Search results for: parallel series combinations
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4351

Search results for: parallel series combinations

3991 Investigating the Effects of Thermal and Surface Energy on the Two-Dimensional Flow Characteristics of Oil in Water Mixture between Two Parallel Plates: A Lattice Boltzmann Method Study

Authors: W. Hasan, H. Farhat

Abstract:

A hybrid quasi-steady thermal lattice Boltzmann model was used to study the combined effects of temperature and contact angle on the movement of slugs and droplets of oil in water (O/W) system flowing between two parallel plates. The model static contact angle due to the deposition of the O/W droplet on a flat surface with simulated hydrophilic characteristic at different fluid temperatures, matched very well the proposed theoretical calculation. Furthermore, the model was used to simulate the dynamic behavior of droplets and slugs deposited on the domain’s upper and lower surfaces, while subjected to parabolic flow conditions. The model accurately simulated the contact angle hysteresis for the dynamic droplets cases. It was also shown that at elevated temperatures the required power to transport the mixture diminished remarkably.

Keywords: lattice Boltzmann method, Gunstensen model, thermal, contact angle, high viscosity ratio

Procedia PDF Downloads 355
3990 Theory of the Optimum Signal Approximation Clarifying the Importance in the Recognition of Parallel World and Application to Secure Signal Communication with Feedback

Authors: Takuro Kida, Yuichi Kida

Abstract:

In this paper, it is shown a base of the new trend of algorithm mathematically that treats a historical reason of continuous discrimination in the world as well as its solution by introducing new concepts of parallel world that includes an invisible set of errors as its companion. With respect to a matrix operator-filter bank that the matrix operator-analysis-filter bank H and the matrix operator-sampling-filter bank S are given, firstly, we introduce the detail algorithm to derive the optimum matrix operator-synthesis-filter bank Z that minimizes all the worst-case measures of the matrix operator-error-signals E(ω) = F(ω) − Y(ω) between the matrix operator-input-signals F(ω) and the matrix operator-output-signals Y(ω) of the matrix operator-filter bank at the same time. Further, feedback is introduced to the above approximation theory, and it is indicated that introducing conversations with feedback do not superior automatically to the accumulation of existing knowledge of signal prediction. Secondly, the concept of category in the field of mathematics is applied to the above optimum signal approximation and is indicated that the category-based approximation theory is applied to the set-theoretic consideration of the recognition of humans. Based on this discussion, it is shown naturally why the narrow perception that tends to create isolation shows an apparent advantage in the short term and, often, why such narrow thinking becomes intimate with discriminatory action in a human group. Throughout these considerations, it is presented that, in order to abolish easy and intimate discriminatory behavior, it is important to create a parallel world of conception where we share the set of invisible error signals, including the words and the consciousness of both worlds.

Keywords: matrix filterbank, optimum signal approximation, category theory, simultaneous minimization

Procedia PDF Downloads 127
3989 Identification of Classes of Bilinear Time Series Models

Authors: Anthony Usoro

Abstract:

In this paper, two classes of bilinear time series model are obtained under certain conditions from the general bilinear autoregressive moving average model. Bilinear Autoregressive (BAR) and Bilinear Moving Average (BMA) Models have been identified. From the general bilinear model, BAR and BMA models have been proved to exist for q = Q = 0, => j = 0, and p = P = 0, => i = 0 respectively. These models are found useful in modelling most of the economic and financial data.

Keywords: autoregressive model, bilinear autoregressive model, bilinear moving average model, moving average model

Procedia PDF Downloads 393
3988 Clinicopathological Characteristics in Male Breast Cancer: A Case Series and Literature Review

Authors: Mohamed Shafi Mahboob Ali

Abstract:

Male breast cancer (MBC) is a rare entity with overall cases reported less than 1%. However, the incidence of MBC is regularly rising every year. Due to the lack of data on MBC, diagnosis and treatment are tailored to female breast cancer. MBC risk increases with age and is usually diagnosed ten years late as the disease progression is slow compared to female breast cancer (FBC). The most common feature of MBC is an intra-ductal variant, and often, upon diagnosis, the stage of the disease is already advanced. The Prognosis of MBC is often flawed, but new treatment modalities are emerging with the current knowledge and advancement. We presented a series of male breast cancer in our center, highlighting the clinicopathological, radiological and treatment options.

