Search results for: nonhomogeneous dynamic model

Authors: Khalid Yousuf Ahmed

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At the beginning of growth period, East Asian countries achieved impressive economic growth for the decades. They transformed from agricultural economy toward industrialization and contributed to dynamic structural transformation. The achievements were driven by government-led development policies that implemented effective innovation policy to boost technological capability of local firms. Recently, most Sub-Saharan African have been showing sustainable growth. Exceptionally, Ethiopia has been recording double-digit growth for a decade. Hence, Ethiopia has claimed to follow the footstep of East Asia development model. The study is going to examine whether Ethiopia can replicate innovation and economic growth model of East Asia by using Japan, Taiwan, South Korea and China as a case to illustrate their model of growth. This research will be based on empirical data gathering and extended theory of national innovation system and economic growth theory. Moreover, the methodology is based on Knowledge Assessment Methodology (KAM) and also employing cross-countries regression analysis. The results explained that there is a significant relationship between innovation indicators and economic growth in East Asian countries while the relationship is non-existing for Ethiopia except implementing similar policies and achieving similar growth trend. Therefore, Ethiopia needs to introduce inclusive policies that give priority to improving human capital and invest on the knowledge-based economy to replicate East Asian Model.

Keywords: economic growth, FDI, endogenous growth theory, East Asia model

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Authors: Anwar Ul Haque, Waqar Asrar, Erwin Sulaeman, Jaffar S. M. Ali

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Pressure distribution data of the standard airfoils is usually used for the calibration purposes in subsonic wind tunnels. Results of such experiments are quite old and obtained by using the model in the spanwise direction. In this manuscript, pressure distribution over NACA 4412 airfoil model was presented by placing the 3D model in the lateral direction. The model is made of metal with pressure ports distributed longitudinally as well as in the lateral direction. The pressure model was attached to the floor of the tunnel with the help of the base plate to give the specified angle of attack to the model. Before the start of the experiments, the pressure tubes of the respective ports of the 128 ports pressure scanner are checked for leakage, and the losses due to the length of the pipes were also incorporated in the results for the specified pressure range. Growth rate maps of the boundary layer thickness were also plotted. It was found that with the increase in the velocity, the dynamic pressure distribution was also increased for the alpha seep. Plots of pressure distribution so obtained were overlapped with those obtained by using XFLR software, a low fidelity tool. It was found that at moderate and high angles of attack, the distribution of the pressure coefficients obtained from the experiments is high when compared with the XFLR ® results obtained along with the span of the wing. This under-prediction by XFLR ® is more obvious on the windward than on the leeward side.

Keywords: subsonic flow, boundary layer, wind tunnel, pressure testing

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Authors: Zeyad Abdelmageid, Xianbin Wang

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Choosing the operational channel for a WLAN access point (AP) in WLAN networks has been a static channel assignment process initiated by the user during the deployment process of the AP, which fails to cope with the dynamic conditions of the assigned channel at the station side afterward. However, the dramatically growing number of Wi-Fi APs and stations operating in the unlicensed band has led to dynamic, distributed, and often severe interference. This highlights the urgent need for the AP to dynamically select the best overall channel of operation for the basic service set (BSS) by considering the distributed and changing channel conditions at all stations. Consequently, dynamic channel selection algorithms which consider feedback from the station side have been developed. Despite the significant performance improvement, existing channel selection algorithms suffer from very high feedback overhead. Feedback latency from the STAs, due to the high overhead, can cause the eventually selected channel to no longer be optimal for operation due to the dynamic sharing nature of the unlicensed band. This has inspired us to develop our own dynamic channel selection algorithm with reduced overhead through the proposed low-overhead, cluster-based station reporting mechanism. The main idea behind the cluster-based station reporting is the observation that STAs which are very close to each other tend to have very similar channel conditions. Instead of requesting each STA to report on every candidate channel while causing high overhead, the AP divides STAs into clusters then assigns each STA in each cluster one channel to report feedback on. With the proper design of the cluster based reporting, the AP does not lose any information about the channel conditions at the station side while reducing feedback overhead. The simulation results show equal performance and, at times, better performance with a fraction of the overhead. We believe that this algorithm has great potential in designing future dynamic channel selection algorithms with low overhead.

