Search results for: regularization parameter search

Authors: Priyadarsini Samal, Rajesh Singla

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Many mobile games come with the benefits of entertainment by introducing stress to the human brain. In recognizing this mental stress, the brain-computer interface (BCI) plays an important role. It has various neuroimaging approaches which help in analyzing the brain signals. Electroencephalogram (EEG) is the most commonly used method among them as it is non-invasive, portable, and economical. Here, this paper investigates the pattern in brain signals when introduced with mental stress. Two healthy volunteers played a game whose aim was to search hidden words from the grid, and the levels were chosen randomly. The EEG signals during gameplay were recorded to investigate the impacts of stress with the changing levels from easy to medium to hard. A total of 16 features of EEG were analyzed for this experiment which includes power band features with relative powers, event-related desynchronization, along statistical features. Support vector machine was used as the classifier, which resulted in an accuracy of 93.9% for three-level stress analysis; for two levels, the accuracy of 92% and 98% are achieved. In addition to that, another game that was similar in nature was played by the volunteers. A suitable regression model was designed for prediction where the feature sets of the first and second game were used for testing and training purposes, respectively, and an accuracy of 73% was found.

Keywords: brain computer interface, electroencephalogram, regression model, stress, word search

Procedia PDF Downloads 175

Authors: Shyamlal Kumawat

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Cloud computing is shifting the approach IT capital are utilized. Cloud computing dynamically delivers convenient, on-demand access to shared pools of software resources, platform and hardware as a service through internet. The cloud computing model—made promising by sophisticated automation, provisioning and virtualization technologies. Users want the ability to access these services including infrastructure resources, how and when they choose. To accommodate this shift in the consumption model technology has to deal with the security, compatibility and trust issues associated with delivering that convenience to application business owners, developers and users. Absent of these issues, trust has attracted extensive attention in Cloud computing as a solution to enhance the security. This paper proposes a trusted computing technology through Standard Resource parameter Based Trust Model in Cloud Computing to select the appropriate cloud service providers. The direct trust of cloud entities is computed on basis of the interaction evidences in past and sustained on its present performances. Various SLA parameters between consumer and provider are considered in trust computation and compliance process. The simulations are performed using CloudSim framework and experimental results show that the proposed model is effective and extensible.

Keywords: cloud, Iaas, Saas, Paas

Procedia PDF Downloads 321

Authors: Pavel Borodkin, Nikolay Khrennikov, Azamat Gazetdinov

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The problem of ensuring of VVER type reactor equipment integrity is now most actual in connection with justification of safety of the NPP Units and extension of their service life to 60 years and more. First of all, it concerns old units with VVER-440 and VVER-1000. The justification of the VVER equipment integrity depends on the reliability of estimation of the degree of the equipment damage. One of the mandatory requirements, providing the reliability of such estimation, and also evaluation of VVER equipment lifetime, is the monitoring of equipment radiation loading parameters. In this connection, there is a problem of justification of such normative parameters, used for an estimation of the pressure vessel metal embrittlement, as the fluence and fluence rate (FR) of fast neutrons above 0.5 MeV. From the point of view of regulatory practice, a comparison of displacement per atom (DPA) and fast neutron fluence (FNF) above 0.5 MeV has a practical concern. In accordance with the Russian regulatory rules, neutron fluence F(E > 0.5 MeV) is a radiation exposure parameter used in steel embrittlement prediction under neutron irradiation. However, the DPA parameter is a more physically legitimate quantity of neutron damage of Fe based materials. If DPA distribution in reactor structures is more conservative as neutron fluence, this case should attract the attention of the regulatory authority. The purpose of this work was to show what radiation load parameters (fluence, DPA) on all VVER equipment should be under control, and give the reasonable estimations of such parameters in the volume of all equipment. The second task is to give the conservative estimation of each parameter including its uncertainty. Results of recently received investigations allow to test the conservatism of calculational predictions, and, as it has been shown in the paper, combination of ex-vessel measured data with calculated ones allows to assess unpredicted uncertainties which are results of specific unique features of individual equipment for VVER reactor. Some results of calculational-experimental investigations are presented in this paper.

Keywords: equipment integrity, fluence, displacement per atom, nuclear power plant, neutron activation measurements, neutron transport calculations

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Authors: Junjie Zhong, Kai Hong, Lei Wang

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Passage Retrieval (PR) plays an important role in many Natural Language Processing (NLP) tasks. Traditional efficient retrieval models relying on exact term-matching, such as TF-IDF or BM25, have nowadays been exceeded by pre-trained language models which match by semantics. Though they gain effectiveness, deep language models often require large memory as well as time cost. To tackle the trade-off between efficiency and effectiveness in PR, this paper proposes Graph Passage Retriever (GraphPR), a graph-based model inspired by the development of graph learning techniques. Different from existing works, GraphPR is end-to-end and integrates both term-matching information and semantics. GraphPR constructs a passage-level graph from BM25 retrieval results and trains a GCN-like model on the graph with graph-based objectives. Passages were regarded as nodes in the constructed graph and were embedded in dense vectors. PR can then be implemented using embeddings and a fast vector-similarity search. Experiments on a variety of real-world retrieval datasets show that the proposed model outperforms related models in several evaluation metrics (e.g., mean reciprocal rank, accuracy, F1-scores) while maintaining a relatively low query latency and memory usage.