Keywords: male, breast, cancer, clinicopathology, ultrasound, CT scan

Procedia PDF Downloads 86
3987 Measuring Development through Extreme Observations: An Archetypal Analysis Approach to Index Construction

Authors: Claudeline D. Cellan

Abstract:

Development is multifaceted, and efforts to hasten growth in all these facets have been gaining traction in recent years. Thus, producing a composite index that is reflective of these multidimensional impacts captures the interests of policymakers. The problem lies in going through a mixture of theoretical, methodological and empirical decisions and complexities which, when done carelessly, can lead to inconsistent and unreliable results. This study looks into index computation from a different and less complex perspective. Borrowing the idea of archetypes or ‘pure types’, archetypal analysis looks for points in the convex hull of the multivariate data set that captures as much information in the data as possible. The archetypes or 'pure types' are estimated such that they are convex combinations of all the observations, which in turn are convex combinations of the archetypes. This ensures that the archetypes are realistically observable, therefore achievable. In the sense of composite indices, we look for the best among these archetypes and use this as a benchmark for index computation. Its straightforward and simplistic approach does away with aggregation and substitutability problems which are commonly encountered in index computation. As an example of the application of archetypal analysis in index construction, the country data for the Human Development Index (HDI 2017) of the United Nations Development Programme (UNDP) is used. The goal of this exercise is not to replicate the result of the UNDP-computed HDI, but to illustrate the usability of archetypal analysis in index construction. Here best is defined in the context of life, education and gross national income sub-indices. Results show that the HDI from the archetypal analysis has a linear relationship with the UNDP-computed HDI.

Keywords: archetypes, composite index, convex combination, development

Procedia PDF Downloads 118
3986 In vitro P-Glycoprotein Modulation: Combinatorial Approach Using Natural Products

Authors: Jagdish S. Patel, Piyush Chudasama

Abstract:

Context: Over-expression of P-glycoprotein (P-gp) plays critical role in absorption of many drug candidates which results into lower bioavailability of the drug. P-glycoprotein also over expresses in many pathological conditions like diabetes, affecting the drug therapy. Modulation of P-gp expression using inhibitors can help in designing novel formulation enhancing the bioavailability of the drug in question. Objectives: The main focus of the study was to develop advanced glycation end products (AGEs) induced P-gp over expression in Caco-2 cells. Curcumin, piperine and epigallocatechin gallate were used to evaluate their P-gp inhibitory action using combinatorial approach. Materials and methods: Methylglyoxal (MG) induced P-gp over expression was checked in Caco-2 cells using real time PCR. P-gp inhibitory effects of the phytochemicals were measured after induction with MG alone and in combination of any two compounds. Cytotoxicity of each of the phytochemical was evaluated using MTT assay. Results: Induction with MG (100mM) significantly induced the over expression of P-glycoprotein in Caco-2 cells after 24 hr. Curcumin, piperine and epigallocatechin gallate alone significantly reduced the level of P-gp within 6 hr of treatment period monitored by real time PCR. The combination of any two phytochemical also down regulated the expression of P-gp in cells. Combinations of Curcumin and epigallocatechin gallate have shown significant down regulation when compared with other two combinations. Conclusions: Combinatorial approach for down regulating the expression of P-gp, in pathological conditions like diabetes, has demonstrated promising approach for therapeutic purpose.

Keywords: p-glycoprotein, curcumin, piperine, epigallocatechin gallate, p-gp inhibition

Procedia PDF Downloads 323
3985 Comparative Studies of Modified Clay/Polyaniline Nanocomposites

Authors: Fatima Zohra Zeggai, Benjamin Carbonnier, Aïcha Hachemaoui, Ahmed Yahiaoui, Samia Mahouche-Chergui, Zakaria Salmi

Abstract:

A series of polyaniline (PANI)/modified Montmorillonite (MMT) Clay nanocomposite materials have been successfully prepared by In-Situ polymerization in the presence of modified MMT-Clay or Diazonium-MMT-Clay. The obtained nanocomposites were characterized and compared by various physicochemical techniques. The presence of physicochemical interaction, probably hydrogen bonding, between clay and polyaniline, which was confirmed by FTIR, UV-Vis Spectroscopy. The electrical conductivity of neat PANI and a series of the obtained nanocomposites were also studied by cyclic voltammograms.

Keywords: polyaniline, clay, nanocomposites, in-situ polymerization, polymers conductors, diazonium salt

Procedia PDF Downloads 457
3984 Effects of Incident Angle and Distance on Visible Light Communication

Authors: Taegyoo Woo, Jong Kang Park, Jong Tae Kim

Abstract:

Visible Light Communication (VLC) provides wireless communication features in illumination systems. One of the key applications is to recognize the user location by indoor illuminators such as light emitting diodes. For localization of individual receivers in these systems, we usually assume that receivers and transmitters are placed in parallel. However, it is difficult to satisfy this assumption because the receivers move randomly in real case. It is necessary to analyze the case when transmitter is not placed perfectly parallel to receiver. It is also important to identify changes on optical gain by the tilted angles and distances of them against the illuminators. In this paper, we simulate optical gain for various cases where the tilt of the receiver and the distance change. Then, we identified changing patterns of optical gains according to tilted angles of a receiver and distance. These results can help many VLC applications understand the extent of the location errors with regard to optical gains of the receivers and identify the root cause.

Keywords: visible light communication, incident angle, optical gain, light emitting diode

Procedia PDF Downloads 323
3983 Effect of Diazepam on Internal Organs of Chrysomya megacephala Using Micro-Computed Tomograph

Authors: Sangkhao M., Butcher B. A.