Keywords: channel assignment, Wi-Fi networks, clustering, DBSCAN, overhead

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Authors: Sahba Paktinat, Afshin Salajeghe, Mir Ali Seyyedi, Yousef Rastegari

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Service Oriented Architecture (SOA) allows modeling of dynamic interaction between incongruous providers, which enables governing the development of complex applications. However, implementation of SOA comes with some challenges, including its adaptability and robustness. Dynamism is inherent to the nature of service-based applications and of their running environment. These factors lead to necessity for dynamic adaptation. In this paper, we try to describe basics and main structure of SOA adaptation process with a conceptual view to this issue. In this survey, we will review the relevant adaptation approaches. This paper allows studying how different approaches deal with service oriented architecture adaptation life-cycle and provides basic guidelines for their analysis, evaluation and comparison.

Keywords: context-aware, dynamic adaptation, quality of services, service oriented architecture, service based application

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Authors: Hasibe Berfu Demi̇r, Şakir Esnaf

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In the past decade, extensive improvements have been done in electrical grid infrastructures. It is very important to make plans on supply, demand, transmission, distribution and pricing for the development of the electricity energy sector. Based on this perspective, in this study, Stackelberg game approach is proposed for demand participation management (DRM), which has become an important component in the smart grid to effectively reduce power generation costs and user bills. The purpose of this study is to examine electricity consumption from a dynamic pricing perspective. The results obtained were compared with the current situation and the results were interpreted.

Keywords: lectricity, stackelberg, smart grid, demand response managment, dynamic pricing

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Authors: Jawid Ahmad Baktash, Tadashi Shiroma, Tomokazu Nagata, Yuji Taniguchi, Morikazu Nakamura

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The goal of this paper is to explore the use of formal methods for Dynamic Routing, The purpose of network communication with dynamic routing is sending a massage from one node to others by using pacific protocols. In dynamic routing connections are possible based on protocols of Distance vector (Routing Information Protocol, Border Gateway protocol), Link State (Open Shortest Path First, Intermediate system Intermediate System), Hybrid (Enhanced Interior Gateway Routing Protocol). The responsibility for proper verification becomes crucial with Dynamic Routing. Formal methods can play an essential role in the Routing, development of Networks and testing of distributed systems. Event-B is a formal technique consists of describing rigorously the problem; introduce solutions or details in the refinement steps to obtain more concrete specification, and verifying that proposed solutions are correct. The system is modeled in terms of an abstract state space using variables with set theoretic types and the events that modify state variables. Event-B is a variant of B, was designed for developing distributed systems. In Event-B, the events consist of guarded actions occurring spontaneously rather than being invoked. The invariant state properties must be satisfied by the variables and maintained by the activation of the events.

Keywords: dynamic rout RIP, formal method, event-B, pro-B

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Authors: Ipek Kivanc, Demet Ozgur-Unluakin

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Over the past years, technological innovations and advancements have played an important role in the industrial world. Due to technological improvements, the degree of complexity of the systems has increased. Hence, all systems are getting more uncertain that emerges from increased complexity, resulting in more cost. It is challenging to cope with this situation. So, implementing efficient planning of maintenance activities in such systems are getting more essential. Partially Observable Markov Decision Processes (POMDPs) are powerful tools for stochastic sequential decision problems under uncertainty. Although maintenance optimization in a dynamic environment can be modeled as such a sequential decision problem, POMDPs are not widely used for tackling maintenance problems. However, they can be well-suited frameworks for obtaining optimal maintenance policies. In the classical representation of the POMDP framework, the system is denoted by a single node which has multiple states. The main drawback of this classical approach is that the state space grows exponentially with the number of state variables. On the other side, factored representation of POMDPs enables to simplify the complexity of the states by taking advantage of the factored structure already available in the nature of the problem. The main idea of factored POMDPs is that they can be compactly modeled through dynamic Bayesian networks (DBNs), which are graphical representations for stochastic processes, by exploiting the structure of this representation. This study aims to demonstrate how maintenance planning of dynamic systems can be modeled with factored POMDPs. An empirical maintenance planning problem of a dynamic system consisting of four partially observable components deteriorating in time is designed. To solve the empirical model, we resort to Symbolic Perseus solver which is one of the state-of-the-art factored POMDP solvers enabling approximate solutions. We generate some more predefined policies based on corrective or proactive maintenance strategies. We execute the policies on the empirical problem for many replications and compare their performances under various scenarios. The results show that the computed policies from the POMDP model are superior to the others. Acknowledgment: This work is supported by the Scientific and Technological Research Council of Turkey (TÜBİTAK) under grant no: 117M587.

