Search results for: ozone decomposition
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 758

Search results for: ozone decomposition

578 Dynamical Analysis of the Fractional-Order Mathematical Model of Hashimoto’s Thyroiditis

Authors: Neelam Singha

Abstract:

The present work intends to analyze the system dynamics of Hashimoto’s thyroiditis with the assistance of fractional calculus. Hashimoto’s thyroiditis or chronic lymphocytic thyroiditis is an autoimmune disorder in which the immune system attacks the thyroid gland, which gradually results in interrupting the normal thyroid operation. Consequently, the feedback control of the system gets disrupted due to thyroid follicle cell lysis. And, the patient perceives life-threatening clinical conditions like goiter, hyperactivity, euthyroidism, hyperthyroidism, etc. In this work, we aim to obtain the approximate solution to the posed fractional-order problem describing Hashimoto’s thyroiditis. We employ the Adomian decomposition method to solve the system of fractional-order differential equations, and the solutions obtained shall be useful to provide information about the effect of medical care. The numerical technique is executed in an organized manner to furnish the associated details of the progression of the disease and to visualize it graphically with suitable plots.

Keywords: adomian decomposition method, fractional derivatives, Hashimoto's thyroiditis, mathematical modeling

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577 High-Frequency Modulation of Light-Emitting Diodes for New Ultraviolet Communications

Authors: Meng-Chyi Wu, Bonn Lin, Jyun-Hao Liao, Chein-Ju Chen, Yu-Cheng Jhuang, Mau-Phon Houng, Fang-Hsing Wang, Min-Chu Liu, Cheng-Fu Yang, Cheng-Shong Hong

Abstract:

Since the use of wireless communications has become critical nowadays, the available RF spectrum has become limited. Ultraviolet (UV) communication system can alleviate the spectrum constraint making UV communication system a potential alternative to future communication demands. Also, UV links can provide faster communication rate and can be used in combination with existing RF communication links, providing new communications diversity with higher user capacity. The UV region of electromagnetic spectrum has been of interest to detector, imaging and communication technologies because the stratospheric ozone layer effectively absorbs some solar UV radiation from reaching the earth surface. The wavebands where most of UV radiation is absorbed by the ozone are commonly known as the solar blind region. By operating in UV-C band (200-280 nm) the communication system can minimize the transmission power consumption since it will have less radiation noise. UV communication uses the UV ray as the medium. Electric signal is carried on this band after being modulated and then be transmitted within the atmosphere as channel. Though the background noise of UV-C communication is very low owing to the solar-blind feature, it leads to a large propagation loss. The 370 nm UV provides a much lower propagation loss than that the UV-C does and the recent device technology for UV source on this band is more mature. The fabricated 370 nm AlGaN light-emitting diodes (LEDs) with an aperture size of 45 m exhibit a modulation bandwidth of 165 MHz at 30 mA and a high power of 7 W/cm2 at 230 A/cm2. In order to solve the problem of low power in single UV LED, a UV LED array is presented in.

Keywords: ultraviolet (UV) communication, light-emitting diodes (LEDs), modulation bandwidth, LED array, 370 nm

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576 Localization of Pyrolysis and Burning of Ground Forest Fires

Authors: Pavel A. Strizhak, Geniy V. Kuznetsov, Ivan S. Voytkov, Dmitri V. Antonov

Abstract:

This paper presents the results of experiments carried out at a specialized test site for establishing macroscopic patterns of heat and mass transfer processes at localizing model combustion sources of ground forest fires with the use of barrier lines in the form of a wetted lay of material in front of the zone of flame burning and thermal decomposition. The experiments were performed using needles, leaves, twigs, and mixtures thereof. The dimensions of the model combustion source and the ranges of heat release correspond well to the real conditions of ground forest fires. The main attention is paid to the complex analysis of the effect of dispersion of water aerosol (concentration and size of droplets) used to form the barrier line. It is shown that effective conditions for localization and subsequent suppression of flame combustion and thermal decomposition of forest fuel can be achieved by creating a group of barrier lines with different wetting width and depth of the material. Relative indicators of the effectiveness of one and combined barrier lines were established, taking into account all the main characteristics of the processes of suppressing burning and thermal decomposition of forest combustible materials. We performed the prediction of the necessary and sufficient parameters of barrier lines (water volume, width, and depth of the wetted lay of the material, specific irrigation density) for combustion sources with different dimensions, corresponding to the real fire extinguishing practice.

Keywords: forest fire, barrier water lines, pyrolysis front, flame front

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575 Speech Intelligibility Improvement Using Variable Level Decomposition DWT

Authors: Samba Raju, Chiluveru, Manoj Tripathy

Abstract:

Intelligibility is an essential characteristic of a speech signal, which is used to help in the understanding of information in speech signal. Background noise in the environment can deteriorate the intelligibility of a recorded speech. In this paper, we presented a simple variance subtracted - variable level discrete wavelet transform, which improve the intelligibility of speech. The proposed algorithm does not require an explicit estimation of noise, i.e., prior knowledge of the noise; hence, it is easy to implement, and it reduces the computational burden. The proposed algorithm decides a separate decomposition level for each frame based on signal dominant and dominant noise criteria. The performance of the proposed algorithm is evaluated with speech intelligibility measure (STOI), and results obtained are compared with Universal Discrete Wavelet Transform (DWT) thresholding and Minimum Mean Square Error (MMSE) methods. The experimental results revealed that the proposed scheme outperformed competing methods

Keywords: discrete wavelet transform, speech intelligibility, STOI, standard deviation

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574 Speaker Identification by Atomic Decomposition of Learned Features Using Computational Auditory Scene Analysis Principals in Noisy Environments

Authors: Thomas Bryan, Veton Kepuska, Ivica Kostanic

Abstract:

Speaker recognition is performed in high Additive White Gaussian Noise (AWGN) environments using principals of Computational Auditory Scene Analysis (CASA). CASA methods often classify sounds from images in the time-frequency (T-F) plane using spectrograms or cochleargrams as the image. In this paper atomic decomposition implemented by matching pursuit performs a transform from time series speech signals to the T-F plane. The atomic decomposition creates a sparsely populated T-F vector in “weight space” where each populated T-F position contains an amplitude weight. The weight space vector along with the atomic dictionary represents a denoised, compressed version of the original signal. The arraignment or of the atomic indices in the T-F vector are used for classification. Unsupervised feature learning implemented by a sparse autoencoder learns a single dictionary of basis features from a collection of envelope samples from all speakers. The approach is demonstrated using pairs of speakers from the TIMIT data set. Pairs of speakers are selected randomly from a single district. Each speak has 10 sentences. Two are used for training and 8 for testing. Atomic index probabilities are created for each training sentence and also for each test sentence. Classification is performed by finding the lowest Euclidean distance between then probabilities from the training sentences and the test sentences. Training is done at a 30dB Signal-to-Noise Ratio (SNR). Testing is performed at SNR’s of 0 dB, 5 dB, 10 dB and 30dB. The algorithm has a baseline classification accuracy of ~93% averaged over 10 pairs of speakers from the TIMIT data set. The baseline accuracy is attributable to short sequences of training and test data as well as the overall simplicity of the classification algorithm. The accuracy is not affected by AWGN and produces ~93% accuracy at 0dB SNR.

Keywords: time-frequency plane, atomic decomposition, envelope sampling, Gabor atoms, matching pursuit, sparse dictionary learning, sparse autoencoder

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573 Study on Technological Development for Reducing the Sulfur Dioxide Residue Problem in Fresh Longan for Exporting

Authors: Wittaya Apai, Satippong Rattanakam, Suttinee Likhittragulrung, Nuttanai Tungmunkongvorakul, Sompetch Jaroensuk

Abstract:

The objective of this study was to find some alternative ways to decrease sulfur dioxide (SO₂) residue problem and prolong storage life in fresh longan for export. Office of Agricultural Research and Development Region 1, Chiang Mai province conducted the research and development from 2016-2018. A grade longan cv. Daw fruit with panicle attached was placed in 11.5 kg commercial perforated plastic basket. They had 5 selected treatments comprising of 3 baskets as replication for each treatment, i.e. 1.5% SO₂ fumigation prior to insert SO₂-generated pads (Uvasys®) (1.5% SO₂+SO₂ pad), dipping in 5% hydrochloric acid (HCl) mixed with 1% sodium metabisulfite (SMS) for 5 min (5% HCl +1% SMS), ozone (O₃) fumigation for 1 hours (h) prior to 1.5% SO₂ fumigation (O₃ 1 h+1.5% SO₂), 1.5% SO₂ fumigation prior to O₃ fumigation for 1 h (1.5% SO₂+O₃ 1 h) and 1.5% SO₂ fumigation alone as commercial treatment (1.5% SO₂). They were stored at 5 ˚C, 90% relative humidity (RH) for 40-80 days. The results found that the possible treatments were 1.5% SO₂+O₃ 1 h and 5% HCl +1% SMS respectively and prevented pericarp browning for 80 days at 5 ºC. There were no significant changes in some parameters in any treatments; 1.5% SO₂+O₃ 1 h and 1.5% SO₂ during storage, i.e., pericarp browning, flesh discoloration, disease incidence (%) and sensory evaluation during storage. Application 1.5% SO₂+O₃ 1 h had a tendency less both SO₂ residue in fruit and disease incidence (%) including brighter pericarp color as compared with commercial 1.5% SO₂ alone. Moreover, HCl 5%+SMS 1% showed the least SO₂ residue in whole fruit below codex tolerance at 50 mg/kg throughout period of time. The fruit treated with 1.5% SO₂+O₃ 1 h, 1.5% SO₂, 5% HCl+1% SMS, O₃ 1 h+1.5% SO₂, and 1.5% SO₂+SO₂ pad could prolong storage life for 40, 40, 40, 30 and 30 days respectively at 5°C, 90% RH. Thus, application 1.5% SO₂+O₃ 1 h and/or 5% HCl +1% SMS could be used for extending shelf life fresh longan exported to restricted countries due to less SO₂ residue and fruit quality was maintained as compared with the conventional method.

Keywords: longan, sulfur dioxide, ozone fumigation, sodium metabisulfite

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572 Body Farming in India and Asia

Authors: Yogesh Kumar, Adarsh Kumar

Abstract:

A body farm is a research facility where research is done on forensic investigation and medico-legal disciplines like forensic entomology, forensic pathology, forensic anthropology, forensic archaeology, and related areas of forensic veterinary. All the research is done to collect data on the rate of decomposition (animal and human) and forensically important insects to assist in crime detection. The data collected is used by forensic pathologists, forensic experts, and other experts for the investigation of crime cases and further research. The research work includes different conditions of a dead body like fresh, bloating, decay, dry, and skeleton, and data on local insects which depends on the climatic conditions of the local areas of that country. Therefore, it is the need of time to collect appropriate data in managed conditions with a proper set-up in every country. Hence, it is the duty of the scientific community of every country to establish/propose such facilities for justice and social management. The body farms are also used for training of police, military, investigative dogs, and other agencies. At present, only four countries viz. U.S., Australia, Canada, and Netherlands have body farms and related facilities in organised manner. There is no body farm in Asia also. In India, we have been trying to establish a body farm in A&N Islands that is near Singapore, Malaysia, and some other Asian countries. In view of the above, it becomes imperative to discuss the matter with Asian countries to collect the data on decomposition in a proper manner by establishing a body farm. We can also share the data, knowledge, and expertise to collaborate with one another to make such facilities better and have good scientific relations to promote science and explore ways of investigation at the world level.

