Search results for: spectral clustering

Authors: B. Siva Kumar Reddy, B. Lakshmi

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WiMAX is a high speed broadband wireless access technology that adopted OFDM/OFDMA techniques to supply higher data rates with high spectral efficiency. However, OFDM suffers in view of high Peak to Average Power Ratio (PAPR) and high affect to synchronization errors. In this paper, the high PAPR problem is solved by using phase modulation to get Constant Envelop Orthogonal Frequency Division Multiplexing (CE-OFDM). The synchronization failures are brought down by employing a frequency lock loop, Poly phase clock synchronizer, Costas loop and blind equalizers such as Constant Modulus Algorithm (CMA) equalizer and Sign Kurtosis Maximization Adaptive Algorithm (SKMAA) equalizers. The WiMAX physical layer is executed on Software Defined Radio (SDR) prototype by utilizing USRP N210 as hardware and GNU Radio as software plat-forms. A SNR estimation is performed on the signal received through USRP N210. To empathize wireless propagation in specific environments, a sliding correlator wireless channel sounding system is designed by using SDR testbed.

Keywords: BER, CMA equalizer, Kurtosis equalizer, GNU Radio, OFDM/OFDMA, USRP N210

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Authors: Sukhleen Kaur

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In security groundwork, Intrusion Detection System (IDS) has become an important component. The IDS has received increasing attention in recent years. IDS is one of the effective way to detect different kinds of attacks and malicious codes in a network and help us to secure the network. Data mining techniques can be implemented to IDS, which analyses the large amount of data and gives better results. Data mining can contribute to improving intrusion detection by adding a level of focus to anomaly detection. So far the study has been carried out on finding the attacks but this paper detects the malicious files. Some intruders do not attack directly, but they hide some harmful code inside the files or may corrupt those file and attack the system. These files are detected according to some defined parameters which will form two lists of files as normal files and harmful files. After that data mining will be performed. In this paper a hybrid classifier has been used via Naive Bayes and Ripper classification methods. The results show how the uploaded file in the database will be tested against the parameters and then it is characterised as either normal or harmful file and after that the mining is performed. Moreover, when a user tries to mine on harmful file it will generate an exception that mining cannot be made on corrupted or harmful files.

Keywords: data mining, association, classification, clustering, decision tree, intrusion detection system, misuse detection, anomaly detection, naive Bayes, ripper

Procedia PDF Downloads 393

Authors: Devansh Desai, Chamandeep Kaur, Nirmal Kullu, George Christopher

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Study of aerosols has become very important tool in assuming the climatic changes over a region.Spectral and temporal variability’s in aerosol optical depth(AOD) and size distribution are investigated using ground base measurements over Ahmedabad during the months of January(2013) to may (2013). Angstrom coefficient (ἁ) was found to be higher in winter season (January to march) indicating the dominance of fine mode aerosol concentration over Ahmedabad, and the Angstrom coefficient (ἁ) was found to be lower indicating the dominance of coarse mode aerosol concentration over Ahmedabad. The different values of alpha are observed when calculated over different wavelength ranges indicating bimodal aerosol size distribution. Discrimination of aerosol size during different seasons is made using the coefficient of polynomial fit (ἁ1 and ἁ2) which shows the presence of changing dominant aerosol types as a function of season over Ahmedabad. The ἁ2- ἁ1 value is used to get the confirmation on the dominant aerosol mode over Ahmedabad in both seasons. During pre-monsoon about 90% of AOD spectra is dominated by coarse mode aerosols and during winter about 60% of AOD spectra is dominated by fine mode aerosols. This characterization of aerosols is important in assessing the response of different aerosols type in radiative forcing and over climate of Ahmedabad.

Keywords: radiative forcing, aerosol optical depth, fine mode, coarse mode

Procedia PDF Downloads 475

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: Nancy Ibrahim Abdalla, Abdelaziz Karamalla Gaiballa

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Rangelands in semi-arid areas provide a good source for feeding huge numbers of animals and serving environmental, economic and social importance; therefore, these areas are considered economically very important for the pastoral sector in Sudan. This paper investigates the means of differentiating between different rangelands sites according to soil types using principal component analysis to assist in monitoring and assessment purposes. Three rangeland sites were identified in the study area as flat sandy sites, sand dune site, and hard clay site. Principal component analysis (PCA) was used to reduce the number of factors needed to distinguish between rangeland sites and produce a new set of data including the most useful spectral information to run satellite image processing. It was performed using selected types of data (two vegetation indices, topographic data and vegetation surface reflectance within the three bands of MODIS data). Analysis with PCA indicated that there is a relatively high correspondence between vegetation and soil of the total variance in the data set. The results showed that the use of the principal component analysis (PCA) with the selected variables showed a high difference, reflected in the variance and eigenvalues and it can be used for differentiation between different range sites.

