidity: 100%) or dry air (Relative humidity: 60%) environment, excessively large expansion strain occurred. Specifically, typical turtle shell-like swelling expansion cracks were confirmed in the specimens that underwent long-term curing in an underwater and moist environment. According to the result of hydration analysis, the formation of expansive substances, calcium hydroxide and alumina, ferric oxide, tri-sulfate contribute to the occurrence of delayed expansion.

Keywords: ultra-high strength mortar, expansive additive, autogenous shrinkage, delayed expansion

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Authors: Paolo Lenzuni

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Cost-effectiveness of noise abatement treatments at the workplace has not yet received adequate consideration. Furthermore, most of the published work is focused on productivity, despite the poor correlation of this quantity with noise levels. There is currently no tool to estimate the social benefit associated to a specific noise abatement treatment, and no comparison among different options is accordingly possible. In this paper, we present an algorithm which has been developed to predict the cost-effectiveness of any planned noise control treatment in a workplace. This algorithm is based the estimates of hearing threshold shifts included in ISO 1999, and on compensations that workers are entitled to once their work-related hearing impairments have been certified. The benefits of a noise abatement treatment are estimated by means of the lower compensation costs which are paid to the impaired workers. Although such benefits have no real meaning in strictly monetary terms, they allow a reliable comparison between different treatments, since actual social costs can be assumed to be proportional to compensation costs. The existing European legislation on occupational exposure to noise it mandates that the noise exposure level be reduced below the upper action limit (85 dBA). There is accordingly little or no motivation for employers to sustain the extra costs required to lower the noise exposure below the lower action limit (80 dBA). In order to make this goal more appealing for employers, the algorithm proposed in this work also includes an ad-hoc element that promotes actions which bring the noise exposure down below 80 dBA. The algorithm has a twofold potential: 1) it can be used as a quality index to promote cost-effective practices; 2) it can be added to the existing criteria used by workers’ compensation authorities to evaluate the cost-effectiveness of technical actions, and support dedicated employers.

Keywords: cost-effectiveness, noise, occupational exposure, treatment

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Authors: Ben Soltane Cheima, Ittansa Yonas Kelbesa

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Speaker Identification (SI) is the task of establishing identity of an individual based on his/her voice characteristics. The SI task is typically achieved by two-stage signal processing: training and testing. The training process calculates speaker specific feature parameters from the speech and generates speaker models accordingly. In the testing phase, speech samples from unknown speakers are compared with the models and classified. Even though performance of speaker identification systems has improved due to recent advances in speech processing techniques, there is still need of improvement. In this paper, a Closed-Set Tex-Independent Speaker Identification System (CISI) based on a Multiple Classifier System (MCS) is proposed, using Mel Frequency Cepstrum Coefficient (MFCC) as feature extraction and suitable combination of vector quantization (VQ) and Gaussian Mixture Model (GMM) together with Expectation Maximization algorithm (EM) for speaker modeling. The use of Voice Activity Detector (VAD) with a hybrid approach based on Short Time Energy (STE) and Statistical Modeling of Background Noise in the pre-processing step of the feature extraction yields a better and more robust automatic speaker identification system. Also investigation of Linde-Buzo-Gray (LBG) clustering algorithm for initialization of GMM, for estimating the underlying parameters, in the EM step improved the convergence rate and systems performance. It also uses relative index as confidence measures in case of contradiction in identification process by GMM and VQ as well. Simulation results carried out on voxforge.org speech database using MATLAB highlight the efficacy of the proposed method compared to earlier work.

Keywords: feature extraction, speaker modeling, feature matching, Mel frequency cepstrum coefficient (MFCC), Gaussian mixture model (GMM), vector quantization (VQ), Linde-Buzo-Gray (LBG), expectation maximization (EM), pre-processing, voice activity detection (VAD), short time energy (STE), background noise statistical modeling, closed-set tex-independent speaker identification system (CISI)

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Authors: R. Sabre, W. Horrigue, J. C. Simon

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This paper is interested in two difficulties encountered in practice when observing a continuous time process. The first is that we cannot observe a process over a time interval; we only take discrete observations. The second is the process frequently observed with a constant additive error. It is important to give an estimator of the spectral density of such a process taking into account the additive observation error and the choice of the discrete observation times. In this work, we propose an estimator based on the spectral smoothing of the periodogram by the polynomial Jackson kernel reducing the additive error. In order to solve the aliasing phenomenon, this estimator is constructed from observations taken at well-chosen times so as to reduce the estimator to the field where the spectral density is not zero. We show that the proposed estimator is asymptotically unbiased and consistent. Thus we obtain an estimate solving the two difficulties concerning the choice of the instants of observations of a continuous time process and the observations affected by a constant error.

