Search results for: headspace extraction temperature

Authors: J.-C. Cexus, A.O. Boudraa

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In this paper, a new approach for target recognition based on the Empirical mode decomposition (EMD) algorithm of Huang etal. [11] and the energy tracking operator of Teager [13]-[14] is introduced. The conjunction of these two methods is called Teager-Huang analysis. This approach is well suited for nonstationary signals analysis. The impulse response (IR) of target is first band pass filtered into subsignals (components) called Intrinsic mode functions (IMFs) with well defined Instantaneous frequency (IF) and Instantaneous amplitude (IA). Each IMF is a zero-mean AM-FM component. In second step, the energy of each IMF is tracked using the Teager energy operator (TEO). IF and IA, useful to describe the time-varying characteristics of the signal, are estimated using the Energy separation algorithm (ESA) algorithm of Maragos et al .[16]-[17]. In third step, a set of features such as skewness and kurtosis are extracted from the IF, IA and IMF energy functions. The Teager-Huang analysis is tested on set of synthetic IRs of Sonar targets with different physical characteristics (density, velocity, shape,? ). PCA is first applied to features to discriminate between manufactured and natural targets. The manufactured patterns are classified into spheres and cylinders. One hundred percent of correct recognition is achieved with twenty three echoes where sixteen IRs, used for training, are free noise and seven IRs, used for testing phase, are corrupted with white Gaussian noise.

Keywords: Target recognition, Empirical mode decomposition, Teager-Kaiser energy operator, Features extraction.

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Authors: Hajar Sadeghi, Payman Moallem, S. Amirhassn Monadjemi

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This paper presents a new feature based dense stereo matching algorithm to obtain the dense disparity map via dynamic programming. After extraction of some proper features, we use some matching constraints such as epipolar line, disparity limit, ordering and limit of directional derivative of disparity as well. Also, a coarseto- fine multiresolution strategy is used to decrease the search space and therefore increase the accuracy and processing speed. The proposed method links the detected feature points into the chains and compares some of the feature points from different chains, to increase the matching speed. We also employ color stereo matching to increase the accuracy of the algorithm. Then after feature matching, we use the dynamic programming to obtain the dense disparity map. It differs from the classical DP methods in the stereo vision, since it employs sparse disparity map obtained from the feature based matching stage. The DP is also performed further on a scan line, between any matched two feature points on that scan line. Thus our algorithm is truly an optimization method. Our algorithm offers a good trade off in terms of accuracy and computational efficiency. Regarding the results of our experiments, the proposed algorithm increases the accuracy from 20 to 70%, and reduces the running time of the algorithm almost 70%.

Keywords: Chain Correspondence, Color Stereo Matching, Dynamic Programming, Epipolar Line, Stereo Vision.

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Authors: V. Balanica, W. I. D. Rae, M. Caramihai, S. Acho, C. P. Herbst

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Mammographic images and data analysis to facilitate modelling or computer aided diagnostic (CAD) software development should best be done using a common database that can handle various mammographic image file formats and relate these to other patient information. This would optimize the use of the data as both primary reporting and enhanced information extraction of research data could be performed from the single dataset. One desired improvement is the integration of DICOM file header information into the database, as an efficient and reliable source of supplementary patient information intrinsically available in the images. The purpose of this paper was to design a suitable database to link and integrate different types of image files and gather common information that can be further used for research purposes. An interface was developed for accessing, adding, updating, modifying and extracting data from the common database, enhancing the future possible application of the data in CAD processing. Technically, future developments envisaged include the creation of an advanced search function to selects image files based on descriptor combinations. Results can be further used for specific CAD processing and other research. Design of a user friendly configuration utility for importing of the required fields from the DICOM files must be done.

Keywords: Database Integration, Mammogram Classification, Tumour Classification, Computer Aided Diagnosis.