Abstract:

Diazepam (known as valium) is a medication for calming effect. Many reports on committed suicide cases shown that diazepam is frequently used for this purpose. This research aims to study effect of diazepam on the development of forensically important blowflies, Chrysomya megacephala (Diptera: Calliphoridae) using micro-computed tomography (micro CT). In this study, four rabbits were treated with three different lethal doses of diazepam and one control (LD₀, LD₅₀, LD₁₀₀ and LC). The rabbit’s livers were removed for rearing the blowflies. Pupae were sampled for two series (ages; S1: 24h and S2: 120h) of development. After preparing the specimens, all samples were performed Micro CT using Skyscan 1172. The results shown the effect of diazepam on internal organs and tissues such as brain, cavity of the body, gas bubble, meconium and especially fat body. In the control group, in series 1 (LCS1), fat body was equally dispersed in the head, thorax, and abdomen, development of internal organs were not completed, however, brain, thoracic muscle, wings, legs and rectum were able to observe at 24h after developing into the pupal stage. Development of each organ in the control group in the series two was completed. In the treatment groups, LD₀, LD₅₀, LD₁₀₀ (Series 1 and Series 2), tissues are different, such as gas bubble in LD₀S1, was observed due to rapidity morphological changes during the metamorphosis of blowfly’s pupa in this treatment. Meconium was observed in LD₅₀S2 group because excretion of metabolic waste was not completed. All of the samples in the treatment groups had differentiation of fat bodies because metabolic activities were not completed and these changes affected on functions of every internal system. Discovering of differentiated fat bodies are important results because fat bodies of insect functions as liver in human, therefore it is shown that toxin eliminates from blowfly’s body and homeostatic maintenance of the hemolymph proteins, lipid and carbohydrates in each treatment group are abnormal.

Keywords: forensic toxicology, forensic entomology, diptera, diazepam

Procedia PDF Downloads 119
3982 One-Step Time Series Predictions with Recurrent Neural Networks

Authors: Vaidehi Iyer, Konstantin Borozdin

Abstract:

Time series prediction problems have many important practical applications, but are notoriously difficult for statistical modeling. Recently, machine learning methods have been attracted significant interest as a practical tool applied to a variety of problems, even though developments in this field tend to be semi-empirical. This paper explores application of Long Short Term Memory based Recurrent Neural Networks to the one-step prediction of time series for both trend and stochastic components. Two types of data are analyzed - daily stock prices, that are often considered to be a typical example of a random walk, - and weather patterns dominated by seasonal variations. Results from both analyses are compared, and reinforced learning framework is used to select more efficient between Recurrent Neural Networks and more traditional auto regression methods. It is shown that both methods are able to follow long-term trends and seasonal variations closely, but have difficulties with reproducing day-to-day variability. Future research directions and potential real world applications are briefly discussed.

Keywords: long short term memory, prediction methods, recurrent neural networks, reinforcement learning

Procedia PDF Downloads 213
3981 Microbial Bioagent Triggered Biochemical Response in Tea (Camellia sinensis) Inducing Resistance against Grey Blight Disease and Yield Enhancement

Authors: Popy Bora, L. C. Bora, A. Bhattacharya, Sehnaz S. Ahmed

Abstract:

Microbial bioagents, viz., Pseudomonas fluorescens, Bacillus subtilis, and Trichoderma viride were assessed for their ability to suppress grey blight caused by Pestalotiopsis theae, a major disease of tea crop in Assam. The expression of defense-related phytochemicals due to the application of these bioagents was also evaluated. The individual bioagents, as well as their combinations, were screened for their bioefficacy against P. theae in vitro using nutrient agar (NA) as basal medium. The treatment comprising a combination of the three bioagents, P. fluorescens, B. subtilis, and T. viride showed significantly the highest inhibition against the pathogen. Bioformulation of effective bioagent combinations was further evaluated under field condition, where significantly highest reduction of grey blight (90.30%), as well as the highest increase in the green leaf yield (10.52q/ha), was recorded due to application of the bioformulation containing the three bioagents. The application of the three bioformulation also recorded an enhanced level of caffeine (4.15%) and polyphenols (22.87%). A significant increase in the enzymatic activity of phenylalanine ammonia-lyase, peroxidase and polyphenol oxidase were recorded in the plants treated with the microbial bioformulation of the three bioagents. The present investigation indicates the role of microbial agents in suppressing disease, inducing plant defense response, as well as improving the quality of tea.

Keywords: enzymatic activity, grey blight, microbial bioagents, Pestalotiopsis theae, phytochemicals, plant defense, tea

Procedia PDF Downloads 133
3980 Electrical Characterization of Hg/n-bulk GaN Schottky Diode

Authors: B. Nabil, O. Zahir, R. Abdelaziz

Abstract:

We present the results of electrical characterizations current-voltage and capacity-voltage implementation of a method of making a Schottky diode on bulk gallium nitride doped n. We made temporary Schottky contact of Mercury (Hg) and an ohmic contact of silver (Ag), the electrical characterizations current-voltage (I-V) and capacitance-voltage (C-V) allows us to determine the difference parameters of our structure (Hg /n-GaN) as the barrier height (ΦB), the ideality factor (n), the series resistor (Rs), the voltage distribution (Vd), the doping of the substrate (Nd) and density of interface states (Nss).