Keywords: factored representation, maintenance, multi-component system, partially observable Markov decision processes

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Authors: Kawser Ahmed, K. Bousson, Milca F. Coelho

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4D flight trajectory optimization is one of the key ingredients to improve flight efficiency and to enhance the air traffic capacity in the current air traffic management (ATM). The present paper explores the iterative dynamic programming (IDP) as a potential numerical optimization method for 4D flight trajectory optimization. IDP is an iterative version of the Dynamic programming (DP) method. Due to the numerical framework, DP is very suitable to deal with nonlinear discrete dynamic systems. The 4D waypoint representation of the flight trajectory is similar to the discretization by a grid system; thus DP is a natural method to deal with the 4D flight trajectory optimization. However, the computational time and space complexity demanded by the DP is enormous due to the immense number of grid points required to find the optimum, which prevents the use of the DP in many practical high dimension problems. On the other hand, the IDP has shown potentials to deal successfully with high dimension optimal control problems even with a few numbers of grid points at each stage, which reduces the computational effort over the traditional DP approach. Although the IDP has been applied successfully in chemical engineering problems, IDP is yet to be validated in 4D flight trajectory optimization problems. In this paper, the IDP has been successfully used to generate minimum length 4D optimal trajectory avoiding any obstacle in its path, such as a no-fly zone or residential areas when flying in low altitude to reduce noise pollution.

Keywords: 4D waypoint navigation, iterative dynamic programming, obstacle avoidance, trajectory optimization

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Authors: Xupin Zhang, Maria Caterina Bramati, Enrest Fokoue

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Understanding the career placement of graduates from the university is crucial for both the qualities of education and ultimate satisfaction of students. In this research, we adapt the capabilities of dynamic Bayesian networks to characterize and predict students’ job placement using data from various universities. We also provide elements of the estimation of the indicator (score) of the strength of the network. The research focuses on overall findings as well as specific student groups including international and STEM students and their insight on the career path and what changes need to be made. The derived Bayesian network has the potential to be used as a tool for simulating the career path for students and ultimately helps universities in both academic advising and career counseling.

Keywords: dynamic bayesian networks, indicator estimation, job placement, social networks

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Authors: James Moran, Anusarn Permsuwan

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This paper compares oscillations in the dry friction coefficient in different journal bearings. Measurements are made of the average and standard deviation in the coefficient of friction as a function of sliding velocity. The standard deviation of the friction coefficient changed dramatically with sliding velocity. The magnitude and frequency of the oscillations were a function of the velocity. A numerical model was developed for the frictional oscillations. There was good agreement between the model and results. Five different materials were used as the sliding surfaces in the experiments, Aluminum, Bronze, Mild Steel, Stainless Steel, and Nylon.

Keywords: Coulomb friction, dynamic friction, non-lubricated bearings, frictional oscillations

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Authors: Iffat Ara Ebu, Fahmida Islam, Mohammad Abdus Shahid Rafi, Mahfuzur Rahman, Umar Iqbal, John Ball

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The application of multi-sensor fusion for enhanced distance estimation accuracy in dynamic environments is crucial for advanced driver assistance systems (ADAS) and autonomous vehicles. Limitations of single sensors such as cameras or radar in adverse conditions motivate the use of combined camera and radar data to improve reliability, adaptability, and object recognition. A multi-sensor fusion approach using an extended Kalman filter (EKF) is proposed to combine sensor measurements with a dynamic system model, achieving robust and accurate distance estimation. The research utilizes the Mississippi State University Autonomous Vehicular Simulator (MAVS) to create a controlled environment for data collection. Data analysis is performed using MATLAB. Qualitative (visualization of fused data vs ground truth) and quantitative metrics (RMSE, MAE) are employed for performance assessment. Initial results with simulated data demonstrate accurate distance estimation compared to individual sensors. The optimal sensor measurement noise variance and plant noise variance parameters within the EKF are identified, and the algorithm is validated with real-world data from a Chevrolet Blazer. In summary, this research demonstrates that multi-sensor fusion with an EKF significantly improves distance estimation accuracy in dynamic environments. This is supported by comprehensive evaluation metrics, with validation transitioning from simulated to real-world data, paving the way for safer and more reliable autonomous vehicle control.

