Ihsanas Islamic Ethical Virtue For Neighborhood Community Coexistence

This study demonstrates that there is a need of addressing neighborhood relationships in contemporary times. And in this regard, a position from Islam is considered in which neighborly relationships are based on Quranic ethical virtue ihsan i.e., doing good to others. The word neighbor in the Quran and Hadith is a general term that is not discriminatory. It includes Muslims and non-Muslims. This insight is very useful for building relationships in multicultural and multireligious communities for harmony and peace. To locate a neighbor, though there are jurisprudential opinions, leaving it to its customary use is preferred in this study. The neighborhood rights and duties are given in detail. And it is also demonstrated that those prophetic narrations in which harming neighbors or committing sins against them is considered as the consequence of the absence of faith in fact show the disgust of such sinful acts; therefore, a sinful Muslim is not considered as a non-believer. The harm is especially illustrated with infringing the privacy of a neighbor. It has been shown that Ihsan includes ethically both non-maleficence and beneficence. Most of the prophetic traditions can be classified under these two categories. In addition to this, it is also shown that the neighborhood relations in Islam also include the Golden Rule which is all-encompassing and in principle exhaustive.

The Role of Intergenerational Neighborhood Relations for Precarious Aging During the COVID-19 Pandemic in Germany

Throughout the Covid-19 pandemic, the immediate living environment has significantly gained importance - particularly for people framed as ‘risk-groups’, such as older adults. Effects of contact restrictions to contain the spread of the virus have affected inequalities, uncertainties and loneliness in later life differently depending on the intergenerational relations, informal infrastructures of provisioning and networks of solidarity given in a certain neighborhood. The paper presents findings from a recent mixed-methods study in Frankfurt, Germany, combining a quantitative survey (n=1.000) with a longitudinal qualitative study (n=60). Results show how intergenerational neighborhood relations can play a crucial role in mediating risks of pandemic precariousness in later life, but also how older adults themselves significantly contributing to neighborhood networks of provisioning. Strengthening such very local relations is key to protecting all age groups from the effects of crises beyond the pandemic, and, in conclusion, ways to do so are being discussed.

Factors Influencing Urban Livability in Seoul, Korea: Urban Environmental Satisfaction and Neighborhood Relations

This study examines the correlations between urban environmental satisfaction, neighborhood relations, and livability. Previous studies on livability have insufficiently dealt with urban environments and neighborhood relations and have failed to conduct an integrated analysis that considers the causal relationships between these factors. To fill these knowledge gaps, this study includes urban environmental satisfaction and neighborhood relations as factors affecting livability. Moreover, this study verified the mediating effect of neighborhood relations between urban environmental satisfaction and livability. Online surveys were carried out with 750 residents in Seoul, South Korea, and the structural equation model (SEM) was employed. The results indicated that a higher level of urban environmental satisfaction affected livability positively. In particular, the accessibility had the greatest effect on livability. In addition, neighborhood relations had a mediating effect on the pleasantness and safety of urban environments. Today, many developing countries are undergoing rapid urbanization, as Seoul has experienced in the past. However, this can cause a number of simultaneous side effects, which lower livability. Furthermore, this leads to population decline which might hinder urban sustainability. Therefore, this study suggests important policy implications for achieving urban sustainability by improving livability.

A Hierarchical Clustering Method to Repair Gaps in Point Clouds of Powerline Corridor for Powerline Extraction

Powerline detection is becoming a significant issue for powerline monitoring and maintenance, which further ensures transmission security. As an efficient method, laser scanning has attracted considerable attention in powerline detection for its high precision and robustness during the night period. However, due to occlusion and varying point density, gaps will appear in scans and greatly influence powerline detection by over–clustering, insufficient extraction, or misclassification in existing methods. Moreover, this situation will be worse in terrestrial laser scanning (TLS), because TLS suffers more from gaps due to its unique ground–based scanning mode compared to other laser scanning systems. Thereby, this paper explores a robust method to repair gaps for extracting powerlines from TLS data. Firstly, a hierarchical clustering method is used to extract the powerlines. During the clustering, gaps are repaired based on neighborhood relations of powerline candidates, and repaired gaps can create continuous neighborhood relations that ensure the execution of the clustering method in return. Test results show that the hierarchical clustering method is robust in powerline extraction with repaired gaps. Secondly, reconstruction is performed for further detection. Pylon–powerline connections are found by the slope change method, and powerlines with multi–span are successfully fitted using these connections. Experiment shows that it is feasible to find connections for multi–span reconstruction.