Keywords: Bulk Gallium nitride, electrical characterization, Schottky diode, series resistance, substrate doping

Procedia PDF Downloads 476
3979 General Architecture for Automation of Machine Learning Practices

Authors: U. Borasi, Amit Kr. Jain, Rakesh, Piyush Jain

Abstract:

Data collection, data preparation, model training, model evaluation, and deployment are all processes in a typical machine learning workflow. Training data needs to be gathered and organised. This often entails collecting a sizable dataset and cleaning it to remove or correct any inaccurate or missing information. Preparing the data for use in the machine learning model requires pre-processing it after it has been acquired. This often entails actions like scaling or normalising the data, handling outliers, selecting appropriate features, reducing dimensionality, etc. This pre-processed data is then used to train a model on some machine learning algorithm. After the model has been trained, it needs to be assessed by determining metrics like accuracy, precision, and recall, utilising a test dataset. Every time a new model is built, both data pre-processing and model training—two crucial processes in the Machine learning (ML) workflow—must be carried out. Thus, there are various Machine Learning algorithms that can be employed for every single approach to data pre-processing, generating a large set of combinations to choose from. Example: for every method to handle missing values (dropping records, replacing with mean, etc.), for every scaling technique, and for every combination of features selected, a different algorithm can be used. As a result, in order to get the optimum outcomes, these tasks are frequently repeated in different combinations. This paper suggests a simple architecture for organizing this largely produced “combination set of pre-processing steps and algorithms” into an automated workflow which simplifies the task of carrying out all possibilities.

Keywords: machine learning, automation, AUTOML, architecture, operator pool, configuration, scheduler

Procedia PDF Downloads 42
3978 Algorithm Optimization to Sort in Parallel by Decreasing the Number of the Processors in SIMD (Single Instruction Multiple Data) Systems

Authors: Ali Hosseini

Abstract:

Paralleling is a mechanism to decrease the time necessary to execute the programs. Sorting is one of the important operations to be used in different systems in a way that the proper function of many algorithms and operations depend on sorted data. CRCW_SORT algorithm executes ‘N’ elements sorting in O(1) time on SIMD (Single Instruction Multiple Data) computers with n^2/2-n/2 number of processors. In this article having presented a mechanism by dividing the input string by the hinge element into two less strings the number of the processors to be used in sorting ‘N’ elements in O(1) time has decreased to n^2/8-n/4 in the best state; by this mechanism the best state is when the hinge element is the middle one and the worst state is when it is minimum. The findings from assessing the proposed algorithm by other methods on data collection and number of the processors indicate that the proposed algorithm uses less processors to sort during execution than other methods.

Keywords: CRCW, SIMD (Single Instruction Multiple Data) computers, parallel computers, number of the processors

Procedia PDF Downloads 298
3977 The Influence of Disturbances Generated by Arc Furnaces on the Power Quality

Authors: Z. Olczykowski

Abstract:

The paper presents the impact of work on the electric arc furnace. Arc equipment is one of the largest receivers powered by the power system. Electric arc disturbances arising during melting process occurring in these furnaces are the cause of an abrupt change of the passive power of furnaces. Currents drawn by these devices undergo an abrupt change, which in turn cause voltage fluctuations and light flicker. The quantitative evaluation of the voltage fluctuations is now the basic criterion of assessment of an influence of unquiet receiver on the supplying net. The paper presents the method of determination of range of voltage fluctuations and light flicker at parallel operation of arc devices. The results of measurements of voltage fluctuations and light flicker indicators recorded in power supply networks of steelworks were presented, with different number of parallel arc devices. Measurements of energy quality parameters were aimed at verifying the proposed method in practice. It was also analyzed changes in other parameters of electricity: the content of higher harmonics, asymmetry, voltage dips.

Keywords: power quality, arc furnaces, propagation of voltage fluctuations, disturbances

Procedia PDF Downloads 123
3976 Control Strategy for Two-Mode Hybrid Electric Vehicle by Using Fuzzy Controller

Authors: Jia-Shiun Chen, Hsiu-Ying Hwang

Abstract:

Hybrid electric vehicles can reduce pollution and improve fuel economy. Power-split hybrid electric vehicles (HEVs) provide two power paths between the internal combustion engine (ICE) and energy storage system (ESS) through the gears of an electrically variable transmission (EVT). EVT allows ICE to operate independently from vehicle speed all the time. Therefore, the ICE can operate in the efficient region of its characteristic brake specific fuel consumption (BSFC) map. The two-mode powertrain can operate in input-split or compound-split EVT modes and in four different fixed gear configurations. Power-split architecture is advantageous because it combines conventional series and parallel power paths. This research focuses on input-split and compound-split modes in the two-mode power-split powertrain. Fuzzy Logic Control (FLC) for an internal combustion engine (ICE) and PI control for electric machines (EMs) are derived for the urban driving cycle simulation. These control algorithms reduce vehicle fuel consumption and improve ICE efficiency while maintaining the state of charge (SOC) of the energy storage system in an efficient range.