Keywords: sensor fusion, EKF, MATLAB, MAVS, autonomous vehicle, ADAS

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Authors: Xinyuan Y. Song, Kai Kang

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Joint models for analyzing longitudinal and survival data are widely used to investigate the relationship between a failure time process and time-variant predictors. A common assumption in conventional joint models in the survival analysis literature is that all predictors are observable. However, this assumption may not always be supported because unobservable traits, namely, latent variables, which are indirectly observable and should be measured through multiple observed variables, are commonly encountered in the medical, behavioral, and financial research settings. In this study, a joint modeling approach to deal with this feature is proposed. The proposed model comprises three parts. The first part is a dynamic factor analysis model for characterizing latent variables through multiple observed indicators over time. The second part is a random coefficient trajectory model for describing the individual trajectories of latent variables. The third part is a proportional hazard model for examining the effects of time-invariant predictors and the longitudinal trajectories of time-variant latent risk factors on hazards of interest. A Bayesian approach coupled with a Markov chain Monte Carlo algorithm to perform statistical inference. An application of the proposed joint model to a study on the Alzheimer's disease neuroimaging Initiative is presented.

Keywords: Bayesian analysis, joint model, longitudinal data, time-to-event data

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Authors: Ben Mansour Mouin, Elloumi Abdelkarim

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We will discuss the problem of routing a fleet of different vehicles from a central depot to different types of infrastructure-defaults with dynamic maintenance requests, modified time windows, and control of default maintained. For this reason, we propose a modified metaheuristicto to solve our mathematical model. SVRDP-CMTW is a variant VRP of an optimal vehicle plan that facilitates the maintenance task of different types of infrastructure-defaults. This task will be monitored after the maintenance, based on its priorities, the degree of danger associated with each default, and the neighborhood at the black-spots. We will present, in this paper, a multidimensional genetic algorithm “MGA” by detailing its characteristics, proposed mechanisms, and roles in our work. The coding of this algorithm represents the necessary parameters that characterize each infrastructure-default with the objective of minimizing a combination of cost, distance and maintenance times while satisfying the priority levels of the most urgent defaults. The developed algorithm will allow the dynamic integration of newly detected defaults at the execution time. This result will be displayed in our programmed interactive system at the routing time. This multidimensional genetic algorithm replaces N genetic algorithm to solve P different type problems of infrastructure defaults (instead of N algorithm for P problem we can solve in one multidimensional algorithm simultaneously who can solve all these problemsatonce).

Keywords: mathematical model, VRP, multidimensional genetic algorithm, metaheuristics

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Authors: Daleesha M. Viswanathan, Sumam Mary Idicula

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Dynamic hand gestures are an intrinsic component in sign language communication. Extracting spatial temporal features of the hand gesture trajectory plays an important role in a dynamic gesture recognition system. Finding a discrete feature descriptor for the motion trajectory based on the orientation feature is the main concern of this paper. Kalman filter algorithm and Hidden Markov Models (HMM) models are incorporated with this recognition system for hand trajectory tracking and for spatial temporal classification, respectively.

Keywords: orientation features, discrete feature vector, HMM., Indian sign language

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Authors: Ahmed Guerine, Ali El Hafidi, Bruno Martin, Philippe Leclaire

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In this paper, we propose a method for the dynamic response of multi-storey structures with uncertain-but-bounded parameters. The effectiveness of the proposed method is demonstrated by a numerical example of three-storey structures. This equation is integrated numerically using Newmark’s method. The numerical results are obtained by the proposed method. The simulation accounting the interval analysis method results are compared with a probabilistic approach results. The interval analysis method provides a mean curve that is between an upper and lower bound obtained from the probabilistic approach.

Keywords: multi-storey structure, dynamic response, interval analysis method, random parameters

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Authors: Maryam Azimi, Amin Banitalebi-Dehkordi, Yuanyuan Dong, Mahsa T. Pourazad, Panos Nasiopoulos

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While there exists a wide variety of Low Dynamic Range (LDR) quality metrics, only a limited number of metrics are designed specifically for the High Dynamic Range (HDR) content. With the introduction of HDR video compression standardization effort by international standardization bodies, the need for an efficient video quality metric for HDR applications has become more pronounced. The objective of this study is to compare the performance of the existing full-reference LDR and HDR video quality metrics on HDR content and identify the most effective one for HDR applications. To this end, a new HDR video data set is created, which consists of representative indoor and outdoor video sequences with different brightness, motion levels and different representing types of distortions. The quality of each distorted video in this data set is evaluated both subjectively and objectively. The correlation between the subjective and objective results confirm that VIF quality metric outperforms all to their tested metrics in the presence of the tested types of distortions.

