Search results for: models error comparison

Authors: Ali Hesari, Arezoo Esmaeeli

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Regarding to dramatic changes of fertility and higher order births during recent decades in Iran, access to knowledge about affecting factors on different birth orders has crucial importance. In this study, According to hierarchical structure of many of social sciences data and the effect of variables of different levels of social phenomena that determine different birth orders in 365 days ending to 1390 census have been explored by multilevel approach. In this paper, 2% individual row data for 1390 census is analyzed by HLM software. Three different hierarchical linear regression models are estimated for data analysis of the first and second, third, fourth and more birth order. Research results displays different outcomes for three models. Individual level variables entered in equation are; region of residence (rural/urban), age, educational level and labor participation status and province level variable is GDP per capita. Results show that individual level variables have different effects in these three models and in second level we have different random and fixed effects in these models.

Keywords: fertility, birth order, hierarchical approach, fixe effects, random effects

Procedia PDF Downloads 339

Authors: Ehsan Eshtehardian, Saeed Khodaverdi

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This paper surveys the studies on construction change and reveals some of the potential future works. A full-scale investigation of change literature, including change definitions, types, causes and effects, and change management systems, is accomplished to explore some of the coming change trends. It is tried to pick up the critical works in each section to deduct a true timeline of construction changes. The findings show that leaping from best practice guides in late 1990s and generic process models in the early 2000s to very advanced modeling environments in the mid-2000s and the early 2010s have made gaps along with opportunities for change researchers in order to develop some more easy and applicable models. Another finding is that there is a compelling similarity between the change and risk prediction models. Therefore, integrating these two concepts, specifically from proactive management point of view, may lead to a synergy and help project teams avoid rework. Also, the findings show that exploitation of cause-effect relationship models, in order to facilitate the dispute resolutions, seems to be an interesting field for future works.

Keywords: construction change, change management systems, dispute resolutions, change literature

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Authors: Hasan Hassoun, Jaafar Hallal, Denis Duhamel, Mohammad Hammoud, Ali Hage Diab

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This paper aims to prove the accuracy of an inexpensive smartphone camera as a non-contact vibration sensor to recover the vibration modes of a vibrating structure such as a cantilever beam. A video of a vibrating beam is filmed using a smartphone camera and then processed by the motion magnification technique. Based on this method, the first two natural frequencies and their associated mode shapes are estimated experimentally and compared to the analytical ones. Results show a relative error of less than 4% between the experimental and analytical approaches for the first two natural frequencies of the beam. Also, for the first two-mode shapes, a Modal Assurance Criterion (MAC) value of above 0.9 between the two approaches is obtained. This slight error between the different techniques ensures the viability of a cheap smartphone camera as a non-contact vibration sensor, particularly for structures vibrating at relatively low natural frequencies.

Keywords: modal analysis, motion magnification, smartphone camera, structural vibration, vibration modes

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Authors: Suren Chilingaryan

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We study two models describing a single two-level system coupled to two boson field modes in either a parallel or orthogonal setup. Both models may be feasible for experimental realization through Raman adiabatic driving in cavity QED. We study their ground state configurations; that is, we find the quantum precursors of the corresponding semi-classical phase transitions. We found that the ground state configurations of both models present the same critical coupling as the quantum Rabi model. Around this critical coupling, the ground state goes from the so-called normal configuration with no excitation, the qubit in the ground state and the fields in the quantum vacuum state, to a ground state with excitations, the qubit in a superposition of ground and excited state, while the fields are not in the vacuum anymore, for the first model. The second model shows a more complex ground state configuration landscape where we find the normal configuration mentioned above, two single-mode configurations, where just one of the fields and the qubit are excited, and a dual-mode configuration, where both fields and the qubit are excited.