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Authors: Adrienne Kline, Jaydip Desai

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Electroencephalogram (EEG) is a noninvasive technique that registers signals originating from the firing of neurons in the brain. The Emotiv EEG Neuroheadset is a consumer product comprised of 14 EEG channels and was used to record the reactions of the neurons within the brain to two forms of stimuli in 10 participants. These stimuli consisted of auditory and visual formats that provided directions of ‘right’ or ‘left.’ Participants were instructed to raise their right or left arm in accordance with the instruction given. A scenario in OpenViBE was generated to both stimulate the participants while recording their data. In OpenViBE, the Graz Motor BCI Stimulator algorithm was configured to govern the duration and number of visual stimuli. Utilizing EEGLAB under the cross platform MATLAB®, the electrodes most stimulated during the study were defined. Data outputs from EEGLAB were analyzed using IBM SPSS Statistics® Version 20. This aided in determining the electrodes to use in the development of a brain-machine interface (BMI) using real-time EEG signals from the Emotiv EEG Neuroheadset. Signal processing and feature extraction were accomplished via the Simulink® signal processing toolbox. An Arduino™ Duemilanove microcontroller was used to link the Emotiv EEG Neuroheadset and the right and left Mecha TE™ Hands.

Keywords: Brain-machine interface, EEGLAB, emotiv EEG neuroheadset, openViBE, simulink.

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Authors: Siti Kudnie Sahari, Jane Chai Hai Sing, Khairuddin Ab. Hamid

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Shrunken patterning for integrated device manufacturing requires surface cleanliness and surface smoothness in wet chemical processing [1]. It is necessary to control all process parameters perfectly especially for the common cleaning technique RCA clean (SC-1 and SC-2) [2]. In this paper the characteristic and effect of surface preparation parameters are discussed. The properties of RCA wet chemical processing in silicon technology is based on processing time, temperature, concentration and megasonic power of SC-1 and QDR. An improvement of wafer surface preparation by the enhanced variables of the wet cleaning chemical process is proposed.

Keywords: RCA, SC-1, SC-2, QDR

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Authors: Valentina Obradović, Josip Mesić, Maja Ergović Ravančić, Kamila Mijowska, Brankica Svitlica

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French oak and American oak barrels are most famous all over the world, but barrels of different origin can also be used for obtaining high quality wines. The aim of this research was to compare the influence of different Slovenian (Croatian) and French oak barrels on the quality of Chardonnay wine. Grapes were grown in the Croatian wine growing region of Kutjevo in 2015. Chardonnay wines were tested for basic oenological parameters (alcohol, extract, reducing sugar, SO₂, acidity), total polyphenols content (Folin-Ciocalteu method), antioxidant activity (ABTS and DPPH method) and colour density. Sensory evaluation was performed by students of viticulture/oenology. Samples produced by classical fermentation and ageing in French oak barrels had better results for polyphenols and sensory evaluation (especially low toasting level) than samples in Slovenian barrels. All tested samples were scored as a “quality” or “premium quality” wines. Sur lie method of fermentation and ageing in Slovenian oak barrel had very good extraction of polyphenols and high antioxidant activity with the usage of authentic yeasts, while commercial yeast strain resulted in worse chemical and sensory parameters.

Keywords: Chardonnay, French oak, Slovenian oak, sur lie.

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Authors: M. Cuevas-González, O. Monserrat, A. Barra, C. Reyes-Carmona, R. M. Mateos, J. P. Galve, R. Sarro, M. Cantalejo, E. Peña, M. Martínez-Corbella, J. A. Luque, J. M. Azañón, A. Millares, M. Béjar, J. A. Navarro, L. Solari

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Geohazard prone areas require continuous monitoring to detect risks, understand the phenomena occurring in those regions and prevent disasters. Satellite interferometry (InSAR) has come to be a trustworthy technique for ground movement detection and monitoring in the last few years. InSAR based techniques allow to process large areas providing high number of displacement measurements at low cost. However, the results provided by such techniques are usually not easy to interpret by non-experienced users hampering its use for decision makers. This work presents a set of tools developed in the framework of different projects (Momit, Safety, U-Geohaz, Riskcoast) and an example of their use in the Granada Coastal area (Spain) is shown. The ADA (Active Displacement Areas) tool has been developed with the aim of easing the management, use and interpretation of InSAR based results. It provides a semi-automatic extraction of the most significant ADAs through the application ADAFinder tool. This tool aims to support the exploitation of the European Ground Motion Service (EU-GMS), which will offer reliable and systematic information on natural and anthropogenic ground motion phenomena across Europe.