Keywords: HDR, dynamic range, LDR, subjective evaluation, video compression, HEVC, video quality metrics

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Authors: Misagh Faezipour

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This paper explores the effects of screen time on children from a systems engineering perspective. We reviewed literature from several related works on the effects of screen time on children to explore all factors and interrelationships that would impact children that are subjected to using long screen times. Factors such as kids' age, parent attitudes, parent screen time influence, amount of time kids spend with technology, psychosocial and physical health outcomes, reduced mental imagery, problem-solving and adaptive thinking skills, obesity, unhealthy diet, depressive symptoms, health problems, disruption in sleep behavior, decrease in physical activities, problematic relationship with mothers, language, social, emotional delays, are examples of some factors that could be either a cause or effect of screen time. A systems engineering perspective is used to explore all the factors and factor relationships that were discovered through literature. A causal model is used to illustrate a graphical representation of these factors and their relationships. Through the causal model, the factors with the highest impacts can be realized. Future work would be to develop a system dynamics model to view the dynamic behavior of the relationships and observe the impact of changes in different factors in the model. The different changes on the input of the model, such as a healthier diet or obesity rate, would depict the effect of the screen time in the model and portray the effect on the children’s health and other factors that are important, which also works as a decision support tool.

Keywords: children, causal model, screen time, systems engineering, system dynamics

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Authors: Soumia Merat, Lynda Djerbal, Ramdane Bahar, Mohammed Amin Benbouras

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Along with shear wave, many soil parameters are associated with the standard penetration test (SPT) as a dynamic in situ experiment. Both SPT-N data and geophysical data do not often exist in the same area. Statistical analysis of correlation between these parameters is an alternate method to estimate Vₛ conveniently and without additional investigations or data acquisition. Shear wave velocity is a basic engineering tool required to define dynamic properties of soils. In many instances, engineers opt for empirical correlations between shear wave velocity (Vₛ) and reliable static field test data like standard penetration test (SPT) N value, CPT (Cone Penetration Test) values, etc., to estimate shear wave velocity or dynamic soil parameters. The relation between Vs and SPT- N values of Algiers area is predicted using the collected data, and it is also compared with the previously suggested formulas of Vₛ determination by measuring Root Mean Square Error (RMSE) of each model. Algiers area is situated in high seismic zone (Zone III [RPA 2003: réglement parasismique algerien]), therefore the study is important for this region. The principal aim of this paper is to compare the field measurements of Down-hole test and the empirical models to show which one of these proposed formulas are applicable to predict and deduce shear wave velocity values.

Keywords: empirical models, RMSE, shear wave velocity, standard penetration test

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Authors: Mohamed Moustafa Mahmoud Sedky

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In line start permanent magnet synchronous motor, eccentricity is a common fault that can make it necessary to remove the motor from the production line. However, because the motor may be inaccessible, diagnosing the fault is not easy. This paper presents an FEM that identifies different models, static eccentricity, dynamic eccentricity, and mixed eccentricity, at no load and full load. The method overcomes the difficulty of applying FEMs to transient behavior. It simulates motor speed, torque and flux density distribution along the air gap for SE, DE, and ME. This paper represents the various effects of different eccentricities types on the transient performance.

Keywords: line start permanent magnet, synchronous machine, static eccentricity, dynamic eccentricity, mixed eccentricity

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Authors: Chiung-Hui Chen

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The Internet of Things (IoT) was designed for widespread convenience. With the smart tag and the sensing network, a large quantity of dynamic information is immediately presented in the IoT. Through the internal communication and interaction, meaningful objects provide real-time services for users. Therefore, the service with appropriate decision-making has become an essential issue. Based on the science of human behavior, this study employed the environment model to record the time sequences and locations of different behaviors and adopted the probability module of the hierarchical Hidden Markov Model for the inference. The statistical analysis was conducted to achieve the following objectives: First, define user behaviors and predict the user behavior routes with the environment model to analyze user purposes. Second, construct the hierarchical Hidden Markov Model according to the logic framework, and establish the sequential intensity among behaviors to get acquainted with the use and activity fabric of the intelligent environment. Third, establish the intensity of the relation between the probability of objects’ being used and the objects. The indicator can describe the possible limitations of the mechanism. As the process is recorded in the information of the system created in this study, these data can be reused to adjust the procedure of intelligent design services.