Keywords: principal component analysis, PCA, rangeland sites, semi-arid areas, soil types

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Authors: Swati Sharma, R. P. Sharma

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We intend to study the nonlinear evolution of the parallel propagating finite frequency Alfvén wave (also called Dispersive Alfvén wave/Hall MHD wave) propagating in the solar wind regime of the solar region when a perpendicularly propagating magnetosonic wave is present in the background. The finite frequency Alfvén wave behaves differently from the usual non-dispersive behavior of the Alfvén wave. To study the nonlinear processes (such as filamentation) taking place in the solar regions such as solar wind, the dynamical equation of both the waves are derived. Numerical simulation involving finite difference method for the time domain and pseudo spectral method for the spatial domain is then performed to analyze the transient evolution of these waves. The power spectra of the Dispersive Alfvén wave is also investigated. The power spectra shows the distribution of the magnetic field intensity of the Dispersive Alfvén wave over different wave numbers. For DAW the spectra shows a steepening for scales larger than the proton inertial length. This means that the wave energy gets transferred to the solar wind particles as the wave reaches higher wave numbers. This steepening of the power spectra can be explained on account of the finite frequency of the Alfvén wave. The obtained results are consistent with the observations made by CLUSTER spacecraft.

Keywords: solar wind, turbulence, dispersive alfven wave

Procedia PDF Downloads 579

Authors: Nina N. Serdar, Jelena R. Pejović

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This paper presents seismic risk assessment of two bridge structure, based on the probabilistic performance-based seismic assessment methodology. Both investigated bridges are tree span continuous RC curved bridges with the difference in column shapes. First bridge (type A) has a wall-type pier and second (type B) has a two-column bent with circular columns. Bridges are designed according to European standards: EN 1991-2, EN1992-1-1 and EN 1998-2. Aim of the performed analysis is to compare seismic behavior of these two structures and to detect the influence of column shapes on the seismic response. Seismic risk assessment is carried out by obtaining demand fragility curves. Non-linear model was constructed and time-history analysis was performed using thirty five pairs of horizontal ground motions selected to match site specific hazard. In performance based analysis, peak column drift ratio (CDR) was selected as engineering demand parameter (EDP). For seismic intensity measure (IM) spectral displacement was selected. Demand fragility curves that give probability of exceedance of certain value for chosen EDP were constructed and based on them conclusions were made.

Keywords: RC curved bridge, demand fragility curve, wall type column, nonlinear time-history analysis, circular column

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Authors: Hassan S. Hussein, Rania A. Abul Seoud, Amr M. Refaat

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Scientific researchers face in the analysis of very large data sets that is increasing noticeable rate in today’s and tomorrow’s technologies. Hadoop and Spark are types of software that developed frameworks. Hadoop framework is suitable for many Different hardware platforms. In this research, a scientific Linux cluster for Big Data analysis (SLBD) is presented. SLBD runs open source software with large computational capacity and high performance cluster infrastructure. SLBD composed of one cluster contains identical, commodity-grade computers interconnected via a small LAN. SLBD consists of a fast switch and Gigabit-Ethernet card which connect four (nodes). Cloudera Manager is used to configure and manage an Apache Hadoop stack. Hadoop is a framework allows storing and processing big data across the cluster by using MapReduce algorithm. MapReduce algorithm divides the task into smaller tasks which to be assigned to the network nodes. Algorithm then collects the results and form the final result dataset. SLBD clustering system allows fast and efficient processing of large amount of data resulting from different applications. SLBD also provides high performance, high throughput, high availability, expandability and cluster scalability.

Keywords: big data platforms, cloudera manager, Hadoop, MapReduce

Procedia PDF Downloads 334

Authors: Waziralilah N. Fathiah, A. Aminudin, U. Alyaa Hashim, T. Vikneshvaran D. Shakirah Shukor

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This paper presents the experimental analysis conducted on a structure borne noise in a rectangular enclosure prototype made by joining of sheet aluminum metal and plywood. The study is significant as many did not realized the annoyance caused by structural borne-noise. In this study, modal analysis is carried out to seek the structure’s behaviour in order to identify the characteristics of enclosure in frequency domain ranging from 0 Hz to 200 Hz. Here, numbers of modes are identified and the characteristic of mode shape is categorized. Modal experiment is used to diagnose the structural behaviour while microphone is used to diagnose the sound. Spectral testing is performed on the enclosure. It is acoustically excited using shaker and as it vibrates, the vibrational and noise responses sensed by tri-axis accelerometer and microphone sensors are recorded respectively. Experimental works is performed on each node lies on the gridded surface of the enclosure. Both experimental measurement is carried out simultaneously. The modal experimental results of the modal modes are validated by simulation performed using MSC Nastran software. In pursuance of reducing the structure borne-noise, mitigation method is used whereby the stiffener plates are perpendicularly placed on the sheet aluminum metal. By using this method, reduction in structure borne-noise is successfully made at the end of the study.