Keywords: efficiency, effectiveness, graph learning, language model, passage retrieval, term-matching model

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Authors: S. Pradhan, V. Kumaran

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Centrifugal gas separation processes effect separation by utilizing the difference in the mole fraction in a high speed rotating cylinder caused by the difference in molecular mass, and consequently the centrifugal force density. These have been widely used in isotope separation because chemical separation methods cannot be used to separate isotopes of the same chemical species. More recently, centrifugal separation has also been explored for the separation of gases such as carbon dioxide and methane. The efficiency of separation is critically dependent on the secondary flow generated due to temperature gradients at the cylinder wall or due to inserts, and it is important to formulate accurate models for this secondary flow. The widely used Onsager model for secondary flow is restricted to very long cylinders where the length is large compared to the diameter, the limit of high stratification parameter, where the gas is restricted to a thin layer near the wall of the cylinder, and it assumes that there is no mass difference in the two species while calculating the secondary flow. There are two objectives of the present analysis of the rarefied gas flow in a rotating cylinder. The first is to remove the restriction of high stratification parameter, and to generalize the solutions to low rotation speeds where the stratification parameter may be O (1), and to apply for dissimilar gases considering the difference in molecular mass of the two species. Secondly, we would like to compare the predictions with molecular simulations based on the direct simulation Monte Carlo (DSMC) method for rarefied gas flows, in order to quantify the errors resulting from the approximations at different aspect ratios, Reynolds number and stratification parameter. In this study, we have obtained analytical and numerical solutions for the secondary flows generated at the cylinder curved surface and at the end-caps due to linear wall temperature gradient and external gas inflow/outflow at the axis of the cylinder. The effect of sources of mass, momentum and energy within the flow domain are also analyzed. The results of the analytical solutions are compared with the results of DSMC simulations for three types of forcing, a wall temperature gradient, inflow/outflow of gas along the axis, and mass/momentum input due to inserts within the flow. The comparison reveals that the boundary conditions in the simulations and analysis have to be matched with care. The commonly used diffuse reflection boundary conditions at solid walls in DSMC simulations result in a non-zero slip velocity as well as a temperature slip (gas temperature at the wall is different from wall temperature). These have to be incorporated in the analysis in order to make quantitative predictions. In the case of mass/momentum/energy sources within the flow, it is necessary to ensure that the homogeneous boundary conditions are accurately satisfied in the simulations. When these precautions are taken, there is excellent agreement between analysis and simulations, to within 10 %, even when the stratification parameter is as low as 0.707, the Reynolds number is as low as 100 and the aspect ratio (length/diameter) of the cylinder is as low as 2, and the secondary flow velocity is as high as 0.2 times the maximum base flow velocity.

Keywords: rotating flows, generalized onsager and carrier-Maslen model, DSMC simulations, rarefied gas flow

Procedia PDF Downloads 389

Authors: Umar Farouk Abbas, Danjuma Mustapha, Hamisu Idi

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It is now a known fact that quality is an important issue in manufacturing industries. A control chart is an integrated and powerful tool in statistical process control (SPC). The mean µ and standard deviation σ parameters are estimated. In general, the multivariate exponentially weighted moving average (MEWMA) and multivariate cumulative sum (MCUSUM) are used in the detection of small shifts in joint monitoring of several correlated variables; the charts used information from past data which makes them sensitive to small shifts. The aim of the paper is to compare the performance of Shewhart xbar, MEWMA, and MCUSUM control charts in terms of their false rates when parameters are estimated with autocorrelation. A simulation was conducted in R software to generate the average run length (ARL) values of each of the charts. After the analysis, the results show that a comparison of the false alarm rates of the charts shows that MEWMA chart has lower false alarm rates than the MCUSUM chart at various levels of parameter estimated to the number of ARL0 (in control) values. Also noticed was that the sample size has an advert effect on the false alarm of the control charts.

Keywords: average run length, MCUSUM chart, MEWMA chart, false alarm rate, parameter estimation, simulation

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Authors: Yang Zhong, Mei-Jie Xu

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To study the dynamic mechanics response of asphalt pavement under the temperature load and vehicle loading, asphalt pavement was regarded as multilayered elastic half-space system, and theory analysis was conducted by regarding dynamic modulus of asphalt mixture as the parameter. Firstly, based on the dynamic modulus test of asphalt mixture, function relationship between the dynamic modulus of representative asphalt mixture and temperature was obtained. In addition, the analytical solution for thermal stress in the single layer was derived by using Laplace integral transformation and Hankel integral transformation respectively by using thermal equations of equilibrium. The analytical solution of calculation model of thermal stress in asphalt pavement was derived by transfer matrix of thermal stress in multilayer elastic system. Finally, the variation of thermal stress in pavement structure was analyzed. The result shows that there is an obvious difference between the thermal stress based on dynamic modulus and the solution based on static modulus. Therefore, the dynamic change of parameter in asphalt mixture should be taken into consideration when the theoretical analysis is taken out.