Keywords: body farm, rate of decomposition, forensically important flies, time since death

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571 A Spatial Information Network Traffic Prediction Method Based on Hybrid Model

Authors: Jingling Li, Yi Zhang, Wei Liang, Tao Cui, Jun Li

Abstract:

Compared with terrestrial network, the traffic of spatial information network has both self-similarity and short correlation characteristics. By studying its traffic prediction method, the resource utilization of spatial information network can be improved, and the method can provide an important basis for traffic planning of a spatial information network. In this paper, considering the accuracy and complexity of the algorithm, the spatial information network traffic is decomposed into approximate component with long correlation and detail component with short correlation, and a time series hybrid prediction model based on wavelet decomposition is proposed to predict the spatial network traffic. Firstly, the original traffic data are decomposed to approximate components and detail components by using wavelet decomposition algorithm. According to the autocorrelation and partial correlation smearing and truncation characteristics of each component, the corresponding model (AR/MA/ARMA) of each detail component can be directly established, while the type of approximate component modeling can be established by ARIMA model after smoothing. Finally, the prediction results of the multiple models are fitted to obtain the prediction results of the original data. The method not only considers the self-similarity of a spatial information network, but also takes into account the short correlation caused by network burst information, which is verified by using the measured data of a certain back bone network released by the MAWI working group in 2018. Compared with the typical time series model, the predicted data of hybrid model is closer to the real traffic data and has a smaller relative root means square error, which is more suitable for a spatial information network.

Keywords: spatial information network, traffic prediction, wavelet decomposition, time series model

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570 Comparison of Soils of Hungarian Dry and Humid Oak Forests Based on Changes in Nutrient Content

Authors: István Fekete, Imre Berki, Áron Béni, Katalin Juhos, Marianna Makádi, Zsolt Kotroczó

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The average annual precipitation significantly influences the moisture content of the soils and, through this, the decomposition of the organic substances in the soils, the leaching of nutrients from the soils, and the pH of the soils. Climate change, together with the lengthening of the vegetation period and the increasing CO₂ level, can increase the amount of biomass that is formed. Degradation processes, which accelerate as the temperature increases and slow down due to the drying climate, and the change in the degree of leaching can cancel out or strengthen each other's effects. In the course of our research, we looked for oak forests with climate-zonal soils where the geological, geographical and ecological background conditions are as similar as possible, apart from the different annual precipitation averages and the differences that can arise from them. We examined 5 dry and 5 humid Hungarian oak soils. Climate change affects the soils of drier and wetter forests differently. The aim of our research was to compare the content of carbon, nitrogen and some other nutrients, as well as the pH of the soils of humid and dry forests. Showing the effects of the drier climate on the tested soil parameters. In the case of the examined forest soils, we found a significant difference between the soils of dry and humid forests: in the case of the annual average precipitation values (p≥ 0.0001, for dry forest soils: 564±5.2 mm; for humid forest soils: 716±3.8 mm) for pH (p= 0.0004, for dry forest soils: 5.49±0.16; for wet forest soils: 5.36±0.21); for C content (p= 0.0054, for dry forest soils: 6.92%±0.59; for humid forest soils 3.09%±0.24), for N content (p= 0.0022, dry forest in the case of soils: 0.44%±0.047; in the case of humid forest soils: 0.23%±0.013), for the K content (p=0.0017, in the case of dry forest soils: 5684±732 (mg/kg); in the case of humid forest soils 2169±196 (mg/kg)), for the Ca content (p= 0.0096, for dry forest soils: 8207±2118 (mg/kg); for wet forest soils 957±320 (mg/kg)). No significant difference was found in the case of Mg. In a wetter environment, especially if the moisture content of the soil is also optimal for the decomposing organisms during the growing season, the decomposition of organic residues accelerates, and the processes of leaching from the soil are also intensified. The different intensity of the leaching processes is also well reflected in the quantitative differences of Ca and K, and in connection with these, it is also reflected in the difference in pH values. The differences in the C and N content can be explained by differences in the intensity of the decomposition processes. In addition to warming, drying is expected in a significant part of Hungary due to climate change. Thus, the comparison of the soils of dry and humid forests allows us to predict the subsequent changes in the case of the examined parameters.

Keywords: soil nutrients, precipitation difference, climate change, organic matter decomposition, leaching

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569 Vibration Propagation in Structures Through Structural Intensity Analysis

Authors: Takhchi Jamal, Ouisse Morvan, Sadoulet-Reboul Emeline, Bouhaddi Noureddine, Gagliardini Laurent, Bornet Frederic, Lakrad Faouzi

Abstract:

Structural intensity is a technique that can be used to indicate both the magnitude and direction of power flow through a structure from the excitation source to the dissipation sink. However, current analysis is limited to the low frequency range. At medium and high frequencies, a rotational component appear in the field, masking the energy flow and make its understanding difficult or impossible. The objective of this work is to implement a methodology to filter out the rotational components of the structural intensity field in order to fully understand the energy flow in complex structures. The approach is based on the Helmholtz decomposition. It allows to decompose the structural intensity field into rotational, irrotational, and harmonic components. Only the irrotational component is needed to describe the net power flow from a source to a dissipative zone in the structure. The methodology has been applied on academic structures, and it allows a good analysis of the energy transfer paths.

