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Strengthening the Security of Deniable Authentication Scheme Using Zero-Knowledge Proof 11

Strengthening the Security of Deniable Authentication Scheme...

引用

11th International Conference on Communication and Network Security, ICCNS 2021

作者： Moesriami Barmawi, Ari Rizal Nurjaman, Asep Informatics Graduate Program School of Computing Telkom University Bandung Indonesia

ISBN: (纸本)9781450386425

In an electronic voting system, authentication is used to ensure that the voter is legitimate without knowing his/her identity, while the vote collectors verify the data is received from a legitimate user without knowing the identity of the voter. One of the authentication schemes that fulfilled this requirement is called a deniable authentication scheme, where the receiver can prove the source of the message while another party cannot identify the source of the message. In 2013, Li-Takagi et al. proposed a deniable authentication scheme. However, Li-Takagi's scheme has weaknesses if the receiver fully cooperates with the third party. In this case, the third party can identify the source of a given message. In the proposed method, zero-knowledge proof is introduced to preserve the anonymity of the deniable authentication scheme when the receiver fully cooperates with the third party. Based on the analysis, the proposed scheme fulfills the requirement of the deniable authentication scheme when the receiver fully cooperates with the third party. However, the proposed scheme has additional computation costs for securing the shared secret key. Two attack schemes that are carried out on both Li-Takagi and the proposed scheme are the MITM attack and the impersonation attack. The probability of breaking the proposed scheme using an MITM attack is lower than when using Li-Takagi's scheme, but the probability of breaking the proposed scheme using an impersonation attack is the same as Li-Takagi's scheme. © 2021 ACM.

关键词： Authentication

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Estimation Algorithms for MLE of Three-Mode GMANOVA Model with Kronecker Product Covariance Matrix 15th

Estimation Algorithms for MLE of Three-Mode GMANOVA Model ...

引用

15th International KES Conference on Intelligent Decision Technologies, KESIDT 2023

作者： Horikawa, Keito Nagai, Isamu Monden, Rei Yanagihara, Hirokazu Informatics and Data Science Program Graduate School of Advanced Science and Engineering Hiroshima University Hiroshima Higashi-Hiroshima739-8521 Japan Faculty of Liberal Arts and Science Chukyo University Aichi Nagoya466-8666 Japan Mathematics Program Graduate School of Advanced Science and Engineering Hiroshima University Hiroshima Higashi-Hiroshima739-8526 Japan

ISBN: (纸本)9789819929689

Currently, there are a lot of measurement data on different items collected over time. The GMANOVA model is appropriate for analyzing the trends in such data, in order to analyze some longitudinal data collected on different items simultaneously, we need to create separate GMANOVA models, but separate GMANOVA models cannot reveal the relationships between items. Also, if we try to apply one model to all of these data, the problem arises that there are too many parameters and the covariance structure is too large. Therefore, we propose an extended GMANOVA model and two estimation algorithms. The proposed model’s covariance matrix has a Kronecker structure. Therefore, because the estimator cannot be uniquely determined using the log-likelihood, we propose two parameter estimation algorithms. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Covariance matrix

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Implications of the Usage of Three-Mode Principal Component Analysis with a Fixed Polynomial Basis 15th

Implications of the Usage of Three-Mode Principal Compone...

引用

15th International KES Conference on Intelligent Decision Technologies, KESIDT 2023

作者： Monden, Rei Nagai, Isamu Yanagihara, Hirokazu Informatics and Data Science Program Graduate School of Advanced Science and Engineering Hiroshima University Hiroshima Higashi-Hiroshima739-8521 Japan Faculty of Liberal Arts and Science Chukyo University Aichi Nagoya466-8666 Japan Mathematics Program Graduate School of Advanced Science and Engineering Hiroshima University Hiroshima Higashi-Hiroshima739-8526 Japan

ISBN: (纸本)9789819929689

When I subjects answer questions regarding J variables K times, the data can be stored in a three-mode data set of size I× J× K. Among the various component analysis approaches to summarize such data, Three-mode Principal Component Analysis (3MPCA) is often used. 3MPCA expresses a three-mode data set by means of A-, B-, and C-mode components and a core array, but this approach is not suitable for predicting data at unobserved time points. To handle this issue, the current study suggests a fixed orthonormal polynomial basis for the 3MPCA model. Briefly, we fix the C-mode component matrix with an orthonormal polynomial basis. More specifically, i) measurement time points, and ii) log transformation of the measurement time points were used as an orthonormal polynomial basis. The use of our proposed methods was demonstrated by applying them to a longitudinal data set collected from patients with depression. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Principal component analysis

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Deciphering Key Features in Online Buying Session Prediction Using Logistic Regression and Naive Bayes

Deciphering Key Features in Online Buying Session Prediction...

