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The motivation of women to study STEM-related careers does not increase over the years. This article presents an exploratory review to identify factors, current initiatives and models that favor and hinder adolescents and women from studying and staying in careers linked to these vocational training areas. Among the most outstanding results is the visualization of a pattern as a role model and the influence of parents.

The trend of tourism 4.0 has become one of the issues in tourism and implemented in many ways. Malang city, Kota Batu and Kabupaten Malang areas such as Kota Batu and Kabupaten Malang are well-known as Malang Raya. Tourist attraction can be found in Malang raya. Since there are so many tourist attraction places and scattered across Malang Raya, tourist needs to find the best path in order to visit as many places as possible. This research project is conducted to find and apply the algorithm of Dijkstra to give recommendation of shortest path to tourist interesting places. There are four considerations in this research including first attraction place that will be visited by the tourist, distance between attraction places, types of the attraction places and the nearest attraction places from the first attraction place. Methodology in this research consist of several steps, including identification of required parameters, analysis of recommendation systems, data gathering, data validation and analysis, system development based on Dijkstra Algorithm, implementation and evaluation of the recommendation system. The proposed recommendation system able to recommend shortest path in three to four seconds. It is hoped that this project able to provide a ready – to – apply recommendation system for tourist attraction places in Indonesian’s cities, especially in Malang City.

This paper mainly establishes a multilevel fuzzy evaluation model, and takes Wuhu City as an example to evaluate the talent attraction level. Based on this, combined with the cluster model, the five cities in Wuhu City and Anhui Province are clustered and analyzed to compare the talent attraction. The advantages and disadvantages of all aspects of the level, while short-term forecast of the trend of the future talent attraction level of Wuhu City. The results show that Wuhu City has a good level of talent attraction. It is in the middle and upper reaches of the city compared with Hefei and other cities. Under the government’s policy of actively implementing innovative industry reform, the level of talent attraction will show a growing trend in the future.

Technology has changed the way we live and interact through the rapid adoption of global smartphones and smart devices. This new technology has changed the various ways in which industries including the tourism industry works to remain beneficial and innovative. However, current travel planning applications has the same functionalities and outdated travel information that affects tourists who may have difficulty in planning their tourist vacations. To provide users with innovative way to schedule their trip and get basic attraction information in Malaysia, this work will propose a design of an Android-based application with an added innovation on top of current solutions that incorporate the use of a recommender system and Augmented Reality (AR). This work would address the issues of current applications which include low information maintenance and real time update, it will then offer useful recommendations based on user preferences for attraction sites.

Opportunistic network is a type of self-organizing network that uses node movements to bring about encounter opportunities for communication, and characterized by sparse node connections and frequent network topology changes. The prediction of node link probability is the key to study the topological changes of opportunistic network. We propose a node-attraction-based link prediction method of opportunistic network (OLPA), which analyzes node properties and the connection relationship of node pairs to obtain the attraction between nodes, and introduces a time decay factor to weight the evolution sequence of attraction to obtain the probability of future connections between nodes. By comparing with LSTM, E-LSTM-D, GCN-GAN link prediction models on multiple real opportunistic network data sets, the propose link prediction method we mentioned has good accuracy.

Graph clustering is to partition a large graph into several subgraphs according to the topological structure and node characteristics of the graph. It can discover the community structures of complex networks and thus help researchers better understand the characteristics and structures of complex networks. This paper first proposes the concepts of direct attraction force and indirect attraction force. Then, it defines a new structural similarity, attraction-force similarity. Finally, the AF-Cluster algorithm is proposed based on the attraction-force similarity. Through the experimental analysis, we can conclude that the AF-Cluster algorithm is effective for clustering graph compared with other contrast algorithms.

Cuckoo search (CS) algorithm has been proved to be an effective method in solving numerical optimization problems. Nevertheless, with regard to Levy flight, each individual is attracted by the best solution found so far in the entire population, which may lead to premature convergence. Motivated by this observation, a new cuckoo search with neighborhood attraction (NACS) is proposed. In NACS, the neighborhood attraction scheme based on ring topology is firstly designed, where the best solution in a predefined neighborhood is employed to guide individual evolution. Then, to further enhance the exploration ability, the neighborhood attraction scheme and Levy flight are combined to generate potential candidate solutions. Moreover, the step size is adaptively regulated according to the degree of individual evolution. To validate the effectiveness of the presented algorithm, 25 extensively used benchmark test problems with different dimensions are employed. Experimental results reveal that the presented method is a competitive optimizer compared with other algorithms.