Keywords: structural intensity, power flow, helmholt decomposition, irrotational intensity

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568 Inverse Prediction of Thermal Parameters of an Annular Hyperbolic Fin Subjected to Thermal Stresses

Authors: Ashis Mallick, Rajeev Ranjan

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The closed form solution for thermal stresses in an annular fin with hyperbolic profile is derived using Adomian decomposition method (ADM). The conductive-convective fin with variable thermal conductivity is considered in the analysis. The nonlinear heat transfer equation is efficiently solved by ADM considering insulated convective boundary conditions at the tip of fin. The constant of integration in the solution is to be estimated using minimum decomposition error method. The solution of temperature field is represented in a polynomial form for convenience to use in thermo-elasticity equation. The non-dimensional thermal stress fields are obtained using the ADM solution of temperature field coupled with the thermo-elasticity solution. The influence of the various thermal parameters in temperature field and stress fields are presented. In order to show the accuracy of the ADM solution, the present results are compared with the results available in literature. The stress fields in fin with hyperbolic profile are compared with those of uniform thickness profile. Result shows that hyperbolic fin profile is better choice for enhancing heat transfer. Moreover, less thermal stresses are developed in hyperbolic profile as compared to rectangular profile. Next, Nelder-Mead based simplex search method is employed for the inverse estimation of unknown non-dimensional thermal parameters in a given stress fields. Owing to the correlated nature of the unknowns, the best combinations of the model parameters which are satisfying the predefined stress field are to be estimated. The stress fields calculated using the inverse parameters give a very good agreement with the stress fields obtained from the forward solution. The estimated parameters are suitable to use for efficient and cost effective fin designing.

Keywords: Adomian decomposition, inverse analysis, hyperbolic fin, variable thermal conductivity

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567 Examining Microbial Decomposition, Carbon Cycling and Storage in Cefni Coastal Salt Marsh, Anglesey Island, Wales, United Kingdom

Authors: Dasat G. S., Christopher F. Tim, J. Dun C.

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Salt marshes are known to sequester carbon dioxide from the atmosphere into the soil, but natural and anthropogenic activities could trigger the release of large quantities of centuries of buried carbon dioxide, methane and nitrous oxide (CO2, CH4 and N2O) which are the major greenhouse gases (GHGs) implicated with climate change. Therefore, this study investigated the biogeochemical activities by collecting soil samples from low, mid and high zones of the Cefni salt marsh, within the Maltreat estuary, on the island of Anglesey, north Wales, United Kingdom for a consortium of laboratory based experiments using standard operating protocols (POS) to quantify the soil organic matter contents and the rate of microbial decomposition and carbon storage at the Carbon Capture Laboratory of Bangor University Wales. Results of investigations reveals that the mid zone had 56.23% and 9.98% of soil water and soil organic matter (SOM) contents respectively higher than the low and high zones. Phenol oxidase activity (1193.53µmol dicq g-1 h-1) was highest at the low zone in comparison to the high and mid zones (867.60 and 608.74 µmol dicq g-1 h-1) respectively. Soil phenolic concentration was found to be highest in the mid zone (53.25 µg-1 g-1) when compared with those from the high (15.66 µg-1 g-1) and low (4.18 µg-1 g-1) zones respectively. Activities of hydrolase enzymes showed similar trend for the high and low zones and much lower activities in the mid zone. CO2 flux from the mid zone (6.79 ug g-1 h-1) was significantly greater than those from high (-2.29 ug g-1 h-1) and low (1.30 µg g-1 h-1) zones. Since salt marshes provide essential ecosystem services, their degradation or alteration in whatever form could compromise such ecosystem services and could convert them from net sinks into net sources with consequential effects to the global environment.

Keywords: saltmarsh, decomposition, carbon cycling, enzymes

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566 Application of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Multipoint Optimal Minimum Entropy Deconvolution in Railway Bearings Fault Diagnosis

Authors: Yao Cheng, Weihua Zhang

Abstract:

Although the measured vibration signal contains rich information on machine health conditions, the white noise interferences and the discrete harmonic coming from blade, shaft and mash make the fault diagnosis of rolling element bearings difficult. In order to overcome the interferences of useless signals, a new fault diagnosis method combining Complete Ensemble Empirical Mode Decomposition with adaptive noise (CEEMDAN) and Multipoint Optimal Minimum Entropy Deconvolution (MOMED) is proposed for the fault diagnosis of high-speed train bearings. Firstly, the CEEMDAN technique is applied to adaptively decompose the raw vibration signal into a series of finite intrinsic mode functions (IMFs) and a residue. Compared with Ensemble Empirical Mode Decomposition (EEMD), the CEEMDAN can provide an exact reconstruction of the original signal and a better spectral separation of the modes, which improves the accuracy of fault diagnosis. An effective sensitivity index based on the Pearson's correlation coefficients between IMFs and raw signal is adopted to select sensitive IMFs that contain bearing fault information. The composite signal of the sensitive IMFs is applied to further analysis of fault identification. Next, for propose of identifying the fault information precisely, the MOMED is utilized to enhance the periodic impulses in composite signal. As a non-iterative method, the MOMED has better deconvolution performance than the classical deconvolution methods such Minimum Entropy Deconvolution (MED) and Maximum Correlated Kurtosis Deconvolution (MCKD). Third, the envelope spectrum analysis is applied to detect the existence of bearing fault. The simulated bearing fault signals with white noise and discrete harmonic interferences are used to validate the effectiveness of the proposed method. Finally, the superiorities of the proposed method are further demonstrated by high-speed train bearing fault datasets measured from test rig. The analysis results indicate that the proposed method has strong practicability.

Keywords: bearing, complete ensemble empirical mode decomposition with adaptive noise, fault diagnosis, multipoint optimal minimum entropy deconvolution

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565 The Continuously Supported Infinity Rail Subjected to a Moving Complex Bogie System

Authors: Vladimir Stojanović, Marko D. Petković

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The vibration of a complex bogie system that moves on along the high order shear deformable beam on a viscoelastic foundation is studied. The complex bogie system has been modeled by elastically connected rigid bars on an identical supports. Elastic coupling between bars is introduced to simulate rigidly or flexibly (transversal or/and rotational) connection. Identical supports are modeled as a system of attached spring and dashpot to the bar on one side and interact with the beam through the concentrated mass on the other side. It is assumed that the masses and the beam are always in contact. New analytically determined critical velocity of the system is presented. It is analyzed the case when the complex bogie system exceeds the minimum phase velocity of waves in the beam when the vibration of the system may become unstable. Effect of an elastic coupling between bars on the stability of the system has been analyzed. The instability regions are found for the complex bogie system by applying the principle of the argument and D-decomposition method.

