ON THE ROLE OF MATRIX-WEIGHTS ELEMENTS IN CONSENSUS ALGORITHMS FOR MULTI-AGENT SYSTEMS

This paper extends the concept of weighted graphs to matrix weighted graphs. The consensus algorithms dictate that all agents reach consensus when the weighted graph is connected. However, it is not always the case for matrix weighted graphs. The conditions leading to different types of consensus have been extensively analysed based on the properties of matrix-weighted Laplacians and graph theoretic methods. However, in practice, there is concern on how to pick matrix-weights to achieve some desired consensus, or how the change of elements in matrix weights affects the consensus algorithm. By selecting the elements in the matrix weights, different clusters may be possible. In this paper, we map the roles of the elements of the matrix weights in the systems consensus algorithm. We explore the choice of matrix weights to achieve different types of consensus and clustering. Our results are demonstrated on a network of three agents where each agent has three states.

Industrial Agglomeration Analysis Based on Spatial Durbin Model: Evidence from Beijing-Tianjin-Hebei Economic Circle in China

Based on the data of Beijing-Tianjin-Hebei Economic Circle from 2010 to 2019, this paper uses the spatial Durbin model to empirically analyze the impact of financial development and technological innovation on industrial agglomeration. The following are the conclusions of this study: (1) financial development has a positive effect on industrial agglomeration; however, a significant difference exists in the weight effect of the geographic distance matrix compared to the weight of the economic distance matrix; (2) in the spatial Durbin model with two matrix weights, technological innovation has a significant positive effect on industrial agglomeration; and (3) in the spatial Durbin model with two matrix weights, the interaction has a significant negative effect on industrial agglomeration. Therefore, the government should further implement the coordinated development strategy, promoting regional technological innovation for a long time to realize its integration with financial development.

EVALUATING THE PERFORMANCE OF COLOMBIAN BANKS BY HYBRID MULTICRITERIA DECISION MAKING METHODS

The aim of the study in this paper is to show how the performance of banks can be evaluated by ranking them based on Balanced Scorecard (BSC) and Multicriteria Decision Making (MCDM) methods. Nowadays, assessing the performance of companies is a vital work for finding their weaknesses and strengths. The banking sector is an important area in the service sector. Many people want to know which bank performs best when entrusting their money to them. For assessing the performance of banks, BSC can be used. This method helps to translate strategic issues to meaningful insights for the respective financial institutions. After that, the banks will be ranked based on performance indicators by the Weighted Aggregated Sum Product Assessment (WASPAS) method. Because this method is based on a decision matrix, weights are required. To find such weights, the Step-wise Weight Assessment Ratio Analysis (SWARA) method is applied. The results show that the International Bank of Colombia has a much better performance than other Colombian banks. Besides, further insights regarding the evaluation process based on BSC, SWARA, and WASPAS are obtained.

IMPROVEMENT IN PRODUCTIVITY OF INCUBATION OF THERMAL HANDLING OF EGGS OF DISTINCT LIGHT MATRIX WEIGHTS

The objective of the experiment was to evaluate the influence of thermal manipulation on the improvement of hatching eggs of different weights of light matrices in the last embryonic stage. The experiment was carried out in a commercial hatchery of light laying hens, located in Birigui - SP, Brazil. 1950 light-colored eggs of the Dekalb White commercial strain were used. The eggs were classified among different sizes and n in incubation trays. In the period from 19 to 21 days, two incubator machines were used, where the first machine maintained the temperature and humidity values of the hatchery's standard air (37.0 ° C and 60% RH) and in the second machine the temperature was adjusted to 37.7 ° C with 60% RH. The treatments differed according to the residence time in the second machine, and egg weight (G and M) controls T1 (0h-G) and T6(0h-M), 1 hour T2(1h-G) and T7(1h-M), 3 hours T3(3h-G) and T8(3h-M), 6 hours T4(6h-G) and T9(6h-M) 9 hours T5(9h-G) and T10 (9h-M). The design was completely randomized, in a 2X5 factorial scheme. Regarding thermal stimulation, the best results were observed in the 1h-G treatment. However, in the productive life of these birds, the thermal stimulation showed no influence. Concluded that for large eggs (G), the residence time of 1 hour (T2), obtained a better index of commercially viable females and lower rates of late-stage embryo mortality and shelter.

Variability and Reproducibility of Directed and Undirected Functional MRI Connectomes in the Human Brain

A growing number of studies are focusing on methods to estimate and analyze the functional connectome of the human brain. Graph theoretical measures are commonly employed to interpret and synthesize complex network-related information. While resting state functional MRI (rsfMRI) is often employed in this context, it is known to exhibit poor reproducibility, a key factor which is commonly neglected in typical cohort studies using connectomics-related measures as biomarkers. We aimed to fill this gap by analyzing and comparing the inter- and intra-subject variability of connectivity matrices, as well as graph-theoretical measures, in a large (n = 1003) database of young healthy subjects which underwent four consecutive rsfMRI sessions. We analyzed both directed (Granger Causality and Transfer Entropy) and undirected (Pearson Correlation and Partial Correlation) time-series association measures and related global and local graph-theoretical measures. While matrix weights exhibit a higher reproducibility in undirected, as opposed to directed, methods, this difference disappears when looking at global graph metrics and, in turn, exhibits strong regional dependence in local graphs metrics. Our results warrant caution in the interpretation of connectivity studies, and serve as a benchmark for future investigations by providing quantitative estimates for the inter- and intra-subject variabilities in both directed and undirected connectomic measures.