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This paper proposes a dynamical model for the gamification@learning and presents its simulation. Based on the theories of Game Design Features (GDF - cool features, fancy graphics, challenging puzzles, and an intriguing setting and story), Key Characteristics of a Learning Game (KCLG - Challenge, Curiosity, Fantasy and Control), a theory of educational environment design model (ARCS - attention, relevance, confidence and satisfaction), and the theoretical background of Gamification labeled as the MDA (Mechanics, dynamics, and aesthetics) framework, four primary factors such as curiosity, challenge, fantasy and control have been originated. By using these four primary factors, the dynamical model for Gamification was developed. In this paper an example for the model is considered and simulated. The example and simulation make the values and characteristics of the four primary factors meaningful. I posit that this dynamical model for the gamification can strengthen the ‘theoretical foundation’ of gamification as well as spread the idea of ‘the pure and right function of game’.

Aiming at the market shares of automatic mechanical transmission, the driving smoothness was studied. Based on the dynamical model of automatic mechanical transmission, the numerical model of automatic mechanical transmission had been established and a shifting strategy was analyzed. The result shows that the impact of automatic mechanical transmission on the condition of shifting fast can meet the national legislation.

In this paper an example for the dynamical model for gamification is considered and simulated. Based on the theories of Game Design Features (GDF - cool features, fancy graphics, challenging puzzles, and an intriguing setting and story), Key Characteristics of a Learning Game (KCLG - Challenge, Curiosity, Fantasy and Control), a theory of educational environment design model (ARCS - attention, relevance, confidence and satisfaction), and the theoretical background of Gamification labeled as the MDA (Mechanics, dynamics, and aesthetics) framework, four primary factors such as curiosity, challenge, fantasy and control have been originated. By using these four primary factors, the dynamical model for Gamification was developed and simulated. Furthermore the sensitivities of the four primary factors are considered for different individuals and simulations are represented. The examples and simulations make the values and characteristics of the four primary factors meaningful.

It was announced by Chinese government at the Copenhagen Conference that there would be 40-45% mitigation of the 2005 level intensity of carbon by 2020. Every industry in China is preparing to realize this national reduction target. A lot of work have been tried to achieve low-carbon development in different industries, but relatively little work has linked low-carbon development to municipal solid waste management(MSWM). This article focuses on how to develop low-carbon MSWM using a quantitative approach. Firstly, the MSWM system including some mutual influence factors is investigated and some historical data are given in support for the research of their quantitative relationship. Secondly, a differential dynamic system model with fuzzy coefficients is proposed to predict waste amount, disposal cost, energy consumption and carbon intensity. Finally, an application to Chengdu in southwestern China, as a representative of a developed city, is presented to show the trend of MSWM in a low-carbon economy and prove the effectiveness of the proposed model.

본 논문은 미국과 쿠바의 협상 과정과 국제적 행위자로서 교황의 중개 역할에 대한 이론적 분석을 시도하였다. 건설적 관여의 역동적 시스템 모델은 협상의 여건성숙이론을 바탕으로 협상과정에서 다양한 이해관계자의 동기를 역동적 측면에서 설명한다. 오랜 갈등을 겪으면서 쿠바와 미국은 정치적, 경제적, 외교적 비용 증가에 따른 ‘고통’이 커졌다. ‘탈출구’로서의 대안을 모색하려는 동기는 건설적 상호작용 방향으로 나아갔고, 국제환경의 변화는 그러한 동기에 대한 장애요인을 약화시켰다. 양국이 분쟁 지속의 ‘비용’보다 화해의 ‘미래이득’이 더 크다는 공동의 인식을 이룸으로써, 양국관계를 묘사하는 어트랙터 지형도 변화하기 시작했다. 하지만 50여 년간 축적된 불신이 하루아침에 해소되지는 않았고, 협상은 교착상태에 빠졌다. 이러한 난관에서 빠져나와 화해의 어트랙터로 양국 관계 시스템이 옮겨가는 과정에서 프란치스코 교황의 중개역할이 결정적이었다. 즉, 교황의 관여가 티핑 포인트 기능을 수행한 것이다. 이것이 가능했던 이유는 (1) 가톨릭교회와 쿠바와의 오랜 특수 관계, (2) 쇠퇴한 혁명정부에 대한 대중적 지지 확보를 위한 카스트로의 전략적 선택, (3) 오바마 행정부의 실리적 접근, (4) 프란치스코 교황의 출신 배경과 적극적 외교 정책 등의 요인들이 존재했기 때문이다.

This study analyzes Pope Francis’ mediation role in the US-Cuba rapprochement from the perspective of dynamic systems model of constructive engagement, which is a revised model of ripeness theory of negotiation. Over fifty years, Cuba and the United States have been in conflict. Due to the swift changes of international environment after the end of Cold War, they began to conceive that the future benefit of reconciliation would be bigger than the painful cost of maintaining hostile policies. Their common motives to seek a ‘way-out’ changed the attractor landscape representing the tendencies of their relationship system. Although an alternative attractor of constructive interaction between two countries made a series of secret negotiations started, their long-lasting distrust caused an impasse. Pope’s constructive engagement as a tipping point was decisive in reaching the agreement. The success of the Papal diplomacy was attributed to (1) the long-lasting special relationship between the Catholic Church and Cuba, (2) Castro’s strategic choice to gain popular support for the decrepit revolutionary government. (3) Obama administration’s practical approach, and (4) Pope Francis’ background of origin and active diplomacy.