Keywords: Reddy-Bickford beam, D-decomposition method, principle of argument, critical velocity

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564 Evolution of Microstructure through Phase Separation via Spinodal Decomposition in Spinel Ferrite Thin Films

Authors: Nipa Debnath, Harinarayan Das, Takahiko Kawaguchi, Naonori Sakamoto, Kazuo Shinozaki, Hisao Suzuki, Naoki Wakiya

Abstract:

Nowadays spinel ferrite magnetic thin films have drawn considerable attention due to their interesting magnetic and electrical properties with enhanced chemical and thermal stability. Spinel ferrite magnetic films can be implemented in magnetic data storage, sensors, and spin filters or microwave devices. It is well established that the structural, magnetic and transport properties of the magnetic thin films are dependent on microstructure. Spinodal decomposition (SD) is a phase separation process, whereby a material system is spontaneously separated into two phases with distinct compositions. The periodic microstructure is the characteristic feature of SD. Thus, SD can be exploited to control the microstructure at the nanoscale level. In bulk spinel ferrites having general formula, MₓFe₃₋ₓ O₄ (M= Co, Mn, Ni, Zn), phase separation via SD has been reported only for cobalt ferrite (CFO); however, long time post-annealing is required to occur the spinodal decomposition. We have found that SD occurs in CoF thin film without using any post-deposition annealing process if we apply magnetic field during thin film growth. Dynamic Aurora pulsed laser deposition (PLD) is a specially designed PLD system through which in-situ magnetic field (up to 2000 G) can be applied during thin film growth. The in-situ magnetic field suppresses the recombination of ions in the plume. In addition, the peak’s intensity of the ions in the spectra of the plume also increases when magnetic field is applied to the plume. As a result, ions with high kinetic energy strike into the substrate. Thus, ion-impingement occurred under magnetic field during thin film growth. The driving force of SD is the ion-impingement towards the substrates that is induced by in-situ magnetic field. In this study, we report about the occurrence of phase separation through SD and evolution of microstructure after phase separation in spinel ferrite thin films. The surface morphology of the phase separated films show checkerboard like domain structure. The cross-sectional microstructure of the phase separated films reveal columnar type phase separation. Herein, the decomposition wave propagates in lateral direction which has been confirmed from the lateral composition modulations in spinodally decomposed films. Large magnetic anisotropy has been found in spinodally decomposed nickel ferrite (NFO) thin films. This approach approves that magnetic field is also an important thermodynamic parameter to induce phase separation by the enhancement of up-hill diffusion in thin films. This thin film deposition technique could be a more efficient alternative for the fabrication of self-organized phase separated thin films and employed in controlling of the microstructure at nanoscale level.

Keywords: Dynamic Aurora PLD, magnetic anisotropy, spinodal decomposition, spinel ferrite thin film

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563 Comprehensive, Up-to-Date Climate System Change Indicators, Trends and Interactions

Authors: Peter Carter

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Comprehensive climate change indicators and trends inform the state of the climate (system) with respect to present and future climate change scenarios and the urgency of mitigation and adaptation. With data records now going back for many decades, indicator trends can complement model projections. They are provided as datasets by several climate monitoring centers, reviewed by state of the climate reports, and documented by the IPCC assessments. Up-to-date indicators are provided here. Rates of change are instructive, as are extremes. The indicators include greenhouse gas (GHG) emissions (natural and synthetic), cumulative CO2 emissions, atmospheric GHG concentrations (including CO2 equivalent), stratospheric ozone, surface ozone, radiative forcing, global average temperature increase, land temperature increase, zonal temperature increases, carbon sinks, soil moisture, sea surface temperature, ocean heat content, ocean acidification, ocean oxygen, glacier mass, Arctic temperature, Arctic sea ice (extent and volume), northern hemisphere snow cover, permafrost indices, Arctic GHG emissions, ice sheet mass, sea level rise, and stratospheric and surface ozone. Global warming is not the most reliable single metric for the climate state. Radiative forcing, atmospheric CO2 equivalent, and ocean heat content are more reliable. Global warming does not provide future commitment, whereas atmospheric CO2 equivalent does. Cumulative carbon is used for estimating carbon budgets. The forcing of aerosols is briefly addressed. Indicator interactions are included. In particular, indicators can provide insight into several crucial global warming amplifying feedback loops, which are explained. All indicators are increasing (adversely), most as fast as ever and some faster. One particularly pressing indicator is rapidly increasing global atmospheric methane. In this respect, methane emissions and sources are covered in more detail. In their application, indicators used in assessing safe planetary boundaries are included. Indicators are considered with respect to recent published papers on possible catastrophic climate change and climate system tipping thresholds. They are climate-change-policy relevant. In particular, relevant policies include the 2015 Paris Agreement on “holding the increase in the global average temperature to well below 2°C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5°C above pre-industrial levels” and the 1992 UN Framework Convention on Climate change, which has “stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference with the climate system.”

Keywords: climate change, climate change indicators, climate change trends, climate system change interactions

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562 One Dimensional Unsteady Boundary Layer Flow in an Inclined Wavy Wall of a Nanofluid with Convective Boundary Condition

Authors: Abdulhakeem Yusuf, Yomi Monday Aiyesimi, Mohammed Jiya

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The failure in an ordinary heat transfer fluid to meet up with today’s industrial cooling rate has resulted in the development of high thermal conductivity fluid which nanofluids belongs. In this work, the problem of unsteady one dimensional laminar flow of an incompressible fluid within a parallel wall is considered with one wall assumed to be wavy. The model is presented in its rectangular coordinate system and incorporates the effects of thermophoresis and Brownian motion. The local similarity solutions were also obtained which depends on Soret number, Dufour number, Biot number, Lewis number, and heat generation parameter. The analytical solution is obtained in a closed form via the Adomian decomposition method. It was found that the method has a good agreement with the numerical method, and it is also established that the heat generation parameter has to be kept low so that heat energy are easily evacuated from the system.

