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  • Analysis of Factors Affecting the Profits of Closed-Loop Supply Chain Members Under Different Subsidy Objects
  • Abstract Based on the research hypothesis in a fully competitive closed-loop supply chain for mixed recycling channels, different closed-loop supply chain pricing models are established for the government’s strategy of adopting different subsidies (consumers, retailers, manufacturers or third-party recyclers). In this work, we use game theory to establish a price formula, and identify the factors affecting the profit of five closed-loop supply chain members. Through solution verification, the sales channel pricing, the recycling channel pricing and the channel member profit change of the closed-loop supply chain under different subsidy objects are compared after changing only one influencing factor. By providing a…
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  • Research on E-Commerce Transaction Payment System Basedf on C4.5 Decision Tree Data Mining Algorithm
  • Abstract In this paper, according to the information classification algorithm in data mining, data in the network payment system of e-commerce is mined, forming an effective evaluation of the security of the network payment system. Firstly, the method of network security risk prediction is discussed. Secondly, according to the characteristics of network payment system, the system security index system is analyzed in detail, and the specific application process of the C4.5 Classification Algorithm in security evaluation is discussed. Finally, the data mining process is designed in detail and the corresponding code established. In this paper, data mining theory is applied to…
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  • Enhanced Schemes for Data Fragmentation, Allocation, and Replication in Distributed Database Systems
  • Abstract With the growth of information technology and computer networks, there is a vital need for optimal design of distributed databases with the aim of performance improvement in terms of minimizing the round-trip response time and query transmission and processing costs. To address this issue, new fragmentation, data allocation, and replication techniques are required. In this paper, we propose enhanced vertical fragmentation, allocation, and replication schemes to improve the performance of distributed database systems. The proposed fragmentation scheme clusters highly-bonded attributes (i.e., normally accessed together) into a single fragment in order to minimize the query processing cost. The allocation scheme is…
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  • Application Research of Color Design and Collocation in Image Processing
  • Abstract Color is one of the primary elements of artistic expression. Its design and collocation play a very important role in image processing. While the number of people using the Internet is increasing, more attention is being paid to the user’s experience including the color design and matching of the Internet web interface, in order to reach the color design of the web interface with image processing as the core. This thesis firstly discusses the importance of web interface color design and matching in image processing from the image processing appeal of the web interface and the color characteristics of the…
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  • Intelligent Choice of Machine Learning Methods for Predictive Maintenance of Intelligent Machines
  • Abstract Machines are serviced too often or only when they fail. This can result in high costs for maintenance and machine failure. The trend of Industry 4.0 and the networking of machines opens up new possibilities for maintenance. Intelligent machines provide data that can be used to predict the ideal time of maintenance. There are different approaches to create a forecast. Depending on the method used, appropriate conditions must be created to improve the forecast. In this paper, results are compiled to give a state of the art of predictive maintenance. First, the different types of maintenance and economic relationships are…
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  •   Views:786       Downloads:764        Download PDF
  • A Model to Create Organizational Value with Big Data Analytics
  • Abstract Value creation is a major factor not only in the sustainability of organizations but also in the maximization of profit, customer retention, business goals fulfillment, and revenue. When the value is intended to be created from Big Data scenarios, value creation entails being understood over a broader range of complexity. A question that arises here is how organizations can use this massive quantity of data and create business value? The present study seeks to provide a model for creating organizational value using Big Data Analytics (BDA). To this end, after reviewing the related literature and interviewing experts, the BDA-based organizational…
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  • Multi Level Key Exchange and Encryption Protocol for Internet of Things (IoT)
  • Abstract The burgeoning network communications for multiple applications such as commercial, IoT, consumer devices, space, military, and telecommunications are facing many security and privacy challenges. Over the past decade, the Internet of Things (IoT) has been a focus of study. Security and privacy are the most important problems for IoT applications and are still facing huge difficulties. To promote this high-security IoT domain and prevent security attacks from unauthorized users, keys are frequently exchanged through a public key exchange algorithm. This paper introduces a novel algorithm based on Elliptic Curve Cryptography(ECC) for multi-level Public Key Exchange and Encryption Mechanism. It also…
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  • Impact of Fuzzy Normalization on Clustering Microarray Temporal Datasets Using Cuckoo Search
  • Abstract Microarrays have reformed biotechnological research in the past decade. Deciphering the hidden patterns in gene expression data proffers a prodigious preference to strengthen the understanding of functional genomics. The complexity of biological networks with larger volume of genes also increases the challenges of comprehending and interpretation of the resulting mass of data. Clustering addresses these challenges, which is essential in the data mining process to reveal natural structures and identify interesting patterns in the underlying data. The clustering of gene expression data has been proven to be useful in making known the natural structure inherent in gene expression data, understanding…
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  • Enhanced GPU-Based Anti-Noise Hybrid Edge Detection Method
  • Abstract Today, there is a growing demand for computer vision and image processing in different areas and applications such as military surveillance, and biological and medical imaging. Edge detection is a vital image processing technique used as a pre-processing step in many computer vision algorithms. However, the presence of noise makes the edge detection task more challenging; therefore, an image restoration technique is needed to tackle this obstacle by presenting an adaptive solution. As the complexity of processing is rising due to recent high-definition technologies, the expanse of data attained by the image is increasing dramatically. Thus, increased processing power is…
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  •   Views:585       Downloads:547        Download PDF
  • Developing an Adaptation Process for Real-Coded Genetic Algorithms
  • Abstract The genetic algorithm (GA) is a metaheuristic method which simulates the life cycle and the survival of the fittest in the nature for solving optimization problems. This study aimed to develop enhanced operation by modifying the current GA. This development process includes an adaptation method that contains certain developments and adds a new process to the classic algorithm. Individuals of a population will be trialed to adapt to the current solution of the problem by taking them separately for each generation. With this adaptation method, it is more likely to get better results in a shorter time. Experimental results show…
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  •   Views:615       Downloads:652        Download PDF
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