Keywords: enclosure, modal analysis, sound analysis, structure borne-noise

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Authors: Igor Filikhin, Vladimir M. Suslov, Roman Ya. Kezerashvili, Branislav Vlahivic

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The mass-polarization term of the three-body kinetic energy operator is evaluated for different systems which include two identical particles: A+A+B. The term has to be taken into account for the analysis of AB- and AA-interactions based on experimental data for two- and three-body ground state energies. In this study, we present three-body calculations within the framework of a potential model for the kaonic clusters K−K−p and ppK−, nucleus 3H and hypernucleus 6 ΛΛHe. The systems are well clustering as A+ (A+B) with a ground state energy E2 for the pair A+B. The calculations are performed using the method of the Faddeev equations in configuration space. The phenomenological pair potentials were used. We show a correlation between the mass ratio mA/mB and the value δB of the mass-polarization term. For bosonic-like systems, this value is defined as δB = 2E2 − E3, where E3 is three-body energy when VAA = 0. For the systems including three particles with spin(isospin), the models with average AB-potentials are used. In this case, the Faddeev equations become a scalar one like for the bosonic-like system αΛΛ. We show that the additional energy conected with the mass-polarization term can be decomposite to a sum of the two parts: exchenge related and reduced mass related. The state of the system can be described as the following: the particle A1 is bound within the A + B pair with the energy E2, and the second particle A2 is bound with the pair with the energy E3 − E2. Due to the identity of A particles, the particles A1 and A2 are interchangeable in the pair A + B. We shown that the mass polarization δB correlates with a type of AB potential using the system αΛΛ as an example.

Keywords: three-body systems, mass polarization, Faddeev equations, nuclear interactions

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Authors: Avram Irina, Coiciu Eugenia-Mihaela, Popovici Mara-Georgiana, Mitu Iani Octavian

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ELI-NP stands as a cutting-edge facility globally, hosting unique radiological setups. It conducts experiments leveraging high-power lasers capable of producing extremely brief 10 PW pulses on two fronts. Moreover, it houses an exceptional gamma beam system with distinctive spectral characteristics. The facility hosts various experiments across designated experimental areas, encompassing ultra-short high-power laser tests, high-intensity gamma beam trials, and combined experiments utilizing both setups. The facility hosts a dosimetry laboratory, which recently obtained accreditation, where the radiation safety group employs a host of different types of detectors for monitoring the personnel, environment, and public exposure to ionizing radiation generated in experiments performed. ELI-NP's design was shaped by radiological protection assessments conducted through Monte Carlo simulations. The poster exemplifies an assessment conducted using the FLUKA code in an experimental area where a high-power laser system is implemented, and the future diagnostic system for variable energy gamma beams will soon be operational.

Keywords: radiation protection, Monte Carlo simulation, FLUKA, dosimetry

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Authors: Fei Gao, Xinyang Dong, Yisu Ge, Shufang Lu, Libo Weng

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Vehicle color recognition plays an important role in traffic accident investigation. However, due to the influence of illumination, weather, and noise, vehicle color recognition still faces challenges. In this paper, a vehicle color classification network based on spatial cluster loss and channel attention mechanism (SCNet) is proposed for vehicle color recognition. A channel attention module is applied to extract the features of vehicle color representative regions and reduce the weight of nonrepresentative color regions in the channel. The proposed loss function, called spatial clustering loss (SC-loss), consists of two channel-specific components, such as a concentration component and a diversity component. The concentration component forces all feature channels belonging to the same class to be concentrated through the channel cluster. The diversity components impose additional constraints on the channels through the mean distance coefficient, making them mutually exclusive in spatial dimensions. In the comparison experiments, the proposed method can achieve state-of-the-art performance on the public datasets, VCD, and VeRi, which are 96.1% and 96.2%, respectively. In addition, the ablation experiment further proves that SC-loss can effectively improve the accuracy of vehicle color recognition.

Keywords: feature extraction, convolutional neural networks, intelligent transportation, vehicle color recognition

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Authors: Vahid Bayrami Rad

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In this research, common methods and techniques have been investigated with a focus on intelligent fault finding and monitoring systems in the oil industry. In fact, remote and intelligent control methods are considered a necessity for implementing various operations in the oil industry, but benefiting from the knowledge extracted from countless data generated with the help of data mining algorithms. It is a avoid way to speed up the operational process for monitoring and troubleshooting in today's big oil companies. Therefore, by comparing data mining algorithms and checking the efficiency and structure and how these algorithms respond in different conditions, The proposed (Bayesian) algorithm using data clustering and their analysis and data evaluation using a colored Petri net has provided an applicable and dynamic model from the point of view of reliability and response time. Therefore, by using this method, it is possible to achieve a dynamic and consistent model of the remote control system and prevent the occurrence of leakage in oil pipelines and refineries and reduce costs and human and financial errors. Statistical data The data obtained from the evaluation process shows an increase in reliability, availability and high speed compared to other previous methods in this proposed method.