Keywords: behavior, big data, hierarchical hidden Markov model, intelligent object

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Authors: O. Hinrichs, H. Franz, G. Reiter

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Electron guns have a key function in a series of thermal processes, like EB (electron beam) melting, evaporation or welding. These techniques need a high-intensity continuous electron beam that defocuses itself due to high space charge forces. A proper beam transport throughout the magnetic focusing system can be ensured by a space charge compensation via residual gas ions. The different pressure stages in the EB gun cause various degrees of compensation. A numerical model was installed to simulate realistic charge distributions within the beam by using CST-Particle Studio code. We will present current status of beam dynamic simulations. This contribution will focus on the creation of space charge ions and their influence on beam and gun components. Furthermore, the beam transport in the gun will be shown for different beam parameters. The electron source allows to produce beams with currents of 3 A to 15 A and energies of 40 keV to 45 keV.

Keywords: beam dynamic simulation, space charge compensation, thermionic electron source, EB melting, EB thermal processing

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Authors: Yao Song, Danni Cheng, Jianjun Ren

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Objectives: We aimed to explore the prognostic effects of absolute values and dynamic changes of common hematological indices on oropharynx squamous cell carcinoma (OPSCC) patients treated with radiation. Methods and materials: The absolute values of white blood cell (WBC), absolute neutrophil count (ANC), absolute lymphocyte count (ALC), hemoglobin (Hb), platelet (Plt), albumin (Alb), neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) at baseline (within 45 days before radiation), 1-, 3-, 6- and 12-months after the start of radiotherapy were retrospectively collected. Locally-estimated smoothing scatterplots were used to describe the smooth trajectory of each index. A mixed-effect model with a random slope was fitted to describe the changing rate and trend of indices over time. Cox proportional hazard analysis was conducted to assess the correlation between hematological indices and treatment outcomes. Results: Of the enrolled 85 OPSCC patients, inflammatory indices, such as WBC and ALC, dropped rapidly during acute treatment and gradually recovered, while NLR and PLR increased at first three months and subsequently declined within 3-12 months. Higher absolute value or increasing trend of nutritional indices (Alb and Hb) was associated with better prognosis (all p<0.05). In contrast, patients with higher absolute value or upward trend of inflammatory indices (WBC, ANC, Plt, PLR and NLR) had worse survival (all p<0.05). Conclusions: The absolute values and dynamic changes of hematological indices were valuable prognostic factors for OPSCC patients who underwent radiotherapy.

Keywords: hematological indices, oropharyngeal cancer, radiotherapy, NLR, PLR

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Authors: Zahra Abdolkarimi, Naser Zourikalatehsamad,

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Up to 40 years ago, after recognition of epilepsy, it was generally believed that these attacks occurred randomly and suddenly. However, thanks to the advance of mathematics and engineering, such attacks can be predicted within a few minutes or hours. In this way, various algorithms for long-term prediction of the time and frequency of the first attack are presented. In this paper, by considering the nonlinear nature of brain signals and dynamic recorded brain signals, ANFIS model is presented to predict the brain signals, since according to physiologic structure of the onset of attacks, more complex neural structures can better model the signal during attacks. Contribution of this work is the co-evolution algorithm for optimization of ANFIS network parameters. Our objective is to predict brain signals based on time series obtained from brain signals of the people suffering from epilepsy using ANFIS. Results reveal that compared to other methods, this method has less sensitivity to uncertainties such as presence of noise and interruption in recorded signals of the brain as well as more accuracy. Long-term prediction capacity of the model illustrates the usage of planted systems for warning medication and preventing brain signals.

Keywords: co-evolution algorithms, brain signals, time series, neural networks, ANFIS model, physiologic structure, time prediction, epilepsy suffering, illustrates model

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Authors: Nattabhorn Leamcharaskul

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This study aims to examine determining factors of the dynamics of poverty in Thailand by using panel data of 3,567 households in 2007-2017. Four techniques of estimation are employed to analyze the situation of poverty across households and time periods: the multinomial logit model, the sequential logit model, the quantile regression model, and the difference in difference model. Households are categorized based on their experiences into 5 groups, namely chronically poor, falling into poverty, re-entering into poverty, exiting from poverty and never poor households. Estimation results emphasize the effects of demographic and socioeconomic factors as well as unexpected events on the economic status of a household. It is found that remittances have positive impact on household’s economic status in that they are likely to lower the probability of falling into poverty or trapping in poverty while they tend to increase the probability of exiting from poverty. In addition, not only receiving a secondary source of household income can raise the probability of being a never poor household, but it also significantly increases household income per capita of the chronically poor and falling into poverty households. Public work programs are recommended as an important tool to relieve household financial burden and uncertainty and thus consequently increase a chance for households to escape from poverty.