Keywords: spectral density, stable processes, aliasing, periodogram

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Authors: Min-ju Kwon, Chae-won Kim, Jeong-yun Seo, Hee-guk Chae, Yong-seo Koo

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In this paper, we presented the LDO (low-dropout) regulator which enhanced the PSRR by applying the constant current source generation technique through the BGR (Band Gap Reference) to form the noise sensing circuit. The current source through the BGR has a constant current value even if the applied voltage varies. Then, the noise sensing circuit, which is composed of the current source through the BGR, operated between the error amplifier and the pass transistor gate of the LDO regulator. As a result, the LDO regulator has a PSRR of -68.2 dB at 1k Hz, -45.85 dB at 1 MHz and -45 dB at 10 MHz. the other performance of the proposed LDO was maintained at the same level of the conventional LDO regulator.

Keywords: LDO regulator, noise sensing circuit, current reference, pass transistor

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Authors: A. Ikhlef

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Image noise in computed tomography, is mainly caused by the statistical noise, system noise reconstruction algorithm filters. Since last few years, low dose x-ray imaging became more and more desired and looked as a technical differentiating technology among CT manufacturers. In order to achieve this goal, several technologies and techniques are being investigated, including both hardware (integrated electronics and photon counting) and software (artificial intelligence and machine learning) based solutions. From a hardware point of view, electronic noise could indeed be a potential driver for low and ultra-low dose imaging. We demonstrated that the reduction or elimination of this term could lead to a reduction of dose without affecting image quality. Also, in this study, we will show that we can achieve this goal using conventional electronics (low cost and affordable technology), designed carefully and optimized for maximum detective quantum efficiency. We have conducted the tests using large imaging objects such as 30 cm water and 43 cm polyethylene phantoms. We compared the image quality with conventional imaging protocols with radiation as low as 10 mAs (<< 1 mGy). Clinical validation of such results has been performed as well.

Keywords: computed tomography, electronic noise, scintillation detector, x-ray detector

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Authors: Gustavo Menezes De Souza Melo, Arnaud Heitz, Johannes Henrich Schleifenbaum

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Additive manufacturing is a growing market that is taking over in many industries as it offers numerous advantages like new design possibilities, weight-saving solutions, ease of manufacture, and simplification of assemblies. These are all unquestionable technical or financial assets. As to the environmental aspect, additive manufacturing is often discussed whether it is the best solution to decarbonize our industries or if conventional manufacturing remains cleaner. This work presents a life cycle assessment (LCA) comparison based on the technological case of a motorbike swing-arm. We compare the original equipment manufacturer part made with conventional manufacturing (CM) methods to an additive manufacturing (AM) version printed using the laser powder bed fusion process. The AM version has been modified and optimized to achieve better dynamic performance without any regard to weight saving. Lightweight not being a priority in the creation of the 3D printed part brings us a unique perspective in this study. To achieve the LCA, we are using the open-source life cycle, and sustainability software OpenLCA combined with the ReCiPe 2016 at midpoint and endpoint level method. This allows the calculation and the presentation of the results through indicators such as global warming, water use, resource scarcity, etc. The results are then showing the relative impact of the AM version compared to the CM one and give us a key to understand and answer questions about the environmental sustainability of additive manufacturing.

