درخت حوزه‌های تخصصی

Falls are a serious concern among the elderly people, causing severe physical pain to them and placing a strain on medical infrastructure. The global elderly population is expected to grow significantly in the coming years, as advances in healthcare allow lifespans to increase globally. This will bring more chances for falls to occur. With this in mind, there is a need for new research to be conducted on finding ways to reduce this problem. One area which shows promise is the use of Machine Learning to perform fall detection. Machine Learning is a rapidly growing field, and it has many applications in various fields such as finance, technology and medicine. When it comes to fall detection, Machine Learning systems are often able to detect falls much better and efficiently than a human can, given the same input data. The goal of this paper is to conduct a survey study on the main and most common machine learning algorithms implemented in the field of early fall detection for elderly people and the characteristics. The paper will discuss the different types of fall detection systems, algorithms, tools, datasets, applications, and challenges.  By conducting this research, a better understanding of the context, progress and trends in the field will be possible so that future research will have a guide to build upon.

The state of the world's environment reveals the fact that in recent decades, due to human activities and increasing consumerism, Earth has suffered irreparable damage and the world is witnessing unprecedented growth in environmental degradation, just as consumers activities can lead to deteriorating environmental conditions. The environmentally conscious behaviors such as green purchase behavior, can be agents of change, motivation and attention to the environment. The purpose of this research is to develop   a model for implementing green purchase behavior that recognizes the dimensions of this behavior to determine the effective factors, operational strategies, and consequences of its implementation.The overall approach is qualitative and Grounded Theory has been done. Using purpose foul and snowball sampling methods, semi-structured interviews were conducted with 13 experts from the field of business researchers and environmental activists.The results of data coding led to the identification of 448 initial codes which finally cited the approach Systematic in the given data theory, paradigm model show that causal categories (environmental belief, health concern, green attitude, mental norm), causal categories (green purchase behavior), background categories (economic indicators, government support for capital Eco-friendly investments, the country's environmental policies, the impact of green consumption culture), interventionist category (distribution of green products, financial and economic constraints of households and promotion, encouragement to green purchase), strategies (Indian market strategies, prices, innovation), and the consequence (at the macro-level including increasing the level of health in society, development, and growth of organizational performance and promoting green lifestyle and at the micro-level including preference to buy environmentally friendly products and increase the repetition of purchases behavior) Impact on the implementation of green purchases behavior.  

The objective of this study was to validate a bilingual Spanish-English version of the Vocabulary Size Test (VST) considering its potential use as a discriminator between learners in terms of language competence. This version was designed based on the two forms available on one of the creators’ websites as well as considering practices recommended regarding the elimination of cognates and loans. A one-way ANOVA test was used to confirm the test’s capacity to discriminate among learners of different linguistic competence. Additionally, Principal Axis Factoring (PAF) was conducted to revise the existence of only one underlying variable. As a result of this study, a VST version for Spanish speakers consisting of 9 vocabulary frequency levels is shared. This version is in line with validation standards put forward in previous research. It is expected that this instrument will help future studies that seek to measure Spanish speakers’ competence in English as a foreign or second language without having to deal with the interference of other intervening factors.

The present semantic research has been performed in order to provide a cognitive and cultural explanation of conceptual metaphors in parts 20 to 30 of the Holy Qur’an. Extraction of ‘types of conceptual metaphors,’ determination of ‘high frequency metaphors,’ ‘source domains’ and ‘target domains’ is the process of conducting research using the conceptual metaphor theory. The variety of concepts of ‘target’ and the functional frequency of ‘source’ concepts indicate what concepts are intended in the holy Qur’an through metaphorical conceptualization. This study provides a basis for further understanding of the worldview presented in the Holy Qur’an and the possibility of determining the behavioral patterns of religion by identifying metaphors. The results of the present study represent a septenary classification of metaphors in the ‘empirical source domain,’ containing: ‘social life,’ ‘needs of the body and its activity,’ ‘image schemas (schema-based),’ ‘elements of nature,’ ‘person,’ ‘body parts,’ and ‘similarity-based metaphors (simile)’; Among which, the highest percentage of metaphorical conceptualization in the source domain is in ‘social life’ and the lowest one is in the domain of ‘person.’ Considering the fact that most of the human knowledge is about the elements and subdomains of ‘social life,’ Qur’anic sources in this domain have played the major role in abstracting the cultural and doctrinal concepts of religion and organizing Islamic religious experiences using the sources of this field and have been used as customary (conventional) and practical models. Accordingly, Qur’anic metaphors lead to the formation of cultural and cognitive patterns, and the ‘monotheistic belief system’ (Qur’anic) directs human bodily experiences in metaphorical conceptualization, and this ‘Qur’anic worldview’ can be seen as an Islamic cultural and cognitive model in the Qur’anic metaphorical schema.