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Technology Innovation and Its Applications (ICTIIA), International Conference on

作者： Arnold Aribowo I Made Murwantara Information Systems Department (Undergraduate Program) Universitas Pelita Harapan Tangerang Indonesia Informatics Department (Graduate Program) Universitas Pelita Harapan Tangerang Indonesia

ISBN: (数字)9798350351613

ISBN: (纸本)9798350351620

This paper explores the key factors influencing online buying session prediction using nomogram analysis with Logistic Regression and Naive Bayes models. We analyzed a dataset containing various attributes of online shoppers. Our results underscore that the Logistic Regression has superior capability for both True and False targets in terms of accuracy (0.883) and AUC (0.897). While Naïve Bayes performs better for the True target with an F1Score of 0.555, Logistic Regression demonstrates superior performance for the False target with an F1 Score of 0.934. Nomogram analysis revealed that for Naive Bayes, page values, exit rates, and bounce rates are the most significant factors, while for Logistic Regression, page values and product-related features (ProductRelated and ProductRelated_Duration) are the most significant. Visualizing these key factors through nomograms helps interpret their relative importance to support the accuracy and interpretability of machine learning predictions.

关键词： Logistic regression Analytical models Technological innovation Accuracy Social networking (online) Reviews Predictive models Bayes methods Ensemble learning Electronic commerce

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Energy Planning and Utilization in the North Sulawesi Electricity System

Energy Planning and Utilization in the North Sulawesi Electr...

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2023 International Conference on Electrical Engineering and informatics, ICEEI 2023

作者： Pratama, Arif Majiid Nusa Sutardi, Bagas Maulana Zidny, Irfan Lewi, Irvan Hasanuddin Hidayat, Syarif Hadi, Pradita Octaviandiningrum Pln Corporate University Graduate Program PLN-ITB Jakarta Indonesia Pln UIP3B Sulawesi Makassar Indonesia Bandung Institute of Technology School of Electrical and Informatics Engineering Bandung Indonesia

ISBN: (纸本)9798350381290

Energy sector is one of the contributors to climate change besides forestry, environment, and transportation sectors. Then, the results of the COP 26 in Glasgow meeting states that Indonesia have a target to achieve Net Zero Emission (NZE) by 2060 if there is international support for funding and technology with some note that this project does not interfere with availability and affordability. In achieving the zero-emission target, the government is implementing five main principles, which include increasing the use of new renewable energy (NRE), reducing fossil energy, explore the use of electric vehicles in the transportation sector, increasing the use of electricity in households and industries, and utilizing Carbon Capture and Storage (CCS). In this paper several proposals can be made to further reduce production costs and reduce greenhouse gas emissions in the North Sulawesi system compared to Electricity Supply Business Plan by PLN which is called RUPTL. Two additional scenarios can be used for the proposal, which are addition of geothermal, solar and pump hydro to replace coal power plant and construction of North Sulawesi interconnection with Central Sulawesi. From the simulation results of the cost and carbon emission analysis between three scenarios, the scenario from RUPTL is the cheapest in terms of cost at 3.295 billion USD and the interconnection scenario is the smallest in terms of emissions, with CO2 emissions reaching 0 Mt. © 2023 IEEE.

关键词： Climate change

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Performance Modeling of MARE2DEM's Adaptive Mesh Refinement for Makespan Estimation

Performance Modeling of MARE2DEM's Adaptive Mesh Refinement ...

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International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD)

作者： Bruno Da Silva Alves Lucas Mello Schnorr Graduate Program in Computer Science (PPGC) Institute of Informatics – UFRGS Porto Alegre Brazil

Adaptive Mesh Refinement (AMR) is a widely known technique to adapt the accuracy of a solution in critical areas of the problem domain instead of using regular or irregular but static meshes. The MARE2DEM is a parallel application that employs the AMR technique to model 2D electromagnetics in oil and gas exploration. The modeling consists in iteratively applying a data inversion based on a set of measurements collected and registered by a survey on an area of interest. The parallelism of the MARE2DEM works by dividing the workload into a set of refinement groups that represent overlapping areas of the problem domain. Each refinement group can be computed independently of the others by a set of workers, carrying out the AMR in the meshes when necessary. The shape and compute performance of the refinement group depend directly of a set of user-defined parameters. In this article, we provide a method to estimate the MARE2DEM performance for all possible values that can be used in the influencing parameters of the application for a given case study. Our relatively cheap method enables the geologist to configure MARE2DEM correctly and extract the best performance for a given cluster configuration. We detail how the method works and evaluate its effectiveness with success, pinpointing the best values for the creating refinement groups using a real case study from the Marlim field on the coast of Rio de Janeiro, Brazil. Although we demonstrate our evaluation with this scenario, our method works for any input of MARE2DEM.

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Internet of Things-based Hydroponic: Literature Review 4

Internet of Things-based Hydroponic: Literature Review

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4th International Conference on Electrical, Electronics, informatics, and Vocational Education, ICE-ELINVO 2021

作者： Hadinata, Alan Mashoedah Graduate Program of Electronics and Informatics Engineering Education State University of Yogyakarta Indonesia

Hydroponics is a method of growing crops without using soil, with the benefits of controlling the environment and nutrients, conserving water, and reducing labor. The applied technology is used to improve results that have consistency. This research was conducted with the aim of knowing the IoT devices and platforms used in the development of IoT-based hydroponics. Data obtained from the website *** and *** from 2016 to 2021. This study is a literature review using the PRISMA method. This method is used for literature review using a systematic and structured basic framework. The results of this study indicate that the variables measured are Temperature, Potential Hydrogen (pH), Total Dissolve Solid, Water Temperature, Humidity, UV, Carbon Dioxide, Soil Moisture and Electrical Conductivity. The device used is the ESP8266, Arduino, and Raspberry PI with the MySQL, Thingspeak, Firebase, Domoticz, and Wyliodrin IoT Platforms. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Hydroponics

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Analysis of Digital Population Services for the Poor in Palembang City Using the Information Technology Infrastructure Library (ITIL) Framework 4

Analysis of Digital Population Services for the Poor in Pale...