Keywords: additive manufacturing, environmental impact, life cycle assessment, laser powder bed fusion

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Authors: Malika Foudia, Larbi Zerroual

Abstract:

The objective of this work is to improve the electrical proprieties of lead-acid battery with the addition of additives in electrolyte and in the cured plates before oxidation. The results showed that the addition of surfactant in sulfuric acid and 3% mineral additive in the cured plates change the morphology and the crystallite size of PAM after oxidation. The discharge capacity increases with the decrease of the crystallite size and the resistance of the active mass. This shows that the addition of mineral additive and the surfactant additive to the PAM, the electrical performance and the cycle life of lead- acid battery are significantly increases.

Keywords: lead-acid battery, additives, positive plate, impedance (EIS).

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Authors: N. Alhazmi

Abstract:

Knowing the thermodynamics properties of hydrocarbons is vital when it comes to analyzing the related chemical reaction outcomes and understanding the reaction process, especially in terms of petrochemical industrial applications, combustions, and catalytic reactions. However, measuring the thermodynamics properties experimentally is time-consuming and costly. In this paper, Gaussian process regression (GPR) has been used to directly predict the main thermodynamic properties - standard enthalpy of formation, standard entropy, and heat capacity -for more than 360 cyclic and non-cyclic alkanes, alkenes, and alkynes. A simple workflow has been proposed that can be applied to directly predict the main properties of any hydrocarbon by knowing its descriptors and chemical structure and can be generalized to predict the main properties of any material. The model was evaluated by calculating the statistical error R², which was more than 0.9794 for all the predicted properties.

Keywords: thermodynamic, Gaussian process regression, hydrocarbons, regression, supervised learning, entropy, enthalpy, heat capacity

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Authors: Farrukh Jamil, Ala'a H. Al-Muhtaseb, Lamya Al-Haj, Mohab A. Al-Hinai

Abstract:

Glycerol is considered as high boiling polar triol and immiscible with fossil fuel fractions due to which it is transformed into its respective ketals and acetals which help to improve the quality of diesel emitting less amount of aldehydes and carbon monoxide. Solketal visual appearance is transparent, and it is odorless organic liquid used as a fuel additive for diesel to improve its cold flow properties. Condensation of bio-glycerol with bio-acetone in presence of beta zeolite has been done for synthesizing solketal. It was observed that glycerol conversion and selectivity of solketal was largely effected by temperature, as it increases from 40 ºC to 60 ºC the conversion of glycerol rises from 80.04 % to 94.26 % and selectivity of solketal from 80.0 % to 94.21 % but further increase in temperature to 100 ºC glycerol conversion reduced to 93.06 % and solketal selectivity to 92.08 %. At the optimum conditions, the bio-glycerol conversion and solketal yield were about 94.26% and 94.21wt% respectively. This process offers an attractive route for converting bio-glycerol, the main by-product of biodiesel to solketal with bio-acetone; a value-added green product with potential industrial applications as a valuable green fuel additive or combustion promoter for gasoline/diesel engines.

Keywords: bio-glycerol, catalyst, green additive, biomass

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Authors: Funke Morenike Jiyah, Joshua Jiyah

Abstract:

The occurrence of various health issues have been linked to excessive noise pollution in all works of life as evident in many research efforts. This study provides empirical analysis of the effects of noise pollution on the well-being of the residents of Bida Local Government Area, Niger State, Nigeria. The study adopted a case study research design, involving cross-sectional procedure. Field observations and medical reports were obtained to support the respondents’ perception on the state of their well-being. The sample size for the study was selected using the housing stock in the various wards. One major street in each ward was selected. A total of 1,833 buildings were counted along the sampled streets and 10% of this was selected for the administration of structured questionnaire.The environmental quality of the wards was determined by measuring the noise level using Testo 815 noise meters. The result revealed that Bariki ward which houses the GRA has the lowest noise level of 37.8 dB(A)while the noise pollution levels recorded in the other thirteen wards were all above the recommended levels. The average ambient noise level in sawmills, commercial centres, road junctions and industrial areas were above 90 dB(A). The temporal record from the Federal Medical Centre, Bida revealed that, apart from malaria, hypertension (5,614 outpatients) was the most prevalent health issue in 2013 alone. The paper emphasised the need for compatibility consideration in the choice of residential location, the use of ear muffler and effective enforcement of zoning regulations.

Keywords: bida, decibels, environmental quality, noise, well-being

Procedia PDF Downloads 110