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11th International Conference on Cyber and IT Service Management, CITSM 2023

作者： Setianingrum, Anif Hanifa Hulliyah, Khodijah Amrilla, Muhammad Fitroh Syarif Hidayatullah State Islamic University Jakarta Faculty of Science and Technology Informatics Engineering Jakarta Indonesia

ISBN: (纸本)9798350305968

In Indonesia, the Sundanese language is known for its diverse dialects. The distinction between the Bantenese and South Sundanese dialects lies in their usage of words, which can give the impression of shouting. These dialectal differences in pronunciation frequencies can lead to misunderstandings. This study utilized Convolutional Neural Network (CNN) and mel-spectrogram to do speech recognition of Sundanese dialects. Mel-spectrogram is a method for extracting features from a sound. It has advantages because it offers sound information to our models that is comparable to what a person would experience, and produced visual representations of the sound frequency spectrum as pictures for these speech data. Furthermore, CNN used as the speech recognition model from these spectrogram images. The research findings proved that mel-spectogram and CNN combination successfully identifies and distinguishes Sundanese dialects. The CNN model, utilizing a filter configuration of 32-32-64-64 on a dataset comprising 50 Bantenese dialect voice samples and 50 South Sundanese dialect voice samples, achieves 93.75% of training accuracy and 95.00% of testing accuracy. This study will help indonesian people to recognize different dialects of Sundanese dialects and reduce misunderstanding between ethnics in Indonesia. © 2023 IEEE.

关键词： Speech recognition

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Comparative Evaluation of Resampling Techniques on Machine Learning for Predicting Customer Purchasing Behavior 8

Comparative Evaluation of Resampling Techniques on Machine L...

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8th International Conference on Information technology, InCIT 2024

作者： Diwandari, Saucha Permanasari, Adhistya Erna Hidayah, Indriana Universitas Gadjah Mada Department of Electrical and Information Engineering Indonesia Universitas Teknologi Yogyakarta Faculty of Science and Technology Informatics Department Indonesia

ISBN: (纸本)9798350366303

In the era of subscription-based services, customer purchasing behavior presents a significant challenge for organizations because customer retention is essential to long-term success. Imbalanced datasets, where the majority class significantly outweighs the minority class, often cause models to favor the dominant class, leading to biased predictions. This study investigates customer purchasing behavior, focusing specifically on the issue of class imbalance. It offers a comparative analysis of various classification techniques and includes widely used resampling methods such as the Synthetic Minority Over-sampling Technique (SMOTE), Edited Nearest Neighbors, Tomek Links, and several hybrid sampling approaches. Our research findings demonstrate the competitive effectiveness of using the Random Forest algorithm with undersampling methods such as TomekLinks and Edited Nearest Neighbors (ENN), which have shown the highest F1 scores. However, the hybridization of oversampling and undersampling yields unsatisfactory results, below our expectations. This suggests that the dataset used in this study exhibits a high degree of overlap between the two classes. Consequently, undersampling proves to be an effective method for mitigating the negative impact of class overlap. This research makes a substantial contribution to the field of predicting customer purchasing behavior. © 2024 IEEE.

关键词： Adversarial machine learning

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Selection of a Simple 5G Handover Algorithm: Preparation for Named Data Networking 10

Selection of a Simple 5G Handover Algorithm: Preparation for...

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10th International Conference on Wireless and Telematics, ICWT 2024

作者： Nurhayati, Ade Ahdan, Syaiful Juhana, Tutun Syambas, Nana Rachmana Bandung Institute of Technology School of Electrical Engineering and Informatics Bandung40132 Indonesia Telkom University Faculty of Applied Science Jakarta11710 Indonesia Universitas Teknokrat Indonesia Faculty of Engineering & Computer Science 35132 Indonesia