Keywords: asphalt pavement, dynamic modulus, integral transformation, transfer matrix, thermal stress

Procedia PDF Downloads 487

Authors: Srinivasacharya Darbhasayanam, Jagadeeshwar Pashikanti

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This paper analyzes the Soret and Dufour effects on mixed convection flow, heat and mass transfer from an exponentially stretching surface in a viscous fluid with Hall Effect. The governing partial differential equations are transformed into ordinary differential equations using similarity transformations. The nonlinear coupled ordinary differential equations are reduced to a system of linear differential equations using the successive linearization method and then solved the resulting linear system using the Chebyshev pseudo spectral method. The numerical results for the velocity components, temperature and concentration are presented graphically. The obtained results are compared with the previously published results, and are found to be in excellent agreement. It is observed from the present analysis that the primary and secondary velocities and concentration are found to be increasing, and temperature is decreasing with the increase in the values of the Soret parameter. An increase in the Dufour parameter increases both the primary and secondary velocities and temperature and decreases the concentration.

Keywords: Exponentially stretching sheet, Hall current, Heat and Mass transfer, Soret and Dufour Effects

Procedia PDF Downloads 199

Authors: Y. D. Lim, K. S. Yap, K. T. Ooi

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In recent years, environmental issue has been a hot topic in the world, especially the global warming effect caused by conventional non-environmentally friendly refrigerants has increased. Several studies of a more energy-efficient and environmentally friendly refrigeration system have been conducted in order to tackle the issue. In search of a better refrigeration system, CO2 refrigeration system has been proposed as a better option. However, the high throttling loss involved during the expansion process of the refrigeration cycle leads to a relatively low efficiency and thus the system is impractical. In order to improve the efficiency of the refrigeration system, it is suggested by replacing the conventional expansion valve in the refrigeration system with an expander. Based on this issue, a new type of expander-compressor combined unit, named Cross Vane Expander-Compressor (CVEC) was introduced to replace the compressor and the expansion valve of a conventional refrigeration system. A mathematical model was developed to calculate the performance of CVEC, and it was found that the machine is capable of saving the energy consumption of a refrigeration system by as much as 18%. Apart from energy saving, CVEC is also geometrically simpler and more compact. To further improve its efficiency, optimization study of the device is carried out. In this report, several design parameters of CVEC were chosen to be the variables of optimization study. This optimization study was done in a simulation program by using complex optimization method, which is a direct search, multi-variables and constrained optimization method. It was found that the main design parameters, which was shaft radius was reduced around 8% while the inner cylinder radius was remained unchanged at its lower limit after optimization. Furthermore, the port sizes were increased to their upper limit after optimization. The changes of these design parameters have resulted in reduction of around 12% in the total frictional loss and reduction of 4% in power consumption. Eventually, the optimization study has resulted in an improvement in the mechanical efficiency CVEC by 4% and improvement in COP by 6%.

Keywords: complex optimization method, COP, cross vane expander-compressor, CVEC, design optimization, direct search, energy saving, improvement, mechanical efficiency, multi variables

Procedia PDF Downloads 361

Authors: Won Jung, Wan Emri

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Ferrite magnet is widely used in many automotive components such as motors and alternators. Magnets used inside the components must be in good quality to ensure the high level of performance. The purpose of this study is to design input parameters that optimize the ferrite magnet production process to ensure the quality and reliability of manufactured products. Design of Experiments (DOE) and Statistical Process Control (SPC) are used as mutual supplementations to optimize the process. DOE and SPC are quality tools being used in the industry to monitor and improve the manufacturing process condition. These tools are practically used to maintain the process on target and within the limits of natural variation. A mixed Taguchi method is utilized for optimization purpose as a part of DOE analysis. SPC with proportion data is applied to assess the output parameters to determine the optimal operating conditions. An example of case involving the monitoring and optimization of ferrite magnet process was presented to demonstrate the effectiveness of this approach. Through the utilization of these tools, reliable magnets can be produced by following the step by step procedures of proposed framework. One of the main contributions of this study was producing the crack free magnets by applying the proposed parameter design.

Keywords: ferrite magnet, crack, reliability, process optimization, Taguchi method

