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A natural approach to enhance portfolio diversification is to rely on factor-risk parity, which yields the portfolio whose risk is equally spread among a set of uncorrelated factors. The standard choice is to take the variance as risk measure, and the principal components (PCs) of asset returns as factors. Although PCs are unique and useful for dimension reduction, they are an arbitrary choice: any rotation of the PCs results in uncorrelated factors. This is problematic because we demonstrate that any portfolio is a factor-variance-parity portfolio for some rotation of the PCs. More importantly, choosing the PCs does not account for the higher moments of asset returns. To overcome these issues, we propose using the independent components (ICs) as factors, which are the rotation of the PCs that are maximally independent, and care about higher moments of asset returns. We demonstrate that using the IC-variance-parity portfolio helps to reduce the return kurtosis. We also show how to exploit the near independence of the ICs to parsimoniously estimate the factor-risk-parity portfolio based on value at risk. Finally, we empirically demonstrate that portfolios based on ICs outperform those based on PCs, and several state-of-the-art benchmarks.

Principal component analysis (PCA) is often used for analyzing data in the most diverse areas. In this work, we report an integrated approach to several theoretical and practical aspects of PCA. We start by providing, in an intuitive and accessible manner, the basic principles underlying PCA and its applications. Next, we present a systematic, though no exclusive, survey of some representative works illustrating the potential of PCA applications to a wide range of areas. An experimental investigation of the ability of PCA for variance explanation and dimensionality reduction is also developed, which confirms the efficacy of PCA and also shows that standardizing or not the original data can have important effects on the obtained results. Overall, we believe the several covered issues can assist researchers from the most diverse areas in using and interpreting PCA.

Для проверки гипотезы о независимости критериев в пакете NIST для 10000 отрезков двоичных последовательностей вычислялось число $\nu$ критериев, отклонявших гипотезу о том, что это отрезок равновероятной последовательности Бернулли. Для независимых критериев с одной и той же вероятностью ошибки число $\nu$ должно иметь биномиальное распределение. Оказалось, что совокупности из 14 и из 162 критериев пакета NIST не удовлетворяют этому условию, но 11 критериев из 14 удовлетворяют. Показано также, что некоторые последовательности, состоящие из чередующихся отрезков двух линейных рекуррент, не отклоняются критериями пакета NIST.

Polycystic ovary syndrome (PCOS) is a condition that affects about 15% of women of reproductive age and is correlated with infertility, insulin resistance, and obesity. The etiology of PCOS is multifactorial and genetic, endocrine, and metabolic causes are involved. : New evidence suggests a link between microorganisms residing in the digestive tracts of humans and the development of PCOS. Moreover, an imbalance in the gut microbial community could be a possible factor for the onset of insulin resistance and obesity. Hyperandrogenism, a key feature of PCOS, could also play a critical role in shaping the microbiome community. : Probiotics could modify the gut microbiota and serve as a potential treatment for PCOS. Here we disclose the association between PCOS and intestinal microbiota and the possible role of probiotics as a new treatment approach.

Most students learn in different ways and have different strengths and challenges. Turkish students suffer from some kinds of difficulty in learning chemistry taught in English, whether in school or university.The language of instruction can affect aspects of a student’s ability to learn. In this study, the difficulties that Turkish students face in studying chemistry in English are evaluated through a survey of students’ opinions at the Department of Nutrition in the University of Gelisim. The results showed that a 52.6% of students suffer from learning difficulties in the English language, which was reflected in their participation in discussions during the lecture, so a large percentage of them (48.6%) resorted to taking notes during the lecture in Turkish and a large proportion of them (45.6%) also believed that the situation would be better if English terms were used alongside Turkish in textbooks. The study claims there is a possibilityof improving students’ level in the English language thus improving students’ abilities to comprehend chemistry through the applicability of various teaching methods. The study draws heavily on both the Communicative and Natural Approach to deal with communication difficulties in chemistry classes.

