Search results for: temporal reasoning.

Authors: L. Parisi

Abstract:

In this research work, neural networks were applied to classify two types of hip joint implants based on the relative hip joint implant side speed and three components of each ground reaction force. The condition of walking gait at normal velocity was used and carried out with each of the two hip joint implants assessed. Ground reaction forces’ kinetic temporal changes were considered in the first approach followed but discarded in the second one. Ground reaction force components were obtained from eighteen patients under such gait condition, half of which had a hip implant type I-II, whilst the other half had the hip implant, defined as type III by Orthoload®. After pre-processing raw gait kinetic data and selecting the time frames needed for the analysis, the ground reaction force components were used to train a MLP neural network, which learnt to distinguish the two hip joint implants in the abovementioned condition. Further to training, unknown hip implant side and ground reaction force components were presented to the neural networks, which assigned those features into the right class with a reasonably high accuracy for the hip implant type I-II and the type III. The results suggest that neural networks could be successfully applied in the performance assessment of hip joint implants.

Keywords: Kinemic gait data, Neural networks, Hip joint implant, Hip arthroplasty, Rehabilitation Engineering.

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Authors: Deniz T. Sodiri, Venkat V S S Sastry

Abstract:

The paper presents an on-line recognition machine (RM) for continuous/isolated, dynamic and static gestures that arise in Flight Deck Officer (FDO) training. RM is based on generic pattern recognition framework. Gestures are represented as templates using summary statistics. The proposed recognition algorithm exploits temporal and spatial characteristics of gestures via dynamic programming and Markovian process. The algorithm predicts corresponding index of incremental input data in the templates in an on-line mode. Accumulated consistency in the sequence of prediction provides a similarity measurement (Score) between input data and the templates. The algorithm provides an intuitive mechanism for automatic detection of start/end frames of continuous gestures. In the present paper, we consider isolated gestures. The performance of RM is evaluated using four datasets - artificial (W TTest), hand motion (Yang) and FDO (tracker, vision-based ). RM achieves comparable results which are in agreement with other on-line and off-line algorithms such as hidden Markov model (HMM) and dynamic time warping (DTW). The proposed algorithm has the additional advantage of providing timely feedback for training purposes.

Keywords: On-line Recognition Algorithm, IsolatedDynamic/Static Gesture Recognition, On-line Markovian/DynamicProgramming, Training in Virtual Environments.

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Authors: Randhir Singh Baghel, Joydip Dhar, Renu Jain

Abstract:

In this paper, for the understanding of the phytoplankton dynamics in marine ecosystem, a susceptible and an infected class of phytoplankton population is considered in spatiotemporal domain. Here, the susceptible phytoplankton is growing logistically and the growth of infected phytoplankton is due to the instantaneous Holling type-II infection response function. The dynamics are studied in terms of the local and global stabilities for the system and further explore the possibility of Hopf -bifurcation, taking the half saturation period as (i.e., ) the bifurcation parameter in temporal domain. It is also observe that the reaction diffusion system exhibits spatiotemporal chaos and pattern formation in phytoplankton dynamics, which is particularly important role play for the spatially extended phytoplankton system. Also the effect of the diffusion coefficient on the spatial system for both one and two dimensional case is obtained. Furthermore, we explore the higher-order stability analysis of the spatial phytoplankton system for both linear and no-linear system. Finally, few numerical simulations are carried out for pattern formation.

Keywords: Phytoplankton dynamics, Reaction-diffusion system, Local stability, Hopf-bifurcation, Global stability, Chaos, Pattern Formation, Higher-order stability analysis.

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Authors: A. Junpen, S. Garivait, S. Bonnet, A. Pongpullponsak

Abstract:

The forest fires in Thailand are annual occurrence which is the cause of air pollutions. This study intended to estimate the emission from forest fire during 2005-2009 using MODerateresolution Imaging Spectro-radiometer (MODIS) sensor aboard the Terra and Aqua satellites, experimental data, and statistical data. The forest fire emission is estimated using equation established by Seiler and Crutzen in 1982. The spatial and temporal variation of forest fire emission is analyzed and displayed in the form of grid density map. From the satellite data analysis suggested between 2005 and 2009, the number of fire hotspots occurred 86,877 fire hotspots with a significant highest (more than 80% of fire hotspots) in the deciduous forest. The peak period of the forest fire is in January to May. The estimation on the emissions from forest fires during 2005 to 2009 indicated that the amount of CO, CO2, CH4, and N2O was about 3,133,845 tons, 47,610.337 tons, 204,905 tons, and 6,027 tons, respectively, or about 6,171,264 tons of CO2eq. They also emitted 256,132 tons of PM10. The year 2007 was found to be the year when the emissions were the largest. Annually, March is the period that has the maximum amount of forest fire emissions. The areas with high density of forest fire emission were the forests situated in the northern, the western, and the upper northeastern parts of the country.