Keywords: quantum optics, quantum phase transition, cavity QED, circuit QED

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Authors: Liqin Zhang, Liang Yan

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This paper addresses the speed synchronization control problem for a network-based multi-motor system from the perspective of cluster consensus theory. Each motor is considered as a single agent connected through fixed and undirected network. This paper presents an improved control protocol from three aspects. First, for the purpose of improving both tracking and synchronization performance, this paper presents a distributed leader-following method. The improved control protocol takes the importance of each motor’s speed into consideration, and all motors are divided into different groups according to speed weights. Specifically, by using control parameters optimization, the synchronization error and tracking error can be regulated and decoupled to some extent. The simulation results demonstrate the effectiveness and superiority of the proposed strategy. In practical engineering, the simplified models are unrealistic, such as single-integrator and double-integrator. And previous algorithms require the acceleration information of the leader available to all followers if the leader has a varying velocity, which is also difficult to realize. Therefore, the method focuses on an observer-based variable structure algorithm for consensus tracking, which gets rid of the leader acceleration. The presented scheme optimizes synchronization performance, as well as provides satisfactory robustness. What’s more, the existing algorithms can obtain a stable synchronous system; however, the obtained stable system may encounter some disturbances that may destroy the synchronization. Focus on this challenging technological problem, a state-dependent-switching approach is introduced. In the presence of unmeasured angular speed and unknown failures, this paper investigates a distributed fault-tolerant consensus tracking algorithm for a group non-identical motors. The failures are modeled by nonlinear functions, and the sliding mode observer is designed to estimate the angular speed and nonlinear failures. The convergence and stability of the given multi-motor system are proved. Simulation results have shown that all followers asymptotically converge to a consistent state when one follower fails to follow the virtual leader during a large enough disturbance, which illustrates the good performance of synchronization control accuracy.

Keywords: consensus control, distributed follow, fault-tolerant control, multi-motor system, speed synchronization

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Authors: Salah Alrabeei, Mohammad Yousuf

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The goal of option pricing theory is to help the investors to manage their money, enhance returns and control their financial future by theoretically valuing their options. However, most of the option pricing models have no analytical solution. Furthermore, not all the numerical methods are efficient to solve these models because they have nonsmoothing payoffs or discontinuous derivatives at the exercise price. In this paper, we solve the American option under jump diffusion models by using efficient time-dependent numerical methods. several techniques are integrated to reduced the overcome the computational complexity. Fast Fourier Transform (FFT) algorithm is used as a matrix-vector multiplication solver, which reduces the complexity from O(M2) into O(M logM). Partial fraction decomposition technique is applied to rational approximation schemes to overcome the complexity of inverting polynomial of matrices. The proposed method is easy to implement on serial or parallel versions. Numerical results are presented to prove the accuracy and efficiency of the proposed method.

Keywords: integral differential equations, jump–diffusion model, American options, rational approximation

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Authors: Li Minghui, Min Shaorong, Zhang Jun

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This paper aims for studying the operational efficiency of surface warship’s motorized evasion to acoustic homing torpedo. It orderly developed trajectory model, self-guide detection model, vessel evasion model, as well as anti-torpedo error model in three-dimensional space to make up for the deficiency of precious researches analyzing two-dimensionally confrontational models. Then, making use of the Monte Carlo method, it carried out the simulation for the confrontation process of evasion in the environment of MATLAB. At last, it quantitatively analyzed the main factors which determine vessel’s survival probability. The results show that evasion relative bearing and speed will affect vessel’s survival probability significantly. Thus, choosing appropriate evasion relative bearing and speed according to alarming range and alarming relative bearing for torpedo, improving alarming range and positioning accuracy and reducing the response time against torpedo will improve the vessel’s survival probability significantly.