ISBN: (纸本)9798350377057

Named Data Networking as an alternative network for 5G network traffic is required to be able to provide better performance compared to other networks such as internet protocol networks. In NDN wireless, it is known that there is producer mobility and consumer mobility, so optimal mobility management is needed, including the handover process. In this paper the author proposes a simple RSSI-based 5G handover algorithm with distance as a reference RSSI value. This algorithm is a preparation for the handover algorithm on the NDN wireless network. By using the assumed distance value MS to eNB as the basic value for calculating RSSI, handover determination is determined by comparing the RSSI value to the RSSI threshold value. With the scenario of different numbers of users and cluster sizes, from the handover process involving 8 eNB. It can be calculated how big the handover probability is for each user. From the simulation results, it can be concluded that the more users and the larger the cluster size, the greater the handover probability value. This is linear, with the wider the cluster, the probability of getting an RSSI signal from the original eNB becomes smaller, making it possible to get an RSSI signal from neighboring eNB, so that a handover occurs. © 2024 IEEE.

关键词： 5G mobile communication systems

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Modeling heterogeneous behaviors with different strategies in a terrorist attack

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Virtual Reality & Intelligent Hardware 2023年第4期5卷 351-365页

作者： Le BI Tingting LIU Zhen LIU Jason TEO Yumeng ZHAO Yanjie CHAI Faculty of Electrical Engineering and Computer Science Ningbo UniversityNingbo 315211China College of Science&Technology Ningbo UniversityCixi 315300China Faculty of Computing&Informatics Universiti Malaysia SabahKota Kinabalu 88000Malaysia

Existing simulations of terrorist attacks do not consider individual *** overcome this lim-itation,we propose a framework to model heterogeneous behavior of individuals during terrorist *** constructed an emotional model that integrated personality and visual perception for *** emotional model was then integrated with pedestrian relationship networks to establish a decision-making model that sup-ported pedestrians’altruistic behaviors.A mapping model has been developed to correlate antisocial personality traits with attack strategies employed by *** demonstrate that the proposed algorithm can generate practical heterogeneous behaviors that align with existing psychological research findings.

关键词： Terrorist attack simulation Computer animation Big Five personality Intelligent decision making Heterogeneous behaviors

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Semi-analytical finite element method applied for characterizing micropolar fibrous composites

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Applied Mathematics and Mechanics(English Edition) 2024年第12期45卷 2147-2164页

作者： J.A.OTERO Y.ESPINOSA-ALMEYDA R.RODRIGUEZ-RAMOS J.MERODIO School of Engineering and Sciences Monterrey Institute of TechnologyEstado de Mexico 52926Mexico Institute of Engineering and Technology Autonomous University of Ciudad JuarezCiudad JuarezChihuahua 32310Mexico Postgraduate Program in Computational Modeling in Science and Technology Federal Fluminense UniversityRıo de Janeiro 27255-125Brazil Faculty of Mathematics and Computer Science University of HavanaLa Habana 10400Cuba Department of Mathematics Applied to ICT School of Informatics Systems EngineeringTechnical University of MadridMadrid 28031Spain

A semi-analytical finite element method(SAFEM),based on the two-scale asymptotic homogenization method(AHM)and the finite element method(FEM),is implemented to obtain the effective properties of two-phase fiber-reinforced composites(FRCs).The fibers are periodically distributed and unidirectionally aligned in a homogeneous *** framework addresses the static linear elastic micropolar problem through partial differential equations,subject to boundary conditions and perfect interface contact *** mathematical formulation of the local problems and the effective coefficients are presented by the *** local problems obtained from the AHM are solved by the FEM,which is denoted as the *** numerical results are provided,and the accuracy of the solutions is analyzed,indicating that the formulas and results obtained with the SAFEM may serve as the reference points for validating the outcomes of experimental and numerical computations.