Keywords: Adomian decomposition method, Biot number, Dufour number, nanofluid

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561 A Multi Sensor Monochrome Video Fusion Using Image Quality Assessment

Authors: M. Prema Kumar, P. Rajesh Kumar

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The increasing interest in image fusion (combining images of two or more modalities such as infrared and visible light radiation) has led to a need for accurate and reliable image assessment methods. This paper gives a novel approach of merging the information content from several videos taken from the same scene in order to rack up a combined video that contains the finest information coming from different source videos. This process is known as video fusion which helps in providing superior quality (The term quality, connote measurement on the particular application.) image than the source images. In this technique different sensors (whose redundant information can be reduced) are used for various cameras that are imperative for capturing the required images and also help in reducing. In this paper Image fusion technique based on multi-resolution singular value decomposition (MSVD) has been used. The image fusion by MSVD is almost similar to that of wavelets. The idea behind MSVD is to replace the FIR filters in wavelet transform with singular value decomposition (SVD). It is computationally very simple and is well suited for real time applications like in remote sensing and in astronomy.

Keywords: multi sensor image fusion, MSVD, image processing, monochrome video

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560 Fast and Accurate Model to Detect Ictal Waveforms in Electroencephalogram Signals

Authors: Piyush Swami, Bijaya Ketan Panigrahi, Sneh Anand, Manvir Bhatia, Tapan Gandhi

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Visual inspection of electroencephalogram (EEG) signals to detect epileptic signals is very challenging and time-consuming task even for any expert neurophysiologist. This problem is most challenging in under-developed and developing countries due to shortage of skilled neurophysiologists. In the past, notable research efforts have gone in trying to automate the seizure detection process. However, due to high false alarm detections and complexity of the models developed so far, have vastly delimited their practical implementation. In this paper, we present a novel scheme for epileptic seizure detection using empirical mode decomposition technique. The intrinsic mode functions obtained were then used to calculate the standard deviations. This was followed by probability density based classifier to discriminate between non-ictal and ictal patterns in EEG signals. The model presented here demonstrated very high classification rates ( > 97%) without compromising the statistical performance. The computation timings for each testing phase were also very low ( < 0.029 s) which makes this model ideal for practical applications.

Keywords: electroencephalogram (EEG), epilepsy, ictal patterns, empirical mode decomposition

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559 Multidimensional Study on the Deprivations Faced by Women in India

Authors: Ramya Rachel S.

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For women in a developing country like India, poverty is an ever-clinging problem which has rooted itself without any trace of absolute abolition. Poverty is a deprivation of many imminent needs and must be measured accordingly. Therefore, it is important to study the dimensions of education, health, and standard of living to understand the true nature of the impoverished. The study focused on studying the deprivation on these aspects using the Alkire-Foster methodology to estimate the Multidimensional Poverty Index. The study has utilized the individual data of women aged 15 to 49 of the National Family Health Survey (NFHS) for the year 2015-16. Findings reveal that women in India still face extreme levels of deprivation in various dimensions. More than one-third of the total women aged 15 to 24 in India were multidimensionally poor. Dimensional breakdown of the levels of multidimensional poverty indicates that the dimension of Education is the highest contributor to poverty. Decomposition of the multidimensional poverty among various demographic sub-groups, reveals that the multidimensional poverty level increases with age. Results point out that deprivations were higher among widowed and married women, and among women who lived alone. There was also a huge rural-urban divide with respect to poverty. The basic needs of these women must be targeted and met so that they are withdrawn from all forms of poverty.

Keywords: deprivations, multidimensional poverty, sub-group decomposition, women

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558 Labview-Based System for Fiber Links Events Detection

Authors: Bo Liu, Qingshan Kong, Weiqing Huang

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With the rapid development of modern communication, diagnosing the fiber-optic quality and faults in real-time is widely focused. In this paper, a Labview-based system is proposed for fiber-optic faults detection. The wavelet threshold denoising method combined with Empirical Mode Decomposition (EMD) is applied to denoise the optical time domain reflectometer (OTDR) signal. Then the method based on Gabor representation is used to detect events. Experimental measurements show that signal to noise ratio (SNR) of the OTDR signal is improved by 1.34dB on average, compared with using the wavelet threshold denosing method. The proposed system has a high score in event detection capability and accuracy. The maximum detectable fiber length of the proposed Labview-based system can be 65km.

Keywords: empirical mode decomposition, events detection, Gabor transform, optical time domain reflectometer, wavelet threshold denoising

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557 Rethinking the Air Quality Health Index: Harmonizing Health Protection and Climate Mitigation

Authors: Kimberly Tasha Jiayi Tang, Changqing Lin, Zhe Wang, Tze-Wai Wong, Md. Shakhaoat Hossain, Jian Yu, Alexis Lau

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Hong Kong has practiced a risk-based Air Quality Health Index (AQHI) system that sums hospitalization risks associated with short-term exposure to air pollu-tants. As an air pollution risk communication tool, it informs the public about the current air quality, anchoring around the World Health Organization's (WHO) 2005 Air Quality Guidelines (AQGs). Given the WHO's recent update in 2021, assessing how Hong Kong’s air quality risk communication can be en-hanced using these updated guidelines is essential. Hong Kong’s AQHI is lim-ited by solely focusing on short-term health risks, which could lead the public to underestimate cumulative health impacts. Therefore, we propose the intro-duction of a composite AQHI that reports both long-term and short-term health risks. Additionally, the WHO interim targets will be considered as anchor points for various health risk categories. Furthermore, with the increasing ozone levels in Hong Kong and Southern China due to improved NOx mitigation measures, it has been a challenging task in balancing health protection against climate mitigation. However, our findings present a promising outlook. Despite the rise in ozone levels, the combined health risks in Hong Kong and Guang-dong have seen a decline, largely due to reductions in NO2 and PM concentra-tions, both having significant health implications. By shifting from a concentra-tion-based approach to a health risk-based system like the AQHI, our study highlights the prospective of harmonizing health protection and climate mitiga-tion goals. This health-focused framework suggests that rigorous NOx controls can effective-ly serve both objectives in parallel.