The effect of toxicants on ecological systems is an important issue from mathematical and experimental points of view. Here we have studied dynamical model of a single-species population-toxicant system. Two cases are studied: constant exogeneous input of toxicant and rapidly fluctuating random exogeneous input of toxicant into the environment. The dynamical behaviour of the system is analyzed by using deterministic linearized technique, Lyapunov method and stochastic linearization on the assumption that exogeneous input of toxicant into the environment behaves like ‘Coloured noise’.

We propose a mathematical model which describes the frictional contact between a piezoelectric body and an electrically conductive foundation. The behavior of the material is described with a linearly electro-viscoelastic constitutive law with long term memory. The mechanical process is dynamic and the electrical conductivity coefficient depends on the total slip rate, the friction is modeled with Tresca's law which the friction bound depends on the total slip rate with taking into account the electrical conductivity of the foundation both. The main results of this paper concern the existence and uniqueness of the weak solution of the model; the proof is based on results for second order evolution variational inequalities with a time-dependent hemivariational inequality in Banach spaces.

In this paper we have considered a dynamical mathematical model of the sub-populations of potential smokers (non-smokers), smokers, smokers who temporarily quit smoking, smokers who permanently quit smoking and a class of smoking associated illness by introducing time dependent parameters and distributed time delay to acquire smoking habit. Here, we have established some sufficient conditions on the permanence and extinction of the smoking class in the community by using inequality analytical technique. We have introduced some new threshold values $R_0$ and $R^*$ and further obtained that the smoking class in the community will be permanent when $R_0$ > 1 and the smoking class in the community will be going to extinct when $R^*$ < 1. By Lyapunov functional method, we have also obtained some sufficient conditions for global asymptotic stability of this model. Computer simulations are carried out to explain the analytical findings. The aim of the analysis of this model is to identify the parameters of interest for further study, with a view to informing and assisting policy-maker in targeting prevention and treatment resources for maximum effectiveness.

Using two-dimensional numerical hydrodynamic simulations, we investigate the regulation of star ormation rates in turbulent, multiphase, galactic gaseous disks. Our simulation domain is xisymmetric, and local in the radial direction and global in the vertical direction. Our models nclude galactic rotation, vertical stratification, self-gravity, heating and cooling, and thermal onduction. Turbulence in our models is driven by momentum feedback from supernova events ccurring in localized dense regions formed by thermal and gravitational instabilities. Self-onsistent radiative heating, representing enhanced/reduced FUV photons from the star formation, s also taken into account. Evolution of our model disks is highly dynamic, but reaches a quasi-teady state. The disks are overall in effective hydrostatic equilibrium with the midplane thermal ressure set by the vertical gravity. The star formation rate is found to be proportional pproximately linearly to the midplane thermal pressure. These results are in good agreement with the predictions of a recent theory by Ostriker, McKee, and Leroy (2010) for the thermal/dynamic equilibrium model of star formation regulation.

In this paper we have constructed a mathematical model of alcohol abuse which consists of four compartments corresponding to four population classes, namely, moderate and occasional drinkers, heavy drinkers, drinkers in treatment and temporarily recovered class. Basic reproduction number $R_0$ has been determined and sensitivity analysis of $R_0$ indicates that ${\beta}1$ (the transmission coefficient from moderate and occasional drinker to heavy drinker) is the most useful parameter for preventing drinking habit. Stability analysis of the model is made using the basic reproduction number. The model is locally asymptotically stable at disease free or problem free equilibrium (DFE) $E_0$ when $R_0<1$. It is found that, when $R_0=1$, a backward bifurcation can occur and when $R_0>1$, the endemic equilibrium $E^*$ becomes stable. Further analysis gives the global asymptotic stability of DFE under some conditions. Our important analytical findings are illustrated through computer simulation. Epidemiological implications of our analytical findings are addressed critically.

The first part of the paper deals with a brief introduction of the plant-herbivore model system along with deterministic analysis of local stability and Hopf-bifurcations. The second part consists of stability analysis of the limit cycle arising from Hopf-bifurcation and uniqueness of limit cycle. The third part deals with the study of global stability of the model system under consideration.

The conversion of mechanical energy into electrical energy at nanoscale using piezoelectric nanowire arrays has been in detail shown by deflection of nanowires. Recently it has performed an analytical model, both at classical and at quantum level, for describing the most important quantities concerning transport phenomena; the model predicts interesting peculiarities, as high initial charge diffusion in nanodevices constituting by nanowires and permits also in particular to deduce interesting informations about the devices sensitivity, focusing on the correlation between sensitivity and high initial diffusivity of these materials at nanometric level.