Keywords: acoustic homing torpedo, vessel evasion, monte carlo method, torpedo defense, vessel's survival probability

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Authors: Hany Mohamed Abdu, Mohamed Hassan Gadallah, El-Giushi Mokhtar, Yehia Mahmoud Ismail

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Laser beam cutting is one nontraditional machining process. This paper optimizes the parameters of Laser beam cutting machining parameters of Stainless steel (316L) by considering the effect of input parameters viz. power, oxygen pressure, frequency and cutting speed. Statistical design of experiments are carried in three different levels and process responses such as 'Average kerf taper (Ta)' and 'Surface Roughness (Ra)' are measured accordingly. A quadratic mathematical model (RSM) for each of the responses is developed as a function of the process parameters. Responses predicted by the models (as per Taguchi’s L27 OA) are employed to search for an optimal parametric combination to achieve desired yield of the process. RSM models are developed for mean responses, S/N ratio, and standard deviation of responses. Optimization models are formulated as single objective problem subject to process constraints. Models are formulated based on Analysis of Variance (ANOVA) using MATLAB environment. Optimum solutions are compared with Taguchi Methodology results.

Keywords: optimization, laser cutting, robust design, kerf width, Taguchi method, RSM and DOE

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Authors: Hechmi Saidi, Noureddine Hamdi

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The performance of Decode and Forward (DF) multihop Free Space Optical ( FSO) scheme deploying Multiple Input Multiple Output (MIMO) configuration under Gamma-Gamma (GG) statistical distribution, that adopts M-ary Pulse Position Modulation (MPPM) coding, is investigated. We have extracted exact and estimated values of Symbol-Error Rates (SERs) respectively. A closed form formula related to the Probability Density Function (PDF) is expressed for our designed system. Thanks to the use of DF multihop MIMO FSO configuration and MPPM signaling, atmospheric turbulence is combatted; hence the transmitted signal quality is improved.

Keywords: free space optical, multiple input multiple output, M-ary pulse position modulation, multihop, decode and forward, symbol error rate, gamma-gamma channel

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Authors: T. Y. Liu, C. H. Lin, Y. M. Ferng

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Wind energy is one of the clean renewable energy. However, the low frequency (20-200HZ) noise generated from the wind turbine blades, which bothers the residents, becomes the major problem to be developed. It is useful for predicting the aerodynamic noise by flow field and pressure distribution analysis on the wind turbine blades. Therefore, the main objective of this study is to use different turbulence models to analyse the flow field and pressure distributions of the wing blades. Three-dimensional Computation Fluid Dynamics (CFD) simulation of the flow field was used to calculate the flow phenomena for the National Renewable Energy Laboratory (NREL) Phase VI horizontal axis wind turbine rotor. Two different flow cases with different wind speeds were investigated: 7m/s with 72rpm and 15m/s with 72rpm. Four kinds of RANS-based turbulence models, Standard k-ε, Realizable k-ε, SST k-ω, and v2f, were used to predict and analyse the results in the present work. The results show that the predictions on pressure distributions with SST k-ω and v2f turbulence models have good agreements with experimental data.

Keywords: horizontal axis wind turbine, turbulence model, noise, fluid dynamics

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Authors: Yang Fu, Jaime Rodrigo Navarro, Jose F. Monserrat, Faiza Bouchmal, Oscar Carrasco Quilis

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Cellular Vehicle to Everything (C-V2X) is considered a promising solution for future autonomous driving. From Release 16 to Release 17, the Third Generation Partnership Project (3GPP) has introduced the definitions and services for 5G New Radio (NR) V2X. Experience from previous generations has shown that establishing a simulator for C-V2X communications is an essential preliminary step to achieve reliable and stable communication links. This paper proposes a complete framework of a link-level simulator based on the 3GPP specifications for the Physical Sidelink Share Channel (PSSCH) of the 5G NR Physical Layer (PHY). In this framework, several algorithms in the receiver part, i.e., sliding window in channel estimation and Minimum Mean Square Error (MMSE)-based equalization, are developed. Finally, the performance of the developed PSSCH receiver is validated through extensive simulations under different assumptions.

Keywords: C-V2X, channel estimation, link-level simulator, sidelink, 3GPP

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Authors: Abdellatif Chebboub

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Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change’s representative concentration pathway with end-of-century radiative forcing of 8.5 W/m2. The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.