Keywords: Emissions, Forest fire, Remote sensing information.

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Authors: Sulaiman Al Amro

Abstract:

There are currently considerable challenges concerning data security and privacy, particularly in relation to modern technologies. This includes the virtual world known as the Metaverse, which consists of a virtual space that integrates various technologies, and therefore susceptible to cyber threats such as malware, phishing, and identity theft. This has led recent studies to propose the development of Metaverse forensic frameworks and the integration of advanced technologies, including machine learning for intrusion detection and security. In this context, the application of first-order logic offers a formal and systematic approach to defining the conditions of cyberattacks, thereby contributing to the development of effective detection mechanisms. In addition, formalizing the rules and patterns of cyber threats has the potential to enhance the overall security posture of the Metaverse and thus the integrity and safety of this virtual environment. The current paper focuses on the primary actions employed by avatars for potential attacks, including Interval Temporal Logic (ITL) and behavior-based detection to detect an avatar’s abnormal activities within the Metaverse. The research established that the proposed framework attained an accuracy of 92.307%, resulting in the experimental results demonstrating the efficacy of ITL, including its superior performance in addressing the threats posed by avatars within the Metaverse domain.

Keywords: Cyberattacks, detection, first-order logic, Metaverse, privacy, security.

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Authors: Sriranjani Srinivasan

Abstract:

To appreciate Indian art and architecture by studying it in India alone will only lead to partial understanding of the whole story and the variety of the statement has been amply proved by subsequent decades of patient research. The results of the work of the Archaeological Survey of India forms only one half of the picture, the other half emerges with the studies of the archaeology and art of the Far East that progressed almost simultaneously under the Archaeological Survey of the Dutch East Indies, the École française d'Extrême-Orient (EFEO), or French School of Asian Studies, and allied institutions. The conclusions arrived at have only rendered the assertion that India produced her ultimate master pieces only through foreign influences and in foreign lands (the South-Eastern peninsular and archipelagic regions) almost axiomatic. Angkor in Cambodia and Borobudur in Java, undoubtedly the two greatest architectural marvels of Indian genius, for in content and spirit these (and other monuments of varying magnitudes), are purely Indian, would well illustrate the statement mentioned earlier. Stimulated research followed the discoveries and among the many studies and publications of such pioneers like Coedes, Parmentier, Coomaraswamy and many others in Dutch, French and English made growing contributions to the subject. This paper will discuss in detail the impact of India on the architecture of South East Asia by detailed comparison of architectural styles, elements, and construction materials of a few specific architectural master pieces, in both India and South East Asian countries. It will also analyze the reasoning behind the influence of India on South East Asian countries in spite of them being exposed to the equally culturally rich and civilized kingdoms of China. The intention of this paper is to understand that, conquest by war is not always the only reason for architectural influences and impacts.

Keywords: Architectural influence, Buddhist architecture, Indian architecture, Southeast Asian architecture.

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Authors: Achut Manandhar, Kenneth D. Morton, Peter A. Torrione, Leslie M. Collins

Abstract:

The current trends in affect recognition research are to consider continuous observations from spontaneous natural interactions in people using multiple feature modalities, and to represent affect in terms of continuous dimensions, incorporate spatio-temporal correlation among affect dimensions, and provide fast affect predictions. These research efforts have been propelled by a growing effort to develop affect recognition system that can be implemented to enable seamless real-time human-computer interaction in a wide variety of applications. Motivated by these desired attributes of an affect recognition system, in this work a multi-dimensional affect prediction approach is proposed by integrating multivariate Relevance Vector Machine (MVRVM) with a recently developed Output-associative Relevance Vector Machine (OARVM) approach. The resulting approach can provide fast continuous affect predictions by jointly modeling the multiple affect dimensions and their correlations. Experiments on the RECOLA database show that the proposed approach performs competitively with the OARVM while providing faster predictions during testing.

Keywords: Dimensional affect prediction, Output-associative RVM, Multivariate regression.

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Authors: Jörg Lenhardt, Wolfram Schiffmann, Jörg Keller

Abstract:

While the feature sizes of recent Complementary Metal Oxid Semiconductor (CMOS) devices decrease the influence of static power prevails their energy consumption. Thus, power savings that benefit from Dynamic Frequency and Voltage Scaling (DVFS) are diminishing and temporal shutdown of cores or other microchip components become more worthwhile. A consequence of powering off unused parts of a chip is that the relative difference between idle and fully loaded power consumption is increased. That means, future chips and whole server systems gain more power saving potential through power-aware load balancing, whereas in former times this power saving approach had only limited effect, and thus, was not widely adopted. While powering off complete servers was used to save energy, it will be superfluous in many cases when cores can be powered down. An important advantage that comes with that is a largely reduced time to respond to increased computational demand. We include the above developments in a server power model and quantify the advantage. Our conclusion is that strategies from datacenters when to power off server systems might be used in the future on core level, while load balancing mechanisms previously used at core level might be used in the future at server level.