Keywords: wireless sensors, petroleum equipment troubleshooting, Bayesian algorithm, colored Petri net, rapid miner, data mining-reliability

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Authors: Barbora Chmelova, Radek Sachl

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Gangliosides are amphipathic membrane lipids. Due to the composition of bulky oligosaccharide chains containing one or more sialic acids linked to the hydrophobic ceramide base, gangliosides are classified among glycosphingolipids. This unique structure induces a high self-aggregating tendency of gangliosides and, therefore, the formation of nanoscopic clusters called nanodomains. Gangliosides are preferentially present in an extracellular membrane leaflet of all human tissues and thus have an impact on a huge number of biological processes, such as intercellular communication, cell signalling, membrane trafficking, and regulation of receptor activity. Defects in their metabolism, impairment of proper ganglioside function, or changes in their organization lead to serious health conditions such as Alzheimer´s and Parkinson´s diseases, autoimmune diseases, tumour growth, etc. This work mainly focuses on ganglioside organization into nanodomains and their dynamics within the plasma membrane. Current research investigates static ganglioside nanodomains characterization; nevertheless, the information about their diffusion is missing. In our study, fluorescence correlation spectroscopy is implemented together with stimulated emission depletion (STED-FCS), which combines the diffraction-unlimited spatial resolution with high temporal resolution. By comparison of the experiments performed on model vesicles containing 4 % of either GM1, GM2, or GM3 and Monte Carlo simulations of diffusion on the plasma membrane, the description of ganglioside clustering, diffusion of nanodomains, and even diffusion of ganglioside molecules inside investigated nanodomains are described.

Keywords: gangliosides, nanodomains, STED-FCS, flourescence microscopy, membrane diffusion

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Authors: Prashant Pandey

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In the present article, an effective Laguerre collocation method is used to obtain the approximate solution of a system of coupled fractional-order non-linear reaction-advection-diffusion equation with prescribed initial and boundary conditions. In the proposed scheme, Laguerre polynomials are used together with an operational matrix and collocation method to obtain approximate solutions of the coupled system, so that our proposed model is converted into a system of algebraic equations which can be solved employing the Newton method. The solution profiles of the coupled system are presented graphically for different particular cases. The salient feature of the present article is finding the stability analysis of the proposed method and also the demonstration of the lower variation of solute concentrations with respect to the column length in the fractional-order system compared to the integer-order system. To show the higher efficiency, reliability, and accuracy of the proposed scheme, a comparison between the numerical results of Burger’s coupled system and its existing analytical result is reported. There are high compatibility and consistency between the approximate solution and its exact solution to a higher order of accuracy. The exhibition of error analysis for each case through tables and graphs confirms the super-linearly convergence rate of the proposed method.

Keywords: fractional coupled PDE, stability and convergence analysis, diffusion equation, Laguerre polynomials, spectral method

Procedia PDF Downloads 116

Authors: Raymond Feng, Shadi Ghiasi

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An electroencephalogram (EEG) is a non-invasive technique that records electrical activity in the brain using scalp electrodes. Researchers have studied the use of EEG to detect emotions and moods by collecting signals from participants and analyzing how those signals correlate with their activities. In this study, researchers investigated the relationship between EEG signals and music enjoyment. Participants listened to music while data was collected. During the signal-processing phase, power spectral densities (PSDs) were computed from the signals, and dominant brainwave frequencies were extracted from the PSDs to form a comprehensive feature matrix. A machine learning approach was then taken to find correlations between the processed data and the music enjoyment level indicated by the participants. To improve on previous research, multiple machine learning models were employed, including K-Nearest Neighbors Classifier, Support Vector Classifier, and Decision Tree Classifier. Hyperparameters were used to fine-tune each model to further increase its performance. The experiments showed that a strong correlation exists, with the Decision Tree Classifier with hyperparameters yielding 85% accuracy. This study proves that EEG is a reliable means to detect music enjoyment and has future applications, including personalized music recommendation, mood adjustment, and mental health therapy.

Keywords: EEG, electroencephalogram, machine learning, mood, music enjoyment, physiological signals

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Authors: Acheampong Addo, Emmanuel Odartei Armah, Seth Koranteng Agyakwah, Ruby Asmah, Emmanuel Tetteh-Doku Mensah, Rhoda Lims Diyie, Sena Amewu, Catherine Ragasa, Edward Kofi Abban, Mike Yaw Osei-Atweneboana

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The study investigated genetic variation and relationships among populations of Nile tilapia cultured in small-scale fish farms in selected regions of Ghana. A total of 700 samples were collected. All samples were screened with five microsatellite markers and results were analyzed using (Genetic Analysis in Excel), (Molecular and Evolutionary Genetic Analysis software, and Genpop on the web for Heterozygosity and Shannon diversity, (Analysis of Molecular Variance), and (Principal Coordinate Analysis). Fish from the 16 populations (made up of 14 farms and 2 selectively bred populations) clustered into three groups: 7 populations clustered with the GIFT-derived strain, 4 populations clustered with the Akosombo strain, and three populations were in a separate cluster. The clustering pattern indicated groups of different strains of Nile tilapia cultured. Mantel correlation test also showed low genetic variations among the 16 populations hence the need to boost seed quality in order to accelerate aquaculture production in Ghana.