Procedia PDF Downloads 507

Authors: M. Mueller, M. Kuehn, M. Voelker

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In small and medium-sized enterprises (SMEs), the challenge is to create a well-grounded and reliable basis for process analysis, optimization and planning due to a lack of data. SMEs have limited access to methods with which they can effectively and efficiently analyse processes and identify cause-and-effect relationships in order to generate the necessary database and derive optimization potential from it. The implementation of digitalization within the framework of Industry 4.0 thus becomes a particular necessity for SMEs. For these reasons, the abstract presents an analysis methodology that is subject to the objective of developing an SME-appropriate methodology for efficient, temporarily feasible data collection and evaluation in flexible production and logistics systems as a basis for process analysis and optimization. The overall methodology focuses on retrospective, event-based tracing and analysis of material flow objects. The technological basis consists of Bluetooth low energy (BLE)-based transmitters, so-called beacons, and smart mobile devices (SMD), e.g. smartphones as receivers, between which distance data can be measured and derived motion profiles. The distance is determined using the Received Signal Strength Indicator (RSSI), which is a measure of signal field strength between transmitter and receiver. The focus is the development of a software-based methodology for interpretation of relative movements of transmitters and receivers based on distance data. The main research is on selection and implementation of pattern recognition methods for automatic process recognition as well as methods for the visualization of relative distance data. Due to an existing categorization of the database regarding process types, classification methods (e.g. Support Vector Machine) from the field of supervised learning are used. The necessary data quality requires selection of suitable methods as well as filters for smoothing occurring signal variations of the RSSI, the integration of methods for determination of correction factors depending on possible signal interference sources (columns, pallets) as well as the configuration of the used technology. The parameter settings on which respective algorithms are based have a further significant influence on result quality of the classification methods, correction models and methods for visualizing the position profiles used. The accuracy of classification algorithms can be improved up to 30% by selected parameter variation; this has already been proven in studies. Similar potentials can be observed with parameter variation of methods and filters for signal smoothing. Thus, there is increased interest in obtaining detailed results on the influence of parameter and factor combinations on data quality in this area. The overall methodology is realized with a modular software architecture consisting of independently modules for data acquisition, data preparation and data storage. The demonstrator for initialization and data acquisition is available as mobile Java-based application. The data preparation, including methods for signal smoothing, are Python-based with the possibility to vary parameter settings and to store them in the database (SQLite). The evaluation is divided into two separate software modules with database connection: the achievement of an automated assignment of defined process classes to distance data using selected classification algorithms and the visualization as well as reporting in terms of a graphical user interface (GUI).

Keywords: event-based tracing, machine learning, process classification, parameter settings, RSSI, signal smoothing

Procedia PDF Downloads 118

Authors: Arnab Mondal, Sanjeev Kumar Sharma, Ranjit Kumar Upadhyay

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We study the spatiotemporal dynamics of a neuronal cable. The processes of one- dimensional (1D) and 2D diffusion are considered for a single variable, which is the membrane voltage, i.e., membrane voltage diffusively interacts for spatiotemporal pattern formalism. The recovery and other variables interact through the membrane voltage. A 3D Leech-Heart (LH) model is introduced to investigate the nonlinear responses of an excitable neuronal cable. The deterministic LH model shows different types of firing properties. We explore the parameter space of the uncoupled LH model and based on the bifurcation diagram, considering v_k2_ashift as a bifurcation parameter, we analyze the 1D diffusion dynamics in three regimes: bursting, regular spiking, and a quiescent state. Depending on parameters, it is shown that the diffusive system may generate regular and irregular bursting or spiking behavior. Further, it is explored a 2D diffusion acting on the membrane voltage, where different types of patterns can be observed. The results show that the LH neurons with different firing characteristics depending on the control parameters participate in a collective behavior of an information processing system that depends on the overall network.

Keywords: bifurcation, pattern formation, spatio-temporal dynamics, stability analysis

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Authors: Amir Hadi Ziaie

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In the present work, we revisit the collapse process of a spherically symmetric homogeneous scalar field (in FRW background) minimally coupled to gravity, when the phase-space deformations are taken into account. Such a deformation is mathematically introduced as a particular type of noncommutativity between the canonical momenta of the scale factor and of the scalar field. In the absence of such deformation, the collapse culminates in a spacetime singularity. However, when the phase-space is deformed, we find that the singularity is removed by a non-singular bounce, beyond which the collapsing cloud re-expands to infinity. More precisely, for negative values of the deformation parameter, we identify the appearance of a negative pressure, which decelerates the collapse to finally avoid the singularity formation. While in the un-deformed case, the horizon curve monotonically decreases to finally cover the singularity, in the deformed case the horizon has a minimum value that this value depends on deformation parameter and initial configuration of the collapse. Such a setting predicts a threshold mass for black hole formation in stellar collapse and manifests the role of non-commutative geometry in physics and especially in stellar collapse and supernova explosion.

Keywords: gravitational collapse, non-commutative geometry, spacetime singularity, black hole physics

Procedia PDF Downloads 330

Authors: Ashish Ashish

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In the last few decades, the discrete chaos of difference equations has gained a massive attention of academicians and scholars due to its tremendous applications in each and every branch of science, such as cryptography, traffic control models, secure communications, weather forecasting, and engineering. In this article, a generalized logistic discrete map is established and discrete chaos is reported through period doubling bifurcation, period three orbit and Lyapunov exponent. It is interesting to see that the generalized logistic map exhibits superior chaos due to the presence of an extra degree of freedom of an ordered parameter. The period doubling bifurcation and Lyapunov exponent are demonstrated for some particular values of parameter and the discrete chaos is determined in the sense of Devaney's definition of chaos theoretically as well as numerically. Moreover, the study discusses an extended chaos based image encryption and decryption scheme in cryptography using this novel system. Surprisingly, a larger key space for coding and more sensitive dependence on initial conditions are examined for encryption and decryption of text messages, images and videos which secure the system strongly from external cyber attacks, coding attacks, statistic attacks and differential attacks.

