Application of Artificial Intelligence in an Unsupervised Algorithm for Trajectory Segmentation Based on Multiple Motion Features

With the development of the wireless network, location-based services (e.g., the place of interest recommendation) play a crucial role in daily life. However, the data acquired is noisy, massive, it is difficult to mine it by artificial intelligence algorithm. One of the fundamental problems of trajectory knowledge discovery is trajectory segmentation. Reasonable segmentation can reduce computing resources and improvement of storage effectiveness. In this work, we propose an unsupervised algorithm for trajectory segmentation based on multiple motion features (TS-MF). The proposed algorithm consists of two steps: segmentation and mergence. The segmentation part uses the Pearson coefficient to measure the similarity of adjacent trajectory points and extract the segmentation points from a global perspective. The merging part optimizes the minimum description length (MDL) value by merging local sub-trajectories, which can avoid excessive segmentation and improve the accuracy of trajectory segmentation. To demonstrate the effectiveness of the proposed algorithm, experiments are conducted on two real datasets. Evaluations of the algorithm’s performance in comparison with the state-of-the-art indicate the proposed method achieves the highest harmonic average of purity and coverage.

IMPLEMENTASI MOODLE SEBAGAI MEDIA PEMBELAJARAN JARAK JAUH

This study aims to determine the results of implementing the Moodle application as a distance learning medium for students who cannot do face-to-face learning, due to the COVID-19 pandemic. This type of research is a qualitative descriptive with a frequency distribution, which is concluded based on the data obtained during the study. The sample studied was 21 students. The results of the study found that there were 16.9% of students answered strongly agree; 45.5% of students answered agree; 30.7% of students answered disagree; 6.9% of students answered strongly disagree. Some students who answered disagreed or strongly disagreed had problems, namely not having a cellphone/laptop, unstable internet network, and expensive data packages. Educators must carefully prepare the material to be delivered and students must look for a stable network location. In conclusion, using Moodle as a distance learning medium is very effective, to support learning activities that cannot be carried out during the COVID-19 pandemic. The availability of infrastructure is very necessary so that learning objectives can be realized.

Financial Security Analysis of E-Commerce Platform Based on Supply Chain for Heterogeneous Network Location Verification

The development of supply chain finance, its pricing strategy for bilateral business cooperation between e-commerce, banking institutions, and fourth-party logistics services providers has gained the attention of researchers. This paper combines the heterogeneous network location verification technology, starting from information asymmetry and Rubens bargaining game ideas, and combines it with game theory methods to provide a reference for bilateral cooperation decision-making on e-commerce platforms. The experiment results indicated the pricing decisions of e-commerce platforms which are affected by the efforts of the other party and the ability of bargaining. The quoted price increases with the decrease of the bank’s ability and the increase of the service provider’s ability. The pricing decisions of banks and service providers are only affected by the direct proportion of their respective business costs. When considering the introduction of incentive mechanism conditions, it is found that appropriate incentive conditions can increase the quotation of the e-commerce platform. The price quoted by the e-commerce platform that chooses to bargain with the bank is higher than the price quoted by the bank after negotiating with the service provider, which will help to better realize the benefits. Finally, the paper numerically analyzes the results of the bargaining game between e-commerce platforms and banks and fourth-party logistics service providers, and the numerical results verify the better performance.

Logistics Distribution Location Algorithm Based on Improved Imperial Competition Algorithm

To solve the problems of warehouse explosion and delay of logistics distribution network under the sudden explosion of demand on “double 11” and “618,” this paper proposes a logistics distribution network location algorithm that can consider reliability, green environmental protection, and path optimization. Firstly, the transportation model of logistics distribution network location-route optimization is established. Under the condition that the transportation model satisfies the vehicle path reliability constraint, it can minimize the total cost, including logistics distribution cost, transportation oil consumption, and CO2 emission cost. This paper designs an improved imperial competition algorithm to solve it according to the characteristics of the transportation model. Firstly, the competition mechanism of “United Lian Heng” was introduced in the initial national stage, enhancing the information exchange and retaining the superior population. Secondly, in the process of empire assimilation, we can learn from the colonial rule strategy, which is gradually infiltrated and assimilated by all levels of the country to enhance the development ability of the algorithm. Finally, the algorithm designs a mechanism to judge and jump out of local optimum, so as to avoid “premature” affecting the optimization performance. The rationality of the model and the effectiveness of the improved imperial competition algorithm are verified by simulation experiments of different scales, while the influence of reliability level is analyzed. Experimental results show that the proposed method can effectively solve problems of different scales and maintain stable performance under different reliability levels. Moreover, its algorithm performance is better than that of the standard imperial competition algorithm.

Research on LRP Integration of E-Commerce Logistics under the Background of Integration of Collection and Distribution

The distribution network composed of location and route is an important part of e-commerce logistics. With the continuous improvement of e-commerce requirements for logistics level, the practice of planning logistics network only from the perspective of the network location or the vehicle route can no longer meet the actual demand. In addition to the comprehensive consideration of the location-routing problem, the reverse logistics caused by customers’ returning goods should be taken into account. In this paper, the destruction and reorganization strategy of adaptive large-scale neighborhood search algorithm was introduced into the traditional genetic algorithm, so as to conduct research on the logistics location-routing problem under the background of integration of collection and distribution. Finally, the effectiveness of the optimized genetic algorithm was verified by Matlab tools and the existing bench-marking data set of the location-routing problem, which provided reference for the planning and decision-making of logistics enterprises.

Metabolic Signaling in a Theoretical Model of the Human Retinal Microcirculation

Impaired blood flow and oxygenation contribute to many ocular pathologies, including glaucoma. Here, a mathematical model is presented that combines an image-based heterogeneous representation of retinal arterioles with a compartmental description of capillaries and venules. The arteriolar model of the human retina is extrapolated from a previous mouse model based on confocal microscopy images. Every terminal arteriole is connected in series to compartments for capillaries and venules, yielding a hybrid model for predicting blood flow and oxygenation throughout the retinal microcirculation. A metabolic wall signal is calculated in each vessel according to blood and tissue oxygen levels. As expected, a higher average metabolic signal is generated in pathways with a lower average oxygen level. The model also predicts a wide range of metabolic signals dependent on oxygen levels and specific network location. For example, for high oxygen demand, a threefold range in metabolic signal is predicted despite nearly identical PO2 levels. This whole-network approach, including a spatially nonuniform structure, is needed to describe the metabolic status of the retina. This model provides the geometric and hemodynamic framework necessary to predict ocular blood flow regulation and will ultimately facilitate early detection and treatment of ischemic and metabolic disorders of the eye.

Information-Centric Networking Cache Placement Method Based on Cache Node Status and Location

Information-Centric Networking with caching is a very promising future network architecture. The research on its cache deployment strategy is divided into three categories, namely, noncooperative cache, explicit collaboration cache, and implicit collaboration cache. Noncooperative caching can cause problems such as high content repetition rate in the web cache space. Explicit collaboration caching generally reflects the best caching effect but requires a lot of communication to satisfy the exchange of cache node information and depends on the controller to perform the calculation. On this basis, implicit cooperative caching can reduce the information exchange and calculation between cache nodes while maintaining a good caching effect. Therefore, this paper proposes an on-path implicit cooperative cache deployment method based on the dynamic LRU-K cache replacement strategy. This method evaluates the cache nodes based on their network location and state and selects the node with the best state value on the transmission path for caching. Each request will only select one or two nodes for caching on the request path to reduce the redundancy of the data. Simulation experiments show that the cache deployment method based on the state and location of the cache node can improve the hit rate and reduce the average request length.