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检索条件"主题词=software algorithms"

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Comparison of C4.5 algorithms and Naive Bayes In Measuring Customer Satisfaction in Airlines

Comparison of C4.5 Algorithms and Naive Bayes In Measuring C...

引用

Advanced Information Scientific Development (ICAISD), International Conference on

作者： Luthfi Ainiya Putri Rahayu Ningsih Sinta Rukiastiandar Minda Septiani Wati Erawati Sigit Wibawa Information Technology Bina Sarana Informatika University Jakarta Indonesia

ISBN: (数字)9798350392036

ISBN: (纸本)9798350392043

The various activities of daily life cannot be separated from dependence on modes of transportation. Air transportation is one of the most important modes of transport. The airline industry is the one that acts as an air transportation service provider. As service providers, it is very important for them to pay attention to customer satisfaction. In 2023, the highest complaint of users as much as 56% was caused by lost luggage. On an average, other passenger complaints are caused by aircraft delays, operational reasons, and long transit times. Knowing the level of customer satisfaction can be used as a preference for improving service quality, so that customer loyalty that has been obtained can be maintained. The level of customer satisfaction on airlines can be determined by applying the C4.5 and Naïve Bayes algorithms, as well as the help of Rapidminer software. The C4.5 algorithm was chosen because it can present a large amount of data, which then results in a decision tree. The Naïve Bayes classification method was chosen because it is assumed to have the best performance compared with other types of classification methods. The data attributes used in this study included satisfaction level, age, class, flight distance, seat comfort, food and beverages, gate location, in-flight Wi-Fi service, ease of online booking, in-flight service, baggage handling, check-in service, cleanliness, and online boarding service. The results of this study indicate that the accuracy level of the C4.5 algorithm produces a better value than Naïve Bayes, with an accuracy difference of 4.94%; therefore, it can be concluded that the C4.5 algorithm is the best method for measuring the level of airline customer satisfaction.

关键词： Accuracy Customer satisfaction software algorithms Logic gates software Bayes methods Classification algorithms Delays Wireless fidelity Airline industry

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Intelligent Operation and Maintenance Method of Zone Area Based on Machine Learning Expert Model

Intelligent Operation and Maintenance Method of Zone Area Ba...

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Artificial Intelligence and Automation Control (AIAC), International Conference on

作者： Moxin Ju Lijun Liu Zhaorui Liu Chunyu Zhan Qiang Ding Yanrong Tao Center of State Grid Jilin Electric Power Co. LTD. Changchun China Marketing Service Center of State Grid Jilin Electric Power Co. LTD. China State Grid Siping Power Supply Company. Changchun China

ISBN: (数字)9798331529147

ISBN: (纸本)9798331529154

Acquisition operations closed-loop management system as electricity information acquisition system output work unified export, established the acquisition operations standardization online control process, standardize the abnormal processing link, however with the complex business scenarios and work order processing timeliness requirements, homework redundancy, receive task source, lack of effective invalid business data filtering means, a large number of high mechanical, repetitive task consumes a lot of human resources, limit the operational efficiency and quality of further improve, need to improve acquisition operations closed loop automation analysis and intelligent auxiliary ability. Therefore, this paper puts forward a kind of intelligent operations method and device based on machine learning expert model of the area, first based on logical regression machine algorithm, learning the users behavior habits and daily work focus on index data, realize focus on index refining, electricity abnormal monitoring, equipment fault warning, and then according to the probability of the output of logical regression algorithm intelligent generate work order, finally usingRobotic Process Automation software in accordance with the rules to realize data acquisition, work order generation and processing of automation, improve the automation level. Effectively promoted the transformation of the management mode from extensive to refined, and the duration of closed-loop work order processing increased by 49.4%.

