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Volume 10 Issue 03 (March 2023)

S.No. Title & Authors Page No View
1

Title : The Impact of Innovation on Export Performance: Evidence from Morocco

Authors : Sara El Behja

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Abstract :

This study examines the impact of innovation on export performance in Moroccan export companies. A survey was distributed online to export department employees from different Moroccan export businesses in various industries, and a total of 180 responses were collected. The survey data was analyzed using descriptive statistics, correlation, and regression analysis in SPSS. The results indicate a significant positive link between innovation and export performance in Moroccan export companies. The findings suggest that innovation plays a crucial role in enhancing the export performance of Moroccan export companies, highlighting the importance of investing in innovation as a strategy for achieving a competitive advantage in international markets. The study contributes to the literature by providing empirical evidence of the impact of innovation on export performance in an emerging market context. It provides policymakers and export managers with insights into enhancing their firms' export performance through innovation.

1-6
2

Title : Graph Clustering of Social Networks on Map Reduce

Authors : Jinyu Zhou

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Abstract :

Graph clustering is an important technique in graph data mining. It plays an important role to reveal community clusters, hubs and outliers in social networks. There are several graph clustering algorithms have been proposed based on the SCAN algorithm. For large graph, SCAN and its improved algorithms are slow due to the limitations on a single node. Therefore, in this paper, we proposed a graph clustering algorithm based on SCAN using the widely used MapReduce framework on social networks. Moreover, we conducted experiments on real world data sets to justify the feasibility of the proposed graph clustering algorithm.

7-9
3

Title : Research on the Privacy-Preserving Method of Medical Data Based on Blockchain

Authors : Kaili Lu, Haiyan Kang

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Abstract :

With the continuous development and progress of big data technology, the storage and sharing of information-based medical data has greatly promoted the development of medical treatment. However, the information systems of most medical institutions use their own independent centralized storage methods, which makes it difficult to carry out efficient data interconnection between medical institutions and brings inconvenience to patients' cross-institution treatment. On the other hand, when the server is attacked by criminals, some important data is likely to be leaked, and then a series of chain problems such as private information being illegally sold are produced. Blockchain technology has the characteristics of decentralization, tamper-proof, traceability and so on, which can ensure that the system has good robustness and data security, and can solve the problem of data privacy security. Therefore, the medical data privacy protection platform based on blockchain technology will play a huge role in medical data security.

10-15
4

Title : Application of Operations Research in Training Binary Neural Networks

Authors : Zhang Xian

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Abstract :

In this paper, a binary neural network training (BNNs) method, namely in the runtime binary weight and activation functions of neural network. Inspired by training the network method solving 0-1 integer programming problems in operations research. In training, the binary weight and activation parameters used to compute the gradient. In the process of the forward pass, BNN greatly reduces the memory size and access, and will be most arithmetic for bitwise operations, it is expected to significantly improve energy efficiency.

16-18
5

Title : Investigating the Determinants of Transfer Passengers Compliance to Route Guidance Information in Metro Stations

Authors : Chen Zhang, Xiaokun Wang, Caixia Chen

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Abstract :

Congestion often occurs in interchange stations of urban rail transit in China. Guidance information is often used to alleviate the congestion of facilities and routes in subway stations. But, most of them are static guidance signs and staff guidance, which can't show the service ability of each transfer route. And, while grasping the determinants of passengers compliance to the guidance information, it can satisfy passengers preferences for guidance information and optimize the attributes of guidance information. However, the determinants of passengers compliance to the guidance information are rarely studied, and the uniqueness of guidance information in the urban rail transit is justified. Therefore, we analyze the key factors of passengers' compliance to the guidance information at the metro interchange station. An empirical study using samples from Xi'an Road Subway Station in Dalian was conducted, and survey data were collected via the Internet. Specifically, respondents social demographic data and travel attribute variables are obtained, and their preferences for the content, release channel and release cycle of route guidance information are obtained. On this basis, an ordinal logistic model and partial proportional odds model were estimated to investigate the key factors of passengers compliance to the guidance information. The results show that the partial proportional odds model provides the best statistical fit. Then, based on the results of the partial proportional odds model, the significant results of the determinants are obtained. Furthermore, for the elasticity analysis of determinants, we find that social demographic (e.g., gender, age, occupation, and weight of luggage) and travel attributes (e.g., travel purpose, number of people traveling together, number of station passes per week, and familiarity with the station) have a significant impact on passengers compliance of route guidance information. Additionally, the preference for the content, release channel and release cycle of route guidance information have a significant and positive impact on passengers compliance of route guidance information.

19-31