The second language can be defined as any other language which is learned or acquired after their first language or their mother tongue. Learning or acquiring a second language can be a difficult task for anybody that wishes to speak or write in a language other than their first language. Teachers should have the basic knowledge of second language acquisition theories to provide a comprehensive teaching and learning environment to students. One of the most applied and well-accepted theories is Stephen’s Krashen’s theory of second language acquisition. The present study was carried out as an observation on students to address the importance of Krashen’s Monitor Model and the Natural Approach in the stages of second language development to ensure effective teaching of the second language. The findings show that the cause of the input factor should be taken into consideration when teaching a second language/foreign language. The findings also indicated that cooperative learning can be a good method for students to get comprehensible input from their classmates.

Climatic changes affect the natural and human socio-economic system. In addition to mitigation and nature conservation, climate change adaptation (CCA) plays an essential role in strategies on climate change. The urge for CCA has been recognised by experts and leaders for decades, although actions so far are lagging behind, implying a gap between policy development and implementation. Understanding policy processes and the functioning of institutions is therefore essential. Currently, CCA policy processes lack significantly in the implementation stages or focus unilaterally on water management, encouraging a status quo mode. Such an attachment to the status quo is known as a ‘lock-in’.Focusing on the field of nature conservation and enhancing biodiversity in the ‘Geuldal’ area in the Netherlands, this research concentrates on revealing potential lock-ins in climate change adaptation policies. It aims to sharpen our understanding of lock-in mechanisms, to explain them, and to additionally formulates recommendations for future policy designs.A theoretical and empirical cross-disciplinary research is conducted, using qualitative mixed methodologies: semi-structured expert interviews, desk study and field observations, to evaluate three specific types of lock-in mechanisms regarding institutions, infrastructure & technology, and human behaviour.The research results identify local lock-in mechanisms within CCA policy development, as well as a current lack of CCA implementation. Until recently, policies essentially focused on infrastructural and technological measures in water management and additionally ignoring CCA on heat and drought. Lock-ins are determined specifically on the basis of performance on spatial planning (infrastructure), governance and human behaviour (institutions). This research aims to provide insight in lock-in mechanisms that lead to a status quo in CCA implementation. The review of the research results shows that:1. an impressive number of lock-in mechanisms has been reported from experts’ points of view;2. lock-in mechanisms are not adequately defined or recognised in practice;3. the most frequently reported lock-in mechanisms relate to the institutional domain (governance and human behaviour) and spatial planning (infrastructure).The main findings of this research endorse total system approaches (food chain, water systems, energy transition, etc.), while focusing on the use of natural systems (both aquatic and terrestrial), expelling the exclusive use of technologies in water management. Based on land use, we should divide between a focus on rural areas and urban areas and address crucial actors specifically, i.e., agriculture (rural areas) and civilians (urban areas). Additionally, all this asks for good communication, adequate budgets, human capacity, facilitating expert engagement, and access to knowledge. These facts represent complexity in policy development and implementation. A transformation of thinking and acting (different mindset) in society is needed to realise a sustainable adaptive system to climatic changes and to enhance biodiversity. To prevent lock-ins it is essential to concentrate on institutions and human behaviour and additionally meeting space to implement CCA in practise.

Emotion plays a crucial role in gratifying users’ needs during their experience of movies and TV series, and may be underutilized as a framework for exploring video content and analysis. In this paper, we present EmotionMap, a novel way of presenting emotion for daily users in 2D geography, fusing spatio-temporal information with emotional data. The interface is composed of novel visualization elements interconnected to facilitate video content exploration, understanding, and searching. EmotionMap allows understanding of the overall emotion at a glance while also giving a rapid understanding of the details. Firstly, we develop EmotionDisc which is an effective tool for collecting audiences’ emotion based on emotion representation models. We collect audience and character emotional data, and then integrate the metaphor of a map to visualize video content and emotion in a hierarchical structure. EmotionMap combines sketch interaction, providing a natural approach for users’ active exploration. The novelty and the effectiveness of EmotionMap have been demonstrated by the user study and experts’ feedback.

