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The teaching of SVT in general offers learners an environment that allows them to explore and explain natural phenomena, to understand different spatio-temporal scales, to understand the world around them so that they can decide and act responsibly. It is interesting to note that the scientific ecological outing (SES) is an integral part of the SVT teaching program, at both college and qualifying secondary level, and that teachers are called to organize these outings in agreement with the programs as recalled by the circulars of the MEN. However, the SES allows the real observation and the execution of experiential practices in the field, it is the opportunity to place the learner in a learning situation according to a reflective and investigative scientific approach from his confrontation with reality Cariou J (2013), (2015) Offers a didactic framework and formalizes evaluation criteria for the implementation and management of a scientific investigation process. So that he can make connections with what the learner acquires as abstract knowledge in class in order to be able to decide and act responsibly and critically on the scale of everyday situations as an Eco citizen.

The epidemic situation generated as a result of COVID -19 crossways the sphere observed the practices of various emerging technology like Internet of Thing (IoT) along with norm of dynamic fields. The wireless communication  based on networks such as wireless mesh networks (WMN) and Mobile Ad-hoc networks (MANETS) proven to be very successful for monitoring of patients remotely. The MANET protocols that are simulated in this study are  Ad-hoc On Demand Vector (AODV), Secure AODV (SAODV) and Hybrid Wireless Mesh Protocol (HWMP). In this investigation work, most appropriate routing protocols to knob DDoS attacks are simulated using NS-2 and assessed in terms of average energy consumption in the state of changing speed connections among devices called mesh nodes. Further ANOVA test is utilized for further accessing for the best suited routing protocol for handling the data packets, which is HWMP , considerable less susceptible for DDoS assaults dominant in healthcare field.

The volume of digital text data is continuously increasing both online and offline storage, which makes it difficult to read across documents on a particular topic and find the desired information within a possible available time. This necessitates the use of technique such as automatic text summarization. Many approaches and algorithms have been proposed for automatic text summarization including; supervised machine learning, clustering, graph-based and lexical chain, among others. This paper presents a novel systematic review of various graph-based automatic text summarization models.

The study has two main objectives: firstly, to examine the opportunity of the Momentum and Contrarian investment strategy for three different monetary systems to trade currencies in Forex markets using Symlet wavelet decomposition approach. Secondly, to examine the co-movements between the three monetary systems using wavelet coherence analysis. The findings indicate that an investor with momentum strategy can consider investing in Bitcoin and Gold market, while the contrarian investment strategy is more advisable for the fiat money market during crisis period. Furthermore, the wavelet coherence analysis indicates that Bitcoin currency is the most leading monetary system during the Covid-19 pandemic crisis, followed by gold. However, US dollar mostly leads Bitcoin during non-crisis periods, while Gold is found to lead the US dollar throughout the sample period of the study. This suggests that the cryptocurrency system or gold standard should be considered as the alternative monetary system for better economic stability specially during the crisis period. Moreover, Bitcoin and gold had an anti-phase correlation before the Covid-19 pandemic crisis, which implies better benefits of hedging in the non-crisis period, while during a crisis they are moving together across different horizons. In contrast, Bitcoin and Fiat Money are strongly correlated during non-crisis periods, while during covide-19 pandemic crisis the correlation is statistically insignificant. Overall, the outcomes offer significant guidance for policymakers in understanding which monetary system leads to better economic stability during the crisis period and provides many implications for market players such hedging and Diversification investments strategy in forex markets.

This study aims to test the relationship between knowledge generation and organizational creativity. The second method was surveyed (analytical) using exploratory research through the survey as a data collection tool. The validity coefficient was measured as a reasonable degree of stability was obtained for a sample of (46) individuals. The data was analyzed using statistical package (SPSS V25). Descriptive Statistic Among the findings is that CASNOS has a medium level of the knowledge generation process, and there is a statistically significant effect of knowledge generation on the organizational innovation of CASNOS (El-Oued), according to the dimensions adopted in the study model.

Sentiment Analysis or opinion mining is NLP's method to computationally identify and categorize user opinions expressed in textual data.  Mainly it is used to determine the user's opinions, emotions, appraisals, or judgments towards a specific event, topic, product, etc. is positive, negative, or neutral. In this approach, a huge amount of digital data generated online from blogs and social media websites is gathered and analyzed to discover the insights and help make business decisions. Social media is web-based applications that are designed and developed to allow people to share digital content in real-time quickly and efficiently.  Many people define social media as apps on their Smartphone or tablet, but the truth is, this communication tool started with computers. It became an essential and inseparable part of human life. Most business uses social media to market products, promote brands, and connect to current customers and foster new business. Online social media data is pervasive. It allows people to post their opinions and sentiments about products, events, and other people in the form of short text messages. For example, Twitter is an online social networking service where users post and interact with short messages, called "tweets." Hence, currently, social media has become a prospective source for businesses to discover people's sentiments and opinions about a particular event or product. This paper focuses on the development of a Multinomial Naïve Bayes Based social media data emotion analyzer and sentiment classifier. This paper also explains various enriched methods used in pre-processing techniques. This paper also focuses on various Machine Learning Techniques and steps to use the text classifier and different types of language models.