Keywords: chaos, period-doubling, logistic map, Lyapunov exponent, image encryption

Procedia PDF Downloads 136

Authors: Boumesbah Asma, Chergui Mohamed El-amine

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Since it has been shown that the multi-objective minimum spanning tree problem (MOST) is NP-hard even with two criteria, we propose in this study a hybrid NSGA-II algorithm with an exact mutation operator, which is only used with low probability, to find an approximation to the Pareto front of the problem. In a connected graph G, a spanning tree T of G being a connected and cycle-free graph, if k edges of G\T are added to T, we obtain a partial graph H of G inducing a reduced size multi-objective spanning tree problem compared to the initial one. With a weak probability for the mutation operator, an exact method for solving the reduced MOST problem considering the graph H is then used to give birth to several mutated solutions from a spanning tree T. Then, the selection operator of NSGA-II is activated to obtain the Pareto front approximation. Finally, an adaptation of the VNS metaheuristic is called for further improvements on this front. It allows finding good individuals to counterbalance the diversification and the intensification during the optimization search process. Experimental comparison studies with an exact method show promising results and indicate that the proposed algorithm is efficient.

Keywords: minimum spanning tree, multiple objective linear optimization, combinatorial optimization, non-sorting genetic algorithm, variable neighborhood search

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Authors: M. Y. Ismail, M. Inam

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This paper presents the design and analysis of Liquid Crystal (LC) based tunable reflectarray antenna with slot embedded patch element configurations within X-band frequency range. The slots are shown to modify the surface current distribution on the patch element of reflectarray which causes the resonant patch element to provide different resonant frequencies depending on the slot dimensions. The simulated results are supported and verified by waveguide scattering parameter measurements of different reflectarray unit cells. Different rectangular slots on patch element have been fabricated and a change in resonant frequency from 10.46GHz to 8.78GHz has been demonstrated as the width of the rectangular slot is varied from 0.2W to 0.6W. The rectangular slot in the center of the patch element has also been utilized for the frequency tunable reflectarray antenna design based on K-15 Nematic LC. For the active reflectarray antenna design, a frequency tunability of 1.2% from 10GHz to 9.88GHz has been demonstrated with a dynamic phase range of 103° provided by the measured scattering parameter results. Time consumed by liquid crystals for reconfiguration, which is one of the drawback of LC based design, has also been disused in this paper.

Keywords: liquid crystal, tunable reflectarray, frequency tunability, dynamic phase range

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Authors: Moti Zwilling, Srečko Natek

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This paper aims to present an innovative predictive analytics analysis in order to find the best combination between two consumers who strive to find their partner or in internet sites. The methodology shown in this paper is based on analysis of consumer preferences and involves data mining and machine learning search techniques. The study is composed of two parts: The first part examines by means of descriptive statistics the correlations between a set of parameters that are taken between man and women where they intent to meet each other through the social media, usually the internet. In this part several hypotheses were examined and statistical analysis were taken place. Results show that there is a strong correlation between the affiliated attributes of man and woman as long as concerned to how they present themselves in a social media such as "Facebook". One interesting issue is the strong desire to develop a serious relationship between most of the respondents. In the second part, the authors used common data mining algorithms to search and classify the most important and effective attributes that affect the response rate of the other side. Results exhibit that personal presentation and education background are found as most affective to achieve a positive attitude to one's profile from the other mate.

Keywords: dating sites, social networks, machine learning, decision trees, data mining

Procedia PDF Downloads 284

Authors: Thang Minh Le, Hadi Khabbaz

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The coefficient of consolidation is a parameter governing the rate at which saturated soil particularly clay undergoes consolidation when subjected to an increase in pressure. The rate and amount of compression in soil varies with the rate that pore water is lost; and hence depends on soil permeability. Over many years, various methods have been proposed to determine the coefficient of consolidation, cv, which is an indication of the rate of foundation settlement on soft ground. However, defining this parameter is often problematic and heavily relies on graphical techniques, which are subject to some uncertainties. This paper initially presents an overview of many well-established methods to determine the vertical coefficient of consolidation from the incremental loading consolidation tests. An array of consolidation tests was conducted on the undisturbed clay samples, collected at various depths from a site in Nakdong river delta, Busan, South Korea. The consolidation test results on these soft sensitive clay samples were employed to evaluate the targeted methods to predict the settlement rate of Busan clay. In relationship of time-displacement-velocity, a total of 3 method groups from 10 common procedures were classified and compared together. Discussions on study results will be also provided.

Keywords: Busan clay, coefficient of consolidation, constant rate of strain, incremental loading

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Authors: Mohammad Hossein Ahmadi, Vahid Haghighatdoost

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Spatial databases have been an active area of research over years. In this paper, we study how to answer the General Time-Dependent Sequenced Route queries. Given the origin and destination of a user over a time-dependent road network graph, an ordered list of categories of interests and a departure time interval, our goal is to find the minimum travel time path along with the best departure time that minimizes the total travel time from the source location to the given destination passing through a sequence of points of interests belonging to each of the specified categories of interest. The challenge of this problem is the added complexity to the optimal sequenced route queries, where we assume that first the road network is time dependent, and secondly the user defines a departure time interval instead of one single departure time instance. For processing general time-dependent sequenced route queries, we propose two solutions as Discrete-Time and Continuous-Time Sequenced Route approaches, finding approximate and exact solutions, respectively. Our proposed approaches traverse the road network based on A*-search paradigm equipped with an efficient heuristic function, for shrinking the search space. Extensive experiments are conducted to verify the efficiency of our proposed approaches.