Keywords: air quality management, air quality health index, health risk management, air pollution

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556 Study of Isoprene Emissions in Biogenic ad Anthropogenic Environment in Urban Atmosphere of Delhi: The Capital City of India

Authors: Prabhat Kashyap, Krishan Kumar

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Delhi, the capital of India, is one of the most populated and polluted city among the world. In terms of air quality, Delhi’s air is degrading day by day & becomes worst of any major city in the world. The role of biogenic volatile organic compounds (BVOCs) is not much studied in cities like Delhi as a culprit for degraded air quality. They not only play a critical role in rural areas but also determine the atmospheric chemistry of urban areas as well. Particularly, Isoprene (2-methyl 1,3-butadiene, C5H8) is the single largest emitted compound among other BVOCs globally, that influence the tropospheric ozone chemistry in urban environment as the ozone forming potential of isoprene is very high. It is mainly emitted by vegetation & a small but significant portion is also released by vehicular exhaust of petrol operated vehicles. This study investigates the spatial and temporal variations of quantitative measurements of isoprene emissions along with different traffic tracers in 2 different seasons (post-monsoon & winter) at four different locations of Delhi. For the quantification of anthropogenic and biogenic isoprene, two sites from traffic intersections (Punjabi Bagh & CRRI) and two sites from vegetative locations (JNU & Yamuna Biodiversity Park) were selected in the vicinity of isoprene emitting tree species like Ficus religiosa, Dalbergia sissoo, Eucalyptus species etc. The concentrations of traffic tracers like benzene, toluene were also determined & their robust ratios with isoprene were used to differentiate anthropogenic isoprene with biogenic portion at each site. The ozone forming potential (OFP) of all selected species along with isoprene was also estimated. For collection of intra-day samples (3 times a day) in each season, a pre-conditioned fenceline monitoring (FLM) carbopack X thermal desorption tubes were used and further analysis was done with Gas chromatography attached with mass spectrometry (GC-MS). The results of the study proposed that the ambient air isoprene is always higher in post-monsoon season as compared to winter season at all the sites because of high temperature & intense sunlight. The maximum isoprene emission flux was always observed during afternoon hours in both seasons at all sites. The maximum isoprene concentration was found to be 13.95 ppbv at Biodiversity Park during afternoon time in post monsoon season while the lower concentration was observed as low as 0.07 ppbv at the same location during morning hours in winter season. OFP of isoprene at vegetation sites is very high during post-monsoon because of high concentrations. However, OFP for other traffic tracers were high during winter seasons & at traffic locations. Furthermore, high correlation between isoprene emissions with traffic volume at traffic sites revealed that a noteworthy share of its emission also originates from road traffic.

Keywords: biogenic VOCs, isoprene emission, anthropogenic isoprene, urban vegetation

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555 Study of Synergetic Effect by Combining Dielectric Barrier Discharge (DBD) Plasma and Photocatalysis for Abatement of Pollutants in Air Mixture System: Influence of Some Operating Conditions and Identification of Byproducts

Authors: Wala Abou Saoud, Aymen Amine Assadi, Monia Guiza, Abdelkrim Bouzaza, Wael Aboussaoud, Abdelmottaleb Ouederni, Dominique Wolbert

Abstract:

Volatile organic compounds (VOCs) constitute one of the most important families of chemicals involved in atmospheric pollution, causing damage to the environment and human health, and need, consequently, to be eliminated. Among the promising technologies, dielectric barrier discharge (DBD) plasma - photocatalysis coupling reveals very interesting prospects in terms of process synergy of compounds mineralization’s, with low energy consumption. In this study, the removal of organic compounds such butyraldehyde (BUTY) and dimethyl disulfide (DMDS) (exhaust gasses from animal quartering centers.) in air mixture using DBD plasma coupled with photocatalysis was tested, in order to determine whether or not synergy effect was present. The removal efficiency of these pollutants, a selectivity of CO₂ and CO, and byproducts formation such as ozone formation were investigated in order to evaluate the performance of the combined process. For this purpose, a series of experiments were carried out in a continuous reactor. Many operating parameters were also investigated such as the specific energy of discharge, the inlet concentration of pollutant and the flowrate. It appears from this study that, the performance of the process has enhanced and a synergetic effect is observed. In fact, we note an enhancement of 10 % on removal efficiency. It is interesting to note that the combined system leads to better CO₂ selectivity than for plasma. Consequently, intermediates by-products have been reduced due to various other species (O•, N, OH•, O₂•-, O₃, NO₂, NOx, etc.). Additionally, the behavior of combining DBD plasma and photocatalysis has shown that the ozone can be easily also decomposed in presence of photocatalyst.

Keywords: combined process, DBD plasma, photocatalysis, pilot scale, synergetic effect, VOCs

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554 A Sparse Representation Speech Denoising Method Based on Adapted Stopping Residue Error

Authors: Qianhua He, Weili Zhou, Aiwu Chen

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A sparse representation speech denoising method based on adapted stopping residue error was presented in this paper. Firstly, the cross-correlation between the clean speech spectrum and the noise spectrum was analyzed, and an estimation method was proposed. In the denoising method, an over-complete dictionary of the clean speech power spectrum was learned with the K-singular value decomposition (K-SVD) algorithm. In the sparse representation stage, the stopping residue error was adaptively achieved according to the estimated cross-correlation and the adjusted noise spectrum, and the orthogonal matching pursuit (OMP) approach was applied to reconstruct the clean speech spectrum from the noisy speech. Finally, the clean speech was re-synthesised via the inverse Fourier transform with the reconstructed speech spectrum and the noisy speech phase. The experiment results show that the proposed method outperforms the conventional methods in terms of subjective and objective measure.