Keywords: Ground displacements, InSAR, natural hazards, satellite imagery.

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Authors: Mohammed Nasir Kajama, Ngozi Claribelle Nwogu, Edward Gobina

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Pt/γ-Al2O3 membrane catalysts were prepared via an evaporative-crystallization deposition method. The obtained Pt/γ- Al2O3 catalyst activity was tested after characterization (SEM-EDAX observation, BET measurement, permeability assessment) in the catalytic oxidation of selected volatile organic compound (VOC) i.e. propane, fed in mixture of oxygen. The VOC conversion (nearly 90%) obtained by varying the operating temperature showed that flow-through membrane reactor might do better in the abatement of VOCs.

Keywords: VOC combustion, flow-through membrane reactor, platinum supported alumina catalysts.

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Authors: Ahmad Kayvani Fard, Yehia Manawi

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Qatar’s primary source of fresh water is through seawater desalination. Amongst the major processes that are commercially available on the market, the most common large scale techniques are Multi-Stage Flash distillation (MSF), Multi Effect distillation (MED), and Reverse Osmosis (RO). Although commonly used, these three processes are highly expensive down to high energy input requirements and high operating costs allied with maintenance and stress induced on the systems in harsh alkaline media. Beside that cost, environmental footprint of these desalination techniques are significant; from damaging marine eco-system, to huge land use, to discharge of tons of GHG and huge carbon footprint. Other less energy consuming techniques based on membrane separation are being sought to reduce both the carbon footprint and operating costs is membrane distillation (MD). Emerged in 1960s, MD is an alternative technology for water desalination attracting more attention since 1980s. MD process involves the evaporation of a hot feed, typically below boiling point of brine at standard conditions, by creating a water vapor pressure difference across the porous, hydrophobic membrane. Main advantages of MD compared to other commercially available technologies (MSF and MED) and specially RO are reduction of membrane and module stress due to absence of trans-membrane pressure, less impact of contaminant fouling on distillate due to transfer of only water vapor, utilization of low grade or waste heat from oil and gas industries to heat up the feed up to required temperature difference across the membrane, superior water quality, and relatively lower capital and operating cost. To achieve the objective of this study, state of the art flat-sheet cross-flow DCMD bench scale unit was designed, commissioned, and tested. The objective of this study is to analyze the characteristics and morphology of the membrane suitable for DCMD through SEM imaging and contact angle measurement and to study the water quality of distillate produced by DCMD bench scale unit. Comparison with available literature data is undertaken where appropriate and laboratory data is used to compare a DCMD distillate quality with that of other desalination techniques and standards. Membrane SEM analysis showed that the PTFE membrane used for the study has contact angle of 127º with highly porous surface supported with less porous and bigger pore size PP membrane. Study on the effect of feed solution (salinity) and temperature on water quality of distillate produced from ICP and IC analysis showed that with any salinity and different feed temperature (up to 70ºC) the electric conductivity of distillate is less than 5 μS/cm with 99.99% salt rejection and proved to be feasible and effective process capable of consistently producing high quality distillate from very high feed salinity solution (i.e. 100000 mg/L TDS) even with substantial quality difference compared to other desalination methods such as RO and MSF.

Keywords: Membrane Distillation, Waste Heat, Seawater Desalination, Membrane, Freshwater, Direct Contact Membrane Distillation

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Authors: Erika J. Ruíz, Jairo R. Cortes, Willian A. Aperador

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In this article was evaluated the protective effect of the alternative concrete obtained from the binary mixture of fly ash, and iron and steel slag. After mixing the cement with aggregates, structural steel was inserted in the matrix cementitious. The study was conducted comparatively with specimens exposed to natural conditions free of chloride ion. The chloride ion effect on the specimens accelerated under controlled conditions (3.5% NaCl and 25°C temperature). The impedance data were acquired in a range of 1 mHz to 100 kHz.

Keywords: Alternative concrete, corrosion, alkaline activation.