Keywords: trip planning, time dependent, sequenced route query, road networks

Procedia PDF Downloads 306

Authors: Masni Mat Yusoff, Michael H. Gordon, Keshavan Niranjan

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The study reports on the effect of aqueous enzymatic extraction (AEE) parameters on the Moringa oleifera (MO) oil yield and the formation of emulsion at the end of the process. A mixture of protease and cellulase enzymes was used at 3:1 (w/w) ratio. The highest oil yield of 19% (g oil/g sample) was recovered with the use of a mixture of pH 6, 1:4 material/moisture ratio, and incubation temperature, time, and shaking speed of 50 ⁰C, 12.5 hr, and 300 stroke/min, respectively. The use of pH 6 and 8 resulted in grain emulsions, while solid-intact emulsion was observed at pH 4. Upon fixing certain parameters, higher oil yield was extracted with the use of lower material/moisture ratio and higher shaking speed. Longer incubation time of 24 hr resulted in significantly (p < 0.05) similar oil yield with that of 12.5 hr, and an incubation temperature of 50 ⁰C resulted in significantly (p < 0.05) higher oil yield than that of 60 ⁰C. In overall, each AEE parameter showed significant effects on both the MO oil yields and the emulsions formed. One of the major disadvantages of an AEE process is the formation of emulsions which require further de-emulsification step for higher oil recovery. Therefore, critical studies on the effect of each AEE parameter may assist in minimizing the amount of emulsions formed whilst extracting highest total MO oil yield possible.

Keywords: enzyme, emulsion, Moringa oleifera, oil yield

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Authors: Matthew J. B. Wilson

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Disaster Risk Reduction relies heavily on the effective cooperation of both humanitarian and development actors, particularly in the wake of a disaster, implementing lasting recovery measures that better protect communities from disasters to come. This can be seen to fit within a broader discussion around integrating humanitarian and development work stretching back to the 1980s. Over time, a number of key concepts have been put forward, including Linking Relief, Rehabilitation, and Development (LRRD), Early Recovery (ER), ‘Build Back Better’ (BBB), and the most recent ‘Humanitarian-Development-Peace Nexus’ or ‘Triple Nexus’ (HDPN) to define these goals and relationship. While this discussion has evolved greatly over time, from a continuum to a more integrative synergistic relationship, there remains a lack of consensus around how to describe it, and as such, the reality of effectively closing this gap has yet to be seen. The objective of this research was twofold. First, to map these four identified concepts (LRRD, ER, BBB & HDPN) used in the literature since 1995 to understand the overall trends in how this relationship is discussed. Second, map articles reference a combination of these concepts to understand their interrelationship. A scoping review was conducted for each concept identified. Results were gathered from Google Scholar by firstly inputting specific boolean search phrases for each concept as they related specifically to disasters each year since 1995 to identify the total number of articles discussing each concept over time. A second search was then done by pairing concepts together within a boolean search phrase and inputting the results into a matrix to understand how many articles contained references to more than one of the concepts. This latter search was limited to articles published after 2017 to account for the more recent emergence of HDPN. It was found that ER and particularly BBB are referred to much more widely than LRRD and HDPN. ER increased particularly in the mid-2000’s coinciding with the formation of the ER cluster, and BBB, whilst emerging gradually in the mid-2000s due to its usage in the wake of the Boxing Day Tsunami, increased significantly from about 2015 after its prominent inclusion in Sendai Framework. HDPN has only just started to increase in the last 4-5 years. In regards to the relationship between concepts, it was found the vast majority of all concepts identified were referred to in isolation from each other. The strongest relationship was between LRRD and HDPN (8% of articles referring to both), whilst ER-BBB and ER-HDPN both were about 3%, LRRD-ER 2%, and BBB-HDPN 1% and BBB-LRRD 1%. This research identified a fundamental issue around the lack of consensus and even awareness of different approaches referred to within academic literature relating to integrating humanitarian and development work. More research into synthesizing and learning from a range of approaches could work towards better closing this gap.

Keywords: build back better, disaster risk reduction, early recovery, linking relief rehabilitation and development, humanitarian development integration, humanitarian-development (peace) nexus, recovery, triple nexus

Procedia PDF Downloads 70

Authors: Anwar Beg, Sireetorn Kuharat, Rashid Mehmood, Rabil Tabassum, Meisam Babaie

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Nano-polymeric solar paints and sol-gels have emerged as a major new development in solar cell/collector coatings offering significant improvements in durability, anti-corrosion and thermal efficiency. They also exhibit substantial viscosity variation with temperature which can be exploited in solar collector designs. Modern manufacturing processes for such nano-rheological materials frequently employ stagnation flow dynamics under high temperature which invokes radiative heat transfer. Motivated by elaborating in further detail the nanoscale heat, mass and momentum characteristics of such sol gels, the present article presents a mathematical and computational study of the steady, two-dimensional, non-aligned thermo-fluid boundary layer transport of copper metal-doped water-based nano-polymeric sol gels under radiative heat flux. To simulate real nano-polymer boundary interface dynamics, thermal slip is analysed at the wall. A temperature-dependent viscosity is also considered. The Tiwari-Das nanofluid model is deployed which features a volume fraction for the nanoparticle concentration. This approach also features a Maxwell-Garnet model for the nanofluid thermal conductivity. The conservation equations for mass, normal and tangential momentum and energy (heat) are normalized via appropriate transformations to generate a multi-degree, ordinary differential, non-linear, coupled boundary value problem. Numerical solutions are obtained via the stable, efficient Runge-Kutta-Fehlberg scheme with shooting quadrature in MATLAB symbolic software. Validation of solutions is achieved with a Variational Iterative Method (VIM) utilizing Langrangian multipliers. The impact of key emerging dimensionless parameters i.e. obliqueness parameter, radiation-conduction Rosseland number (Rd), thermal slip parameter (α), viscosity parameter (m), nanoparticles volume fraction (ϕ) on non-dimensional normal and tangential velocity components, temperature, wall shear stress, local heat flux and streamline distributions is visualized graphically. Shear stress and temperature are boosted with increasing radiative effect whereas local heat flux is reduced. Increasing wall thermal slip parameter depletes temperatures. With greater volume fraction of copper nanoparticles temperature and thermal boundary layer thickness is elevated. Streamlines are found to be skewed markedly towards the left with positive obliqueness parameter.