Keywords: Power efficiency, static power consumption, dynamic power consumption, CMOS.

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Authors: Deniz T. Sodiri, Venkat V S S Sastry

Abstract:

The paper presents an on-line recognition machine (RM) for continuous/isolated, dynamic and static gestures that arise in Flight Deck Officer (FDO) training. RM is based on generic pattern recognition framework. Gestures are represented as templates using summary statistics. The proposed recognition algorithm exploits temporal and spatial characteristics of gestures via dynamic programming and Markovian process. The algorithm predicts corresponding index of incremental input data in the templates in an on-line mode. Accumulated consistency in the sequence of prediction provides a similarity measurement (Score) between input data and the templates. The algorithm provides an intuitive mechanism for automatic detection of start/end frames of continuous gestures. In the present paper, we consider isolated gestures. The performance of RM is evaluated using four datasets - artificial (W TTest), hand motion (Yang) and FDO (tracker, vision-based ). RM achieves comparable results which are in agreement with other on-line and off-line algorithms such as hidden Markov model (HMM) and dynamic time warping (DTW). The proposed algorithm has the additional advantage of providing timely feedback for training purposes.

Keywords: On-line Recognition Algorithm, IsolatedDynamic/Static Gesture Recognition, On-line Markovian/DynamicProgramming, Training in Virtual Environments.

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Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

Abstract:

In this paper, we present the human action recognition method using the variational Bayesian HMM with the Dirichlet process mixture (DPM) of the Gaussian-Wishart emission model (GWEM). First, we define the Bayesian HMM based on the Dirichlet process, which allows an infinite number of Gaussian-Wishart components to support continuous emission observations. Second, we have considered an efficient variational Bayesian inference method that can be applied to drive the posterior distribution of hidden variables and model parameters for the proposed model based on training data. And then we have derived the predictive distribution that may be used to classify new action. Third, the paper proposes a process of extracting appropriate spatial-temporal feature vectors that can be used to recognize a wide range of human behaviors from input video image. Finally, we have conducted experiments that can evaluate the performance of the proposed method. The experimental results show that the method presented is more efficient with human action recognition than existing methods.

Keywords: Human action recognition, Bayesian HMM, Dirichlet process mixture model, Gaussian-Wishart emission model, Variational Bayesian inference, Prior distribution and approximate posterior distribution, KTH dataset.

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Authors: C. Barreto Carvalho, C. da Motta, M. Sousa, J. Cabral, A. L. Carvalho, E. B. Peixoto

Abstract:

The aim of the current study was to develop and validate a Response to Stressful Situations Scale (RSSS) for the Portuguese population. This scale assesses the degree of stress experienced in scenarios that can constitute positive, negative and more neutral stressors, and also describes the physiological, emotional and behavioral reactions to those events according to their intensity. These scenarios include typical stressor scenarios relevant to patients with schizophrenia, which are currently absent from most scales, assessing specific risks that these stressors may bring on subjects, which may prove useful in non-clinical and clinical populations (i.e. Patients with mood or anxiety disorders, schizophrenia). Results from Principal Components Analysis and Confirmatory Factor Analysis of two adult samples from general population allowed to confirm a three-factor model with good fit indices: χ2 (144)= 370.211, p = 0.000; GFI = 0.928; CFI = 0.927; TLI = 0.914, RMSEA = 0.055, P(rmsea ≤0.005) = .096; PCFI = .781. Further data analysis of the scale revealed that RSSS is an adequate assessment tool of stress response in adults to be used in further research and clinical settings, with good psychometric characteristics, adequate divergent and convergent validity, good temporal stability and high internal consistency.

Keywords: Assessment, stress events, stress response, stress vulnerability.

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Authors: Yung-Chien Sun, O. Grant Clark

Abstract:

In this paper, the implementation of a rule-based intuitive reasoner is presented. The implementation included two parts: the rule induction module and the intuitive reasoner. A large weather database was acquired as the data source. Twelve weather variables from those data were chosen as the “target variables" whose values were predicted by the intuitive reasoner. A “complex" situation was simulated by making only subsets of the data available to the rule induction module. As a result, the rules induced were based on incomplete information with variable levels of certainty. The certainty level was modeled by a metric called "Strength of Belief", which was assigned to each rule or datum as ancillary information about the confidence in its accuracy. Two techniques were employed to induce rules from the data subsets: decision tree and multi-polynomial regression, respectively for the discrete and the continuous type of target variables. The intuitive reasoner was tested for its ability to use the induced rules to predict the classes of the discrete target variables and the values of the continuous target variables. The intuitive reasoner implemented two types of reasoning: fast and broad where, by analogy to human thought, the former corresponds to fast decision making and the latter to deeper contemplation. . For reference, a weather data analysis approach which had been applied on similar tasks was adopted to analyze the complete database and create predictive models for the same 12 target variables. The values predicted by the intuitive reasoner and the reference approach were compared with actual data. The intuitive reasoner reached near-100% accuracy for two continuous target variables. For the discrete target variables, the intuitive reasoner predicted at least 70% as accurately as the reference reasoner. Since the intuitive reasoner operated on rules derived from only about 10% of the total data, it demonstrated the potential advantages in dealing with sparse data sets as compared with conventional methods.

Keywords: Artificial intelligence, intuition, knowledge acquisition, limited certainty.

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Authors: Mourad Moussa, Ali Douik, Hassani Messaoud

Abstract:

Events discrimination and decision maker in sport field are the subject of many interesting studies in computer vision and artificial intelligence. A large volume of research has been conducted for automatic semantic event detection and summarization of sports videos. Indeed the results of these researches have a very significant contribution, as well to television broadcasts as to the football teams, since the result of sporting event can be reflected on the economic field. In this paper, we propose a novel fuzzy sequential technique which lead to discriminate events and specify the technico-tactics on going the game, nor the fuzzy system or the sequential one, may be able to respond to the asked question, in fact fuzzy process is not sufficient, it does not respect the chronological order according the time of various events, similarly the sequential process needs flexibility about the parameters used in this study, it may affect a membership degree of each parameter on the one hand and respect the sequencing of events for each frame on the other hand. Indeed this technique describes special events such as dribbling, headings, short sprints, rapid acceleration or deceleration, turning, jumping, kicking, ball occupation, and tackling according velocity vectors of the two players and the ball direction.

Keywords: Sequential process, Event detection, Soccer videos analysis, Fuzzy process, Spatio-temporal parameters.

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Authors: Mohammad Bakhshi, Firas Al Janabi

Abstract:

High resolution rain data are very important to fulfill the input of hydrological models. Among models of high-resolution rainfall data generation, the temporal disaggregation was chosen for this study. The paper attempts to generate three different rainfall resolutions (4-hourly, hourly and 10-minutes) from daily for around 20-year record period. The process was done by DiMoN tool which is based on random cascade model and method of fragment. Differences between observed and simulated rain dataset are evaluated with variety of statistical and empirical methods: Kolmogorov-Smirnov test (K-S), usual statistics, and Exceedance probability. The tool worked well at preserving the daily rainfall values in wet days, however, the generated data are cumulated in a shorter time period and made stronger storms. It is demonstrated that the difference between generated and observed cumulative distribution function curve of 4-hourly datasets is passed the K-S test criteria while in hourly and 10-minutes datasets the P-value should be employed to prove that their differences were reasonable. The results are encouraging considering the overestimation of generated high-resolution rainfall data.

Keywords: DiMoN tool, disaggregation, exceedance probability, Kolmogorov-Smirnov Test, rainfall.

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Authors: Ali Keshavarzi, Fereydoon Sarmadian

Abstract:

Investigation of soil properties like Cation Exchange Capacity (CEC) plays important roles in study of environmental reaserches as the spatial and temporal variability of this property have been led to development of indirect methods in estimation of this soil characteristic. Pedotransfer functions (PTFs) provide an alternative by estimating soil parameters from more readily available soil data. 70 soil samples were collected from different horizons of 15 soil profiles located in the Ziaran region, Qazvin province, Iran. Then, multivariate regression and neural network model (feedforward back propagation network) were employed to develop a pedotransfer function for predicting soil parameter using easily measurable characteristics of clay and organic carbon. The performance of the multivariate regression and neural network model was evaluated using a test data set. In order to evaluate the models, root mean square error (RMSE) was used. The value of RMSE and R2 derived by ANN model for CEC were 0.47 and 0.94 respectively, while these parameters for multivariate regression model were 0.65 and 0.88 respectively. Results showed that artificial neural network with seven neurons in hidden layer had better performance in predicting soil cation exchange capacity than multivariate regression.

Keywords: Easily measurable characteristics, Feed-forwardback propagation, Pedotransfer functions, CEC.