Under the distributed impulsive control with actuator saturation, the local leader-following consensus problem of linear multi-agent systems with fixed topology is considered in this paper. Based on Lyapunov stability theory, average impulsive interval method and contradiction approach, a developed sufficient condition is obtained. In addition, optimization problem constrained by local leader-following consensus criterion is established in the form of linear matrix inequalities, and solved them by YALMIP to obtain the largest domain of attraction. Finally, a numerical example is proposed to demonstrate the feasibility of the obtained results.

This paper investigates the emergence of high-level behaviors, i.e., support localization, in climbing plants upon the interaction of low-level behaviors, i.e., tropisms, activated by environmental stimuli. Light plays antagonistically in phototropic –attraction to light– and skototropic –attraction to shadow– responses in plant shoots. Here, we hypothesize that climbing plants must find a trade-off between shade avoidance and attraction for support localization. A plant-inspired robotic platform with light-sensing capability is used as a robo-physical system to study the possible role of this environmental stimulus in climbing plants' behavior. Out of this analysis, we propose a biomimetic control that can ultimately be integrated into plant-inspired growing robots for improving their ability in environment exploration and mapping.

Recent works in graph visualization attempt to reduce the runtime of repulsion force computation of force-directed algorithms using sampling, however they fail to reduce the runtime for attraction force computation to sublinear in the number of edges.We present new sublinear-time algorithms for the attraction force computation of force-directed algorithms and integrate them with sublinear-time repulsion force computation.Extensive experiments show that our algorithms, operated as part of a fully sublinear-time force computation framework, compute graph layouts on average 80% faster than existing linear-time force computation algorithm, with surprisingly significantly better quality metrics on edge crossing and shape-based metrics.

This paper presents an estimation method for the magnetic attractive force between a crawler robot and a moving surface. The robot has crawlers which have magnets to climb a wall. However, there is a problem that the robot may fall when the magnetic attraction force becomes weak. To solve this problem, we employ a disturbance observer in the control system of the crawler drive motor. The experimental results confirmed that the proposed method can detect the risk of falling due to the decreasing the magnetic attraction force between the crawler robot and the moving surface.

In this paper, we propose an approach for exploring tourists’ behavior based on the extracted dataset from geotagged photographs. We transform the dataset to a suitable format type and apply k-mean clustering to cluster the different tourists’ behavior. After that, the tourists’ behavior of each cluster, especially behavior regards interesting attraction, has been analyzed by statistical test. Entropy also has been employed to measure the diversity of place in each attraction category for presenting each clusters’ characteristics. The results have been demonstrated that k-mean clustering presents the tourists’ behavior into eight groups and each of the tourists prefers conspicuously different attractions.

Over the past years, the development of big data have received great attention, and data growth continues to increase. Deep learning technologies have shown good performance in many practical applications. In this work, we proposed a new deep learning model with low complexity to deal with global attraction classification problem. Due to limited datasets in outdoor scenes, firstly, we constructed a new large-scale global attraction dataset (GAD), containing more than 380k images for the world’s 250 famous attractions. Then we propose a new attraction classification method, where a residual dense module is integrated into a low-complexity convolutional neural network model. Our proposed method is demonstrated to show better performance than several state-of-the-art deep convolutional neural network models on our constructed GAD dataset.

In this talk, existence of unipolar pulses, methods of their generation and interaction with quantum objects are revised. The effective influence of unipolar pulses in comparison with bipolar pulses on quantum systems is shown. The question of mutual attraction and repulsion of unipolar impulses is also considered.

Due to the increasing size of the datasets, instance selection techniques have been applied for reducing the computational resources involved in data mining and machine learning tasks. In this paper, we propose an attraction-based approach for selecting instances. The algorithm adopts the notion of attraction for selecting the most representative instances of each class. The resulting approach allows the user to define how many representative instances should be selected. Our method was evaluated in a classification task considering 14 well-known datasets. The performance of the proposed algorithm was compared to the performances of 8 prototype selection algorithms in terms of accuracy and reduction rate. The experimental results show that, in general, the proposed algorithm provides a good trade-off between reduction rate and accuracy with a low time complexity.