Many physical processes in nature exhibit complex dynamics that result from a combination of multiscale, nonlinear, non-local, and memory effects. Recent experimental measurements conducted in a variety of physical domains have shown that, at the macroscale level, these effects typically result in significant deviations from the behavior predicted by classical models. Notably, the underlying dynamics was often shown to be of non-integer order and possibly better captured by fractional-order models. Fractional operators are intrinsically multiscale; thus, they provide a natural approach to account for non-local and memory effects. In this study, we present the possible application of variable-order (VO) and distributed-order (DO) fractional operators to a few classes of nonlinear lumped parameter models that have great practical relevance in mechanics and dynamics. More specifically, we present a methodology to define VO and DO fractional operators that are capable of capturing various physical transitions characteristic of contact dynamics, nonlinear reversible systems, hysteretic systems, and nonlinear damped oscillator systems. Despite using simplified lumped parameters models to illustrate the application of VO and DO operators to mechanics, we show numerical evidence of their unique modeling capabilities as well as their connection to more complex systems at the continuum scale. Further, for a selected problem involving distributed nonlinear damping, we provide approximate analytical solutions that are helpful to better understand the underlying dynamics and to quantify the accuracy of our numerical models.

This paper proposes an engineering-oriented framework that casts the problem of learning as an automatic control problem, and that can ultimately be used to design education activities that autonomously adapt to individual students’ abilities, prerequisites, learning goals and other restrictions. The framework leverages on quantitative descriptions of knowledge flows within university programs in terms of Knowledge Components Matrices (KCMs) and Knowledge Flow Graphs (KFGs), that serve as the basis for developing the aforementioned automated approach to personalized education. Essentially, the manuscript proposes to: 1) combine these descriptions with results from exams and assessments to statistically estimate the learning status of a student; 2) combine these descriptions with data-driven approaches to derive models of how knowledge ladders logically and in time; 3) use these two ingredients to automatically design suitable and personalized study activities for a student, given his/her current knowledge status and desired learning outcome. We describe all steps (modelling of the knowledge flows, estimating the current learning status, and derivation of suitable learning activities to close the loop) with formal and control-oriented notation. The paper serves thus the purpose of showing how methods from the field of system theory and control engineering are naturally useful for the implementation of quantitative-based personalized education.

Статья характеризует дедуктивный (традиционный) и индуктивный (естественный) подходы к преподаванию иностранных языков, выделяются их преимущества и недостатки. Так отмечается, что полученные при традиционном подходе знания тяжело научиться применять на практике, а использование естественного подхода практически не возможно в образовательном учреждении. Авторы подчеркивают, что выбор подхода зависит от цели и направленности обучения, а для минимизации недостатков целесообразно комбинировать эти подходы в учебном процессе. По мнению авторов наиболее удачным вариантом такой комбинации является неподготовленное устное высказывание, в частности дебаты. В статье приводятся примеры использования такой формы работы на практике., The article characterizes deductive (traditional) and inductive (natural) approaches to teaching foreign languages while highlighting their advantages and disadvantages. It is noted that learning how to apply the knowledge obtained with the traditional approach in practice presents difficulty, while the use of a natural approach is practically impossible in an educational institution. The authors emphasize that the choice of approach depends on the purpose and orientation of training, and in order to minimize disadvantages, it is advisable to combine these approaches during the educational process. According to the authors, the most successful variant of such a combination is an unprepared oral statement, particularly, a debate. The article provides examples of using this form of activity in practice., Международный научно-исследовательский журнал, Выпуск 3 (117) 2022, Pages 96-99

Creating a domain model, even for classical, domain-independent planning, is a notoriously hard knowledge-engineering task. A natural approach to solve this problem is to learn a domain model from observations. However, model learning approaches frequently do not provide safety guarantees: the learned model may assume actions are applicable when they are not, and may incorrectly capture actions' effects. This may result in generating plans that will fail when executed. In some domains such failures are not acceptable, due to the cost of failure or inability to replan online after failure. In such settings, all learning must be done offline, based on some observations collected, e.g., by some other agents or a human. Through this learning, the task is to generate a plan that is guaranteed to be successful. This is called the model-free planning problem. Prior work proposed an algorithm for solving the model-free planning problem in classical planning. However, they were limited to learning grounded domains, and thus they could not scale. We generalize this prior work and propose the first safe model-free planning algorithm for lifted domains. We prove the correctness of our approach, and provide a statistical analysis showing that the number of trajectories needed to solve future problems with high probability is linear in the potential size of the domain model. We also present experiments on twelve IPC domains showing that our approach is able to learn the real action model in all cases with at most two trajectories.

