مطالب

This article aims to demonstrate the dominance and prevalence of mercy and compassion over all principles and rulings related to women in the Holy Qur'an. The Qur'anic view of women has always been subject to criticism and evaluation. Numerous verses in the Qur'an address the status of women in Islam. An overall review of these verses shows that mercy and compassion are two overarching principles that permeate all these principles and rulings. This article examines the supremacy of the principle of mercy in the Qur'anic perspective on women. This examination is conducted across three dimensions of a woman's life: the individual, familial, and social dimensions. In the individual dimension, the Qur'anic merciful view of women is manifested in the following principles:1- Equality of men and women in the essence and substance of creation.2- Shared participation of both genders in the balance of creation, a common human identity, shared servitude as the purpose of creation, similarity in the Divine nature, and shared fundamental human dignity with its various aspects and forms.3- The value of women's deeds in the Qur'an and their equal status in attaining spiritual ranks are other facets of the Qur'anic merciful view regarding the individual dimension of a woman's personality. In familial roles, the dominance of mercy manifests itself in a different, and perhaps more explicit, way. Examples of the Qur'anic merciful view of women in the familial dimension include: The principle of living together amicably. The introduction of affection and mercy as the fundamental pillars of the family. Emphasis on kindness and the invitation to good even in the most critical of marital relationships. The supremacy of mercy in the social sphere can be clearly seen in the presentation of women as role models for the community of believers. This is demonstrated by women such as Asiya, the wife of Pharaoh, who is introduced as an example of faith, resistance against tyranny, and steadfastness against oppression, and Mary, who is introduced as a model of chastity, purity, and innocence. The totality of these cases indicates that the overall and overarching view of the Qur'an regarding women is a perspective founded on mercy, and all other specific issues must be explained and interpreted in light of this perspective.

In his ontological exposition of understanding, Gadamer, by raising the issue of dialogue between the interpreter and the text, paved the way for discussing challenging topics such as relativism in knowledge. In his view, the fusion of the temporal-linguistic horizons of the interpreter and the text explains the possibility of multiplicity of meaning and the endlessness of understanding. In this article, we attempt to examine the possibility of the metaphorical nature of understanding from a different perspective, namely by focusing on the discussion of "metaphor," due to its importance in providing reasons for the possibility of diversity and invention of meaning in language. Although the theory of metaphor is a core discussion in Ricoeur's philosophy, and Gadamer has not extensively addressed the topic of metaphor except for some allusions in explaining language; nevertheless, some commentators have re-examined understanding and the fusion of horizons by resorting to this theory. Therefore, while analyzing these interpretations using a descriptive-analytical method, and based on the relationship between unity and tension between identity and difference in the structure of metaphor, we substantiate the metaphorical characteristic of understanding, language, and the fusion of horizons, and its hermeneutic consequences.

The Internet of Things (IoT) has become increasingly prevalent, and recent advances in machine learning, particularly in healthcare, have gained significant attention from researchers. One prominent interdisciplinary topic in these fields is human activity recognition (HAR). Despite extensive research, several challenges remain in this area, especially concerning the application of modern machine learning techniques for HAR. This study proposes a novel method for human activity recognition by combining radial basis function neural networks (RBFNN) and support vector machines (SVM). The approach enhances recognition accuracy and algorithm efficiency by extracting relevant features using RBFNN and convolutional neural networks (CNN). Classification is then performed using SVM. The proposed method was evaluated using the UCI HAR dataset, which includes six distinct human activities. Results demonstrate that the proposed approach achieves an accuracy of 99%, surpassing existing methods.