The information propagated on the social network is affected by the intimate degree of the relationship among individuals. There are different relationships between individuals. In this study, a network model, including explicit (intimate) edge and implicit (non-intimate) edge, is constructed. Based on this network model, an information propagation mechanism driven by the attraction and drag is proposed, the explicit attraction and implicit attraction generated by the infected individuals to ignorant individuals during the process of the information propagation is studied, so, the explicit drag and implicit drag generated by the recovered individuals to ignorant individuals researched. The simulation experiment found that the major factor of information propagation is the explicit attraction and drag, and the implicit attraction and drag have few effects on information propagation. Based on the above results, a rumor propagation restrained strategy is designed, which reduces the explicit attraction and increases explicit drag of ignorant person. The experimental results clearly revealed the effectiveness of the proposed strategy and its important practical significance for realistic society.

The main result of the paper is a new converse theorem for finite-time Lyapunov functions. We show the existence of a finite-time Lyapunov function for an autonomous continuous-time nonlinear dynamical system if the origin of the system is asymptotically stable. Our proof extends the recent results in finite-time Lyapunov function theory by providing an alternative converse proof for the existence of finite-time Lyapunov functions. In particular, we show that given asymptotic stability of the origin, the linearized dynamics satisfy global finite-time Lyapunov function conditions hence proving the converse theorem. Using our results, we present a consolidated theory for using and constructing Lyapunov functions to certify system stability properties. We also propose a constructive algorithm to efficiently compute non-conservative estimates of the domain of attraction for nonlinear dynamical systems.

Using the Amusement Park’s VR Attraction (VR games emulates amusement park ride), pilot studies of 4 subjects were evaluated eardrum temperature and heart rate variability, assuming that temperature of the vestibular sensory receptor change when VR motion sickness occurs. The types of attractions are roller coasters, rotating swings, and rotating carts. As a result, when VR motion sickness occurred, increase of eardrum temperature was observed. The tendency of the increase of the eardrum temperature and the change of the autonomic nervous activity also differed by the difference of the VR attraction.

International audience; This paper studies the problem of estimating the region of attraction of linear discrete-time systems with asymmetric input saturation. Using a Piecewise Quadratic Lyapunov function, we propose conditions for the local stability of the equilibrium. The asymmetric bounds of the saturation are considered in these conditions. Estimates of the region of attraction, possibly asymmetric with respect to the origin, are computed by solving convex optimization problems. Numerical results illustrate the effectiveness of the proposed method.

Through recent research combining the geometricdesingularization or blow-up method and classicalcontrol tools, it has been possible to locally stabilize nonhyperbolicpoints of singularly perturbed control systems.In this letter we propose a simple method to enlarge theregion of attraction of a non-hyperbolic point in the aforementionedsetting by expanding the geometric analysisaround the singularity. In this way, we can synthesizeimproved controllers that stabilize non-hyperbolic pointswithin a large domain of attraction. Our theoretical resultsare showcased in a couple of numerical examples

This paper examines the effects of introducing controller saturation on the estimated domain of attraction of a droop-controlled inverter connected to an infinite bus. Previous studies have explored the effect of operating conditions and parameters on the inverter's domain of attraction. However, in these studies controller saturation was ignored. This paper accomplishes the above by introducing a saturation function on the controller output. A Takagi-Sugeno Multimodel Linear Matrix Inequality was used to show the effect of the saturation function on the estimated domain of attraction. Simulation results were used to illustrate the results of the estimated domains. Results highlight the importance of including the controller saturation to improve the accuracy of the estimated domain of attraction. Simplified models may be able to correctly estimate the stable domains of many saturated system states.

Paper presents the regions of attraction of two hidden attractors occurring in the dimensionless model of the Chua’s circuit. For a long time it was thought that there is no attractor in the system; later, only one, so-called hidden attractor was discovered. In fact there are up to two hidden attractors close together. Therefore, not only the regions of attraction of two hidden attractors are shown in the paper, but it is pointed out the need to choose the right size and location of the test cuboid for detection the hidden attractor. At the same time, it is pointed out how the accuracy of Matlab solution can lead to (un)detection of two hidden attractors.

In the research of the problem of maximizing the influence of social networks, a propagation model based on the attraction between nodes is proposed for the calculation of node information propagation influence. In this study, we model the node properties of the network and use it to define the direct attraction and cumulative attraction, in which we consider the change and attenuation of the node influence. Also, we discuss the gravitational features of the nodes to establish a propagation method based on the independent cascade model. The probability of the node attraction is designed for activation between nodes. Finally, experiments on actual data sets show that the influence under this method is better than other methods.