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Authors: Mutabar Shah, Muhammad Hassan Sayyad, Khasan S. Karimov

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Thin films of Nickel phthalocynine (NiPc) of different thicknesses (100, 150 and 200 nm) were deposited by thermal evaporator on glass substrates with preliminary deposited aluminum electrodes to form Al/NiPc/Al surface-type capacitive humidity sensors. The capacitance-humidity relationships of the sensors were investigated at humidity levels from 35 to 90% RH. It was observed that the capacitance value increases nonlinearly with increasing humidity level. All measurements were taken at room temperature.

Keywords: Capacitive sensor, Humidity, Nickel phthalocyanine, Organic semiconductor.

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Authors: Ke He, Wumaier Parezhati, Haruka Yamashita

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Recently, online marketplaces in the e-commerce industry, such as Rakuten and Alibaba, have become some of the most popular online marketplaces in Asia. In these shopping websites, consumers can select purchase products from a large number of stores. Additionally, consumers of the e-commerce site have to register their name, age, gender, and other information in advance, to access their registered account. Therefore, establishing a method for analyzing consumer preferences from both the store and the product side is required. This study uses the Doc2Vec method, which has been studied in the field of natural language processing. Doc2Vec has been used in many cases to analyze the extraction of semantic relationships between documents (represented as consumers) and words (represented as products) in the field of document classification. This concept is applicable to represent the relationship between users and items; however, the problem is that one more factor (i.e., shops) needs to be considered in Doc2Vec. More precisely, a method for analyzing the relationship between consumers, stores, and products is required. The purpose of our study is to combine the analysis of the Doc2vec model for users and shops, and for users and items in the same feature space. This method enables the calculation of similar shops and items for each user. In this study, we derive the real data analysis accumulated in the online marketplace and demonstrate the efficiency of the proposal.

Keywords: Doc2Vec, marketing, online marketplace, recommendation system.

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Authors: M. K. Bhuyan

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The use of human hand as a natural interface for humancomputer interaction (HCI) serves as the motivation for research in hand gesture recognition. Vision-based hand gesture recognition involves visual analysis of hand shape, position and/or movement. In this paper, we use the concept of object-based video abstraction for segmenting the frames into video object planes (VOPs), as used in MPEG-4, with each VOP corresponding to one semantically meaningful hand position. Next, the key VOPs are selected on the basis of the amount of change in hand shape – for a given key frame in the sequence the next key frame is the one in which the hand changes its shape significantly. Thus, an entire video clip is transformed into a small number of representative frames that are sufficient to represent a gesture sequence. Subsequently, we model a particular gesture as a sequence of key frames each bearing information about its duration. These constitute a finite state machine. For recognition, the states of the incoming gesture sequence are matched with the states of all different FSMs contained in the database of gesture vocabulary. The core idea of our proposed representation is that redundant frames of the gesture video sequence bear only the temporal information of a gesture and hence discarded for computational efficiency. Experimental results obtained demonstrate the effectiveness of our proposed scheme for key frame extraction, subsequent gesture summarization and finally gesture recognition.

Keywords: Hand gesture, MPEG-4, Hausdorff distance, finite state machine.

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Authors: Bokyung Sung, Jungsoo Kim, Jinman Kwun, Junhyung Park, Jihye Ryeo, Ilju Ko

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In this paper, we propose a practical digital music matching system that is robust to variation in sound qualities. The proposed system is subdivided into two parts: client and server. The client part consists of the input, preprocessing and feature extraction modules. The preprocessing module, including the music onset module, revises the value gap occurring on the time axis between identical songs of different formats. The proposed method uses delta-grouped Mel frequency cepstral coefficients (MFCCs) to extract music features that are robust to changes in sound quality. According to the number of sound quality formats (SQFs) used, a music server is constructed with a feature database (FD) that contains different sub feature databases (SFDs). When the proposed system receives a music file, the selection module selects an appropriate SFD from a feature database; the selected SFD is subsequently used by the matching module. In this study, we used 3,000 queries for matching experiments in three cases with different FDs. In each case, we used 1,000 queries constructed by mixing 8 SQFs and 125 songs. The success rate of music matching improved from 88.6% when using single a single SFD to 93.2% when using quadruple SFDs. By this experiment, we proved that the proposed method is robust to various sound qualities.

Keywords: Digital Music, Music Matching, Variation in Sound Qualities, Robust Matching method.