Keywords: climate change, agriculture, weather change, danger of climate change

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Authors: Kunal Tongaria, Abhishek Mangal, S. Mandal, Devendra Mohan

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The carbonation of concrete is a phenomenon which is a function of various interdependent parameters. Therefore, in spite of numerous literature and database, the useful generalization is not an easy task. These interdependent parameters can be grouped under the category of internal and external factors. This paper focuses on the internal parameters which govern and increase the probability of the ingress of deleterious substances into concrete. The mechanism of effects of internal parameters such as microstructure for with and without supplementary cementing materials (SCM), water/binder ratio, the age of concrete etc. has been discussed. This is followed by the comparison of various proposed mathematical models for the deterioration of concrete. Based on existing laboratory experiments as well as field results, this paper concludes the present understanding of mechanism, modeling and future research needs in this field.

Keywords: carbonation, diffusion coefficient, microstructure of concrete, reinforced concrete

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Authors: Ferhat Demir

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Even if strategic management is highly critical for all types of organizations, only a few maturity models have been proposed in business literature for the area of strategic management activities. This paper updates previous studies and presents a new conceptual model for assessing the maturity of strategic management in any organization. Strategic management maturity model (S-3M) is basically composed of 6 maturity levels with 7 dimensions. The biggest contribution of S-3M is to put innovation into agenda of strategic management. The main objective of this study is to propose a model to align innovation with business strategies. This paper suggests that innovation (breakthrough new products/services and business models) is the only way of creating sustainable growth and strategy studies cannot ignore this aspect. Maturity models should embrace innovation to respond dynamic business environment and rapidly changing customer behaviours.

Keywords: strategic management, innovation, business model, maturity model

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Authors: Ahmad Zaini, F. Muhammad Reza Hadafi, Surya Sumpeno, Muhtadin, Mochamad Hariadi

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The lack of information about museum’s collection reduces the number of visits of museum. Museum’s revitalization is an urgent activity to increase the number of visits. The research's roadmap is building a web-based application that visualizes museum in the virtual form including museum's statue reconstruction in the form of 3D. This paper describes implementation of three-dimensional model reconstruction method based on light-strip pattern on the museum statue using 3D scanner. Noise removal, alignment, meshing and refinement model's processes is implemented to get a better 3D object reconstruction. Model’s texture derives from surface texture mapping between object's images with reconstructed 3D model. Accuracy test of dimension of the model is measured by calculating relative error of virtual model dimension compared against the original object. The result is realistic three-dimensional model textured with relative error around 4.3% to 5.8%.

Keywords: 3D reconstruction, light pattern structure, texture mapping, museum

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Authors: Odón R. Sánchez-Ccoyllo, Elizabeth Ayma-Choque, Alan Llacza

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Sulphur dioxide (SO₂) and surface-ozone (O₃) concentrations are associated with diseases. The objective of this research is to evaluate the effectiveness of the air-quality-WRF-Chem model with a horizontal resolution of 5 km x 5 km. For this purpose, the measurements of the hourly SO₂ and O₃ concentrations available in three air quality monitoring stations in Lima, Peru were used for the purpose of validating the simulations of the SO₂ and O₃ concentrations obtained with the WRF-Chem model in February 2018. For the quantitative evaluation of the simulations of these gases, statistical techniques were implemented, such as the average of the simulations; the average of the measurements; the Mean Bias (MeB); the Mean Error (MeE); and the Root Mean Square Error (RMSE). The results of these statistical metrics indicated that the simulated SO₂ and O₃ values over-predicted the SO₂ and O₃ measurements. For the SO₂ concentration, the MeB values varied from 0.58 to 26.35 µg/m³; the MeE values varied from 8.75 to 26.5 µg/m³; the RMSE values varied from 13.3 to 31.79 µg/m³; while for O₃ concentrations the statistical values of the MeB varied from 37.52 to 56.29 µg/m³; the MeE values varied from 37.54 to 56.70 µg/m³; the RMSE values varied from 43.05 to 69.56 µg/m³.