关键词： Analytical models Automation Machine learning algorithms Filtering Electricity software algorithms Process control Machine learning Indexes Business

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Application of Mode Filtering in Near-Field Measurements

Application of Mode Filtering in Near-Field Measurements

引用

International Symposium on Antennas, Propagation and EM Theory (ISAPE)

作者： Zhipeng Zhang Mingwei Hu Bing Wei School of Physics Xidian University Xi'an China

ISBN: (数字)9798350353129

ISBN: (纸本)9798350353136

This paper briefly introduces the theory of planar near-field measurement and applies cylindrical mode filtering to correct errors in planar near-field measurements. This method decomposes the far-field pattern obtained from planar near-field measurements into cylindrical wave modes. By exploiting the spatial constraint relationship between the cylindrical wave spectrum and the tested antenna, scattering components are filtered out. Finally, the processed far-field pattern is obtained through cylindrical wave spectrum to far-field transformation. By measuring a horn antenna, the algorithmically processed directional pattern is compared with the pattern from simulation software. The results indicate that the algorithm effectively reduces the impact of scattering errors on the far-field pattern.

关键词： Antenna measurements Antenna theory Horn antennas Measurement uncertainty software algorithms Scattering Transforms software Filtering theory software measurement

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Dynamic Orchestration of Service Function Chaining for Multi-user Augmented Reality

Dynamic Orchestration of Service Function Chaining for Multi...

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IEEE Conference on Network Function Virtualization and software Defined Networks (NFV-SDN)

作者： Rodrigo Flexa Hugo Santos Matheus Brito Torsten Braun Eduardo Cerqueira Denis Rosário Federal University of Pará (UFPA) Brazil State University of Pará (UEPA) Brazil Universität Bern Switzerland

ISBN: (数字)9798350380538

ISBN: (纸本)9798350380545

Future media delivery includes immersive applications using augmented reality (AR) technologies, which mix virtual elements into physical reality. This technological trend innovates the experience of online services and content, with interactions between parallel digital worlds. However, the channel for delivering this technology has challenges in meeting the requirements for correct operation, such as correct and timely allocation of processing and memory and respecting energy consumption. Multi-User Augmented Reality (MUAR) service employs multi-access edge computing for collaborative 3D interactions on mobile devices. Service Function (SF) chains contain this service across edge servers to enable partial SF sharing among users with similar views. We propose the dynamic multi-criteria and mobility-aware Orchestration of SF Chains for Immersive Multi-user applications called OSCIM, which minimizes SF chaining instantiation costs with partial SF sharing while maintaining strict computational demands of MUAR services. Results indicate that OSCIM enhances session acceptance, resource efficiency, and latency compared to existing methods.

关键词： Energy consumption Costs Three-dimensional displays Service function chaining Heuristic algorithms software algorithms Resource management Servers Augmented reality Resilience

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Optimization of Iterative Physical Optics Method through CPU-GPU Heterogeneous Technology

Optimization of Iterative Physical Optics Method through CPU...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Qian Cao Yuanguo Zhou Qiang Ren Minxuan Li College of Communication and Information Engineering Xi’an University of Science and Technology Xi’an China School of Electronic and Information Engineering Beihang University Beijing China China Electronic Product Reliability and Environmental Testing Institute Guangzhou China

ISBN: (数字)9798350355581

ISBN: (纸本)9798350355598

With the rapid advancement of radar technology, electromagnetic simulation has found widespread applications across various fields. When solving for the Radar Cross Section (RCS) of electrically large scattering bodies using the Iterative Physical Optics Method (IPO), the number of unknowns is significant, leading to substantial memory usage and computation time. To address this issue, this paper constructs an IPO method based on parameter space for computing the RCS of electrically large radar targets and introduces CUDA parallel computing (Compute Unified Device Architecture) technology to achieve parallel computation on heterogeneous CPU-GPU platforms. Compared with commercial software, a speedup of 137.79× is achieved on an NVIDIA GeForce RTX 3050 GPU. The exemplary results demonstrate the feasibility and efficiency of the CPU-GPU heterogeneous parallel IPO algorithm, enabling the resolution of scattering problems for electrically large targets that previously could only be tackled on high-performance computers or computer clusters.