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Authors: Shih-Yi Chao

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The similarity comparison of RNA secondary structures is important in studying the functions of RNAs. In recent years, most existing tools represent the secondary structures by tree-based presentation and calculate the similarity by tree alignment distance. Different to previous approaches, we propose a new method based on maximum clique detection algorithm to extract the maximum common structural elements in compared RNA secondary structures. A new graph-based similarity measurement and maximum common subgraph detection procedures for comparing purely RNA secondary structures is introduced. Given two RNA secondary structures, the proposed algorithm consists of a process to determine the score of the structural similarity, followed by comparing vertices labelling, the labelled edges and the exact degree of each vertex. The proposed algorithm also consists of a process to extract the common structural elements between compared secondary structures based on a proposed maximum clique detection of the problem. This graph-based model also can work with NC-IUB code to perform the pattern-based searching. Therefore, it can be used to identify functional RNA motifs from database or to extract common substructures between complex RNA secondary structures. We have proved the performance of this proposed algorithm by experimental results. It provides a new idea of comparing RNA secondary structures. This tool is helpful to those who are interested in structural bioinformatics.

Keywords: Clique detection, labeled vertices, RNA secondary structures, subgraph, similarity.

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Authors: Zina Ghiloufi, Tahar Khir

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A transient three-dimensional computational fluid dynamics (CFD) model is developed to determine the velocity and temperature distribution in different positions cold room during pre-cooling of dates. The turbulence model used is the k-ω Shear Stress Transport (SST) with the standard wall function, the air. The numerical results obtained show that cooling rate is not uniform inside the room; the product at the medium of room has a slower cooling rate. This cooling heterogeneity has a large effect on the energy consumption during cold storage.

Keywords: Numerical simulation, CFD, k-ω (SST), cold room, dates, cooling rate.

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Authors: Takaaki Ishibashi

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Frequency domain independent component analysis has a scaling indeterminacy and a permutation problem. The scaling indeterminacy can be solved by use of a decomposed spectrum. For the permutation problem, we have proposed the rules in terms of gain ratio and phase difference derived from the decomposed spectra and the source-s coarse directions. The present paper experimentally clarifies that the gain ratio and the phase difference work effectively in a real environment but their performance depends on frequency bands, a microphone-space and a source-microphone distance. From these facts it is seen that it is difficult to attain a perfect solution for the permutation problem in a real environment only by either the gain ratio or the phase difference. For the perfect solution, this paper gives a solution to the problems in a real environment. The proposed method is simple, the amount of calculation is small. And the method has high correction performance without depending on the frequency bands and distances from source signals to microphones. Furthermore, it can be applied under the real environment. From several experiments in a real room, it clarifies that the proposed method has been verified.

Keywords: blind source separation, frequency domain independent component analysys, permutation correction, scale adjustment, target extraction.

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Authors: Alibek Issakhov

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In this paper presents the mathematical model of hydrothermal processes in thermal power plant with different wind direction scenarios in the water reservoir, which is solved by the Navier - Stokes and temperature equations for an incompressible fluid in a stratified medium. Numerical algorithm based on the method of splitting by physical parameters. Three dimensional Poisson equation is solved with Fourier method by combination of tridiagonal matrix method (Thomas algorithm).

Keywords: thermal power plant, hydrothermal process, large eddy simulation, water reservoir

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Authors: Guo Xiuhua, Sun Tao, Wu Haifeng, He Wen, Liang Zhigang, Zhang Mengxia, Guo Aimin, Wang Wei

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Purpose: To explore the use of Curvelet transform to extract texture features of pulmonary nodules in CT image and support vector machine to establish prediction model of small solitary pulmonary nodules in order to promote the ratio of detection and diagnosis of early-stage lung cancer. Methods: 2461 benign or malignant small solitary pulmonary nodules in CT image from 129 patients were collected. Fourteen Curvelet transform textural features were as parameters to establish support vector machine prediction model. Results: Compared with other methods, using 252 texture features as parameters to establish prediction model is more proper. And the classification consistency, sensitivity and specificity for the model are 81.5%, 93.8% and 38.0% respectively. Conclusion: Based on texture features extracted from Curvelet transform, support vector machine prediction model is sensitive to lung cancer, which can promote the rate of diagnosis for early-stage lung cancer to some extent.