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4th International Conference on Information and Communications Technology, ICOIACT 2021

作者： Antoni, Darius Septiyanti, Reni Akbar, Muhamad Herdiansyah, Muhammad Izman Department of Informatics Engineering Graduate Program Bina Darma University Palembang Indonesia

ISBN: (纸本)9781665433945

As it is known that the city government of Palembang has implemented e-government, but how much e-government can help the Palembang city government to interact between the government and all levels of society including the poor in Palembang city. In its application, the condition of e-government services is still insufficient for the infrastructure to support e-government services for the poor in Palembang city. To design e-government services such as good digital population services, it is necessary to design IS / IT services for people in Palembang City with the Service Design stage in the 2011 Version of the Information Technology Infrastructure Library (ITIL) Framework so that they can be accepted by all levels of society including the poor in Palembang city. This study uses a qualitative approach. The results of this research are in the form of a digital population service information system design such as administrative and population services, Family Hope program (PKH) services and digital archive storage services based on the Service Design stages in ITIL Version 2011 that have been carried out, namely the Service Catalog Management process and Service Level Management in the form of documents. Service Level Requirements, Service Level Agreement and Operational Level Agreement. © 2021 IEEE

关键词： Information management

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Exploring Parallelism in ZynqNet AI Engine to Accelerate Image Classification in Aerospace

Exploring Parallelism in ZynqNet AI Engine to Accelerate Ima...

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IEEE Latin American Symposium on Circuits and Systems (LASCAS)

作者： Eduardo Marañon Aguilar Fabio Benevenuti Fernanda Lima Kastensmidt Federal University of Rio Grande do Sul (UFRGS) Institute of Informatics Microelectronics Graduate Program (PGMICRO) Porto Alegre Brazil

ISBN: (数字)9798331522124

ISBN: (纸本)9798331522131

This research investigates various configurations of the Zynqnet AI Engine to accelerate image classification tasks using the SAT-6 dataset and a 4-layer CNN. The C++ code for the hardware accelerator was translated into RTL using Vivado HLS and integrated with the Zynq Processing System on a ZedBoard Zynq-7000 ARM/FPGA SoC. The AI engine was configured to work with 32 -bit floating point, 8bit fixed point and 8 -bit integer type operations, with different processing elements for parallelizing CNN tasks. Given a 64-bit data memory bus in communication with the accelerator and an 8-bit integer quantization, the variation in the number of processing elements does not result in a significant performance improvement. To address this, 8 values were grouped for reading and writing in 64-bit parallel mode, and different communication architectures were designed to improve data transfer between the accelerator and DDR memory, with optional enablement of L1D and L2 cache. The research analyzes CNN computation performance and FPGA resource usage (LUTs, FFs, BRAMs, DSPs) across configurations, providing insights into the trade-offs in FPGA-based CNN implementations, aiding the development of efficient, high-performance hardware accelerators for Deep Learning applications.

关键词： Quantization (signal) Writing Table lookup System-on-chip Convolutional neural networks Artificial intelligence Hardware acceleration Engines Field programmable gate arrays Image classification

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LongKey: Keyphrase Extraction for Long Documents

LongKey: Keyphrase Extraction for Long Documents

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IEEE International Conference on Big Data

作者： Jeovane Honorio Alves Radu State Cinthia Obladen de Almendra Freitas Jean Paul Barddal SEDAN-SnT University of Luxembourg Graduate Program in Law (PPGD) Pontifícia Universidade Católica do Paraná Graduate Program in Informatics (PPGIa) Pontifícia Universidade Católica do Paraná

ISBN: (数字)9798350362480

ISBN: (纸本)9798350362497

In an era of information overload, manually annotating the vast and growing corpus of documents and scholarly papers is increasingly impractical. Automated keyphrase extraction addresses this challenge by identifying representative terms within texts. However, most existing methods focus on short documents (up to 512 tokens), leaving a gap in processing long-context documents. In this paper, we introduce LongKey, a novel framework for extracting keyphrases from lengthy documents, which uses an encoder-based language model to capture extended text intricacies. LongKey uses a max-pooling embedder to enhance keyphrase candidate representation. Validated on the comprehensive LDKP datasets and six diverse, unseen datasets, LongKey consistently outperforms existing unsupervised and language model-based keyphrase extraction methods. Our findings demonstrate LongKey’s versatility and superior performance, marking an advancement in keyphrase extraction for varied text lengths and domains.

关键词： Training Bridges Navigation Computer architecture Benchmark testing Writing Robustness Data mining Indexing Context modeling

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