关键词： semi-analytical approach fiber-reinforced composite(FRC) effective property finite element method(FEM) asymptotic homogenization method(AHM) micropolar elasticity

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K-Banhatti Invariants Empowered Topological Investigation of Bridge Networks

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Computers, Materials & Continua 2022年第12期73卷 5423-5440页

作者： Khalid Hamid Muhammad Waseem Iqbal Erssa Arif Yasir Mahmood Ahmad Salman Khan Nazri Kama Azri Azmi Atif Ikram Department of Computer Science Superior UniversityLahore54000Pakistan Department of Software Engineering Superior UniversityLahore54000Pakistan Department of Software Engineering Faculty of Information TechnologyThe University of Lahore54000Pakistan Advanced Informatics Department Razak Faculty of Technology and InformaticsUniversiti Teknologi MalaysiaKuala Lumpur54100Malaysia Faculty of Informatics and Applied Mathematics University Malaysia TerengganuMalaysia Department of Computer Science&Information Technology Faculty of Information TechnologyThe University of Lahore54000Pakistan

Any number that can be uniquely determined by a graph is called graph *** the most recent twenty years’innumerable numerical graph invariants have been described and used for correlation *** the fast and advanced environment of manufacturing of networks and other products which used different networks,no dependable assessment has been embraced to choose,how much these invariants are connected with a network graph or molecular *** this paper,it will talk about three distinct variations of bridge networks with great capability of expectation in the field of computer science,chemistry,physics,drug industry,informatics,and mathematics in setting with physical and synthetic constructions and networks,since K-Banhatti invariants are newly introduced and have various forecast characteristics for various variations of bridge graphs or *** review settled the topology of bridge graph/networks of three unique sorts with three types of K-Banhatti *** concluded outcomes can be utilized for the modeling of interconnection networks of Personal computers(PC),networks like Local area network(LAN),Metropolitan area network(MAN)and Wide area network(WAN),the spine of internet and different networks/designs of PCs,power generation interconnection,bio-informatics and chemical structures.

关键词： Bridge networks invariants k-banhatti indices maple network graph molecular graph

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Spectral Generalized Category Discovery by training on combined labels 22

Spectral Generalized Category Discovery by training on combi...

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2024 IEEE 22nd World Symposium on Applied Machine Intelligence and informatics, SAMI 2024

作者： Mao, Ruixuan Al-Shouha, Modafar Szucs, Gabor Eötvös Loránd University Faculty of Informatics Department of Data Science BudapestH-1117 Hungary Budapest University of Technology and Economics Faculty of Electrical Engineering and Informatics Department of Telecommunications and Media Informatics BudapestH-1111 Hungary

ISBN: (纸本)9798350317206

Hyperspectral imaging poses major challenges for supervised classification methods due to the high dimensionality of the data. This classification was solved in previous works with known classes. In this paper we present a different aim where the goal is to discover and distinguish novel categories for hyperspectral images in scenarios where some classes are unknown. This belongs to Generalized Category Discovery (GCD) problem with a further task for automatic clustering of unlabeled data with partial knowledge. Our contribution is an additional supervised learning stage on combined labels coming from two sources. Our approach consists of three stages, (i) dimension reduction, (ii) clusters assignment with the Hungarian method, and (iii) classification, where a special training set is constructed from ground true labels and the filtered test set with (dummy) labels that are the predicted categories from the clustering part. The proposed method (S-GCD) was evaluated on two datasets, and our experiments demonstrate that classification on combined labels greatly improves both classification and clustering scores. © 2024 IEEE.

关键词： Image classification

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Neutrosophic Model for Evaluation Healthcare Security Criteria for Powerful and Lightweight Secure Storage System in Cloud-Based E-Healthcare Services

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Neutrosophic Sets and Systems 2023年 58卷 367-378页

作者： El-Douh, Ahmed A. Lu, SongFeng Abdelhafeez, Ahmed Ali, Ahmed M. Aziz, Alber S. School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan430074 China Faculty of Information Systems and Computer Science October 6th University Giza12585 Egypt Faculty of Computers and Informatics Zagazig University Sharqiyah Zagazig44519 Egypt