Keywords: hybrid electric vehicle, fuel economy, two-mode hybrid, fuzzy control

Procedia PDF Downloads 374
3975 Category-Base Theory of the Optimum Signal Approximation Clarifying the Importance of Parallel Worlds in the Recognition of Human and Application to Secure Signal Communication with Feedback

Authors: Takuro Kida, Yuichi Kida

Abstract:

We show a base of the new trend of algorithm mathematically that treats a historical reason of continuous discrimination in the world as well as its solution by introducing new concepts of parallel world that includes an invisible set of errors as its companion. With respect to a matrix operator-filter bank that the matrix operator-analysis-filter bank H and the matrix operator-sampling-filter bank S are given, firstly, we introduce the detailed algorithm to derive the optimum matrix operator-synthesis-filter bank Z that minimizes all the worst-case measures of the matrix operator-error-signals E(ω) = F(ω) − Y(ω) between the matrix operator-input-signals F(ω) and the matrix operator-output signals Y(ω) of the matrix operator-filter bank at the same time. Further, feedback is introduced to the above approximation theory and it is indicated that introducing conversations with feedback does not superior automatically to the accumulation of existing knowledge of signal prediction. Secondly, the concept of category in the field of mathematics is applied to the above optimum signal approximation and is indicated that the category-based approximation theory is applied to the set-theoretic consideration of the recognition of humans. Based on this discussion, it is shown naturally why the narrow perception that tends to create isolation shows an apparent advantage in the short term and, often, why such narrow thinking becomes intimate with discriminatory action in a human group. Throughout these considerations, it is presented that, in order to abolish easy and intimate discriminatory behavior, it is important to create a parallel world of conception where we share the set of invisible error signals, including the words and the consciousness of both worlds.

Keywords: signal prediction, pseudo inverse matrix, artificial intelligence, conditional optimization

Procedia PDF Downloads 142
3974 Selective Extraction of Couple Nickel(II) / Cobalt(II) by a Series of Schiff Bases in Sulfate Medium, in the Chloroforme-Water

Authors: N. Belhadj, M. Hadj Youcef, T. Benabdallah, Belbachir Ibtissem, N. Boceiri

Abstract:

This work deals with the synthesis, the structural elucidation and the exploration the extracting properties of a series of ortho-hydroxy Schiff base in sulfate medium. After the synthesis and characterization of their structures, the study of their behavior in solution was carried out by pH-metric titration in different media homogeneous and heterogeneous solution. This allowed to explore and to quantify in each of these media, some of their properties in solution such as, their acid-base behavior (determination and comparison of pKa), their distribution powers (determination and comparison of logKd), and their thermodynamic constants (determining ∆H°, ΔS° and ∆G°moy) by optimizing both the temperature and ionic strength. Study of the extraction of nickel (II) and cobalt(II) separately was undertaken in the aqueous-organic system, chloroform-water. Different extraction parameters have been thus optimized such, the pH, the concentration of extractant and the ionic strength, and the extraction constants established in each case. The extracted metal complexes have been isolated and their spatial configurations elucidated. The selective extraction of the couple cobalt (II)/nickel (II) was finally performed by our series of Schiff base in the chloroforme/water.

Keywords: selective extraction, Schiff base, distribution, cobalt(II), nickel(II)

Procedia PDF Downloads 452
3973 Mediation of the Middle Eastern Crises and Economic Growth: An Application of Times Series Analysis

Authors: Gokhan Erkal, Gulsen Aydin, Muge Yuce, Lokman Sahin

Abstract:

This study aims to analyze the impacts of involving in mediation of conflicts in the Middle East from the perspective of the economic growth of the mediators. The Middle East is a highly volatile region of the world with rampant crises whose affects spill beyond its borders. Therefore, management and resolution of the conflicts in the region are of great significance. Mediation is an instrument used for abating violence and settling dispute. The recourse to mediation has grown to an important degree in recent years. However, for mediators, it is a daunting task to involve in the mediation of the deadlocks in the Middle East. This study tries to shed light on the positive correlation between economic growth of the mediator and the successful outcome of the mediation process to provide motivation for mediators. To this end, first, it briefly introduces the conflicts ongoing in the region and their negative impacts. Second, the methodology, time series analysis, and the data to be used, International Crisis Behavior Project Data, are presented. Third, the empirical test is carried out and the findings are evaluated. The conclusion highlights the benefits of successful mediation for the economic growth of the mediators of Middle Eastern crises.