Keywords: difference in difference, dynamic, multinomial logit model, panel data, poverty, quantile regression, remittance, sequential logit model, Thailand, transfer

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Authors: Opeyemi A. Oyewo, Seshibe Makgato

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This paper presents the synthesis, characterization, and application of pelletized chitosan immobilized sawdust cellulose nanocrystals (PCCN) in a fixed-bed column for the continuous adsorption of methyl blue (MB) from water. The product was characterized using FT-IR, XRD, and SEM analysis. Microstructural examination revealed that the pellets are porous and spherical. XRD examination revealed phases that can be attributed to the presence of chitosan in PCCN. The effects of starting concentration, bed depth, and flow rate on synthetic water were explored. To identify MB breakthrough behaviour, performance indices such as bed volume, adsorbent exhaustion rate, and service time were investigated. Furthermore, the breakthrough data were incorporated into both the Thomas and Bohart-Adams models. The Thomas model was suitable for describing MB breakthrough curves. However, more research with diverse water matrices may be required to assess the resilience of PCCN.

Keywords: adsorption, dynamic, methyl blue, pelletization

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Authors: Natarajan Hema, Tamilarasan Karunakaran

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Technology is remodeling the process of teaching and learning. An inflection point is faced where technological interventions are rewiring learning process in formal classrooms. Employment depends on dynamic learning capability. Transforming the functionalities of teaching-learning-assessment through innovation is needed to modify the roles of teacher to enabler and learner to the dynamic learner. This makeover is vital for English language teaching where English is acquired as a skill, exercised as ability and get stabilized as a competence. This reshaping could be achieved through providing autonomy to participants of learning. This paper explores parameters and components aiding such a transformation. The differentiated responsibilities and other critical learning support systems are projected as viable options. New age teaching practices are studied for feasibilities to aid transformation and being put forth an inter-operable teaching-learning system for a learner-centric ELT classrooms. LOTUS model developed by the authors is also studied for its inclusiveness to promote skill acquisition.

Keywords: ELT methodology, communicative competence, skill acquisition , new age teaching

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Authors: Mohammad Reza Ameri, Ali Massumi, Mohammad Haghbin

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Non-linear static analysis, commonly referred to as pushover analysis, is a powerful tool for assessing the seismic response of structures. A suitable lateral load pattern for pushover analysis can bring the results of this simple, quick and low-cost analysis close to the realistic results of nonlinear dynamic analyses. In this research, four samples of 10- and 15 story (two- and four-bay) reinforced concrete frames were studied. The lateral load distribution patterns recommended in FEMA 273/356 guidelines were applied to the sample models in order to perform pushover analyses. The results were then compared to the results obtained from several nonlinear incremental dynamic analyses for a range of earthquakes. Finally, a lateral load distribution pattern was proposed for pushover analysis of medium-rise reinforced concrete buildings based on the results of nonlinear static and dynamic analyses.

Keywords: lateral load pattern, nonlinear static analysis, incremental dynamic analysis, medium-rise reinforced concrete frames, performance based design

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Authors: Ajish Sreedharan

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Security in transmission and storage of digital images has its importance in today’s image communications and confidential video conferencing. Due to the increasing use of images in industrial process, it is essential to protect the confidential image data from unauthorized access. Advanced Encryption Standard (AES) is a well known block cipher that has several advantages in data encryption. However, it is not suitable for real-time applications. This paper presents modifications to the Advanced Encryption Standard to reflect a high level security and better image encryption. The modifications are done by adjusting the ShiftRow Transformation and using On Dynamic chaotic S-BOX. In AES the Substitute bytes, Shift row and Mix columns by themselves would provide no security because they do not use the key. In Dynamic chaotic S-BOX Based AES the Substitute bytes provide security because the S-Box is constructed from the key. Experimental results verify and prove that the proposed modification to image cryptosystem is highly secure from the cryptographic viewpoint. The results also prove that with a comparison to original AES encryption algorithm the modified algorithm gives better encryption results in terms of security against statistical attacks.