Keywords: CT image, Curvelet transform, Small pulmonary nodules, Support vector machines, Texture extraction.

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Authors: Nirmala P. Ratchagar, S. Senthamilselvi

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The heat and mass transfer characteristics of contaminants in groundwater subjected to a biodegradation reaction is analyzed by taking into account the thermal diffusion (Soret) effects. This phenomenon is modulated mathematically by a system of partial differential equations which govern the motion of fluid (groundwater) and solid (contaminants) particles. The numerical results are presented graphically for different values of the parameters entering into the problem on the velocity profiles of fluid, contaminants, temperature and concentration profile.

Keywords: Heat and mass transfer, Soret number, porous media.

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Authors: S. H. Oudjana, A. Hellal, I. Hadj Mahammed

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Photovoltaic power generation forecasting is an important task in renewable energy power system planning and operating. This paper explores the application of neural networks (NN) to study the design of photovoltaic power generation forecasting systems for one week ahead using weather databases include the global irradiance, and temperature of Ghardaia city (south of Algeria) using a data acquisition system. Simulations were run and the results are discussed showing that neural networks Technique is capable to decrease the photovoltaic power generation forecasting error.

Keywords: Photovoltaic Power Forecasting, Regression, Neural Networks.

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Authors: Yong Zhao, Jian He, Cheng Zhang

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Cardiovascular disease resulting from hypertension poses a significant threat to human health, and early detection of hypertension can potentially save numerous lives. Traditional methods for detecting hypertension require specialized equipment and are often incapable of capturing continuous blood pressure fluctuations. To address this issue, this study starts by analyzing the principle of heart rate variability (HRV) and introduces the utilization of sliding window and power spectral density (PSD) techniques to analyze both temporal and frequency domain features of HRV. Subsequently, a hypertension prediction network that relies on HRV is proposed, combining Resnet, attention mechanisms, and a multi-layer perceptron. The network leverages a modified ResNet18 to extract frequency domain features, while employing an attention mechanism to integrate temporal domain features, thus enabling auxiliary hypertension prediction through the multi-layer perceptron. The proposed network is trained and tested using the publicly available SHAREE dataset from PhysioNet. The results demonstrate that the network achieves a high prediction accuracy of 92.06% for hypertension, surpassing traditional models such as K Near Neighbor (KNN), Bayes, Logistic regression, and traditional Convolutional Neural Network (CNN).

Keywords: Feature extraction, heart rate variability, hypertension, residual networks.

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Authors: I. Oloyede

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The COVID-19 dataset is obtained by extracting weather, longitude, latitude, ISO3666, cases and death of coronavirus patients across the globe. The data were extracted for a period of eight day choosing uniform time within the specified period. Then mapping of cases and deaths with reverence to continents were obtained. Bayesian Geostastical modelling was carried out on the dataset. The study found out that countries in the tropical region suffered less deaths/attacks compared to countries in the temperate region, this is due to high temperature in the tropical region.

Keywords: COVID-19, Bayesian, geostastical modelling, prior, posterior.

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Authors: J. Hassan

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Water 2H NMR signal on the surface of nano-silica material, MCM-41, consists of two overlapping resonances. The 2H water spectrum shows a superposition of a Lorentzian line shape and the familiar NMR powder pattern line shape, indicating the existence of two spin components. Chemical exchange occurs between these two groups. Decomposition of the two signals is a crucial starting point for study the exchange process. In this article we have determined these spin component populations along with other important parameters for the 2H water NMR signal over a temperature range between 223 K and 343 K.

Keywords: Nano-Silica, surface water, NMR

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Authors: J. Maděra, M. Jerman, R. Černý

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Temperature, relative humidity and overhygroscopic moisture fields in a sandstone wall provided with interior thermal insulation were calculated in order to assess the hygric performance of the retrofitted wall. Computational simulations showed that during the time period of 10 years which was subject of investigation no overhygroscopic moisture appeared in the analyzed building envelope so that it performed in a satisfactory way from the hygric point of view.

Keywords: Sandstone wall, interior thermal insulation, moisture, computational modeling.