Large data volumes make manually keeping and preserving health records for future reference problematic. Most unusual is the coronavirus epidemic's overcrowding of hospitals. The Secure Pattern Electronic Healthcare Records (SPEHR) scheme provides a powerful and lightweight secure storage system for cloud-based E-healthcare services that meets remote healthcare security criteria. So we proposed a neutrosophic model with a multi-criterion decision-making (MCDM) method for the analysis and evaluation of these criteria. The neutrosophic model is used to deal with vague and uncertain data. Then we integrated the neutrosophic model with the AHP method to rank and compute the weights of the criteria. Offering stakeholders a secure interface and avoiding unwanted access to cloud-stored data mitigates E-healthcare risks. The key derivation ensures end-to-end data. ciphering to prevent unauthorized use (KDF). This work provides robust security solutions for various environments. This work can meet security needs for people and secure-communicating organizations. We found the data privacy is the best criterion. © (2023). All Rights Reserved.

关键词： Access control

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ADVANCED MULTI-OBJECTIVE ALGORITHM USED TO OPTIMIZE CONSUMPTION OF AN INTEGRATED SYSTEM FOR FLEXIBLE MANUFACTURING

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical engineering and Computer science 2024年第2期86卷 113-127页

作者： Păun, Marius-Adrian Coandă, Henri-George Mincă, Eugenia Duca, Octavian Gabriel Făgărășan, Ioana Dragomir, Florin Iliescu, Sergiu Stelian National University of Science and Technology POLITEHNICA of Bucharest Automation and Industrial Informatics Department Romania Faculty of Electrical Engineering Electronics and Information Technology Valahia University of Targoviste Romania Institute of Multidisciplinary Research for Science and Technology Valahia University of Targoviste Romania Academy of Romanian Scientists 54 Splaiul Independentei Bucharest050044 Romania

The optimization of power consumption of manufacturing lines (ML) is a relevant topic in the context of increasing electricity prices. This paper presents the topic of optimizing the energy consumption of a production system, through optimization technique based on the multi-objective PSO (Particle Swarm Optimization) algorithm. The novelty of the approach lies in the development of an Advanced PSO algorithm (APSO), which brings superior results in optimizing energy consumption. The research was carried out in successive stages, starting with data collection, and ending with the implementation of the results on the production line, everything being subordinated to the criterion of optimizing energy consumption. APSO's advanced optimization technique was implemented on a flexible manufacturing line (FML) composed of five linearly interconnected workstations. The APSO optimization algorithm, following implementation and testing on FML, provides a solution for controlling the conveyor speeds of each station that guarantees in the overall approach to the process a minimum energy consumption, but also a minimum execution time of the algorithm. © 2024, Politechnica University of Bucharest. All rights reserved.

关键词： Electric power utilization

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Cross-Layer Distributed Attack Detection Model for the IoT

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International Journal of Ambient Computing and Intelligence 2022年第1期13卷 1-17页

作者： Ahmed, Hassan I. Nasr, Abdurrahman A. Abdel-Mageid, Salah M. Aslan, Heba K. Informatics Department Electronics Research Institute Cairo Egypt Computer Engineering Faculty of Engineering Al-Azhar University Cairo Egypt Computer Engineering Department College of Computer Science and Engineering Taibah University Saudi Arabia Center of Informatics Science Faculty of Information Technology and Computer Science Nile University Egypt

The security of IoT that is based on layered approaches has shortcomings such as the redundancy, inflexibility, and inefficiently of security solutions. There are many harmful attacks in IoT networks such as DoS and DDoS attacks, which can compromise the IoT architecture in all layers. Consequently, cross layer approach is proposed as an effective and practical security defending mechanism. Cross-layer distributed attack detection model (CLDAD) is proposed to enhance security solutions for IoT environments. CLDAD presents a general detection method of DDoS in sensing layer, network layer, and application layer. CLDAD is based on big data analytics techniques, which enable the detection process to be performed in a distributed way, so the model can detect DDoS attacks in any layer on-the-fly and the model support the scalability of the IoT environment. CLDAD is tested based on three datasets, namely artificial jamming attack dataset, BoT-IoT dataset, and BoT-IoT-based HTTP. The results showed that the proposed model is efficient in detecting attacks in the three layers of the IoT. Copyright © 2022, IGI Global.

关键词： Big data

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