Objectives: Taking the teaching in "Rehabilitation Nursing" carried out in our school as an example, the data research and qualitative analysis were performed to discuss the influence of the factors, such as push time, the number of title characters, media richness and subject content, on the effect of medical teaching based on WeChat platform. Methods: Choosing four variables: push time, title characters number, media richness and subject content, the concept model of influencing factors of attraction degree of medical teaching articles is constructed, and the correlation analysis is carried out by logging in to the background of WeChat management to obtain the relevant data. Results: The reading rate was 91.22% on the first day, 131.62% on the seventh day, and the simple correlation coefficient between the reading rate and the number of title characters was -0.234. When the topic content is a basic skill, the probability of correlation coefficient test between reading rate and media richness is 0.039, and the one-way ANOVA p value of subject content and reading rate is 0.026. Conclusions: The closer the class time is, the higher the reading rate of the article is. The reading rate of pushing articles in advance is greatly influenced by the content of the articles. There is a negative correlation between the number of characters in the title and the reading rate of the article, and it is a weak correlation, the influence of which is not significant. The media richness has a weak influence on the reading rate, and the content of the article has a greater influence on the reading rate. The students are more concerned about the content that may be discussed in the classroom and prefer to read enlightening original articles.

The article contains a description of the phenomenon of electroadhesion, the mechanism of its working and formation, as well as application possibilities. The paper also presents the concept of a research system based on a plate (pad) used to generate electroadhesive force. Experimental studies of the influence of temperature, pressure and humidity on different components depending on the material, grammage and weight are described.

We propose a method to estimate the region of attraction of a nonlinear ODE based only on measurements of the trajectory - implying that the nonlinear vector field need not be known a priori. This method is based on using trajectory data to determine values of a form of converse Lyapunov function at a finite number of points in the state-space. Least absolute deviations is then used to fit this data to a Sum-of-Squares polynomial whose level sets then become estimates for the region of attraction. This learned Lyapunov function can then be used to predict whether newly generated initial conditions lie in the region of attraction. Extensive numerical testing is used to show that the method correctly predicts whether a new initial condition is within the region of attraction of the nonlinear ODE on over 95% of a generated set of test data.

Impulsive control is an alternative method for enlarging the region of attraction of nonlinear underactuated systems. The goal of this paper is to propose a method based on impulsive control to enlarge the region of attraction and meanwhile, minimize the consumed control energy. A performance index based on the consumed control energy is defined. Then, minimizing this performance index along with the use of impulsive manifold method enlarge the region of attraction with minimum consumption of control energy. The efficiency of the presented method is shown through a simulation.

This Research-Work-in-Progress presents the development of an e-learning tool that facilitates the integration of science, technology, engineering, and mathematics (STEM) into non-STEM lesson plans. The present effort adds features to promote attraction to STEM. To increase the rate of attracting students to STEM, the researchers are investigating the strategic use of e-learning. The e-learning tool is being designed to be widely accessible online and easily integrated with most K-12 curricula. The tool focuses on enabling students to actively explore the dependencies of STEM-related models without needing to understand the underlying math and science, which is the usual barrier. The researchers previously developed a beta test tool framework for researchers and educators to upload integrated STEM lessons to a shared community of users (K-12 students and teachers). Uploaded lesson materials include a narrative, a representative image, searchable keywords, and a parameterized STEM model. Users can explore various outcomes by dialing-in various input values. This effort advances the prior work by integrating features that are likely to increase attraction to STEM. These features are based on dispelling misconceptions to increase mindfulness and offers guidelines for developing lessons that balance cognitive load and ease. To measure attraction, pre- and post-surveys and statistical analysis will be facilitated through the tool.

This article focuses on the numerical estimation of the Region of Attraction of systems with polynomial vector field. The presented approach, based on a recent theoretical work on positively invariant sets, computes the inner Estimates of the Region of Attraction by means of Sum of Squares techniques. This allows the set containment conditions defining the region to be enforced at the expense of requiring iterative schemes since the ensuing optimization features bilinearities in the decision variables. The main contribution consists of two novel algorithms aimed at addressing some of the shortcomings typically associated with the adoption of iterative schemes. The results confirm the advantages of the proposed approaches, particularly as the size of the system increases.