关键词： Computers Radar cross-sections Spaceborne radar software algorithms Physical optics Graphics processing units Clustering algorithms Parallel processing software Radar applications

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Servo Drive with PWM Controller Simulation

Servo Drive with PWM Controller Simulation

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Annual Siberian Russian Workshop on Electron Devices and Materials (EDM)

作者： Vladislav D. Popov Yuriy V. Shornikov Dmitry N. Dostovalov Department of Automated Control Systems Novosibirsk State Technical University Novosibirsk Russia Department of Automated Control Systems Novosibirsk State Technical University Institute of Automation and Electrometry of the Siberian Branch of the Russian Academy of Sciences Novosibirsk Russia

ISBN: (数字)9798350389234

ISBN: (纸本)9798350353051

The simulating of a servo drive with symmetrical pulse width controlling is implemented by the ISMA platform. This task is classified as an event-continuous or hybrid system. Since the dynamic processes can be event-driven, the finite-state machine notation by D. Harel (statechart as formalism) is applied to build a mathematical model for the problem. The statechart with three states complying the Cauchy problem is designed, predicates for directed transitions, as well as states equations are defined. The original LISMA language, combining both block and textual coding, which allows to form compact models that correspond bijectively to statechart formalism used for event-driven continuous systems, is applied. A fragment of the LISMA language grammar for determining the states and transitions of hybrid systems is presented. The designed ISMA software is resolved by original explicit and semi-explicit numerical methods with the asymptotic algorithm for event detection, included to the ISMA library. Computer experiments demonstrate good results with sufficient accuracy.

关键词： Analytical models Computational modeling software algorithms Pulse width modulation Mathematical models software Libraries

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GNU Radio-Based SSK MIMO System: From Concept to Reality

GNU Radio-Based SSK MIMO System: From Concept to Reality

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International Conf on Electrical and Electronic Engineering (ICEEE)

作者： Raed Mesleh Omar Hiari Ayat Alolimat Mustafa Shawaqfeh Princess Sumaya University for Technology Amman Jordan Computer Engineering Department German Jordanian University Amman Jordan Electrical Engineering Department German Jordanian University Amman Jordan

ISBN: (数字)9798350362541

ISBN: (纸本)9798350362558

The inherent characteristics of space shift keying (SSK) had generated substantial research interest in the domain of multiple-input multiple-output (MIMO) systems, resulting in the development of hardware-based implementations. With the emergence of software-defined radio (SDR) technologies, radios could be implemented through software solutions. One prominent open-source SDR toolkit, GNU Radio, offered a comprehensive suite of signal processing blocks tailored for this purpose. In this study, a 2 × 2 SSK MIMO system was implemented using GNU Radio, inclusive of the deployment of advanced algorithms on a commercially available SDR platform for real-time transmission and reception. To assess the effectiveness of the implementation, meticulous comparisons were made between measurement results and simulation outcomes, revealing a high degree of accuracy in matching for a Rician fading channel characterized by a $K$ -factor of 2.5.

关键词： software algorithms Rician channels Signal processing algorithms Signal processing Transceivers software Real-time systems Trajectory Synchronization software radio

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Utilization of Deep Learning and Machine Learning algorithms in Detection, Segmentation, and Classification of Brain Metastasis: A Systematic Literature Review

Utilization of Deep Learning and Machine Learning Algorithms...

引用

IoT, Communication and Automation Technology (ICICAT), International Conference on

作者： Deepinder Kaur Jaspreet Singh Department of CSE Chandigarh University Mohali

ISBN: (数字)9798350368109

ISBN: (纸本)9798350368116

One-tenth to around a quarter of cancer patients lose their lives to Brain Metastasis (BM) globally. Accurate neuroimaging of BM is essential to encourage early detection, decide treatment options, and increase survival rates. This systematic literature review (SLR) examines the utilization of machine/deep learning algorithms and imaging modalities in the detection, segmentation, and classification of BM. The study adheres to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis Statement) and meticulously evaluates 32 relevant articles spanning from 2018 to 2023. The investigation explores scholarly databases including Google Scholar, SCOPUS, Web of Science, PubMed, SCISPACE, IEEE, Science Direct, Hindawi, and EBSCOhost to pull out relevant studies. The four aspects viz. employment of various imaging modalities, utilization of machine/deep learning algorithms, evaluation of performance metrics, and investigation of software tools for the identification of BM considered in this study. The review identifies Convolutional Neural Networks (CNN) as the most frequently utilized algorithm with the highest AUC-ROC (0.98) and demonstrates its efficacy for BM detection. Furthermore, out of 32, 15 articles highlight the significance of contrast-enhanced T1weighted images (T1CE/ T1c). This SLR unearths the transformative impact of machine/deep learning algorithms and emphasizes the importance of imaging modalities for enhancing the accuracy of diagnostics.