Keywords: international crises, mediation, Middle East, times series analysis

Procedia PDF Downloads 170
3972 Research on the Aero-Heating Prediction Based on Hybrid Meshes and Hybrid Schemes

Authors: Qiming Zhang, Youda Ye, Qinxue Jiang

Abstract:

Accurate prediction of external flowfield and aero-heating at the wall of hypersonic vehicle is very crucial for the design of aircrafts. Unstructured/hybrid meshes have more powerful advantages than structured meshes in terms of pre-processing, parallel computing and mesh adaptation, so it is imperative to develop high-resolution numerical methods for the calculation of aerothermal environment on unstructured/hybrid meshes. The inviscid flux scheme is one of the most important factors affecting the accuracy of unstructured/ hybrid mesh heat flux calculation. Here, a new hybrid flux scheme is developed and the approach of interface type selection is proposed: i.e. 1) using the exact Riemann scheme solution to calculate the flux on the faces parallel to the wall; 2) employing Sterger-Warming (S-W) scheme to improve the stability of the numerical scheme in other interfaces. The results of the heat flux fit the one observed experimentally and have little dependence on grids, which show great application prospect in unstructured/ hybrid mesh.

Keywords: aero-heating prediction, computational fluid dynamics, hybrid meshes, hybrid schemes

Procedia PDF Downloads 226
3971 Evidence Theory Enabled Quickest Change Detection Using Big Time-Series Data from Internet of Things

Authors: Hossein Jafari, Xiangfang Li, Lijun Qian, Alexander Aved, Timothy Kroecker

Abstract:

Traditionally in sensor networks and recently in the Internet of Things, numerous heterogeneous sensors are deployed in distributed manner to monitor a phenomenon that often can be model by an underlying stochastic process. The big time-series data collected by the sensors must be analyzed to detect change in the stochastic process as quickly as possible with tolerable false alarm rate. However, sensors may have different accuracy and sensitivity range, and they decay along time. As a result, the big time-series data collected by the sensors will contain uncertainties and sometimes they are conflicting. In this study, we present a framework to take advantage of Evidence Theory (a.k.a. Dempster-Shafer and Dezert-Smarandache Theories) capabilities of representing and managing uncertainty and conflict to fast change detection and effectively deal with complementary hypotheses. Specifically, Kullback-Leibler divergence is used as the similarity metric to calculate the distances between the estimated current distribution with the pre- and post-change distributions. Then mass functions are calculated and related combination rules are applied to combine the mass values among all sensors. Furthermore, we applied the method to estimate the minimum number of sensors needed to combine, so computational efficiency could be improved. Cumulative sum test is then applied on the ratio of pignistic probability to detect and declare the change for decision making purpose. Simulation results using both synthetic data and real data from experimental setup demonstrate the effectiveness of the presented schemes.

Keywords: CUSUM, evidence theory, kl divergence, quickest change detection, time series data

Procedia PDF Downloads 320
3970 Volatility and Stylized Facts

Authors: Kalai Lamia, Jilani Faouzi

Abstract:

Measuring and controlling risk is one of the most attractive issues in finance. With the persistence of uncontrolled and erratic stocks movements, volatility is perceived as a barometer of daily fluctuations. An objective measure of this variable seems then needed to control risks and cover those that are considered the most important. Non-linear autoregressive modeling is our first evaluation approach. In particular, we test the presence of “persistence” of conditional variance and the presence of a degree of a leverage effect. In order to resolve for the problem of “asymmetry” in volatility, the retained specifications point to the importance of stocks reactions in response to news. Effects of shocks on volatility highlight also the need to study the “long term” behaviour of conditional variance of stocks returns and articulate the presence of long memory and dependence of time series in the long run. We note that the integrated fractional autoregressive model allows for representing time series that show long-term conditional variance thanks to fractional integration parameters. In order to stop at the dynamics that manage time series, a comparative study of the results of the different models will allow for better understanding volatility structure over the Tunisia stock market, with the aim of accurately predicting fluctuation risks.

Keywords: asymmetry volatility, clustering, stylised facts, leverage effect

Procedia PDF Downloads 290
3969 Analysis of Sound Absorption Coefficient

Authors: Zakiul Fuady, Ismail AB, Fauzi, Zulfian

Abstract:

This research was conducted to analyze the absorption coefficients of sound at several types of materials as well as its combinations. The aim of this research was to find the value of sound absorption coefficients on the materials and its combinations. The materials used in this research were gypsum panel, gypsum-fibre palm, fibre palm-gypsum, and foamed concrete-fibre palm. The test was conducted by using a method of reverberation chamber based on the ISO 354-1985 with the types of the sound source: white noise and pink noise at the frequency of 125 Hz - 8000 Hz. Based on the test results of white noise, it was found that the panel of gypsum-fibre palm has α = 0.93 at low frequency; the panel of fibre palm has α = 0.97 at a medium frequency; and the panel of foamed concrete-fibre palm has α = 0.89 at high frequency. Further, for the sound source of pink noise, it was found that the panel of gypsum-fibre palm has α = 0.99 at low level; the panel of fibre palm-gypsum has α = 0.86 at medium level; and the panel of fibre palm-gypsum has α = 0.64 at high level. The fibre palm panel could absorb the sounds well since this material has bigger airspace (pore) than the foamed concrete and gypsum. Consequently, when the sounds wave enters to this material it will be trapped in the space. The panel of fibre palm affected an increasing of sound absorption coefficient value at the combination materials when the panel of fibre palm was placed under another panel. However, the absorption coefficient values of both fibre palm and fibre palm-gypsum panels are about the same.