Federated Learning (FL) is a promising distributed learning paradigm and has gained recent attention from both academia and industry. One challenge in FL is that when local data across different devices are not independent and identically distributed (non-IID), models trained using FL generally have degraded performance. To address the problem, one natural approach is clustering: clients with similar data distributions are grouped into the same clusters and each cluster trains a specialized model. However, features utilized for clustering generally rely on a single global model trained during FL, whose convergence usually incurs high communication cost. In this paper, we propose CAFL, an energy-efficient clustering method in FL. In CAFL, clustering features of a client are not based on a collaboratively trained global model by FL, but a tensor of gradient vectors computed on local data. With this approach, the communication overhead for clustering is greatly reduced. We validated CAFL on simulated datasets include Fashion-MNIST and CIFAR-10, and the results show that compared with existing clustering methods in FL, CAFL has much lower communication cost while still ensuring a high clustering accuracy.

There is a big dilemma among instructors teaching English as a foreign language. Competence and teaching grammar rules are the primary pedagogical concern. Competence is directly related to the ability of proper grammar use of a language. However, methodological discussions end up accepting that grammatical rules are neither sufficient nor demonstrating the acquisition of the language. Learner students may have correctly learned grammatical rules, but some studies disagree on teaching only grammar because it will not be enough for students to speak forcefully. These circumstances lead to the discussion on the English Teaching method used at the Autonomous University of Ciudad Juárez (UACJ). This study aims to answer 1.) Which of the following approaches are more suitable to teach a second language, Natural Approach vs. Cognitive Approach? 2.) As to what extent should we emphasis grammar rules on teaching a second language to obtain the most benefit? Lastly, a sizable neurolinguistics portion of information is added to help us understand how the brain responds to learning a foreign language.

The purpose of this study is to recognise the effect of context on learning new vocabulary in an EFL college reading course and how contextualized vocabulary presentation could help in developing the mental lexicon in EFL readers. The research method followed in this study is quasi-experimental, involving a pretest-post-test control group design. Sixty EFL college students were chosen by convenience to participate in this study. Using a standardised vocabulary test and a vocabulary development intervention derived from the caveats of the natural approach and involving a five-phase instructional paradigm, the experimental group performance on the vocabulary test was compared to a traditionally taught control group. Findings showed that both groups were nearly homogeneous on pretesting. The results also indicated that the experimental group participants outperformed the control group in vocabulary learning on post testing as they improved from pretesting to post testing. Conclusions and implications for research were given in the end

Data Envelopment Analysis (DEA) requires deterministic input/output data for efficiency evaluation of a set of Decision Making Units (DMUs). When there are more than one set of input/output data for each DMU, however, such requirement is infeasible. Stochastic DEA (SDEA), where input/output data are assumed to be stochastic, is a natural approach for such applications. Performance evaluation of DMUs in SDEA naturally calls for ranking methods that can account for stochastic fluctuations of the input/output, and hence the efficiency score. None of the proposed methods in the current literature incorporates all the information in the efficiency score distributions for ranking DMUs. To fill this gap, we introduce two ranking methods, a partial and a linear, for performance evaluation in SDEA using the reliability function of the efficiency scores. Our proposed partial ranking is based on the notion of stochastic ordering, while our linear ordering is a weighted average of the reliability function of the efficiency scores. Special cases of our proposed linear ranking method include mean and median ordering in SDEA. Our proposed partial ordering provides a notion for stochastic dominance using which one can define a natural notion of admissibility as a minimal performance requirement. We demonstrate how the proposed ranking methods can be implemented and illustrate the methods using the Grundfeld data, analyzed using both parametric and non-parametric approaches.