Keywords: advanced encryption standard (AES), on dynamic chaotic S-BOX, image encryption, security analysis, ShiftRow transformation

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Authors: Kim Bower

Abstract:

Evaluating and researching motivation in language learning is a complex and multi-faceted activity. Various models for investigating learner motivation have been proposed in the literature, but no one model supplies a complex and coherent model for investigating a range of motivational characteristics. Here, such a methodological framework, which includes exemplification of sources of evidence and potential methods of investigation, is proposed. The process model for the investigation of motivation within language learning settings proposed is based on a complex dynamic systems perspective that takes account of cognition and affects. It focuses on three overarching aspects of motivation: the learning environment, learner engagement and learner identities. Within these categories subsets are defined: the learning environment incorporates teacher, course and group specific aspects of motivation; learner engagement addresses the principal characteristics of learners' perceived value of activities, their attitudes towards language learning, their perceptions of their learning and engagement in learning tasks; and within learner identities, principal characteristics of self-concept and mastery of the language are explored. Exemplifications of potential sources of evidence in the model reflect the multiple influences within and between learner and environmental factors and the possible changes in both that may emerge over time. The model was initially developed as a framework for investigating different models of Content and Language Integrated Learning (CLIL) in contrasting contexts in secondary schools in England. The study, from which examples are drawn to exemplify the model, aimed to address the following three research questions: (1) in what ways does CLIL impact on learner motivation? (2) what are the main elements of CLIL that enhance motivation? and (3) to what extent might these be transferable to other contexts? This new model has been tried and tested in three locations in England and reported as case studies. Following an initial visit to each institution to discuss the qualitative research, instruments were developed according to the proposed model. A questionnaire was drawn up and completed by one group prior to a 3-day data collection visit to each institution, during which interviews were held with academic leaders, the head of the department, the CLIL teacher(s), and two learner focus groups of six-eight learners. Interviews were recorded and transcribed verbatim. 2-4 naturalistic observations of lessons were undertaken in each setting, as appropriate to the context, to provide colour and thereby a richer picture. Findings were subjected to an interpretive analysis by the themes derived from the process model and are reported elsewhere. The model proved to be an effective and coherent framework for planning the research, instrument design, data collection and interpretive analysis of data in these three contrasting settings, in which different models of language learning were in place. It is hoped that the proposed model, reported here together with exemplification and commentary, will enable teachers and researchers in a wide range of language learning contexts to investigate learner motivation in a systematic and in-depth manner.

Keywords: investigate, language-learning, learner motivation model, dynamic systems perspective

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Authors: Nurullah Buker, Ezgi Karagoz, Yesim Salik Sengul, Sevay Alsen Guney, Gokhan Yoyler, Aylin Ozbek

Abstract:

Attention Deficit Hyperactivity Disorder (ADHD) is one of the most common neurodevelopmental disorders with heterogeneous clinical features such as inattention, hyperactivity, and impulsivity. Many different types of exercise interventions were employed for children with ADHD. However, previous studies have usually examined the effects of non-specific exercise programs or short-term effects of exercise. The aim of this study is to investigate the effect of the Neurocognitive Exercise Program (NEP), which is a structured exercise program derived from Life Kinetik, and a relatively new for children with ADHD, on symptoms, attention, and dynamic balance in medication-naïve children with ADHD. Fourteen medication-naive children (7-12 years) with ADHD were included in the intervention group. NEP was performed once a week for ten weeks. The intervention group also performed a structured home exercise program for another six days, for ten weeks. The children in the intervention group were assessed at baseline, in the third month, in the sixth month, and in the twelfth month regarding ADHD-related symptoms, attention, and dynamic balance. Fifteen age-matched typically developing children were assessed once for establishing normative values. Hyperactivity-Impulsivity score and dynamic balance were found to improve after NEP in the ADHD group in the 3rd month (p<0.05). In addition, these results were similar for both groups after NEP and at the end of the 12th month (p>0.05). The NEP may provide beneficial effects on hyperactivity-impulsivity, oppositional defiant, and dynamic balance in children with ADHD, and the improvements may be maintained in the long term.

Keywords: ADHD, attention problems, dynamic balance, neurocognitive exercise

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