Keywords: microsatellites, small- scale, Nile tilapia, akosombo strain, GIFT strain

Procedia PDF Downloads 128

Authors: Xinke Huang, Huan Wang, Lidong Guo, Changbin Ju, Runbiao Liu, Guoen Cao, Yibo Wang, Honghua Xu

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Grid connected photovoltaic (PV) power system is to be developed in the direction of large-scale, clustering. Large-scale PV generation systems connected to HVDC grid have many advantages compared to its counterpart of AC grid, and DC connection is the tendency. DC/DC converter as the most important device in the system, has become one of the hot spots recently. The paper proposes a Quasi Z-Source(QZS) based Boost Full Bridge Isolated DC/DC Converter(BFBIC) topology as a basis power module and combination through input parallel output series(IPOS) method to improve power capacity and output voltage to match with the HVDC grid. The topology has both traditional voltage source and current source advantages, it permit the H-bridge short through and open circuit, which adopt utility duty cycle control and achieved input current and output voltage balancing through input current sharing control strategy. A ±10kV/200kW system model is built in MATLAB/SIMULINK to verify the proposed topology and control strategy.

Keywords: PV Generation System, Cascaded DC/DC converter, HVDC, Quasi Z Source Converter

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Authors: Khitem Amiri, Mohamed Farah

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Image classification is a challenging task and is gaining lots of interest since it helps us to understand the content of images. Recently Deep Learning (DL) based methods gave very interesting results on several benchmarks. For Hyperspectral images (HSI), the application of DL techniques is still challenging due to the scarcity of labeled data and to the curse of dimensionality. Among other approaches, Deep Belief Network (DBN) based approaches gave a fair classification accuracy. In this paper, we address the problem of the curse of dimensionality by reducing the number of bands and replacing the HSI channels by the channels representing radiometric indices. Therefore, instead of using all the HSI bands, we compute the radiometric indices such as NDVI (Normalized Difference Vegetation Index), NDWI (Normalized Difference Water Index), etc, and we use the combination of these indices as input for the Deep Belief Network (DBN) based classification model. Thus, we keep almost all the pertinent spectral information while reducing considerably the size of the image. In order to test our image representation, we applied our method on several HSI datasets including the Indian pines dataset, Jasper Ridge data and it gave comparable results to the state of the art methods while reducing considerably the time of training and testing.

Keywords: hyperspectral images, deep belief network, radiometric indices, image classification

Procedia PDF Downloads 248

Authors: S. Obregon-Cano, R. Moreno-Rojas, E. Cartea-Gonzalez, A. De Haro-Bailon

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The potential of near-infrared spectroscopy (NIRS) for screening the total glucosinolate (t-GSL) content, and also, the aliphatic glucosinolates gluconapin (GNA), progoitrin (PRO) and glucobrassicanapin (GBN) in turnip greens and turnip tops was assessed. This crop is grown for edible leaves and stems for human consumption. The reference values for glucosinolates, as they were obtained by high performance liquid chromatography on the vegetable samples, were regressed against different spectral transformations by modified partial least-squares (MPLS) regression (calibration set of samples n= 350). The resulting models were satisfactory, with calibration coefficient values from 0.72 (GBN) to 0.98 (tGSL). The predictive ability of the equations obtained was tested using a set of samples (n=70) independent of the calibration set. The determination coefficients and prediction errors (SEP) obtained in the external validation were: GNA=0.94 (SEP=3.49); PRO=0.41 (SEP=1.08); GBN=0.55 (SEP=0.60); tGSL=0.96 (SEP=3.28). These results show that the equations developed for total glucosinolates, as well as for gluconapin can be used for screening these compounds in the leaves and stems of this species. In addition, the progoitrin and glucobrassicanapin equations obtained can be used to identify those samples with high, medium and low contents. The calibration equations obtained were accurate enough for a fast, non-destructive and reliable analysis of the content in GNA and tGSL directly from NIR spectra. The equations for PRO and GBN can be employed to identify samples with high, medium and low contents.