Neighborhood Attentional Memory Networks for Recommendation Systems

Deep learning systems have been phenomenally successful in the fields of computer vision, speech recognition, and natural language processing. Recently, researchers have adopted deep learning techniques to tackle collaborative filtering with implicit feedback. However, the existing methods generally profile both users and items directly, while neglecting the similarities between users’ and items’ neighborhoods. To this end, we propose the neighborhood attentional memory networks (NAMN), a deep learning recommendation model applying two dedicated memory networks to capture users’ neighborhood relations and items’ neighborhood relations respectively. Specifically, we first design the user neighborhood component and the item neighborhood component based on memory networks and attention mechanisms. Then, by the associative addressing scheme with the user and item memories in the neighborhood components, we capture the complex user-item neighborhood relations. Stacking multiple memory modules together yields deeper architectures exploring higher-order complex user-item neighborhood relations. Finally, the output module jointly exploits the user and item neighborhood information with the user and item memories to obtain the ranking score. Extensive experiments on three real-world datasets demonstrate significant improvements of the proposed NAMN method over the state-of-the-art methods.

La famiglia di Giovanni Boccaccio nelle pergamene olivetane

The essay focuses on a documentary corpus that belonged to the San Miniato archive: the papers of Banco di Francesco Botticini, which came to the monastery at the beginning of the 15th century. Botticini’s legacy can be reconstructed in about fifty parchments (represented here in an Appendix as register or excerpt), and offers interesting evidence on the Boccaccio’s family, linked to Banco Botticini by neighborhood relations and common acquaintances. Eleven ‘Olivetan parchments’ bear references to Boccaccio and are able to show different but still close relationships: from the sincere ones with messer Giovanni to the stormy with his brother, Iacopo, up to the long-lasting bond with the Iacopo’s sons, heirs of Boccaccio, who remained in the legal guardianship of Banco Botticini for many years.

Safavid-Russian relations in the first half of the 17th century

The article discusses the diplomatic and economic nature of relations between the Safavid and Russian states in the first half of the 17th century, especially during the reign of Shah Abbas I (1587-1629). The continuation of neighborhood relations by his heirs was analyzed. Also, the geopolitical interests of both countries in the field of treasury trade and the preservation of the traditional Volga-Caspian transit trade route were studied.

New Online Streaming Feature Selection Based on Neighborhood Rough Set for Medical Data

Not all features in many real-world applications, such as medical diagnosis and fraud detection, are available from the start. They are formed and individually flow over time. Online streaming feature selection (OSFS) has recently attracted much attention due to its ability to select the best feature subset with growing features. Rough set theory is widely used as an effective tool for feature selection, specifically the neighborhood rough set. However, the two main neighborhood relations, namely k-neighborhood and neighborhood, cannot efficiently deal with the uneven distribution of data. The traditional method of dependency calculation does not take into account the structure of neighborhood covering. In this study, a novel neighborhood relation combined with k-neighborhood and neighborhood relations is initially defined. Then, we propose a weighted dependency degree computation method considering the structure of the neighborhood relation. In addition, we propose a new OSFS approach named OSFS-KW considering the challenge of learning class imbalanced data. OSFS-KW has no adjustable parameters and pretraining requirements. The experimental results on 19 datasets demonstrate that OSFS-KW not only outperforms traditional methods but, also, exceeds the state-of-the-art OSFS approaches.