Keywords: ground-ozone, lima, sulphur dioxide, WRF-chem

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Authors: Leah Lee

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This paper examines the correlation between deep learning models and emotions with noises to see whether or not noises mask emotions. The deep learning models used are plain convolutional neural networks (CNN), auto-encoder, long short-term memory (LSTM), and Visual Geometry Group-16 (VGG-16). Emotion datasets used are Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS), Crowd-sourced Emotional Multimodal Actors Dataset (CREMA-D), Toronto Emotional Speech Set (TESS), and Surrey Audio-Visual Expressed Emotion (SAVEE). To make it four times bigger, audio set files, stretch, and pitch augmentations are utilized. From the augmented datasets, five different features are extracted for inputs of the models. There are eight different emotions to be classified. Noise variations are white noise, dog barking, and cough sounds. The variation in the signal-to-noise ratio (SNR) is 0, 20, and 40. In summation, per a deep learning model, nine different sets with noise and SNR variations and just augmented audio files without any noises will be used in the experiment. To compare the results of the deep learning models, the accuracy and receiver operating characteristic (ROC) are checked.

Keywords: auto-encoder, convolutional neural networks, long short-term memory, speech emotion recognition, visual geometry group-16

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Authors: Seyedamir Makinejadsanij

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One of the most important factors in the production of quality steel is to know the exact weight of steel in the steelmaking area. In this study, a calculation method is presented to estimate the exact weight of the melt as well as the objects transported by the overhead crane. Iran Alloy Steel Company's steelmaking area has three 90-ton cranes, which are responsible for transferring the ladles and ladle caps between 34 areas in the melt shop. Each crane is equipped with a Disomat Tersus weighing system that calculates and displays real-time weight. The moving object has a variable weight due to swinging, and the weighing system has an error of about +-5%. This means that when the object is moving by a crane, which weighs about 80 tons, the device (Disomat Tersus system) calculates about 4 tons more or 4 tons less, and this is the biggest problem in calculating a real weight. The k-means algorithm is an unsupervised clustering method that was used here. The best result was obtained by considering 3 centers. Compared to the normal average(one) or two, four, five, and six centers, the best answer is with 3 centers, which is logically due to the elimination of noise above and below the real weight. Every day, the standard weight is moved with working cranes to test and calibrate cranes. The results are shown that the accuracy is about 40 kilos per 60 tons (standard weight). As a result, with this method, the accuracy of moving weight is calculated as 99.95%. K-means is used to calculate the exact mean of objects. The stopping criterion of the algorithm is also the number of 1000 repetitions or not moving the points between the clusters. As a result of the implementation of this system, the crane operator does not stop while moving objects and continues his activity regardless of weight calculations. Also, production speed increased, and human error decreased.

Keywords: k-means, overhead crane, melt weight, weight estimation, swing problem

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Authors: Dev Ras Pandey, Bharat Mishra, S. K. Tripathi

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Cloud computing is ready to transform the structure of businesses and learning through supplying the real-time applications and provide an immediate help for small to medium sized businesses. The ability to run a hypervisor inside a virtual machine is important feature of virtualization and it is called nested virtualization. In today’s growing field of information technology, many of the virtualization models are available, that provide a convenient approach to implement, but decision for a single model selection is difficult. This paper explains the applications of operating system based virtualization in cloud computing with an appropriate/suitable model with their different specifications and user’s requirements. In the present paper, most popular models are selected, and the selection was based on container and hypervisor based virtualization. Selected models were compared with a wide range of user’s requirements as number of CPUs, memory size, nested virtualization supports, live migration and commercial supports, etc. and we identified a most suitable model of virtualization.