This paper is concerned with a reaction-diffusion single species model with harvesting on n-dimensional isotropically growing domain. The model on growing domain is derived and the corresponding comparison principle is proved. The asymptotic behavior of the solution to the problem is obtained by using the method of upper and lower solutions. The results show that the growth of domain takes a positive effect on the asymptotic stability of positive steady state solution while it takes a negative effect on the asymptotic stability of the trivial solution, but the effect of the harvesting rate is opposite. The analytical findings are validated with the numerical simulations.

In this paper, we present a Krylov subspace based projection method for reduced-order modeling of large scale bilinear multi-input multi-output (MIMO) systems. The reduced-order bilinear system is constructed in such a way that it can match a desired number of moments of multi-variable transfer functions corresponding to the kernels of Volterra series representation of the original system. Numerical examples report the effectiveness of this method.

The point reactor dynamic model is based on the lumped parameter model and, unlike the traditional reactor kinetics model, takes into account the effects of the fuel and moderator temperature on the system reactivity. This model is a system of nonlinear and nonhomogeneous differential equations and is used in the transient analysis of an initially critical system subjected to any perturbation. In this study, transient analysis of the Th-fueled SMART reactor is performed by the point dynamics model. Initially, the reactor is kept critical using the reactivity control mechanisms such as control rods insertioın and soluble boron addition to the moderator. The required neutronic parameters such as precursors' parameters, neutron generation time, and reactivity coefficients are calculated using the Serpent 2 Monte Carlo code. The moderator average temperature and system pressure are used as two distinct thermodynamic properties to determine thermal-hydraulic parameters such as heat capacity, conductivity coefficient, convection coefficient, and fuel thermal resistance. For different reactivity insertion scenarios, MATLAB ODE45 suite is used to solve the point dynamic equations. The validity of the provided code is also verified either through comparison with the analytically solvable form of the point dynamic model or by analyzing the asymptotic equilibrium values of the considered parameters. Finally, it is seen that when an initially critical reactor operating at a certain power level undergoes a perturbation, after a short time the system becomes again critical and operates at an almost stable power level different from the pre-perturbation power level. This, in turn, implies that the calculated neutronic and thermal-hydraulic parameters are physically meaningful.

이 논문에서는 RNN (Recurrent Neural Networks)-LSTM (Long Short-Term Memory) 을 적용하여 Lorenz 시스템을 예측하는 자료 기반 인공지능 모델을 구축하고, 이 모델이 미분방정식을 차분화하여 해를 구하는 역학 모델을 대체할 수 있는지 가능성을 진단하였다. 구축된 자료기반 모델이 초기 조건의 작은 교란이 근본적으로 다른 결과를 만들어내는 Lorenz 시스템의 카오스적인 특성을 반영한다는 것과, 시스템의 안정적인 두 개의 닻을 중심으로 운동하면서 전이 과정을 반복하는 특성, "결정론적 불규칙 흐름"의 특성, 분기 현상을 모사한다는 것을 확인하였다. 또한, 적분 시간 간격을 조절함으로써 전산자원을 절감할 수 있는 자료기반 모델의 장점을 보였다. 향후 자료기반 모델의 정교화와 자료기반 모델을 위한 자료동화 기법의 연구를 통해 자료기반 인공지능 모델의 활용성을 확대할 수 있을 것으로 기대한다.

In this paper, we built a data-driven artificial intelligence model using RNN-LSTM (Recurrent Neural Networks-Long Short-Term Memory) to predict the Lorenz system, and examined the possibility of whether this model can replace chaotic dynamic models. We confirmed that the data-driven model reflects the chaotic nature of the Lorenz system, where a small error in the initial conditions produces fundamentally different results, and the system moves around two stable poles, repeating the transition process, the characteristic of "deterministic non-periodic flow", and simulates the bifurcation phenomenon. We also demonstrated the advantage of adjusting integration time intervals to reduce computational resources in data-driven models. Thus, we anticipate expanding the applicability of data-driven artificial intelligence models through future research on refining data-driven models and data assimilation techniques for data-driven models.

In this paper, we introduce the identification model of dynamic system using the neural networks, We propose two identification models. The output of the parallel identification model is a linear combination of its past values as well as those of the input. The series-parallel model is a linear combination of the past values in the input and output of the plant. To generate stable adaptive laws, we prove that the series-parallel model is found to be proferable.

This paper propose the systematic procedure of the fuzzy model based controller for the continuous nonlinear system. Fuzzy controller have been successfully applied to many uncertain and complex industrial plants. The design of the fuzzy controller mainly depends on the knowledge from the expert who are familiar with the plant by trial and error. Therefore we need more systematic approach to the design of the fuzzy controller. In this paper, we design fuzzy model based controller applied to the nonlinear system. Unlike the design procedures reported in[8] and[9], we use the nonlinear process directly in designing the controller. This controller has been successfully applied to an inverted pendulum.