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Wireless ad hoc network nodes suffer from limited energy supply. To reduce the power consumption of the routing protocols, many routing algorithms use a subset of the nodes to participate in the routing task. For that reason, topology control for wireless ad hoc networks got great attention in recent years. Geographical locations of the network nodes are used in many topology control algorithms to enhance performance and reduce overhead. In this paper, we review the most known geographical-based topology control algorithms for Ad Hoc Networks with a focus on connectivity, locality, planarity, stretch factor, node degree, and scalability. We conduct a comparison between these algorithms as well. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of the personality characteristics of secondary school students from rural and urban areas. The study was conducted to examine whether there are significant differences in the personality characteristics of students from different geographical locations. A total of 300 students from both rural and urban areas were selected as participants for the study. The personality characteristics of the students were assessed using the Big Five Personality Traits Scale. The results of the study indicate that there are significant differences in the personality characteristics of rural and urban secondary school students. The study found that urban students scored higher on traits such as extraversion and openness to experience, while rural students scored higher on traits such as agreeableness and conscientiousness. These findings have important implications for educators and policymakers in terms of understanding the differences in personality characteristics of students from different geographical locations and designing appropriate interventions to support their academic and personal growth. [ABSTRACT FROM AUTHOR]

With the development of online real estate trading platforms, multi-modal housing trading data, including structural information, location, and interior image data, are being accumulated. The accurate appraisal of real estate makes sense for government officials, urban policymakers, real estate sellers, and personal purchasers. In this study, we propose an interpretable multi-modal stacking-based ensemble learning (IMSEL) method that deals with various modalities for real estate appraisals. We crawl the structural and image data of real estate in Chengdu city, China from the nation's largest real estate transaction platform with the location information, including public services, within 2 km of the real estate using Baidu map. We then compare the predictive results from IMSEL with those from previous state-of-art methods in the literature in terms of the root mean square error, mean absolute percentage error, mean absolute error, and coefficient of determination (R2). The comparison results show that IMSEL outperformed the other methods. We verified the improvement of introducing a data transformation strategy and deep visual features through a 10-fold cross-validation. We also discuss the managerial implications of our research findings. [ABSTRACT FROM AUTHOR]

Avocado is known to be a climacteric fruit that must be harvested during the suitable physiological maturity stage to achieve the best edible characteristics and reach the required export standards. It is very hard to visually determine the optimum maturity phases in the different avocado varieties for harvesting, especially because of the limited changes in the external fruit morphology during the maturity phase and because the harvest season is extended throughout several months. Therefore, some laboratory analyses are very crucial to determine the best timing to harvest the fruit. The aim of this study was to evaluate the postharvest maturity indices over 3 harvest stages, mainly dry matter (DM), oil content (OC), fruit firmness, titratable acidity (TA), total soluble solid (TSS/Brix), and fruit weight in commercial avocado varieties in regard to different altitudes and agricultural practices. The varieties in this study were as follows: Hass, Lambhass, Ettinger, Fuerte, Pinkerton, Reed, and Horshim growing at different altitudes that ranged from 50 to 400 m in 7 different regions in Lebanon. Statistical comparison of maturity indices under different locations by variety and harvest stage was performed using one-way ANOVA as well as by principal component analysis (PCA). The results showed a high linear correlation between DM and OC over the different harvest stages. During the late harvest stage, the weight showed a negative correlation between fruit firmness and TSS. The minimum oil content % and dry matter % were recorded for Reed variety (8.2 DM and 9.7 OC%) and the highest oil content % and dry matter % were recorded for Fuerte variety (28.5 DM and 21.6 OC%). The data obtained during this study are used to achieve the best edible characteristics and export standards of commercial avocado varieties growing along the Lebanese coast. [ABSTRACT FROM AUTHOR]