Many studies in automatic facial expression recognitions merely limit their focus on recognizing basic emotions, ignoring the fact that humans show various emotions in their daily life. Moreover, from psychological perspective humans express multiple emotions simultaneously. Up to now, researchers recognize two basic emotions at the same time, called mixed emotions. Nevertheless, the mixed emotion still does not reflect how humans express the emotion naturally. This paper advances the concept of mixed emotion into a generalized fuzzy emotion. Fuzzy emotion captures multiple emotions in a single image using fuzzy inference engine. We propose a fuzzy emotion framework which consists of processing system and knowledge system. The processing system extracts facial expression parameters, and the knowledge system employs a fuzzy knowledge-based engine, elicited from the psychologist knowledge to recognize facial expressions. Some advantages are offered: (1) no facial template comparison; (2) no training efforts needed; (3) moreover, fuzzy emotion can recognize ambiguous facial expressions adaptively. The experiment gives a recognition result with the highest accuracy rate of 0.90. A research agenda for future study of mixed emotion recognition is proposed.

Resumen: El currículo que regula la ordenación de la Educación Infantil destaca cómo el acercamiento desde edades tempranas a una lengua extranjera permite desarrollar capacidades afectivas, intelectivas y sociales y contribuye, asimismo, a fomentar actitudes positivas ante las lenguas. Por otra parte, la inclusión de las nuevas tecnologías en Educación Infantil es uno de los asuntos principales del propio currículo, donde se destina un bloque de contenido, el II, exclusivamente a su aproximación, exploración y uso moderado, crítico y significativo. Se insta a propiciar experiencias de iniciación temprana en las tecnologías de la información y la comunicación haciendo especial hincapié en el uso de producciones audiovisuales y de las tecnologías de la información y la comunicación para el acercamiento al idioma extranjero. En el presente trabajo abordaremos determinadas metodologías, propias de la enseñanza de lenguas en el aula de infantil, que posibilitan la mediación de las TIC en la enseñanzaaprendizaje del idioma extranjero. Mostraremos además un grupo de herramientas y aplicaciones destinadas ex profeso a promover el contacto del niño con otras lenguas. Abstract: The curriculum that regulates the management of Early Childhood Education emphasizes how learning a foreign language from a young age can develop affective, intellectual and social skills. Furthermore, it stipulates that contributes to foster positive attitudes towards languages. On the other hand, the inclusion of new technologies in Pre-school Education is one of the main issues that concerns the curriculum itself, where a block of content -block number II, to be precise- is exclusively dedicated to its approximation, exploration as well as moderate, critical and significant use. It is recommended to promote experiences of early initiation in information and communication technologies (ICT), and special emphasis is placed on the use of audio-visual productions and information and communication technologies in the process of teaching and learning foreign languages. In the present work we will address to some methodologies, commonly used in the teaching of languages in the preschool classroom, which enable the mediation of ICT in the teachinglearning of the foreign language. We will also show a group of tools and applications designed specifically to promote the child's contact with other languages.

This paper reviews the language acquisition theory in childhood stages. Five models of baby’s language development including pre-linguistic, holophrastic, telegraphic, simple sentence, and compound sentence are central of discussion. In the early stage, characteristics of language development and language learning in the kindergarten level are discussed integratedly. In the area of Second Language Acquisition (SLA), Krashen Theory in Natural Approach is prevalent, prevailing frontier concepts in children language development. In the social context, language view that has closed relationship to culture is included. This way, norm, etiquette, values, and other aspects of communication are valuable to teaching children in the early stage.

The computer technology has incredibly increased. Computer software and hardware compete to meet the customer's needs. The research intends to spread the knowledge o f information technology, specifically, on the artificial intelligence. The concept of artificial intelligence is adopting and imitating human form, character, and habit which to be implemented on the computer. Using natural approach, the research aims to investigate whether artificial intelligence (AI) will produce the duplication of God's creation. Another important reason of other reseaches on AI is to create a computer which is smart and able to understand human brain working system. Hence, AI has been designed into more practical with faster CPU, cheaper mass memory, and sophisticated software tool. The concept of integrating AI science or collaborative art among sub-fields of technology will stimulate and lead to fu r ther AI researches, and it will be an interesting topic for AI researchers for developing AI technology in the future.