Keywords: coefficient of sound absorption, pink noise, white noise, palm

Procedia PDF Downloads 242
3968 Long-Term Economic-Ecological Assessment of Optimal Local Heat-Generating Technologies for the German Unrefurbished Residential Building Stock on the Quarter Level

Authors: M. A. Spielmann, L. Schebek

Abstract:

In order to reach the long-term national climate goals of the German government for the building sector, substantial energetic measures have to be executed. Historically, those measures were primarily energetic efficiency measures at the buildings’ shells. Advanced technologies for the on-site generation of heat (or other types of energy) often are not feasible at this small spatial scale of a single building. Therefore, the present approach uses the spatially larger dimension of a quarter. The main focus of the present paper is the long-term economic-ecological assessment of available decentralized heat-generating (CHP power plants and electrical heat pumps) technologies at the quarter level for the German unrefurbished residential buildings. Three distinct terms have to be described methodologically: i) Quarter approach, ii) Economic assessment, iii) Ecological assessment. The quarter approach is used to enable synergies and scaling effects over a single-building. For the present study, generic quarters that are differentiated according to significant parameters concerning their heat demand are used. The core differentiation of those quarters is made by the construction time period of the buildings. The economic assessment as the second crucial parameter is executed with the following structure: Full costs are quantized for each technology combination and quarter. The investment costs are analyzed on an annual basis and are modeled with the acquisition of debt. Annuity loans are assumed. Consequently, for each generic quarter, an optimal technology combination for decentralized heat generation is provided in each year of the temporal boundaries (2016-2050). The ecological assessment elaborates for each technology combination and each quarter a Life Cycle assessment. The measured impact category hereby is GWP 100. The technology combinations for heat production can be therefore compared against each other concerning their long-term climatic impacts. Core results of the approach can be differentiated to an economic and ecological dimension. With an annual resolution, the investment and running costs of different energetic technology combinations are quantified. For each quarter an optimal technology combination for local heat supply and/or energetic refurbishment of the buildings within the quarter is provided. Coherently to the economic assessment, the climatic impacts of the technology combinations are quantized and compared against each other.

Keywords: building sector, economic-ecological assessment, heat, LCA, quarter level

Procedia PDF Downloads 214
3967 Separating Permanent and Induced Magnetic Signature: A Simple Approach

Authors: O. J. G. Somsen, G. P. M. Wagemakers

Abstract:

Magnetic signature detection provides sensitive detection of metal objects, especially in the natural environment. Our group is developing a tabletop setup for magnetic signatures of various small and model objects. A particular issue is the separation of permanent and induced magnetization. While the latter depends only on the composition and shape of the object, the former also depends on the magnetization history. With common deperming techniques, a significant permanent signature may still remain, which confuses measurements of the induced component. We investigate a basic technique of separating the two. Measurements were done by moving the object along an aluminum rail while the three field components are recorded by a detector attached near the center. This is done first with the rail parallel to the Earth magnetic field and then with anti-parallel orientation. The reversal changes the sign of the induced- but not the permanent magnetization so that the two can be separated. Our preliminary results on a small iron block show excellent reproducibility. A considerable permanent magnetization was indeed present, resulting in a complex asymmetric signature. After separation, a much more symmetric induced signature was obtained that can be studied in detail and compared with theoretical calculations.

Keywords: magnetic signature, data analysis, magnetization, deperming techniques

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3966 Performance Improvement of The Nano-Composite Based Proton Exchange Membranes (PEMs)

Authors: Yusuf Yılmaz, Kevser Dincer, Derya Saygılı

Abstract:

In this study, performance of PEMs was experimentally investigated. Coating on the cathode side of the PEMs fuel cells was accomplished with the spray method by using NaCaNiBO. A solution having 0,1 gr NaCaNiBO +10 mL methanol was prepared. This solution was taken out and filled into a spray. Then the cathode side of PEMs fuel cells was cladded with NaCaNiBO by using spray method. After coating, the membrane was left out to dry for 24 hours. The PEM fuel cells were mounted to the system in single, double, triple and fourfold manner in order to spot the best performance. The performance parameter considered was the power to current ratio. The best performance was found to occur at the 300th second with the power/current ratio of 3.55 Watt/Ampere and on the fourfold parallel mounting after the coating; whereas the poorest performance took place at the 210th second, power to current ratio of 0.12 Watt/Ampere and on the twofold parallel connection after the coating.

