Bearing-Based Network Localization Under Gossip Protocol

This paper proposes a bearing-based network localization algorithm with a randomized gossip protocol. Each sensor node is assumed to be able to obtain the bearing vectors and communicate its position estimates with several neighboring agents. Each update involves two agents, and the update sequence follows a stochastic process. Under the assumption that the network is infinitesimally bearing rigid and contains at least two beacon nodes, we show that the proposed algorithm could successfully estimate the actual positions of the network in probability. The randomized update protocol provides a simple, distributed, and reduces the communication cost of the network. The theoretical result is then supported by a simulation of a 1089-node sensor network.Comment: preprint, 7 pages, 2 figure

Impact of relations between employees and customers to the customers’ positive word-of-mouth in real estate industry

The study aims to explore and measure the relationship between employees and customers impacting positively to the word-of-mouth of customers who bought house from the real estate developers in Ho Chi Minh City. The study was based on survey data from 300 customers who bought house from the real estate developers in Ho Chi Minh City and using techniques of Cronbach Alpha analysis and Exploratory Factor Analysis (EFA). The study shows 4 factors of customer relationship affecting positively customers’ word-of-mouth, including: (1) Familiarity; (2) Personal connection; (3) Care; (4) Trust. From the findings, the study suggests some policy implications to the real estate developers to improve the customers’ positive word-of-mouth

M^2UNet: MetaFormer Multi-scale Upsampling Network for Polyp Segmentation

Polyp segmentation has recently garnered significant attention, and multiple methods have been formulated to achieve commendable outcomes. However, these techniques often confront difficulty when working with the complex polyp foreground and their surrounding regions because of the nature of convolution operation. Besides, most existing methods forget to exploit the potential information from multiple decoder stages. To address this challenge, we suggest combining MetaFormer, introduced as a baseline for integrating CNN and Transformer, with UNet framework and incorporating our Multi-scale Upsampling block (MU). This simple module makes it possible to combine multi-level information by exploring multiple receptive field paths of the shallow decoder stage and then adding with the higher stage to aggregate better feature representation, which is essential in medical image segmentation. Taken all together, we propose MetaFormer Multi-scale Upsampling Network (M$^2$UNet) for the polyp segmentation task. Extensive experiments on five benchmark datasets demonstrate that our method achieved competitive performance compared with several previous methods

Lecane (Rotifera: Lecanidae) community in psammon habitat in Central Coast Vietnam: Diversity and relation to environmental condition

Characteristics of the Lecane (Rotifera) community in psammon in Central Coast Vietnam were investigated. A total of 50 taxa were identified in samples collected at hygropsammon zones of temporary pools, contributing 4 new species to rotifers' record of Vietnam. Psammonxenic species accounted for the largest percentage of Lecane community with 82%, followed by psammophiles (12%) and psammonbionts (6%). Influences of some environmental factors on the distribution of psammic lecanids were also observed. This group of organisms showed a slight tendency towards sand with grain sizes larger than 125 µm. Besides, other abiotic factors including pH, total phosphorus (TP) and total dissolved solids (TDS) were also found to significantly related to the distribution of some common Lecane species

Parameter Estimation of LFM Signal in Low Signal-to-Noise Ratio Using Cross-Correlation Function

The pulse with intra-pulse modulation plays an important role in the design of radar systems. The first class of the signals type is the linear frequency modulation technique. The linear frequency modulation is used to resolve range resolution problems. This paper provides a new algorithm for detecting linear frequency modulation signals at a low signal-to-noise ratio. The core idea of the proposed method is firstly to analyse the linear frequency modulation signals via Fast Fourier Transform; and then to accumulate all energy to achieve signal detection using cross-correlation methods. The proposed algorithm showed better results in comparison with current algorithms, which are used to estimate the parameters of the linear frequency modulation signals at a low signal-to-noise ratio

Ownership Concentration and Accounting Conservatism: The Moderating Role of Board Independence

The purpose of this study is to examine the moderating effect of board independence on the relationship between ownership concentration and accounting conservatism. Using fixed-effect regressions for a sample of 165 Vietnamese listed companies from 2007 to 2017, the results revealed that the proportion of outstanding shares owned by the largest shareholder is negatively associated with accounting conservatism and board independence plays a moderating role in this relationship. Our results are robust after applying alternative measures of the largest ownership and correcting for potential endogeneity using fixed-effects regression with instrumental variables. Overall, our evidence shows that firms with concentrated ownership should keep a high non-executive ratio to maintain accounting conservatism. In other words, increasing the number of non-executive directors on boards in firms with a substantial proportion of shares held by the largest shareholder is likely to strengthen the information environment, giving financial reporting more credibility.JEL Classification: G30; G32. Doi: 10.28991/ESJ-2023-07-01-07 Full Text: PD

Isolation and identification of triterpenoid compounds from Couroupita guianensis Aubl.

In this report, the extracts from the fruit and leaves of Couroupita guianensis were isolated using chromatographic methods and investigated for chemical composition. Four triterpenoid compounds were isolated and identified as betulinic acid, oleanolic acid, β-amyrin and friedelin. Their chemical structures were interpreted based on modern spectra such as MS, NMR and compared with previously published spectral data