Culture, amongst other individual and social factors, plays a crucial role in human-human interactions. If robots should become a part of our society, they should be able to act in culture-specific manners as well. In this paper, we showcase the implementation of a cultural dichotomy, namely individualism vs. collectivism, in a social robots' conversation. Presenting these conversations to human observers from Germany and Japan, we investigate whether the implemented differences are recognized as such, and whether stereotypical culture-specific behaviours that correspond to the observers' cultural background is preferred. Results suggest that the manipulations in behaviour had the intended effect, but are not reflected in personal preferences.

Tourism sector plays an important role in ensuring that tourist attractions are well maintained and taken care of. Facilities such as trash bins, toilets and accessibility to the attraction area are also of importance so that tourists or locals are comfortable and at the same time ensure that the area are properly taken care of with the provided facilities. Nowadays you will rarely see a person without their smart phones and electronic gadgets brought together everywhere they go. They also like to share with friends and family members on what they are currently up to by text or photos shared through social media. Social Media such as Twitter, Facebook and Instagram have been used widely throughout the world. In this research, tweets data from Twitter collected in Sabah, Malaysia have been used to analyze and see its pattern in discovering new tourist attractions. These geographically enabled tweets were retrieved and analyzed to see the current attracted area and to determine potentially new attraction spots. Results in this case study demonstrated encouraging results in revealing new potential tourism spots by examining its intensity and outliers done in spatial analysis using geographic information system from the collected Twitter data. Tourism sector or city council can further develop the targeted area and better facilitated it.

Using principles of the qualitative theory of dynamic systems for enterprise management is discussed in this paper. The types of fixed points for the projections of the phase trajectory characterizing the activity of the enterprise are determined on the phase planes. The regions of attraction of the projections of the phase trajectories on the phase planes are determined. Based on obtained areas of attraction, decision templates for decision-makers in the scope of housing and communal services can be formed.

Current practice for flight stability analysis relies heavily on linear analysis and nonlinear, high-fidelity simulations. In the paper, the method of region of attraction analysis based on Sum Of Square (SOS) theory is proposed and applied on nonlinear system to estimate its stability. The polynomial model of aircraft is deduced from the nonlinear dynamic model, and then the stable flight region is calculated. Simulation results show that the aircraft can resume stable flight while its initial condition is in the region of attraction. The methodology provides a new way to research the stability and control of the nonlinear flight dynamic system. In addition, it has practical significance for guaranteeing the flight safety.

For a nonlinear system that can be represented as an aggregate of interacting linear subsystems, the problem of finding an estimate of the attraction domain of an equilibrium state is posed. The estimate is sought as a Cartesian product of invariant ellipsoids of the subsystems composing the system. The proposed method relies on results of absolute stability theory and reduces construction of the estimate to solving an LMI system.

In the War-Game, the enemy's location is the key information for decision-making, but it's hard to be completely known. And the lack of current location information is one of the typical problems in incomplete-information decision. This paper proposes a pheromone-based model and relevant method for enemy's location estimation in an army tactics War-Game system3. In this paper, the key decision-making factors for moving a unit to a position are modeled as 8 kinds of pheromone; and the unit's intention is modeled as an 8-deimension vector, which represents the attracting or repelling degree for each pheromone. The join effects of all pheromone is taken as the attraction of each location. The location with the most attraction is estimated as the most possible result. The experimental results on the dataset of first national War-Game match show the proposed algorithm is feasible and practical: the top 3 estimation for the enemy who has historical observation is more than 70% accuracy. Moreover, the estimation with one step offset is over 90% accuracy, which is always can be tolerated in War-Game.

In this paper, characteristics of water with the hydrophobic surfaces has been studied. According to the present scenario, when water deals with any surface then adhesive force acts between that surface and water. If adhesive force is strong then, water is absorbed by the surface but if adhesive force is weak then water cannot be absorbed by the surface and these types of surfaces are called hydrophobic surfaces. It has been observed that when some water drops fall on a hydrophobic surface and if the surface is upside down then some droplets fall down but few of them remain stick to the surface for a long time. Many explanations have been given in this regard but due to weak adhesive force, all the explanations seem to be incomplete as weak adhesive force may not result in the stickiness of the water droplet with the surface for a long time. Here, it has been analyzed that along with the adhesive force, a special type of cohesive force also acting there. Thus, due to the presence of adhesive force and this minor cohesive force, water drop remain stick to the hydrophobic surface. Without this special cohesive force, water droplets either slide or fall down from the hydrophobic surface.