Keywords: non-orthogonal stagnation-point heat transfer, solar nano-polymer coating, MATLAB numerical quadrature, Variational Iterative Method (VIM)

Procedia PDF Downloads 126

Authors: Olawole Emmanuel Aina, Liziwe Lizbeth Mugivhisa, Joshua Oluwole Olowoyo, Chikwela Lawrence Obi

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In sustained and consistent efforts to improve food security, numerous and different methods are proposed and used in the production of food crops, and farm produce to meet the demands of consumers. However, unregulated and indiscriminate methods of production present another problem that may expose consumers of these food crops to potential health risks. Therefore, it is imperative that a thorough assessment of farm produce is carried out due to the growing trend of health-conscious consumers preference for minimally processed or raw farm produce. This study evaluated the safety and nutritional quality of food crops. The objectives were to compare the nutritional quality of organic and inorganic farm produce in one hand and, on the other, evaluate the safety of farm produce with respect to trace metal and pathogenic contamination. We conducted a broad systematic search of peer-reviewed published literatures from databases and search engines such as science direct, web-of-science, Google scholar, and Scopus. This study concluded that there is no conclusive evidence to support the notion of nutritional superiority of organic food crops over their inorganic counterparts and there are documented reports of pathogenic and metal contaminations of food crops.

Keywords: food crops, fruits and vegetables, pathogens, nutrition, trace metals

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Authors: André Felipe Gimenez, Flávia Alessandra Ribeiro da Silva, Roberto Saverio Souza Costa

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Currently, the rural producer has been facing problems regarding environmental regularization, which is precisely why the CAR (Rural Environmental Registry) was created. CAR is an electronic registry for rural properties with the purpose of assimilating notions about legal reserve areas, permanent preservation areas, areas of limited use, stable areas, forests and remnants of native vegetation, and all rural properties in Brazil. . The objective of this work was to evaluate and compare altimetry and slope data from google Earth with a digital terrain model (MDT) generated by aerophotogrammetry, in three plots of a steep slope, for the purpose of declaration in the CAR (Rural Environmental Registry). The realization of this work is justified in these areas, in which rural landowners have doubts about the reliability of the use of the free software Google Earth to diagnose inclinations greater than 25 degrees, as recommended by federal law 12651/2012. Added to the fact that in the literature, there is a deficiency of this type of study for the purpose of declaration of the CAR. The results showed that when comparing the drone altimetry data with the Google Earth image data, in areas of high slope (above 40% slope), Google underestimated the real values of terrain slope. Thus, it is concluded that Google Earth is not reliable for diagnosing areas with an inclination greater than 25 degrees (46% declivity) for the purpose of declaration in the CAR, being essential to carry out the local topographic survey.

Keywords: MDT, drone, RPA, SiCar, photogrammetry

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Authors: Fatemeh Abdollahi, Munn-Sann Lye, Jamshid Yazdani Charati, Mehran Zarghami

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Background: In March 2020, the World Health Organization (WHO) declared the outbreak of a new coronavirus disease, COVID-19, as a public health concern and pandemic. This situation is generating psychological consequences such as stress, anxiety, depression, and intimate partner violence (IPV) throughout the population. This is a brief note on the magnitude of this threat and different ways for abused women to minimize the effects of it in their daily life. Methods: A literature review was conducted using the MEDLINE, PSYCHINFO, and SCIENCE DIRECT databases. The keywords used included intimate partner violence, abuse, victims, pandemic, quarantine, coronavirus, and COVID-19. A Google search was also conducted using these words to identify reports published in non-indexed health care and social science journals. The literature search was restricted to English language studies. Results: The prevalence of IPV and its consequences are rising during such a pandemic. Having sufficient support from healthcare workers and acquaintances is critical for women in such circumstances. Conclusion: Community members, healthcare providers, governments, and policymakers should be informed of the increased risk of IPV during such a pandemic. They should provide a supporting structure for abused women. Social networking is also a good approach that could help abusive women during this situation.