Keywords: virtualization, OS based virtualization, container based virtualization, hypervisor based virtualization

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Authors: Sungho Kim, Jaechoul Shin, Yujin Baek

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In recent years, due to the environmental impacts and time factor, etc., various type of pavement deterioration is increasing rapidly such as crack, pothole, rutting and roughness degradation. The Ministry of Land, Infrastructure and Transport maintains regular pavement condition of the highway and the national highway using the pavement condition survey equipment and structural survey equipment in Korea. Local governments that maintain local roads, farm roads, etc. are difficult to maintain the pavement condition using the pavement condition survey equipment depending on economic conditions, skills shortages and local conditions such as narrow roads. This study presents a quantitative evaluation method of the pavement condition through the visual inspection to overcome these problems of roads managed by local governments. It is difficult to evaluate rutting and roughness with the naked eye. However, the condition of cracks can be evaluated with the naked eye. Linear cracks (m), area cracks (m²) and potholes (number, m²) were investigated with the naked eye every 100 meters for survey the cracks. In this paper, crack ratio was calculated using the results of the condition of cracks and pavement condition was evaluated by calculated crack ratio. The pavement condition survey equipment also investigated the pavement condition in the same section in order to evaluate the reliability of pavement condition evaluation by the calculated crack ratio. The pavement condition was evaluated through the SPI (Seoul Pavement Index) and calculated crack ratio using results of field survey. The results of a comparison between 'the SPI considering only crack ratio' and 'the SPI considering rutting and roughness either' using the equipment survey data showed a margin of error below 5% when the SPI is less than 5. The SPI 5 is considered the base point to determine whether to maintain the pavement condition. It showed that the pavement condition can be evaluated using only the crack ratio. According to the analysis results of the crack ratio between the visual inspection and the equipment survey, it has an average error of 1.86%(minimum 0.03%, maximum 9.58%). Economically, the visual inspection costs only 10% of the equipment survey and will also help the economy by creating new jobs. This paper advises that local governments maintain the pavement condition through the visual investigations. However, more research is needed to improve reliability. Acknowledgment: The author would like to thank the MOLIT (Ministry of Land, Infrastructure, and Transport). This work was carried out through the project funded by the MOLIT. The project name is 'development of 20mm grade for road surface detecting roadway condition and rapid detection automation system for removal of pothole'.

Keywords: asphalt pavement maintenance, crack ratio, evaluation of asphalt pavement condition, SPI (Seoul Pavement Index), visual investigation

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Authors: Tea Poklepović, Zdravka Aljinović, Branka Marasović

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Due to the importance of yield curve and its estimation it is inevitable to have valid methods for yield curve forecasting in cases when there are scarce issues of securities and/or week trade on a secondary market. Therefore in this paper, after the estimation of weekly yield curves on Croatian financial market from October 2011 to August 2012 using Nelson-Siegel and Svensson models, yield curves are forecasted using Vector auto-regressive model and Neural networks. In general, it can be concluded that both forecasting methods have good prediction abilities where forecasting of yield curves based on Nelson Siegel estimation model give better results in sense of lower Mean Squared Error than forecasting based on Svensson model Also, in this case Neural networks provide slightly better results. Finally, it can be concluded that most appropriate way of yield curve prediction is neural networks using Nelson-Siegel estimation of yield curves.

Keywords: Nelson-Siegel Model, neural networks, Svensson Model, vector autoregressive model, yield curve

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Authors: S. Belhour, A. K. Ferouani, C. Azizi

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In recent years, a considerable effort (experience, numerical simulation, and theoretical prediction models) has characterised by high efficiency and low cost. Then an improved physics analytical model for simulating is proposed. The performance of GaAs MESFETs has been developed for use in device design for high frequency. This model is based on mathematical analysis, and a new approach for the standard model is proposed, this approach allowed to conceive applicable model for MESFET’s operating in the turn-one or pinch-off region and valid for the short-channel and the long channel MESFET’s in which the two dimensional potential distribution contributed by the depletion layer under the gate is obtained by conventional approximation. More ever, comparisons between the analytical models with different values of mobility are proposed, and a good agreement is obtained.