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Authors: Youngsuck Ji, Youngjoon Han, Hernsoo Hahn

Abstract:

In this paper, we proposed the robust mobile object detection method for light effect in the night street image block based updating reference background model using block state analysis. Experiment image is acquired sequence color video from steady camera. When suddenly appeared artificial illumination, reference background model update this information such as street light, sign light. Generally natural illumination is change by temporal, but artificial illumination is suddenly appearance. So in this paper for exactly detect artificial illumination have 2 state process. First process is compare difference between current image and reference background by block based, it can know changed blocks. Second process is difference between current image-s edge map and reference background image-s edge map, it possible to estimate illumination at any block. This information is possible to exactly detect object, artificial illumination and it was generating reference background more clearly. Block is classified by block-state analysis. Block-state has a 4 state (i.e. transient, stationary, background, artificial illumination). Fig. 1 is show characteristic of block-state respectively [1]. Experimental results show that the presented approach works well in the presence of illumination variance.

Keywords: Block-state, Edge component, Reference backgroundi, Artificial illumination.

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Authors: N. Ikasari, T. Sumransat, U. Eko, R. Kusumastuti

Abstract:

Small and medium enterprises (SMEs) are regarded as the engine for economic development, notwithstanding their continuous financing conundrum. In the case of developing countries, access to finance is a reflection of the effectiveness of government policy. The widely accepted perspective to assess small businesses’ access to finance is that of economic view. The existing body of literature presents access to finance in three dimensions; they are accessibility, eligibility and affordability. Within this perspective, the role of socio-cultural has not explored. This study is aimed at investigating the existence of any socio-cultural factors within access to finance issue in Asian countries where governance is enriched by countries’ values and beliefs. The significance of this study is the instigation of supplementary dimension to assess access to finance that eventually contributes to the development of micro-finance policy. Indonesia and Thailand are selected as cases in point, where distinction is drawn on the level of cultural diversity and micro-finance policy in respective country. A questionnaire is used to collect information related to the three dimensions of access to finance as well as to explore alternative financing reasoning to elaborate the issue from the demand side. Questionnaires are distributed to 60 small business owners operating in Indonesia and the same number in Thailand. In order to present a complete understanding on the matter at hand, interviews with banks are conducted to capture the perspective as presented by the supply side. Research findings show that small business owners and banks in Indonesia and Thailand are in agreement that access to finance is not deemed as an issue. However, trust issue that exists mutually between financing users and providers leads small business owners in Indonesia to look for alternative financing other than banks. The findings contribute to the refinement of micro-financing policy in Indonesia and Thailand.

Keywords: Access to finance, Indonesia, small and medium enterprises, Thailand.

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Authors: Srimuruganandam. B, S.M. Shiva Nagendra

Abstract:

In this paper the influence of heterogeneous traffic on the temporal variation of ambient PM10, PM2.5 and PM1 concentrations at a busy arterial route (Sardar Patel Road) in the Chennai city has been analyzed. The hourly PM concentration, traffic counts and average speed of the vehicles have been monitored at the study site for one week (19th-25th January 2009). Results indicated that the concentrations of coarse (PM10) and fine PM (PM2.5 and PM1) concentrations at SP road are having similar trend during peak and non-peak hours, irrespective of the days. The PM concentrations showed daily two peaks corresponding to morning (8 to 10 am) and evening (7 to 9 pm) peak hour traffic flow. The PM10 concentration is dominated by fine particles (53% of PM2.5 and 45% of PM1). The high PM2.5/PM10 ratio indicates that the majority of PM10 particles originate from re-suspension of road dust. The analysis of traffic flow at the study site showed that 2W, 3W and 4W are having similar diurnal trend as PM concentrations. This confirms that the 2W, 3W and 4W are the main emission source contributing to ambient PM concentration at SP road. The speed measurement at SP road showed that the average speed of 2W, 3W, 4W, LCV and HCV are 38, 40, 38, 40 and 38 km/hr and 43, 41, 42, 40 and 41 km/hr respectively for the weekdays and weekdays.

Keywords: particulate matter, heterogeneous traffic, fineparticles, coarse particles, vehicle speed, weekend and weekday.

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Authors: R. Tlili Yaakoubi, H. Nakouri, O. Blanpain, S. Lallahem

Abstract:

The current tools for real time management of sewer systems are based on two software tools: the software of weather forecast and the software of hydraulic simulation. The use of the first ones is an important cause of imprecision and uncertainty, the use of the second requires temporal important steps of decision because of their need in times of calculation. This way of proceeding fact that the obtained results are generally different from those waited. The major idea of this project is to change the basic paradigm by approaching the problem by the "automatic" face rather than by that "hydrology". The objective is to make possible the realization of a large number of simulations at very short times (a few seconds) allowing to take place weather forecasts by using directly the real time meditative pluviometric data. The aim is to reach a system where the decision-making is realized from reliable data and where the correction of the error is permanent. A first model of control laws was realized and tested with different return-period rainfalls. The gains obtained in rejecting volume vary from 19 to 100 %. The development of a new algorithm was then used to optimize calculation time and thus to overcome the subsequent combinatorial problem in our first approach. Finally, this new algorithm was tested with 16- year-rainfall series. The obtained gains are 40 % of total volume rejected to the natural environment and of 65 % in the number of discharges.

