A revolution is taking place in the marketing field. this paper explores the application of collaborative filtering algorithm (CFA) in the refined push of marketing big data, and studies whether this method can improv...
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ISBN:
(数字)9798331533663
ISBN:
(纸本)9798331533670
A revolution is taking place in the marketing field. this paper explores the application of collaborative filtering algorithm (CFA) in the refined push of marketing big data, and studies whether this method can improve the effect and efficiency of personalized marketing. In order to solve the problem of refined push based on marketing big data, this paper first conducts in-depth mining of users' historical behavior data, and then uses tools such as Pandas to conduct multi-dimensional analysis of different types of users based on these preferences. In addition, this paper uses distributed architectures such as HDFS storage system and MapReduce computing framework, and calls artificial intelligence algorithms such as machine learning to complete the refined push of marketing data. the collaborative filtering algorithm performs well in personalized marketing effects, withthe highest effect score reaching 95.92 points, and the accuracy of CFA can reach up to 96.19%.
Recent years saw an increase in voting systems using public permissionless blockchains. Although public blockchains offer transparency and immutability, permissioned consensus is better suited for voting systems' ...
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ISBN:
(纸本)9781665495387
Recent years saw an increase in voting systems using public permissionless blockchains. Although public blockchains offer transparency and immutability, permissioned consensus is better suited for voting systems' requirements, because an initial level of trust in authorities is always required. Hence, a permissioned distributed Ledger (DL) immutably storing the voting system's audit trail satisfies demands measurably. ProvotuMN 3.0 is a decentralized and receipt-Free (RF) voting system based on an end-to-end verifiable Re-Encryption Mixnet (RMN). RMNs allow for flexible votes and elections and decouple the ballot structure from the cryptographic voting protocol. thus, ProvotuMN decentralizes trust (i) through the use of cryptographic shuffles and Non-Interactive Zero-Knowledge Proofs (NIZKP) in an RMN executed among DL nodes, (ii) by employing a distributed key generation for election keys, and (iii) by offering a decentralized re-encryption service assuring RF. Performance evaluations performed indicate that the voting scheme is scalable for large-scale voting.
In this paper, distributed plug-and-play (PnP) optimization control method for interconnected industrial processes is studied. Due to the influence of information interaction between subsystems, the performance of eac...
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Wireless sensor Networks (WSN) have emerged as a key technology with a wide range of possible applications. In routing methods that are specifically intended for wireless sensor network applications. An major routing ...
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the new paradigm edge computing demonstrates significant advantages in quality of service including low latency and bandwidth efficiency when deployed in autonomous vehicle applications. However, deploying edge comput...
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Vibration monitoring uses data gathered from accelerometers to study kinetic phenomena in applications such as: structural health monitoring and predictive maintenance. the Internet of things (IoT) has the potential t...
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ISBN:
(纸本)9781665439299
Vibration monitoring uses data gathered from accelerometers to study kinetic phenomena in applications such as: structural health monitoring and predictive maintenance. the Internet of things (IoT) has the potential to greatly expand the range and scope of vibration monitoring applications by delivering long-life wireless sensors that can be cost-effectively embedded in hard to reach places such as;within machines, infrastructure or the built environment. However, achieving this vision is difficult due to the stringent resource constraints of contemporary IoT devices and networks. this has led the research community to develop a creative range of application-specific near-sensor processing firmware. However, systematic support for generic vibration monitoring on resource-poor IoT networks remains an open problem. We tackle this challenge by introducing ReFrAEN, a software framework that efficiently enables a wide range of vibration monitoring applications on IoT networks. ReFrAEN achieves this through a deeply configurable combination of compression techniques and data processing algorithms. these features allow end-users to effectively trade-off between resource consumption and data resolution in order to meet battery life constraints while preserving sufficient data quality to support the target application. Our evaluation shows that ReFrAEN is capable of identifying bearing faults, while dramatically improving battery lifetime and reducing latency in comparison to prior approaches.
Traffic sign recognition (TSR) is a key aspect involved in the development of robust automated transportation systems. It inherently involves the task of traffic sign detection (TSD), which can be challenging due to t...
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ISBN:
(纸本)9781665439299
Traffic sign recognition (TSR) is a key aspect involved in the development of robust automated transportation systems. It inherently involves the task of traffic sign detection (TSD), which can be challenging due to traffic signs often being subject to deterioration or occlusion, caused by various environmental factors, or through actions of vandalism. Even though, notable advancements have been achieved in the areas of TSR and TSD, few studies have provided robust algorithms, able to be generalized in real-world applications. this mostly stems from the lack of an extensive traffic sign dataset, standardized for benchmarking purposes. In light of the aforementioned, this paper presents a novel traffic sign dataset, which consists of the Carla Traffic Sign Detection (CTSD), and the Carla Traffic Sign Recognition Dataset (CATERED), targeting the detection and recognition processes respectively. Using the proposed dataset for training and evaluation, a deep Auto-Encoder algorithm is presented, demonstrating high accuracy in detecting and recognizing the distorted traffic signs. Finally, the system is further extended to a federated learning environment, exemplifying its applicability in modern decentralized and interconnected architectures.
the distributed power flow controller (DPFC) works to increase or reduce the reactance of the transmission line by injecting series compensation voltage. the DPFC control system, including DPFC centralized control dev...
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the distributed structure of wireless communication along the decentralized structure of vehicular ad hoc networks makes them susceptible to attacks. the reduction of attacks by providing safety is the ...
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this paper investigates an extended Kalman filter-based barometer and IMU fusion floor localization method, aiming to solve the problem of precise floor localization for mobile robots that need to take elevators. By e...
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