Keywords: analytical, gallium arsenide, MESFET, mobility, models

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Authors: Jinan Fiaidhi, Hashmath Shaik

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Breaking the barrier for practicing evidence-based medicine relies on effective methods for rapidly identifying relevant evidence from the body of biomedical literature. An important challenge confronted by medical practitioners is the long time needed to browse, filter, summarize and compile information from different medical resources. Deep learning can help in solving this based on automatic question answering (Q&A) and transformers. However, Q&A and transformer technologies are not trained to answer clinical queries that can be used for evidence-based practice, nor can they respond to structured clinical questioning protocols like PICO (Patient/Problem, Intervention, Comparison and Outcome). This article describes the use of deep learning techniques for Q&A that are based on transformer models like BERT and GPT to answer PICO clinical questions that can be used for evidence-based practice extracted from sound medical research resources like PubMed. We are reporting acceptable clinical answers that are supported by findings from PubMed. Our transformer methods are reaching an acceptable state-of-the-art performance based on two staged bootstrapping processes involving filtering relevant articles followed by identifying articles that support the requested outcome expressed by the PICO question. Moreover, we are also reporting experimentations to empower our bootstrapping techniques with patch attention to the most important keywords in the clinical case and the PICO questions. Our bootstrapped patched with attention is showing relevancy of the evidence collected based on entropy metrics.

Keywords: automatic question answering, PICO questions, evidence-based medicine, generative models, LLM transformers

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Authors: Nina Penkova, Kalin Krumov, Liliana Zashcova, Ivan Kassabov

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The insulating glass units (IGU) are widely used in the advanced and renovated buildings in order to reduce the energy for heating and cooling. Rules for the choice of IGU to ensure energy efficiency and thermal comfort in the indoor space are well known. The existing of internal loads - gage or vacuum pressure in the hermetized gas space, requires additional attention at the design of the facades. The internal loads appear at variations of the altitude, meteorological pressure and gas temperature according to the same at the process of sealing. The gas temperature depends on the presence of coatings, coating position in the transparent multi-layer system, IGU geometry and space orientation, its fixing on the facades and varies with the climate conditions. An algorithm for modeling and numerical simulation of thermal fields and internal pressure in the gas cavity at insulating glass units as function of the meteorological conditions is developed. It includes models of the radiation heat transfer in solar and infrared wave length, indoor and outdoor convection heat transfer and free convection in the hermetized gas space, assuming the gas as compressible. The algorithm allows prediction of temperature and pressure stratification in the gas domain of the IGU at different fixing system. The models are validated by comparison of the numerical results with experimental data obtained by Hot-box testing. Numerical calculations and estimation of 3D temperature, fluid flow fields, thermal performances and internal loads at IGU in window system are implemented.

Keywords: insulating glass units, thermal loads, internal pressure, CFD analysis

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Authors: Mst. Tuhin Akter, Sharun Akter Khushbu, S. M. Shaqib

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A real-time system architecture is highly effective for monitoring and detecting various damaged products or fruits that may deteriorate over time or become infected with diseases. Deep learning models have proven to be effective in building such architectures. However, building a deep learning model from scratch is a time-consuming and costly process. A more efficient solution is to utilize deep neural network (DNN) based transfer learning models in the real-time monitoring architecture. This study focuses on using a novel strawberry dataset to develop effective transfer learning models for the proposed real-time monitoring system architecture, specifically for evaluating and detecting strawberry freshness. Several state-of-the-art transfer learning models were employed, and the best performing model was found to be Xception, demonstrating higher performance across evaluation metrics such as accuracy, recall, precision, and F1-score.

Keywords: strawberry freshness evaluation, deep neural network, transfer learning, image augmentation

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Authors: Azzedine Hamza, Chouaib Chakour, Messaoud Ramdani

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Energy demand prediction plays a crucial role in achieving next-generation power systems for agricultural greenhouses. As a result, high prediction quality is required for efficient smart grid management and therefore low-cost energy consumption. The aim of this paper is to investigate the effectiveness of a hybrid data-driven model in day-ahead energy demand prediction. The proposed model consists of Discrete Wavelet Transform (DWT), and Adaptive Neuro-Fuzzy Inference System (ANFIS). The DWT is employed to decompose the original signal in a set of subseries and then an ANFIS is used to generate the forecast for each subseries. The proposed hybrid method (DWT-ANFIS) was evaluated using a greenhouse energy demand data for a week and compared with ANFIS. The performances of the different models were evaluated by comparing the corresponding values of Mean Absolute Percentage Error (MAPE). It was demonstrated that discret wavelet transform can improve agricultural greenhouse energy demand modeling.