Keywords: brassica rapa, glucosinolates, gluconapin, NIRS, turnip greens

Procedia PDF Downloads 119

Authors: P. S. Jagadeesh Kumar, Yang Yung, Wenli Hu

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Speech emotion classification is a dominant research field in finding a sturdy and profligate classifier appropriate for different real-life applications. This effort accentuates on classifying different emotions from speech signal quarried from the features related to pitch, formants, energy contours, jitter, shimmer, spectral, perceptual and temporal features. Tensor deep stacking neural networks were supported to examine the factors that influence the classification success rate. Facial electromyography signals were composed of several forms of focuses in a controlled atmosphere by means of audio-visual stimuli. Proficient facial electromyography signals were pre-processed using moving average filter, and a set of arithmetical features were excavated. Extracted features were mapped into consistent emotions using bilinear mapping. With facial electromyography signals, a database comprising diverse emotions will be exposed with a suitable fine-tuning of features and training data. A success rate of 92% can be attained deprived of increasing the system connivance and the computation time for sorting diverse emotional states.

Keywords: speech emotion classification, tensor deep stacking neural networks, facial electromyography, bilinear mapping, audio-visual stimuli

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Authors: Osama Abdallah Mohammed Enan, Amin Babiker A/Nabi Mustafa

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The aim of this study is to evaluate and analyze different parameters of WCDMA (wideband code division multiplication). Moreover, this study also incorporates brief yet throughout analysis of WCDMA’s components as well as its internal architecture. This study also examines different power controls. These power controls may include open loop power control, closed or inner group loop power control and outer loop power control. Different handover techniques or methods of WCDMA are also illustrated in this study. These handovers may include hard handover, inter system handover and soft and softer handover. Different duplexing techniques are also described in the paper. This study has also presented an idea about different parameters of WCDMA that leads the system towards QoS issues. This may help the operator in designing and developing adequate network configuration. In addition to this, the study has also investigated various parameters including Bit Energy per Noise Spectral Density (Eb/No), Noise rise, and Bit Error Rate (BER). After simulating these parameters, using MATLAB environment, it was investigated that, for a given Eb/No value the system capacity increase by increasing the reuse factor. Besides that, it was also analyzed that, noise rise is decreasing for lower data rates and for lower interference levels. Finally, it was examined that, BER increase by using one type of modulation technique than using other type of modulation technique.

Keywords: duplexing, handover, loop power control, WCDMA

Procedia PDF Downloads 188

Authors: Zohreh Derikvand, Hadis Cheraghi, Azadeh Azadbakht, Vaclav Eigner, Michal Dusek

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Two new one and two dimensional metal organic coordination polymers of Cu(II), [Cu(3-nph)2(H2O)2pz]n (1) and Ag(I), {[Ag(3-nph)pz].H2O}n (2) with pyrazine (pz) and 3- nitrophthalic acid (3-nph) have been synthesized and characterized by elemental analysis, spectral (IR, UV-Vis), thermal (TG/DTG) analysis and single crystal X-ray diffraction. We used these compounds to preparation modified electrode with Au/Pt nanosparticles in order to investigation electrochemistry and electrocatalysis activities. The surface structure and composition of the sensor were characterized by scanning electron microscopy (SEM). The Ag(I) coordination polymer shows a 2D layer structure constructed from dinuclear silver (I) building blocks in which two crystallographically Ag+ ions are connected to each other by a covalent bond. The pyrazine ligands adopt μ2 bridging modes, linking the metal centers into a one and two -dimensional coordination framework in 1 and 2. The two AgI cations are surrounded by pyrazine and 3-nitrophthalate mono anions and indicate distorted tetrahedral geometry. In the crystal structures of Ag(I) complex there are non-classical hydrogen bonding arrangements, C–O•••π and π–π stacking interactions. In Cu(II) coordination polymer, the coordination geometry around Cu(II) atom is a distorted octahedron. Interestingly, the structural analysis illustrates that the strong and weak hydrogen bond accompanied with C–H•••π and C–O•••π stacking interactions assemble the crystal structure of 1 and 2 into fascinating 3D supramolecular architecture.

Keywords: 3-nithrophethalic acid, crystal structure, coordination polymer, electrocatalysis

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Authors: Giovanni Meloni

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Recent results are presented from experiments carried out at the Advanced Light Source (ALS) at the Chemical Dynamics Beamline of Lawrence Berkeley National Laboratory using multiplexed synchrotron photoionization mass spectrometry. The reaction mixture and a buffer gas (He) are introduced through individually calibrated mass flow controllers into a quartz slow flow reactor held at constant pressure and temperature. The gaseous mixture effuses through a 650 μm pinhole into a 1.5 mm skimmer, forming a molecular beam that enters a differentially pumped ionizing chamber. The molecular beam is orthogonally intersected by a tunable synchrotron radiation produced by the ALS in the 8-11 eV energy range. Resultant ions are accelerated, collimated, and focused into an orthogonal time-of-flight mass spectrometer. Reaction species are identified by their mass-to-charge ratios and photoionization (PI) spectra. Comparison of experimental PI spectra with literature and/or simulated curves is routinely done to assure the identity of a given species. With the aid of electronic structure calculations, potential energy surface scans are performed, and Franck-Condon spectral simulations are obtained. Examples of these experiments are discussed, ranging from new intermediates characterization to reaction mechanisms elucidation and biofuels oxidation pathways identification.

