A Deep Neural Network-Based Target Recognition Algorithm for Robot Scenes

Intelligent robots are a key vehicle for artificial intelligence and are widely employed in all aspects of everyday life and work, not just in the industry. One of the talents required for intelligent robots to complete their jobs is the capacity to identify their environment, which is a crucial obstacle to be overcome. Deep learning-based target identification algorithms currently do not fully leverage the link between high-level semantic and low-level detail information in the prediction step and hence are less successful in recognizing tiny target objects. Target recognition via vision sensors has also improved in accuracy and efficiency because of the development of deep learning. However, due to the insufficient usage of semantic information and precise texture information of underlying characteristics, tiny target recognition remains a difficulty. To address the aforementioned issues, we propose a target detection method based on a jump-connected pyramid model to improve the target detection performance of robots in complex scenarios. In order to verify the effectiveness of the algorithm, we designed and implemented a software system for target detection of intelligent robots and performed software integration of the proposed algorithm model with excellent experimental results. These experiments reveal that, when compared to other algorithms, our suggested algorithm’s characteristics have higher flexibility and robustness and can deliver a higher scene classification accuracy rate.

Emotional Intelligence & ICTs for Women and Equality

Gender equality is a fundamental human right and is essential for the existence of peaceful societies, with human resources that are fully utilized and sustainable development. Emotional Intelligence is not gender biased and it is an integral key to successful personal and working life. In (Drigas & Papoutsi, 2021) there was an attempt to construct a reliable and valid measurement instrument of emotional intelligence with 81 items, based on the theoretical nine-layer pyramid model of emotional intelligence. The sample was consisted of 520 teachers (129 males and 391 females) from primary and secondary school grade and the data was collected with the Nine Layer Pyramid Model Questionnaire for Emotional Intelligence. Among other results we examined gender differences in emotional intelligence. The results revealed some differences between the two genders on emotional intelligence with women scoring higher on overall emotional intelligence. This article also provides an overview of the prevailing emotional intelligence status of both sexes as it emerges through research, beliefs about emotions between women and men, and suggestions for avoiding stereotypes and proper interventions for raising emotional both men and women. Finally, a reference is made to technology in its various forms, including Information and Communication Technology (ICT), which is also associated with emotional intelligence and has great potential to empower women worldwide and promote gender equality

The respect pyramid: A model of respect based on lay knowledge in two cultures

Respect is a common social concept, yet how lay people define it has not been thoroughly investigated. This study used a grounded theory approach, using in-depth interviews, to conceptualize respect according to lay knowledge. 40 participants from two cultures in the Middle East—20 Jewish Israelis and 20 Palestinians—reported how they define respect ( Kavod in Hebrew and Ihtiram in Arabic). The findings define respect as a complex, multidimensional concept. Based on the findings, a respect pyramid model was developed, which includes four dimensions: avoiding disrespect, deserved/normative respect, conditional respect, and considerate respect. Each dimension indicates an increase in aspects that make the respect less conditional and more intrinsic, while requiring higher sensitivity and greater effort. The implications of the respect pyramid for relationships and the cultural differences regarding definitions of respect are discussed.

Analyzing the Role of Implicit Bias From a DisCrit Perspective

Using a disability studies/critical race theory (Discrit) lens, the authors reviewed and analyzed specific literature within the pyramid model (PM) framework—a three-tier hierarchical framework for promoting social-emotional competence and reducing challenging behavior among young children—to understand the model's framing of implicit bias and the specific strategies noted in the literature that help teachers to recognize and counteract implicit bias and subsequently reduce disciplinary inequities among Black preschool children. Findings revealed that although the PM literature discussed, defined, and emphasized the importance of cultural responsivity, it did not engage critically with the construct of implicit bias (i.e., racism and ableism), specifically as it relates to the experiences of children most vulnerable to disciplinary sanction. This chapter ends with suggestions to help readers rethink the PM framework as a way to shift practice toward more equitable experiences for Black children in their earliest years of schooling.