Keywords: wavelet transform, ANFIS, energy consumption prediction, greenhouse

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Authors: Kanita Beširević

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Open-source software development activities highly rely on Internet gathering communities volunteering in software development projects. Additionally, the libraries and cultural institutions share their metadata in the form of linked metadata to enable dissemination and enrichment. The open-source software provides free alternatives to traditional software solutions. The article aims to investigate the ever-increasing options for the digital library open source software adoption. The software available is presented and compared to other software solutions as well as to their previous versions. The top three open-source digital library software solutions are presented and compared. The comparison criteria are adopted from the UNESCO study by Bankier, J., & Gleason, K. Institutional Repository Software Comparison comprising of twelve criteria to appraise software, namely: infrastructure, front-end design, content discovery, publication tools, interoperability, and preservation. This article adopts a descriptive methodology based on data and information collected through selected software websites and the literature review.

Keywords: open source software, digital library, DSpace, Fedora, Greenstone

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Authors: Kevin Spencer G. Anglim, Zhenyu Zhang, Qingbin Gao

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Reusable launch vehicles (RLVs) present a more environmentally-friendly approach to accessing space when compared to traditional launch vehicles that are discarded after each flight. This paper studies the recyclable nature of RLVs by presenting a solution method for determining minimum-fuel optimal trajectories using principles from optimal control theory and particle swarm optimization (PSO). This problem is formulated as a minimum-landing error powered descent problem where it is desired to move the RLV from a fixed set of initial conditions to three different sets of terminal conditions. However, unlike other powered descent studies, this paper considers the highly nonlinear effects caused by atmospheric drag, which are often ignored for studies on the Moon or on Mars. Rather than optimizing the controls directly, the throttle control is assumed to be bang-off-bang with a predetermined thrust direction for each phase of flight. The PSO method is verified in a one-dimensional comparison study, and it is then applied to the two-dimensional cases, the results of which are illustrated.

Keywords: minimum-fuel optimal trajectory, particle swarm optimization, reusable rocket, SpaceX

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Authors: Sanjay M. Gulhane, Athar Ravish Khan, Umesh W. Kaware

Abstract:

Orthogonal frequency and code division multiplexing (OFCDM) has received large attention as a modulation scheme to realize high data rate transmission. Multiband (MB) Orthogonal frequency division multiplexing (OFDM) Ultra Wide Band (UWB) system become promising technique for high data rate due to its large number of advantage over Singleband (UWB) system, but it suffer from coherent frequency diversity problem. In this paper we have proposed MB-OFCDM UWB system, in which two-dimensional (2D) spreading (time and frequency domain spreading), has been introduced, combining OFDM with 2D spreading, proposed system can provide frequency diversity. This paper presents the basic structure and main functions of the MB-OFCDM system, and evaluates the bit error rate BER performance of MB-OFDM and MB-OFCDM system under UWB indoor multi-path channel model. It is observe that BER curve of MB-OFCDM UWB improve its performance by 2dB as compare to MB-OFDM UWB system.

Keywords: MB-OFDM UWB system, MB-OFCDM UWB system, UWB IEEE channel model, BER

Procedia PDF Downloads 549

Authors: Minjeoung Kim

Abstract:

This paper deals with the comparison of women’s political participation in Korea and China. Korean women are participated more in higher education. As the economic development and the women's social participation can enhance the possibility of women's political participation in advanced democratic countries, in Asian countries such as Korea and China in which Confucianism prohibited women to participate in public life and the process of nation building is different from western countries, the political power takes an initiative to implement policies for women's participation in politics and for women's consciousness.

Keywords: korea, china, women, political participation

Procedia PDF Downloads 400