Current design processes are all generally similar in approach, but none yet address sustainability directly. When sustainable design is pursued, bio-inspired design or biomimicry are invariably used. These approaches attempt to reuse principles found in nature to conceptualize artifact designs. However, sustainable design approaches have yet to be integrated into typical design processes as they occur in practice; these methods generally work by seeking solutions only on a case-by-case basis. As a result, sustainable design methods like biomimicry tend to be used as ancillary or "after the fact" techniques. To fully integrate sustainability into design processes, the authors believe we must look more deeply at the processes that occur in nature and that have led to the organisms often referred to in biomimicry and related methods. The authors’ study of natural evolutionary processes has led them to believe that there is significant similarity in the way successive generations of artifacts and organisms change. We found that we could describe processes in generic terms that applied equally well to natural evolution and the way that artifacts change over time: that is to say, we found an analogy between generational changes in artifacts and in organisms. The authors are now delving into more detail, and are finding that the analogy can extend to cover natural selection, mutation, and genetic structures. A detailed explanation of this analogy, working at several different levels, is given in this paper. Furthermore, natural and artificial lifecycle processes are shown to be nearly identical. Since the analogy appears to hold well at many levels of detail, the authors propose to create a genetic structure (a genome) for artifacts. We contend that such a structure would be useful for designers. For example, we find that using the structure of the analogy as a guide can help reduce complexity of design problems. Also, we show that the artificial “genes” lend themselves to description via pattern languages, which are also known to reduce problem complexity. We hypothesize that using pattern languages to represent an artificial genome for designed artifacts will result in a useful, more holistic approach to sustainable design - one that is literally inspired by nature.

Non-normality is a usual fact when dealing with gene expression data. Thus, flexible models are needed in order to account for the underlying asymmetry and heavy tails of multivariate gene expression measures. This paper addresses the issue by exploring the projection pursuit problem under a flexible framework where the underlying model is assumed to follow a multivariate skew-t distribution. Under this assumption, projection pursuit with skewness and kurtosis indices is addressed as a natural approach for data reduction. The work examines its properties giving some theoretical insights and delving into the computational side in regards to the application to real gene expression data. The results of the theory are illustrated by means of a simulation study, the outputs of the simulation are used in combination with the theoretical insights to shed light on the usefulness of skewness-kurtosis projection pursuit for summarizing multivariate gene expression data. The application to gene expression measures of patients diagnosed with triple-negative breast cancer gives promising findings that may contribute to explain the heterogeneity of this type of tumors.

In order to interact with the world, agents must be able to predict the results of the world's dynamics. A natural approach to learn about these dynamics is through video prediction, as cameras are ubiquitous and powerful sensors. Direct pixel-to-pixel video prediction is difficult, does not take advantage of known priors, and does not provide an easy interface to utilize the learned dynamics. Object-centric video prediction offers a solution to these problems by taking advantage of the simple prior that the world is made of objects and by providing a more natural interface for control. However, existing object-centric video prediction pipelines require dense object annotations in training video sequences. In this work, we present Object-centric Prediction without Annotation (OPA), an object-centric video prediction method that takes advantage of priors from powerful computer vision models. We validate our method on a dataset comprised of video sequences of stacked objects falling, and demonstrate how to adapt a perception model in an environment through end-to-end video prediction training.

A natural approach of animal creativity through insightful problem-solving may offer a panel of how physiological, contextual, cultural and developmental variables related to each other to produce new behaviors. The spontaneous interconnection of acquire behaviors is an Insightful Problem-Solving model based on the new combination and/or chaining of behaviors that were previously and independently trained. This model seems to offer an integrative alternative for the studies of Innovation and Behavioral Flexibility because it allows the research on innovation in a scenario in which the response that solves the problem situation is not available by trial-and-error. Measuring task-appropriateness by behavior flexibility and novelty by behavior innovation under insightful problem-solving paradigm can contribute for the integration of decades of evidence in Cognitive Psychology, Neuro-ethology, Behavior Analysis and Behavioral Neurosciences. The Insightful Problem-Solving allows the independent test of behavioral innovation and behavioral flexibility as it measures the behavioral innovation inside insightful test and tests if the BF depends on variables arranged in the problem-situation and/or on the previous training (e.g. familiarity with access to appetitive stimulus in the pre-test, the number of distinct behaviors trained, and contingency changes in the post-test).