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Authors: Hajer Taktak, Faouzi Moussa

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With the ubiquitous computing’s emergence and the evolution of enterprises’ needs, one of the main challenges is to build context-aware applications based on Web services. These applications have become particularly relevant in the pervasive computing domain. In this paper, we introduce our approach that optimizes the use of Web services with context notions when dealing with contextual environments. We focus particularly on making Web services autonomous and natively context-aware. We implement and evaluate the proposed approach with a pedagogical example of a context-aware Web service treating temperature values. 

Keywords: Context-aware, CXF framework, ubiquitous computing, web service.

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Authors: K. Hiro, Y. Imai, T. Sasayama

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Cavitation under static negative pressure is not revealed well. The Berthelot method to generate such negative pressure can be a means to study cavitation inception. In this study, metal Berthelot tubes built in observation windows are newly developed and are checked whether high static negative pressure is generated or not. Negative pressure in the tube with a pair of a corundum plate and an aluminum gasket increased with temperature cycles. The trend was similar to that as reported before.

Keywords: Berthelot method, negative pressure, cavitation.

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Authors: Hideki Igawa, Yoshinori Kitsutaka, Takashi Yokomuro, Hideo Eguchi

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In this study, the crack self-healing performance of the heavyweight concrete used in the walls of containers and structures designed to shield radioactive materials was investigated. A steam curing temperature that preserves self-healing properties and demolding strength was identified. The presented simultaneously mixing method using the expanding material and the fly ash in the process of admixture can maximize the self-curing performance. Also adding synthetic fibers in the heavyweight concrete improved the self-healing performance.

Keywords: Expanding material, heavyweight concrete, self-healing performance, synthetic fiber.

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Authors: T. Wresdiyati, S. Sa’diah, A. Winarto

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Diabetes mellitus (DM) is a metabolic disease that can be indicated by the high level of blood glucose. The objective of this study was to observe the antidiabetic properties of ethanolic extract of Indonesian Swietenia mahagoni Jacq. seed on the profile of pancreatic superoxide dismutase and β-cells in the alloxan- experimental diabetic rats. The Swietenia mahagoni seed was obtained from Leuwiliang-Bogor, Indonesia. Extraction of Swietenia mahagoni was done by using ethanol with maceration methods. A total of 25 male Sprague dawley rats were divided into five groups; (a) negative control group, (b) positive control group (DM), (c) DM group that was treated with Swietenia mahagoni seed extract, (d) DM group that was treated with acarbose, and (e) non-DM group that was treated with Swietenia mahagoni seed extract. The DM groups were induced by alloxan (110 mg/kgBW). The extract was orally administrated to diabetic rats 500 mg/kg/BW/day for 28 days. The extract showed hypoglycemic effect, increased body weight, increased the content of superoxide dismutase in the pancreatic tissue, and delayed the rate of β-cells damage of experimental diabetic rats. These results suggested that the ethanolic extract of Indonesian Swietenia mahagoni Jacq. seed could be proposed as a potential anti-diabetic agent.

Keywords: β-cell, diabetes mellitus, superoxide dismutase, Swietenia mahagoni.

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Authors: Rabab M. Ramadan, Elaraby A. Elgallad

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With extensive application, the performance of unimodal biometrics systems has to face a diversity of problems such as signal and background noise, distortion, and environment differences. Therefore, multimodal biometric systems are proposed to solve the above stated problems. This paper introduces a bimodal biometric recognition system based on the extracted features of the human palm print and iris. Palm print biometric is fairly a new evolving technology that is used to identify people by their palm features. The iris is a strong competitor together with face and fingerprints for presence in multimodal recognition systems. In this research, we introduced an algorithm to the combination of the palm and iris-extracted features using a texture-based descriptor, the Scale Invariant Feature Transform (SIFT). Since the feature sets are non-homogeneous as features of different biometric modalities are used, these features will be concatenated to form a single feature vector. Particle swarm optimization (PSO) is used as a feature selection technique to reduce the dimensionality of the feature. The proposed algorithm will be applied to the Institute of Technology of Delhi (IITD) database and its performance will be compared with various iris recognition algorithms found in the literature.

Keywords: Iris recognition, particle swarm optimization, feature extraction, feature selection, palm print, scale invariant feature transform.

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