Keywords: speech denoising, sparse representation, k-singular value decomposition, orthogonal matching pursuit

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553 Multi-Objective Four-Dimensional Traveling Salesman Problem in an IoT-Based Transport System

Authors: Arindam Roy, Madhushree Das, Apurba Manna, Samir Maity

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In this research paper, an algorithmic approach is developed to solve a novel multi-objective four-dimensional traveling salesman problem (MO4DTSP) where different paths with various numbers of conveyances are available to travel between two cities. NSGA-II and Decomposition algorithms are modified to solve MO4DTSP in an IoT-based transport system. This IoT-based transport system can be widely observed, analyzed, and controlled by an extensive distribution of traffic networks consisting of various types of sensors and actuators. Due to urbanization, most of the cities are connected using an intelligent traffic management system. Practically, for a traveler, multiple routes and vehicles are available to travel between any two cities. Thus, the classical TSP is reformulated as multi-route and multi-vehicle i.e., 4DTSP. The proposed MO4DTSP is designed with traveling cost, time, and customer satisfaction as objectives. In reality, customer satisfaction is an important parameter that depends on travel costs and time reflects in the present model.

Keywords: multi-objective four-dimensional traveling salesman problem (MO4DTSP), decomposition, NSGA-II, IoT-based transport system, customer satisfaction

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552 Energy Related Carbon Dioxide Emissions in Pakistan: A Decomposition Analysis Using LMDI

Authors: Arsalan Khan, Faisal Jamil

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The unprecedented increase in anthropogenic gases in recent decades has led to climatic changes worldwide. CO2 emissions are the most important factors responsible for greenhouse gases concentrations. This study decomposes the changes in overall CO2 emissions in Pakistan for the period 1990-2012 using Log Mean Divisia Index (LMDI). LMDI enables to decompose the changes in CO2 emissions into five factors namely; activity effect, structural effect, intensity effect, fuel-mix effect, and emissions factor effect. This paper confirms an upward trend of overall emissions level of the country during the period. The study finds that activity effect, structural effect and intensity effect are the three major factors responsible for the changes in overall CO2 emissions in Pakistan with activity effect as the largest contributor to overall changes in the emissions level. The structural effect is also adding to CO2 emissions, which indicates that the economic activity is shifting towards more energy-intensive sectors. However, intensity effect has negative sign representing energy efficiency gains, which indicate a good relationship between the economy and environment. The findings suggest that policy makers should encourage the diversification of the output level towards more energy efficient sub-sectors of the economy.

Keywords: energy consumption, CO2 emissions, decomposition analysis, LMDI, intensity effect

Procedia PDF Downloads 371
551 Novel Recommender Systems Using Hybrid CF and Social Network Information

Authors: Kyoung-Jae Kim

Abstract:

Collaborative Filtering (CF) is a popular technique for the personalization in the E-commerce domain to reduce information overload. In general, CF provides recommending items list based on other similar users’ preferences from the user-item matrix and predicts the focal user’s preference for particular items by using them. Many recommender systems in real-world use CF techniques because it’s excellent accuracy and robustness. However, it has some limitations including sparsity problems and complex dimensionality in a user-item matrix. In addition, traditional CF does not consider the emotional interaction between users. In this study, we propose recommender systems using social network and singular value decomposition (SVD) to alleviate some limitations. The purpose of this study is to reduce the dimensionality of data set using SVD and to improve the performance of CF by using emotional information from social network data of the focal user. In this study, we test the usability of hybrid CF, SVD and social network information model using the real-world data. The experimental results show that the proposed model outperforms conventional CF models.

Keywords: recommender systems, collaborative filtering, social network information, singular value decomposition

Procedia PDF Downloads 260
550 Content-Based Mammograms Retrieval Based on Breast Density Criteria Using Bidimensional Empirical Mode Decomposition

Authors: Sourour Khouaja, Hejer Jlassi, Nadia Feddaoui, Kamel Hamrouni

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Most medical images, and especially mammographies, are now stored in large databases. Retrieving a desired image is considered of great importance in order to find previous similar cases diagnosis. Our method is implemented to assist radiologists in retrieving mammographic images containing breast with similar density aspect as seen on the mammogram. This is becoming a challenge seeing the importance of density criteria in cancer provision and its effect on segmentation issues. We used the BEMD (Bidimensional Empirical Mode Decomposition) to characterize the content of images and Euclidean distance measure similarity between images. Through the experiments on the MIAS mammography image database, we confirm that the results are promising. The performance was evaluated using precision and recall curves comparing query and retrieved images. Computing recall-precision proved the effectiveness of applying the CBIR in the large mammographic image databases. We found a precision of 91.2% for mammography with a recall of 86.8%.

Keywords: BEMD, breast density, contend-based, image retrieval, mammography

Procedia PDF Downloads 210
549 Clustering Color Space, Time Interest Points for Moving Objects

Authors: Insaf Bellamine, Hamid Tairi

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Detecting moving objects in sequences is an essential step for video analysis. This paper mainly contributes to the Color Space-Time Interest Points (CSTIP) extraction and detection. We propose a new method for detection of moving objects. Two main steps compose the proposed method. First, we suggest to apply the algorithm of the detection of Color Space-Time Interest Points (CSTIP) on both components of the Color Structure-Texture Image Decomposition which is based on a Partial Differential Equation (PDE): a color geometric structure component and a color texture component. A descriptor is associated to each of these points. In a second stage, we address the problem of grouping the points (CSTIP) into clusters. Experiments and comparison to other motion detection methods on challenging sequences show the performance of the proposed method and its utility for video analysis. Experimental results are obtained from very different types of videos, namely sport videos and animation movies.

Keywords: Color Space-Time Interest Points (CSTIP), Color Structure-Texture Image Decomposition, Motion Detection, clustering

Procedia PDF Downloads 354