Community-based tourism (CBT) is generally considered a platform for local communities to obtain economic benefits by offering their products and services to tourists. This chapter aims to use the case study of the city of Dharamshala to assess the facilitators and inhibitors of CBT. This study syndicates a case study method with interviews of local stakeholders as the aim is to disclose specific outcomes in an explicit setting. Thus, a qualitative approach is considered appropriate as it comprises a very natural approach to understanding social phenomenon in real-world scenarios or in a specific context, without the researcher’s manipulation. Therefore, this chapter does not deliver statistical data or generalizations but instead provides logical generalization grounded on previous literature and supported by the findings from this study. The findings show that abundant loopholes arise because of the absence of collective decision-making, cooperation and shared vision in Dharamshala. The results support the theory that CBT can perform a vivacious role in encouraging community participation for the unprejudiced and overall development of the local community. CBT is indeed a unique technique for facilitating participation, involvement and flow of benefits to locals with the help of a bottom-up approach. Results also indicated a pressing need for governments, private players, academics and NGOs, etc., to come together to collectively develop a shared vision to formulate programmes to educate and train people for social and human capital growth. The current study integrates the concepts of poverty mitigation, CBT and tourism development to explain the successful establishment of the CBT in Dharamshala.

Se anexa imagen sobre el modelo comunicativo de Weaver and Shannon . Este análisis se realiza con el objetivo de indagar y descubrir un enfoque que pueda mejorar las habilidades orales y de escucha de los estudiantes de octavo grado del colegio San Carlos en Sevilla Valle, donde se ha notado la ausencia de estas competencias en los estudiantes. Estas habilidades son esenciales para alcanzar un nivel avanzado en el idioma con el desarrollo de estas competencias estudiantes podrán comunicarse y emplear el idioma de una forma exitosa. Este es un estudio cualitativo realizado a través de un análisis bibliográfico, para esto fueron consultadas bibliotecas virtuales, artículos y revistas científicas donde fue posible extraer información relevante para el estudio. Inicialmente se definen los conceptos de adquisición de un segundo idioma y aprendizaje de un segundo idioma donde se evidenció como la adquisición si bien, no es posible reproducirla en un salón de clase si puede ser adaptada simulando un entorno natural en a las lecciones de inglés por medio de herramientas tecnológicas. Además, fueron analizadas algunas metodologías y teorías como el constructivismo, el enfoque comunicativo, la teoría de las inteligencias múltiples, la metodología de aula invertida y el aprendizaje basado en tareas. The development of speaking and listening skills in the learning of English as a foreign language (EFL) is essential to the students can progress integrally in the learning of a foreign language. The lack of listening and speaking abilities in students of eighth grade of San Carlos School has affected the performance of students in this area. This paper studies the acquisition theory and how this concept could be adapted in the English lessons of San Carlos School. Likewise, it analyzes different alternative approaches that could be used by teachers with the purpose to change the way teachers design their lessons. This might benefit the development of these abilities when teachers adapt them in the classroom through technological resources. The main purpose of this study is to promote the acquisition through communication and to encourage students to acquire and improve these skills. This document presents a bibliographical study of different theories related to teaching EFL, and through of a qualitative research that extracted from virtual libraries, research of articles and scientific magazines relevant information to answer the question about how can be improved the performance and level of all abilities of students. Initially, the study tries to clarify the concept of acquisition and learning of EFL and how the acquisition theory can be adjusted in the process of teaching a foreign language. On the other hand, different methodologies were analyzed like the Natural Approach, Constructivism, Multiple Intelligences, Task Based Language Teaching, Flipped Classroom and resources of ICT that could help to this purpose. With this study it was possible to determine that the acquisition of language is possible through natural environment where the learner can listen to a wide amount of the target language. To reproduce a natural environment is not possible to teachers, but some technological resources can be used to give some features that permit somehow simulate natural settings. Finally, with the information collected was created a guide template to instruct the planning lessons in San Carlos School, according to the Natural approach taking into account the basic principles of this theory.