Keywords: nano-composites, proton exchange membranes, performance improvement, fuel cell

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3965 Design of S-Shape GPS Application Electrically Small Antenna

Authors: Riki H. Patel, Arpan Desai, Trushit Upadhyaya, Shobhit K. Patel

Abstract:

The micro strip antennas area has seen some inventive work in recent years and is now one of the most dynamic fields of antenna theory. A novel and simple printed wideband monopole antenna is presented. Printed on a single dielectric substrate and easily fed by using a 50 ohm microstip line, low-profile antenna structure with two parallel S-shaped meandered line of same size. In this research, S–form micro strip patch antenna is designed from measuring the prototypes of the proposed antenna one available bands with 10db return loss bandwidths of about GPS application (GPS L2 1490 MHz) and covering the 1400 to 1580 MHz frequency band at 1.5 GHz The simulated results for main parameters such as return loss, impedance bandwidth, radiation patterns and gains are also discussed herein. The modeling study shows that such antennas, in simplicity design and supply, and can satisfy GPS application. Two parallel slots are incorporated to disturb the surface flow path, introducing local inductive effect. This antenna is fed by a coaxial feeding tube.

Keywords: bandwidth, electrically small antenna, microstrip, patch antenna, GPS

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3964 Effect of Variation of Temperature Distribution on Mechanical Properties of Shield Metal Arc Welded Duplex Stainless Steel

Authors: Arvind Mittal, Rajesh Gupta

Abstract:

Influence of heat input on the micro structure and mechanical properties of shield metal arc welded of duplex stainless steel UNSNO.S-31803 has been investigated. Three heat input combinations designated as low heat (0.675 KJ/mm), medium heat (0.860 KJ/mm) and high heat (1.094 KJ/mm) and weld joints made using these combinations were subjected to micro structural evaluations and tensile and impact testing so as to analyze the effect of thermal arc energy on the micro structure and mechanical properties of these joints. The result of this investigation shows that the joints made using low heat input exhibited higher tensile strength than those welded with medium and high heat input. Heat affected zone of welded joint made with medium heat input has austenitic ferritic grain structure with some patchy austenite provide high toughness. Significant grain coarsening was observed in the heat affected zone (HAZ) of medium and high heat input welded joints, whereas low heat input welded joint shows the fine grain structure in the heat affected zone with small amount of dendritic formation and equiaxed grain structure where inner zone indicates slowly cooled grains in the direction of heat dissipation. This is the main reason for the observable changes of tensile properties of weld joints welded with different arc energy inputs.

Keywords: microstructure, mechanical properties, shield metal arc welded, duplex stainless steel

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3963 Double Fourier Series Applied to Supraharmonic Determination: The Specific Cases of a Boost and an Interleaved Boost Converter Used as Active Power Factor Correctors

Authors: Erzen Muharemi, Emmanuel De Jaeger, Jos Knockaert

Abstract:

The work presented here investigates the modeling of power electronics converters in terms of their harmonic production. Specifically, it addresses high-frequency emissions in the range of 2-150 kHz, referred to as supraharmonics. This paper models a conventional converter, namely the boost converter used as an active power factor corrector (APFC). Furthermore, the modeling is extended to the case of the interleaved boost converter, which offers advantages such as halving the emissions. Finally, a comparison between the theoretical, numerical, and experimental results will be provided.

Keywords: APFC, boost converter, converter modeling, double fourier series, supraharmonics

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3962 Application of Vector Representation for Revealing the Richness of Meaning of Facial Expressions

Authors: Carmel Sofer, Dan Vilenchik, Ron Dotsch, Galia Avidan

Abstract:

Studies investigating emotional facial expressions typically reveal consensus among observes regarding the meaning of basic expressions, whose number ranges between 6 to 15 emotional states. Given this limited number of discrete expressions, how is it that the human vocabulary of emotional states is so rich? The present study argues that perceivers use sequences of these discrete expressions as the basis for a much richer vocabulary of emotional states. Such mechanisms, in which a relatively small number of basic components is expanded to a much larger number of possible combinations of meanings, exist in other human communications modalities, such as spoken language and music. In these modalities, letters and notes, which serve as basic components of spoken language and music respectively, are temporally linked, resulting in the richness of expressions. In the current study, in each trial participants were presented with sequences of two images containing facial expression in different combinations sampled out of the eight static basic expressions (total 64; 8X8). In each trial, using single word participants were required to judge the 'state of mind' portrayed by the person whose face was presented. Utilizing word embedding methods (Global Vectors for Word Representation), employed in the field of Natural Language Processing, and relying on machine learning computational methods, it was found that the perceived meanings of the sequences of facial expressions were a weighted average of the single expressions comprising them, resulting in 22 new emotional states, in addition to the eight, classic basic expressions. An interaction between the first and the second expression in each sequence indicated that every single facial expression modulated the effect of the other facial expression thus leading to a different interpretation ascribed to the sequence as a whole. These findings suggest that the vocabulary of emotional states conveyed by facial expressions is not restricted to the (small) number of discrete facial expressions. Rather, the vocabulary is rich, as it results from combinations of these expressions. In addition, present research suggests that using word embedding in social perception studies, can be a powerful, accurate and efficient tool, to capture explicit and implicit perceptions and intentions. Acknowledgment: The study was supported by a grant from the Ministry of Defense in Israel to GA and CS. CS is also supported by the ABC initiative in Ben-Gurion University of the Negev.

Keywords: Glove, face perception, facial expression perception. , facial expression production, machine learning, word embedding, word2vec

Procedia PDF Downloads 171