Keywords: mass spectrometry, reaction intermediates, synchrotron photoionization, oxidation reactions

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Authors: S. Roy, R. Rekha, K. Sriram, G. Subhadra, R. Johana

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Cardiovascular disease remains a leading cause of death in most industrialized countries. Many chemical drugs are available in the market which targets different receptor proteins related to cardiovascular diseases. Of late the traditional herbal drugs are safer when compared to chemical drugs because of its side effects. However, many herbal remedies used in treating cardiovascular diseases have not undergone scientific assessment to prove its pharmacological activities. There are many natural compounds, nature derived and Natural product mimic compounds are available which are in the market as approved drug. In the most of the cases drug activity at the molecular level are not known. Here we have categorized those compounds with our experimental compounds in different classes based on the structural similarity and physicochemical properties, using a tool, Chemmine and has attempted to understand the mechanism of the action of a experimental compound, which are clustered with Simvastatin, Lovastatin, Mevastatin and Pravastatin. Target protein molecule for Simvastatin, Lovastatin, Mevastatin and Pravastatin is HMG-CoA reductase, so we concluded that the experimental compound may be able to bind to the same target. Molecular docking and atomic interaction studies with simvastatin and our experimental compound were compared. A pharmacophore modeling was done based on the experimental compound and HMG-CoA reductase inhibitor.

Keywords: molecular docking, physicochemical properties, pharmacophore modeling structural similarity, pravastatin

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Authors: Harish Rajak, Swati Singh

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A series of novel pyrimidine based semicarbazone were designed and synthesized on the basis of semicarbazone based pharmacophoric model to satisfy the structural prerequisite crucial for antiepileptic activity. The semicarbazones based pharmacophoric model consists of following four essential binding sites: (i) An aryl hydrophobic binding site with halo substituent; (ii) A hydrogen bonding domain; (iii) An electron donor group and (iv) Another hydrophobic-hydrophilic site controlling the pharmacokinetic features of the anticonvulsant. The aryl semicarbazones has been recognized as a structurally novel class of compounds with remarkable anticonvulsant activity. In the present study, all the test semicarbazones were subjected to molecular docking using Glide v5.8. Some of the compounds were found to interact with ARG192, GLU270 and THR353 residues of 1OHV protein, present in GABA-AT receptor. The chemical structures of the synthesized molecules were characterized by elemental and spectral (IR, 1H NMR, 13C NMR and MS) analysis. The anticonvulsant activities of the compounds were investigated using maximal electroshock seizure (MES) and subcutaneous pentylenetrtrazole (scPTZ) models. The neurotoxicity was evaluated in mice by the rotorod test. The attempts were also made to establish structure-activity relationships among synthesized compounds. The results of the present study confirmed that the pharmacophore model with four binding sites is essential for antiepileptic activity.

Keywords: pyrimidine, semicarbazones, anticonvulsant activity, neurotoxicity

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Authors: Radnoosh Mirzajani, Ebrahim Mirzajani, Heshmatollah Ebrahimi-Najafabadi

Abstract:

Introduction: Hydrogen peroxide can be produced over the interaction of sodium dodecyl sulfate (SDS) with hemoglobin which would facilitate the oxidation process of hemoglobin. The presence of ascorbic acid (AA) can hinder the extreme oxidation of oxyhemoglobin. Methods: Hemoglobin was purified from blood samples according to the method of Williams. UV-V is spectra of Hb solutions mixed with different concentrations of SDS and AA were recorded. Chemical components, concentration, and spectral profiles were estimated using MCR-ALS techniques. Results: The intensity of soret band of OxyHb decreased due to the interaction of Hb with SDS. Furthermore, changes were also observed for peaks at 575 and 540. Subspace plots confirm the presence of OxyHb, MetHb, and Hemichrom in each mixture. The resolved concentration profiles using MCR-ALS reveal that the mole fraction of OxyHb increased upon the presence of AA up to a concentration level of 3 mM. The higher concentration of AA shows a reverse effect. AA demonstrated a dual effect on the interaction of hemoglobin with SDS. AA disturbs the interaction of SDS and hemoglobin and exhibits an antioxidative effect. However, it caused a tiny decrease in the mole fraction of OxyHb. Conclusions: H2O2 produces upon the interaction of OxyHb with SDS. Oxidation of OxyHb facilitates due to overproduction of H2O2. Ascorbic acid interacts with H2O2 to form dehydroascorbic acid. Furthermore, the available free SDS was reduced because the Gibbs free energy for micelle production of SDS became more negative in the presence of AA.