Keywords: Automation, optimization, paradigm, RTC.

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Authors: Lorena Alemán de la Garza, Marcela Georgina Gómez-Zermeño

Abstract:

This paper presents the SolarSPELL case study that aims to generate information on the use of indicators that help evaluate the pedagogical quality of a digital library resources. SolarSPELL is a solar-powered digital library with WiFi connectivity. It offers a variety of open educational resources selected for their potential for the digital transformation of educational practices and the achievement of the 2030 Agenda for Sustainable Development, adopted by all United Nations Member States. The case study employed a quantitative methodology and the research instrument was applied to 55 teachers, directors and librarians. The results indicate that it is possible to strengthen the pedagogical quality of open educational resources, through actions focused on improving temporal and technological parameters. They also reveal that users believe that SolarSPELL improves the teaching-learning processes and motivates the teacher to improve his or her development. This study provides valuable information on a tool that supports teaching-learning processes and facilitates connectivity with renewable energies that improves the teacher training in active methodologies for ecosystem learning.

Keywords: Educational innovation, digital library, pedagogical quality, solar energy, teacher training, sustainable development.

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Authors: N. B. Fedosenko, A.A Iatcenko, S.A. Levanov

Abstract:

The paper shows some ability to manage two-phase flows arising from the use of unsteady effects. In one case, we consider the condition of fragmentation of the interface between the two components leads to the intensification of mixing. The problem is solved when the temporal and linear scale are small for the appearance of the developed mixing layer. Showing that exist such conditions for unsteady flow velocity at the surface of the channel, which will lead to the creation and fragmentation of vortices at Re numbers of order unity. Also showing that the Re is not a criterion of similarity for this type of flows, but we can introduce a criterion that depends on both the Re, and the frequency splitting of the vortices. It turned out that feature of this situation is that streamlines behave stable, and if we analyze the behavior of the interface between the components it satisfies all the properties of unstable flows. The other problem we consider the behavior of solid impurities in the extensive system of channels. Simulated unsteady periodic flow modeled breaths. Consider the behavior of the particles along the trajectories. It is shown that, depending on the mass and diameter of the particles, they can be collected in a caustic on the channel walls, stop in a certain place or fly back. Of interest is the distribution of particle velocity in frequency. It turned out that by choosing a behavior of the velocity field of the carrier gas can affect the trajectory of individual particles including force them to fly back.

Keywords: Two-phase, mixing, separating, flow control

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Authors: E. Bruno, F. Lacarbonara, M. C. Placentino, D. Gramegna

Abstract:

Environmental decision making, particularly about hazardous waste management, is inherently exposed to a high potential conflict, principally because of the trade-off between sociopolitical, environmental, health and economic factors. The need to plan complex contexts has led to an increasing request for decision analytic techniques as support for the decision process. In this work, alternative systems of asbestos-containing waste management (ACW) in Puglia (Southern Italy) were explored by a multi-criteria decision analysis. In particular, through Analytic Hierarchy Process five alternatives management have been compared and ranked according to their performance and efficiency, taking into account environmental, health and socio-economic aspects. A separated valuation has been performed for different temporal scale. For short period results showed a narrow deviation between the disposal alternatives “mono-material landfill in public quarry" and “dedicate cells in existing landfill", with the best performance of the first one. While for long period “treatment plant to eliminate hazard from asbestos-containing waste" was prevalent, although high energy demand required to achieve the change of crystalline structure. A comparison with results from a participative approach in valuation process might be considered as future development of method application to ACW management.

Keywords: Multi-criteria decision analysis, Hazardous wastemanagement, Asbestos.

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Authors: Soyoon Bak, Sunyoung Bu, Philsu Kim

Abstract:

In this paper, a backward semi-Lagrangian scheme combined with the second-order backward difference formula is designed to calculate the numerical solutions of nonlinear advection-diffusion equations. The primary aims of this paper are to remove any iteration process and to get an efficient algorithm with the convergence order of accuracy 2 in time. In order to achieve these objects, we use the second-order central finite difference and the B-spline approximations of degree 2 and 3 in order to approximate the diffusion term and the spatial discretization, respectively. For the temporal discretization, the second order backward difference formula is applied. To calculate the numerical solution of the starting point of the characteristic curves, we use the error correction methodology developed by the authors recently. The proposed algorithm turns out to be completely iteration free, which resolves the main weakness of the conventional backward semi-Lagrangian method. Also, the adaptability of the proposed method is indicated by numerical simulations for Burgers’ equations. Throughout these numerical simulations, it is shown that the numerical results is in good agreement with the analytic solution and the present scheme offer better accuracy in comparison with other existing numerical schemes.