The infestation of the world pandemic has significantly changed the landscape of teaching and learning experience in Malaysia.  Particularly for the institution under study, E-learning, previously used as the support medium to face-to-face classroom teaching, has become the primary medium of teaching and learning amid Covid-19.  E-learning platform has replaced the face-to-face classes. Even though it is only a temporary approach, less is known in terms of its effectiveness.  The present paper intends to examine the factors contributing to E-learning's effectiveness in a Higher Education Institution in Malaysia amid the COVID-19 crisis. The Technology Acceptance Model underpinned the conceptual framework.   This study investigated the relationship between the independent variables (perceived usefulness, perceived ease of use, and self-motivation) and E-learning effectiveness.  The data were collected through an online self-administrated questionnaire using Google form and received a total of 354 respondents.  The data were analyzed using SPSS and Smart PLS.  The findings revealed that perceived usefulness, perceived ease of use, and self-motivation positively influenced E-learning's effectiveness.  This paper concluded that regardless of whether as the support medium or the primary medium in the teaching and learning process, the determinant to E-Learning effectiveness is still perceived the same. This study also supports the TAM proposition while incorporate self-motivation in measuring learning effectiveness.

The purpose of this study is to substantiate the basic principles and prerequisites for the formation of project maturity of public administration for the successful implementation of digital governance projects. The relevance of this study is due to the need to implement the task of digital transformation of Ukraine by solving the problem of modernization of public administration on the basis of constant increase of project maturity of the organizations.The study proved the existence of a direct dependence of prospects for the implementation of digital transformation projects on the level of project maturity of public management. A variant of the project maturity model adapted to the local self-government body is being developed. The model assumes three levels of maturity of local governments. It has established that the majority of the created united territorial communities of Ukraine were characterized by the first two levels of maturity. The implementation of the maturity model makes it possible to assess the current state of the system, choose adequate tools for staff training, create conditions for continuous improvement and realization of the potential of the local community for the implementation of digital transformation projects.

Learning effective segment depictions and resemblance measures are fundamental to the recuperation execution of a substance based picture recuperation (CBIR) structure. Regardless of wide research tries for a significant long time, it stays one of the most testing open gives that broadly impedes the achievements of real-world CBIR structures. The key test has been credited to the extraordinary "semantic hole" subject that happens between low-level photo pixels got by technologies and raised close semantic thoughts saw by a human. Among various techniques, AI has been successfully analyzed as a possible course to interface the semantic gap in the whole deal. Impelled by late triumphs of significant learning techniques for PC vision and various applications, in this paper, we try to address an open issue: if significant learning is a longing for spreading over the semantic gap in CBIR and how much updates in CBIR endeavors can be cultivated by exploring the front line significant learning methodology for learning feature depictions and likeness measures. Specifically, we explore a structure of significant learning with application to CBIR assignments with a wide game plan of definite examinations by investigating front line significant learning methodologies for CBIR endeavors under moved settings. From our exploratory examinations, we find some encouraging results and compress some huge bits of information for upcoming research.

The heavy trends of the Information Society are knowledge that requires the spirit of innovation, creativity, flexibility and critical thinking “more than benign introspection.” In addition, information about each other’s relationships with oneself, the other and the environment is crucial to enable individuals to understand the complex reality. The Moroccan school is part of this societal vision, by renovating its education and training programs, which claim the development of the quality of procedural, cognitive and metacognitive strategies. In this perspective this research work aimed at studying the engineering analysis of investigation approaches in the teaching of SVT for the implementation of a reflexive practice in lycian learners, generating the ability to process information and invest in mechanisms for understanding, conceptualizing and proceduralizing cognitive and metacognitive strategies. Informational investigative capacity is crucial because it informs learning decisions, which can lead to innovations in the delivery of cognitive styles. To do this, we chose to conduct our study, through interview surveys and semi-structured questionnaires. The first among teachers and the second for SVT inspectors from three provincial directorates of National Education. The results show that the majority of those involved in education are involved in the classical informational approach and the experimental approach. The use of investigative analysis approaches remains episodic in some learning units (scientific ecological output and DNA extraction). Teachers are keen to introduce new information technologies to create favourable conditions for learning about investigative approaches, in order to improve the power of analysis, treatment and critical thinking and coping with situations of authentic and novel learning. We are concerned about the ability to understand what and how each of its actors is further shaping.

The main aspects of using digital marketing tools in strategic management in the field of tourism have considered in the article. The study proved that the marketing strategy of the tourist enterprise is a determining factor in the choice of the main sales channels in the Internet environment. The article highlights the keydigital marketing tactics and tools. In the main directions defined strategic management in the field of tourismon the basis of optimization of digital marketing tools. To implement the target approach in the implementation of the marketing strategy of the enterprise, a system of KPIs proposed.

It has been proved that in the era of globalization and the development of information technologies, the need to optimize the supply chain of services increases, since the integration of participants in this chain is performed without the use of modern management information systems. In the paper, with the help of logic-cognitive, structural-functional methods, structural-logical and imitation modelling, a management approach to simulation of business interaction in the integration of enterprises with elements of ERP-system and CBIP is developed and proposed, which allows you to create a flexible, adaptive and secure IT infrastructure , which increases the efficiency of the enterprise and allows you to optimize the management of relations with other participants in the service supply chain. As a result of this application of modern supply chain management systems, a synergistic effect is achieved that allows you to minimize the number of technological operations, shorten the production cycle and reduce the cost of services both for each individual enterprise and in the service supply chain as a whole.