Teacher Training and Online Teaching

The WL profession currently does not have a framework to guide pre-service education programs related to online and/or remote instruction. While the ACTFL/CAEP standards affirm that teachers should be able to use technology and adapt and create instructional materials for use in communication, there is an underlying assumption that the technology will be integrated to supplement rather than supplant instruction. The focus, then, remains on in-class, on-campus experiences for learners and educators. This chapter provides a rationale for including online pedagogy in teacher preparation programs, explores current frameworks for online teaching (TPACK, Community of Inquiry, Pyramid Model, ADDIE), and proposes six considerations for integrating online language teaching as a foundational component of preservice preparation.

The Competitiveness of Agriculture in EU Member States According to the Competitiveness Pyramid Model

Agriculture in the European Union is highly differentiated, and one of the objectives of the Common Agricultural Policy is to improve agricultural competitiveness. Therefore, surveys regarding the competitiveness of agriculture and grouping countries of the European Union (EU) according to similar characteristics of agriculture are very valuable. They help make strategic decisions concerning the agricultural sector. This paper aims to evaluate the agricultural competitiveness of EU member states in 2010–2019. Data used is derived from the Eurostat and FADN (Farm Accountancy Data Network). The study employed a competitiveness pyramid model based on two groups of factors–competitiveness sources (bottom of the pyramid) and competitiveness effects. Partial components allocated to the groups mentioned above of factors were used to calculate a synthetic measure to determine the level of agricultural competitiveness in respective countries. The studies revealed that EU agriculture varies both in terms of resources and relationships between production factors, as well as the efficiency of their utilization. A clear difference in the level of competitiveness occurred between old and new member states, although some new countries ranked relatively high in terms of competitiveness sources (Czechia and Poland). Belgium scored highest for the synthetic measure of agricultural competitiveness in 2010–2019, and Cyprus had the lowest. It was demonstrated that human resources were of utmost importance in the structure of competitiveness sources. In turn, the average holding area determined the management conditions to the highest extent.

Metacognitive and Metaemotional Training Strategies through the Nine-layer Pyramid Model of Emotional Intelligence

Emotional intelligence constitutes an important 21st century skill that impacts positively several areas of everyday life. It contains competencies that enhance the ability of other significant skills for self-development. The main purpose of this study is to present the way we can develop and improve our emotional intelligence based on the pyramid model and its nine layers. To achieve this goal, the paper seeks to address the following question: What are the metacognitive and metaemotional skills and strategies that can play a key role in developing, enhancing and improving emotional intelligence?Extensive reference is made to the skills that involved in each layer and have been identified as necessary and should be cultivated by the individual leading gradually to the higher levels of self-actualization and transcendence. Furthermore, we suggest some strategies in each layer that work auxiliary and supportive for the cultivation of the specific skills.Metacognitive and metaemotional skills and strategies are necessary to conquer the levels of emotional intelligence and to apply in a variety of contexts with the aim of developing emotional intelligence and self-improvement.

Iterative Design and Pilot Implementation of a Tiered Coaching Model to Support Socio-Emotional Teaching Practices

We used an iterative process to design the Tiered Coaching Model (TCM) to support preschool teachers’ implementation of the Pyramid Model. In the TCM, teachers are matched to one of three coaching tiers based on their observed classroom practices, individual characteristics, and preferences. Coaching tiers included self-guided coaching, small group coaching, and individual coaching. We describe TCM model development and two field tests exploring its potential usability and effectiveness. In Field Test 1, the model was tested with 16 lead preschool teachers. Focus groups and teacher feedback informed systematic model revisions. In Field Test 2, we gathered preliminary findings from an additional 24 teachers. All teachers across coaching tiers and field tests increased their use of Pyramid Model practices while engaging in the TCM, providing promising evidence for wider demonstrations and future rigorous evaluations of the model.