The underrepresentation of women along the entire computer science (CS) pipeline has been an intractable problem. The relatively high proportion of women attending “coding boot camps”—35%, as compared to 14% in CS university programs—would suggest that CS is of interest in the postsecondary female population. Yet little is known about the profile of women attending these camps and the type of expertise they are learning in the setting. This qualitative work attempts to address this gap by investigating the backgrounds of nine women in two boot camp settings. The research focuses on what they are learning in each environment and how these skills align with the routine to adaptive expertise continuum. Findings from this study may indicate ways in which women may be recruited into public postsecondary institutions to study or major in CS.

In this paper, we propose an iteration method to compute inner-approximations of the domains of attraction for discrete-time switched systems with arbitrary switching. Starting from an initial estimated domain of attraction, which can be obtained by previous methods in the literatures, we firstly present a theoretical framework for obtaining a larger one via iteratively computing common Lyapunov-like functions. Successively, the theoretical framework is under-approximatively realized by using sums of squares programming, associated with a coordinate-wise iteration idea. Further, we propose an alternative method to obtain an initial estimated domain of attraction. Finally, two examples with comparisons are illustrated to show the advantages of our method.

The main purpose of this paper is to present methods for the approximation of the robust domain of attraction (RDA). We consider polynomial systems where the uncertainty is given by a polynomial mapping of an interval into the uncertainties. Using Lyapunovs stability theory as a basis we develop methods to compute in a constructive way based on Bezout matrices and the theorem of Ehlich and Zeller an approximation to RDA. We illustrate the effectiveness of the method with three examples.

In this paper, we propose a mixed reality system consisting of a binocular optical see-through head-mounted display(OST-HMD) and a depth sensor. Based on the proposed system, participants perform manipulation tasks to experience the direct physics-inspired interaction mode. Moreover, we design an active selection rule for accurate detailed manipulation. The result indicates that although direct physics-inspired interaction mode is not sufficiently efficient, it shows an advantage regarding the humanization and attraction.

The study on the electronic virtual community (eVCs) had been rapidly grown for many decades. The sources of social media become important for the firm's leverage interaction among the users. Despite the formation for knowledge exploitation on the contexts of eVCs still unscreened. To address this issue, we draw attraction mechanism to investigate the factor that's influence users intention for knowledge exploitation. We are conceptualizing attraction (i.e., desire for self-presentation and desire for improving online relationship) as the key is driven intention knowledge exploitation, interpersonal relationship (i.e., relationship compatibility and relationship of receptiveness). Proposed model supported by 258 participants who have been active using social media (e.g. Facebook, Amazon). The study shows that Intention knowledge exploitation (KEI) influenced by both desire for self-presentation(DFS)and desire for improving the online relationship (DFI). In addition, DFS and DFI have partially and direct mediating impact between relationship compatibility (RC), relationship receptiveness (RR) and intention for knowledge exploitation. Implications of these results are discussed.

Trajectory reversing is a method commonly used for estimating the region of attraction of stabilized equilibria. Using a discrete set of points obtained by trajectory reversing, this paper presents an algorithm for estimation and mathematical representation of the region of attraction using convex hulls. Several two-dimensional examples are presented to illustrate the usefulness of the algorithm. The method provides larger estimates compared to that obtained by existing algorithms but its main advantage lies in its applicability to higher-order systems. The mathematical representation of the region of attraction is useful in applying the Impulse Manifold Method, which was developed for stabilization of equilibria of underacuated systems from configurations lying outside their region of attraction. The region of attraction of the pendubot upright equilibrium is estimated to demonstrate the applicability of our algorithm to higher-order systems and illustrate the usefulness of the Impulse Manifold Method through simulations.

This paper presents an algorithm to enlarge the estimate of the Region of Attraction of stable equilibria of underactuated systems. To achieve this, we use a combination of the Sum of Squares (SOS) method and the Impulse Manifold Method (IMM). Initially, the SOS method is used to optimize the control input u(x) in order to obtain an enlarged Region of Attraction. The IMM is then applied on enlarged Region of Attraction obtained using SOS to further enlarge it. The IMM is implemented using high gain feedback and to demonstrate the efficacy of our algorithm, we present simulation results where an initial configuration of an acrobot lying outside the true region of attraction is stabilized.