Keywords: hemoglobin, ascorbic acid, sodium dodecyl sulfate, multivariate curve resolution, antioxidant

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Authors: Mai M. Farid, Mona El-Shabrawy, Sameh R. Hussein, Ahmed Elkhateeb, El-Said S. Abdel-Hameed, Mona M. Marzouk

Abstract:

Asphodelus aestivus Brot. Is a wild plant distributed in Egypt and is considered one of the five Asphodelus spp. from the family Asphodelaceae; it grows in dry grasslands and on rocky or sandy soil. The chemical components of A. aestivus flowers extract were analyzed using different chromatographic and spectral techniques and led to the isolation of two anthraquinones identified as emodin and emodin-O-glucoside. In addition to, five flavonoid compounds;kaempferol,Kaempferol-3-O-glucoside,Apigenin-6-C-glucoside-7-O-glucoside (Saponarine), luteolin 7-O-β-glucopyranoside, Isoorientin-O-malic acid which is a new compound in nature. The LC-ESI-MS/MS analysis of the flower extract of A. aestivus led to the identification of twenty- two compounds characterized by the presence of flavones, flavonols, and flavone C-glycosides. While GC/MS analysis led to the identification of 24 compounds comprising 98.32% of the oil, the major components of the oil were 9, 12, 15-Octadecatrieoic acid methyl ester 28.72%, and 9, 12-Octadecadieroic acid (Z, Z)-methyl ester 19.96%. In vitro cytotoxic activity of the aqueous methanol extract of A. aestivus flowers against HEPG2, HCT-116, MCF-7, and A549 culture was examined and showed moderate inhibition (62.3±1.1)% on HEPG2 cell line followed by (36.8±0.2)% inhibition on HCT-116 and a weak inhibition (5.7± 0.0.2) on MCF-7 cell line followed by (4.5± 0.4) % inhibition on A549 cell line and this is considered the first cytotoxic report of A. aestivus flowers.

Keywords: Anthraquinones, Asphodelus aestivus, Cytotoxic activity, Flavonoids, LC-ESI-MS/MS

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Authors: Shahabeddin Sotudian, M. H. Fazel Zarandi, I. B. Turksen

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Hepatitis is one of the most common and dangerous diseases that affects humankind, and exposes millions of people to serious health risks every year. Diagnosis of Hepatitis has always been a challenge for physicians. This paper presents an effective method for diagnosis of hepatitis based on interval Type-II fuzzy. This proposed system includes three steps: pre-processing (feature selection), Type-I and Type-II fuzzy classification, and system evaluation. KNN-FD feature selection is used as the preprocessing step in order to exclude irrelevant features and to improve classification performance and efficiency in generating the classification model. In the fuzzy classification step, an “indirect approach” is used for fuzzy system modeling by implementing the exponential compactness and separation index for determining the number of rules in the fuzzy clustering approach. Therefore, we first proposed a Type-I fuzzy system that had an accuracy of approximately 90.9%. In the proposed system, the process of diagnosis faces vagueness and uncertainty in the final decision. Thus, the imprecise knowledge was managed by using interval Type-II fuzzy logic. The results that were obtained show that interval Type-II fuzzy has the ability to diagnose hepatitis with an average accuracy of 93.94%. The classification accuracy obtained is the highest one reached thus far. The aforementioned rate of accuracy demonstrates that the Type-II fuzzy system has a better performance in comparison to Type-I and indicates a higher capability of Type-II fuzzy system for modeling uncertainty.

Keywords: hepatitis disease, medical diagnosis, type-I fuzzy logic, type-II fuzzy logic, feature selection

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Authors: Proficiency Munsaka, Peter Baricholo, Erich Rohwer

Abstract:

Pulse evolutions along the 5 cm long, 6.0 ×4.2 μm² cross-section silicon germanium (SiGe) photonic waveguides were simulated and compared with experiments. Simulations were carried out by solving a generalized nonlinear Schrodinger equation (GNLSE) for an optical pulse evolution along the length of the SiGe photonic waveguides by the split-step Fourier method (SSFM). The solution obtained from the SSFM gave the pulse envelope in both time and spectral domain calculated at each distance step along the propagation direction. The SiGe photonic waveguides were pumped in an anomalous group velocity dispersion (GVD) regime using a 4.7 μm, 210 fs femtosecond laser to produce a significant supercontinuum (SC). The simulated propagation of ultrafast pulse along the SiGe photonic waveguides produced an SC covering the atmospheric window (2.5-8.5 μm) containing the molecular fingerprints for important gases. Thus, the mid-infrared supercontinuum generation in SiGe photonic waveguides system can be commercialized for gas spectroscopy for detecting gases that include CO₂, CH₄, H₂O, SO₂, SO₃, NO₂, H₂S, CO, and NO at trace level using absorption spectroscopy technique. The simulated profile evolutions are spectrally and temporally similar to those obtained by other researchers. Obtained evolution profiles are characterized by pulse compression, Soliton fission, dispersive wave generation, stimulated Raman Scattering, and Four Wave mixing.

Keywords: silicon germanium photonic waveguide, supercontinuum generation, spectroscopy, mid infrared

Procedia PDF Downloads 104