Keywords: covid-19, intimate partner violence, pandemic, women

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Authors: Babar Sultan, Kiran Sultan, Waseem Khan, Ijaz Mansoor Qureshi

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In this paper, a novel idea for the performance enhancement of secondary network is proposed for Underlay Cognitive Radio Networks (CRNs). In Underlay CRNs, primary users (PUs) impose strict interference constraints on the secondary users (SUs). The proposed scheme is based on Artificial Bee Colony (ABC) optimization for relay selection and power allocation to handle the highlighted primary challenge of Underlay CRNs. ABC is a simple, population-based optimization algorithm which attains global optimum solution by combining local search methods (Employed and Onlooker Bees) and global search methods (Scout Bees). The proposed two-phase relay selection and power allocation algorithm aims to maximize the signal-to-noise ratio (SNR) at the destination while operating in an underlying mode. The proposed algorithm has less computational complexity and its performance is verified through simulation results for a different number of potential relays, different interference threshold levels and different transmit power thresholds for the selected relays.

Keywords: artificial bee colony, underlay spectrum sharing, cognitive radio networks, amplify-and-forward

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Authors: Amirhossein Mohajerzadeh, Abolghasem Mohajerzadeh

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In this paper, target parameter is estimated with desirable precision in hierarchical wireless sensor networks (WSN) while the proposed algorithm also tries to prolong network lifetime as much as possible, using efficient data collecting algorithm. Target parameter distribution function is considered unknown. Sensor nodes sense the environment and send the data to the base station called fusion center (FC) using hierarchical data collecting algorithm. FC builds underlying phenomena based on collected data. Considering the aggregation level, x, the goal is providing the essential infrastructure to find the best value for aggregation level in order to prolong network lifetime as much as possible, while desirable accuracy is guaranteed (required sample size is fully depended on desirable precision). First, the sample size calculation algorithm is discussed, second, the average queue length based on M/M[x]/1/K queue model is determined and it is used for energy consumption calculation. Nodes can decrease transmission cost by aggregating incoming data. Furthermore, the performance of the new algorithm is evaluated in terms of lifetime and estimation accuracy.

Keywords: aggregation, estimation, queuing, wireless sensor network

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Authors: Sung-Min Park, Chan Kwon Park, Chae-Bogk Kim

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The purpose of this study is to analyze the relationship between transaction fairness, social capital, supply chain integration and sustainability. Based on the previous studies, measurement items were determined by using SPSS 22 and exploratory factor analysis was performed, and again, using AMOS 21 for confirmatory factor analysis and path analysis was performed by using study items that satisfy reliability, validity, and appropriateness of measurement model. It has shown that transaction fairness has a (+) significant effect on social capital, social capital on supply chain integration, supply chain integration on economic sustainability and social sustainability, and has a (+), but not significant effect on environmental sustainability. It has shown that supply chain integration has been proven to play a role as a parameter between social capital and economic and social sustainability, but not as a parameter between environmental sustainability. Through this study, it is suggested that clearly examining the relationship between fairness of trade, social capital, supply chain integration and sustainability, maintaining fairness of the transaction make formation of social capital, and further integration of supply chain, and achieve sustainability of entire supply chain.

Keywords: transaction fairness, social capital, supply chain integration, sustainability

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Authors: Jianwei Ma, Diriba Gemechu

Abstract:

In seismic data processing, attenuation of random noise is the basic step to improve quality of data for further application of seismic data in exploration and development in different gas and oil industries. The signal-to-noise ratio of the data also highly determines quality of seismic data. This factor affects the reliability as well as the accuracy of seismic signal during interpretation for different purposes in different companies. To use seismic data for further application and interpretation, we need to improve the signal-to-noise ration while attenuating random noise effectively. To improve the signal-to-noise ration and attenuating seismic random noise by preserving important features and information about seismic signals, we introduce the concept of anisotropic total fractional order denoising algorithm. The anisotropic total fractional order variation model defined in fractional order bounded variation is proposed as a regularization in seismic denoising. The split Bregman algorithm is employed to solve the minimization problem of the anisotropic total fractional order variation model and the corresponding denoising algorithm for the proposed method is derived. We test the effectiveness of theproposed method for synthetic and real seismic data sets and the denoised result is compared with F-X deconvolution and non-local means denoising algorithm.

Keywords: anisotropic total fractional order variation, fractional order bounded variation, seismic random noise attenuation, split Bregman algorithm

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Authors: Nandhini Ravi, Muthukumaran Shanmugam

Abstract:

Metals are being replaced by thermoplastic polymer composites in automotive industries because of their low density, easiness to fabricate, low cost and good wear resistance. Complex polymer components consist of assemblies of smaller parts which can be joined by friction stir welding. This study deals with the additive friction stir welding of 15 wt.% glass fiber reinforced polyamide 66 composite which is a modified technique of the conventional friction stir welding by the addition of a filler plate for the heating of the composite work piece through the tool during the welding process. Welding at different combinations of tool rotational speed, travel speed and tool plunge depth was done after which the tensile strength of the respective experiments was determined. The maximum tensile strength obtained was 77 MPa which was 80% of the strength of the base material. The process parameters were optimized using the L9 orthogonal array and also the effect of individual welding parameter on the tensile strength was studied. The optimum parameter combination was determined with the help of ANOVA studies. The hardness of the welded joints was studied with the help of Shore Durometer which yielded the maximum of D 75.

Keywords: additive friction stir welding, polyamide 66, process parameters, thermoplastic polymer composite

Procedia PDF Downloads 148