Keywords: Semi-Lagrangian method, Iteration free method, Nonlinear advection-diffusion equation.

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Authors: Y. Deng, X. Li, C. Kwan, B. Raj, R. Stern

Abstract:

The current speech interfaces in many military applications may be adequate for native speakers. However, the recognition rate drops quite a lot for non-native speakers (people with foreign accents). This is mainly because the nonnative speakers have large temporal and intra-phoneme variations when they pronounce the same words. This problem is also complicated by the presence of large environmental noise such as tank noise, helicopter noise, etc. In this paper, we proposed a novel continuous acoustic feature adaptation algorithm for on-line accent and environmental adaptation. Implemented by incremental singular value decomposition (SVD), the algorithm captures local acoustic variation and runs in real-time. This feature-based adaptation method is then integrated with conventional model-based maximum likelihood linear regression (MLLR) algorithm. Extensive experiments have been performed on the NATO non-native speech corpus with baseline acoustic model trained on native American English. The proposed feature-based adaptation algorithm improved the average recognition accuracy by 15%, while the MLLR model based adaptation achieved 11% improvement. The corresponding word error rate (WER) reduction was 25.8% and 2.73%, as compared to that without adaptation. The combined adaptation achieved overall recognition accuracy improvement of 29.5%, and WER reduction of 31.8%, as compared to that without adaptation.

Keywords: speaker adaptation; environment adaptation; robust speech recognition; SVD; non-native speech recognition

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Authors: Ashraf M. A. Ahmad

Abstract:

Delivering streaming video over wireless is an important component of many interactive multimedia applications running on personal wireless handset devices. Such personal devices have to be inexpensive, compact, and lightweight. But wireless channels have a high channel bit error rate and limited bandwidth. Delay variation of packets due to network congestion and the high bit error rate greatly degrades the quality of video at the handheld device. Therefore, mobile access to multimedia contents requires video transcoding functionality at the edge of the mobile network for interworking with heterogeneous networks and services. Therefore, to guarantee quality of service (QoS) delivered to the mobile user, a robust and efficient transcoding scheme should be deployed in mobile multimedia transporting network. Hence, this paper examines the challenges and limitations that the video transcoding schemes in mobile multimedia transporting network face. Then handheld resources, network conditions and content based mobile and wireless video transcoding is proposed to provide high QoS applications. Exceptional performance is demonstrated in the experiment results. These experiments were designed to verify and prove the robustness of the proposed approach. Extensive experiments have been conducted, and the results of various video clips with different bit rate and frame rate have been provided.

Keywords: Content, Object detection, Transcoding, Texture, Temporal, Video.

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Authors: Talal Alshammari, Nasser Alshammari, Mohamed Sedky, Chris Howard

Abstract:

With the widespread adoption of the Internet-connected devices, and with the prevalence of the Internet of Things (IoT) applications, there is an increased interest in machine learning techniques that can provide useful and interesting services in the smart home domain. The areas that machine learning techniques can help advance are varied and ever-evolving. Classifying smart home inhabitants’ Activities of Daily Living (ADLs), is one prominent example. The ability of machine learning technique to find meaningful spatio-temporal relations of high-dimensional data is an important requirement as well. This paper presents a comparative evaluation of state-of-the-art machine learning techniques to classify ADLs in the smart home domain. Forty-two synthetic datasets and two real-world datasets with multiple inhabitants are used to evaluate and compare the performance of the identified machine learning techniques. Our results show significant performance differences between the evaluated techniques. Such as AdaBoost, Cortical Learning Algorithm (CLA), Decision Trees, Hidden Markov Model (HMM), Multi-layer Perceptron (MLP), Structured Perceptron and Support Vector Machines (SVM). Overall, neural network based techniques have shown superiority over the other tested techniques.

Keywords: Activities of daily living, classification, internet of things, machine learning, smart home.

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Authors: A. Breda, C. Cruz

Abstract:

The Japanese art of origami provides a rich context for designing exploratory mathematical activities for children and young people. By folding a simple sheet of paper, fascinating and surprising planar and spatial configurations emerge. Equally surprising is the unfolding process, which also produces striking patterns. The procedure of folding, unfolding, and folding again allows the exploration of interesting geometric patterns. When adequately and systematically done, we may deduce some of the mathematical rules ruling origami. As the child/youth folds the sheet of paper repeatedly, he can physically observe how the forms he obtains are transformed and how they relate to the pattern of the corresponding unfolding, creating space for the understanding/discovery of mathematical principles regulating the folding-unfolding process. As part of a 2023 Summer Academy organized by a Portuguese university, a session entitled “Folding, Thinking and Generalizing” took place. 23 students attended the session, all enrolled in the 2nd cycle of Portuguese Basic Education and aged between 10 and 12 years old. The main focus of this session was to foster the development of critical cognitive and socio-emotional skills among these young learners, using origami. These skills included creativity, critical analysis, mathematical reasoning, collaboration, and communication. Employing a qualitative, descriptive, and interpretative analysis of data, collected during the session through field notes and students’ written productions, our findings reveal that structured origami-based activities not only promote student engagement with mathematical concepts in a playful and interactive but also facilitate the development of socio-emotional skills, which include collaboration and effective communication between participants. This research highlights the value of integrating origami into educational practices, highlighting its role in supporting comprehensive cognitive and emotional learning experiences.

Keywords: Active learning, hands-on activities, origami, creativity, critical thinking.

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Authors: Ahmad Sharif Ahmadi, Yoshitaka Kajita

Abstract:

With massive population expansion and fast economic development in last decade, urban land has increasingly expanded and formed high informal development territory in Kabul city. This paper investigates integrated urbanization trends in Kabul city since the formation of the basic structure of the present city using GIS and remote sensing. This study explores the spatial and temporal difference of urban land expansion and land use categories among different time intervals, 1964-1978 and 1978-2008 from 1964 to 2008 in Kabul city. Furthermore, the goal of this paper is to understand the extent of urban land expansion and the factors driving urban land expansion in Kabul city. Many factors like population expansion, the return of refugees from neighboring countries and significant economic growth of the city affected urban land expansion. Across all the study area urban land expansion rate, population expansion rate and economic growth rate have been compared to analyze the relationship of driving forces with urban land expansion. Based on urban land change data detected by interpreting land use maps, it was found that in the entire study area the urban territory has been expanded by 14 times between 1964 and 2008.

Keywords: GIS, Kabul city, land use, urban land expansion, urbanization.

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Authors: Maryam Memarian, Mahmood Naghizadeh

Abstract:

Deconstruction is an approach that is entirely incompatible with the traditional prevalent architecture. Considering the fact that this approach attempts to put architecture in sharp contrast with its opposite events and transpires with attending to the neglected and missing aspects of architecture and deconstructing its stable structures. It also recklessly proceeds beyond the existing frameworks and intends to create a different and more efficient prospect for space. The aim of deconstruction architecture is to satisfy both the prospective and retrospective visions as well as takes into account all tastes of the present in order to transcend time. Likewise, it ventures to fragment the facts and symbols of the past and extract new concepts from within their heart, which coincide with today’s circumstances. Since this approach is an attempt to surpass the limits of the prevalent architecture, it can be employed to design places in which creative events occur and imagination and ambition flourish. Thought-provoking artistic events can grow and mature in such places and be represented in the best way possible to all people. The concept of event proposed in the plan grows out of the interaction between space and creation. In addition to triggering surprise and high impressions, it is also considered as a bold journey into the suspended realms of the traditional conflicts in architecture such as architecture-landscape, interior-exterior, center-margin, product-process, and stability-instability. In this project, at first, through interpretive-historical research method and examining the inputs and data collection, recognition and organizing takes place. After evaluating the obtained data using deductive reasoning, the data is eventually interpreted. Given the fact that the research topic is in its infancy and there is not a similar case in Iran with limited number of corresponding instances across the world, the selected topic helps to shed lights on the unrevealed and neglected parts in architecture. Similarly, criticizing, investigating and comparing specific and highly prized cases in other countries with the project under study can serve as an introduction into this architecture style.

Keywords: Creativity, deconstruction, event.

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Authors: Al-Falahi Amir, Yusoff M. Z, Yusaf T

Abstract:

The aim of this paper is to develop a new two dimensional time accurate Euler solver for shock tube applications. The solver was developed to study the performance of a newly built short-duration hypersonic test facility at Universiti Tenaga Nasional “UNITEN" in Malaysia. The facility has been designed, built, and commissioned for different values of diaphragm pressure ratios in order to get wide range of Mach number. The developed solver uses second order accurate cell-vertex finite volume spatial discretization and forth order accurate Runge-Kutta temporal integration and it is designed to simulate the flow process for similar driver/driven gases (e.g. air-air as working fluids). The solver is validated against analytical solution and experimental measurements in the high speed flow test facility. Further investigations were made on the flow process inside the shock tube by using the solver. The shock wave motion, reflection and interaction were investigated and their influence on the performance of the shock tube was determined. The results provide very good estimates for both shock speed and shock pressure obtained after diaphragm rupture. Also detailed information on the gasdynamic processes over the full length of the facility is available. The agreements obtained have been reasonable.

Keywords: shock tunnel, shock tube, shock wave, CFD.

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