关键词： Deep learning Image segmentation Machine learning algorithms Accuracy software algorithms Imaging Metastasis Classification algorithms Convolutional neural networks Systematic literature review

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Implementation of Hyperparameter Tuning Random Forest Algorithm in Machine Learning for SDN Security: An Innovative Exploration of DDoS Attack Detection

Implementation of Hyperparameter Tuning Random Forest Algori...

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Artificial Intelligence, Blockchain, Cloud Computing, and Data Analytics (ICoABCD), International Conference on

作者： Hijrah Nisya Sofia Naning Hertiana Yudha Purwanto School of Electrical Engineering Telkom University Bandung Indonesia

ISBN: (数字)9798350368451

ISBN: (纸本)9798350368468

software Defined Network (SDN) represents a novel approach to network programming for the design, construction, and administration of computer networks. This approach entails the separation of the control plane from the data plane, with the objective of centralizing the network and consolidating all settings in the control plane. Network design frequently encounters challenges pertaining to network security and network attacks. SDN offers a number of advantages. One such advantage is that it allows the implementation of control functions at the controller level, thus positioning the controller as a key element of SDN. The centralized nature of SDN renders it susceptible to attacks, including Distributed Denial of Service (DDo $S$ ) attack. Consequently, a security system is required to address the issue of attacks directed towards the SDN controller. DDoS attack detection system is created using a machine learning algorithm, namely Random Forest, whose algorithm performance is optimized using Hyperparameter Tuning to achieve high accuracy in the detection process. The InSDN dataset, comprising a total of 56 classes, was employed in this research, and the SelectFromModel feature selection method was utilized to identify crucial features within the InSDN dataset. The method was found to be effective in detecting DDoS attacks, with an accuracy value of 99.99%. The results demonstrate that Hyperparameter Tuning Random Forest is an effective method for detecting DDoS attacks on SDN.

关键词： Machine learning algorithms Accuracy software algorithms Programming Network security Denial-of-service attack software defined networking Computer crime Tuning Random forests

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Development of Intelligent Ground Control Station and Autopilot Architectures for UAVs and UGVs

Development of Intelligent Ground Control Station and Autopi...

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IEEE Signal Processing and Communications Applications (SIU)

作者： Emre Çintaş Barış Özyer Bilgisayar Mühendisliği Bölümü Atatürk Üniversitesi Erzurum Türkiye Bilgisayar Mühendisliği Bölümü Erzurum Teknik Üniversitesi Erzurum Türkiye

ISBN: (数字)9798350388961

ISBN: (纸本)9798350388978

Multi-rotor Unmanned Aerial and Ground Vehicles (UAV/UGV) are utilized for various military and civilian purposes such as detection, mapping, surveillance, target destruction, observation, and logistical applications due to their high agility, mechanical simplicity, ease of control, and autonomous capabilities. With advancing technology, UAVs and UGVs can be remotely controlled autonomously by onboard computers or by a pilot at a ground control station (GCS). Integrating these onboard computers into UAVs/UGVs enables information flow between the different modules they possess and the GCS. However, due to the traditional processing of this information flow in GCS software studies in the literature, there is a need for different and intelligent GCS software and autopilot design approaches. In this study, an intelligent new GCS capable of remotely commanding and controlling UAVs/UGVs has been designed, equipped with artificial intelligence features, capable of real-time recognition, positioning of more than seventy objects, and communication with UAVs/UGVs. The open-source Java programming language was used for coding operations, and the MAVLink (Micro Air Vehicle Link) protocol was utilized for communication between UAVs/UGVs and the GCS. For real-time object detection and localization, one of the fast and highly accurate algorithms in the literature, SSD MobileNet v2, was used and integrated with the GCS via Flask API. The obtained results demonstrated the consistency between the initial motivation and the software outputs, leading to the development of an open-source intelligent ground control station software and autopilot.

关键词： Computers Protocols Surveillance software algorithms Signal processing algorithms Object detection Signal processing

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