Digital Library

Vol. 20, No. 1, Feb. 2024  Cover

1. Semantic Feature Analysis for Multi-Label Text Classification on Topics of the Al-Quran Verses
   Gugun Mediamer, Adiwijaya
   Vol. 20, No. 1, pp. 1-12, Feb. 2024  
   10.3745/JIPS.02.0209
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   Keywords: Text Classification, Tensor Space Model, The Al-Quran Verses, Word Embedding
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   Nowadays, Islamic content is widely used in research, including Hadith and the Al-Quran. Both are mostly used in the field of natural language processing, especially in text classification research. One of the difficulties in learning the Al-Quran is ambiguity, while the Al-Quran is used as the main source of Islamic law and the life guidance of a Muslim in the world. This research was proposed to relieve people in learning the Al-Quran. We proposed a word embedding feature-based on Tensor Space Model as feature extraction, which is used to reduce the ambiguity. Based on the experiment results and the analysis, we prove that the proposed method yields the best performance with the Hamming loss 0.10317.


2. Musical Genre Classification Based on Deep Residual Auto-Encoder and Support Vector Machine
   Xue Han, Wenzhuo Chen, Changjian Zhou
   Vol. 20, No. 1, pp. 13-23, Feb. 2024  
   10.3745/JIPS.04.0300
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   Keywords: Deep Residual Auto-Encoder, MFCC, Music Artificial Intelligence, Musical Genre Classification
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   Music brings pleasure and relaxation to people. Therefore, it is necessary to classify musical genres based on scenes. Identifying favorite musical genres from massive music data is a time-consuming and laborious task. Recent studies have suggested that machine learning algorithms are effective in distinguishing between various musical genres. However, meeting the actual requirements in terms of accuracy or timeliness is challenging. In this study, a hybrid machine learning model that combines a deep residual auto-encoder (DRAE) and support vector machine (SVM) for musical genre recognition was proposed. Eight manually extracted features from the Mel-frequency cepstral coefficients (MFCC) were employed in the preprocessing stage as the hybrid music data source. During the training stage, DRAE was employed to extract feature maps, which were then used as input for the SVM classifier. The experimental results indicated that this method achieved a 91.54% F1-score and 91.58% top-1 accuracy, outperforming existing approaches. This novel approach leverages deep architecture and conventional machine learning algorithms and provides a new horizon for musical genre classification tasks.


3. A Controllable Parallel CBC Block Cipher Mode of Operation
   Ke Yuan, Keke Duanmu, Jian Ge, Bingcai Zhou, Chunfu Jia
   Vol. 20, No. 1, pp. 24-37, Feb. 2024  
   10.3745/JIPS.03.0191
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   Keywords: Edge Amplitude, Image restoration, Kernel, Spatial Scale, Windowed-Total-Variation
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   To address the requirement for high-speed encryption of large amounts of data, this study improves the widely adopted cipher block chaining (CBC) mode and proposes a controllable parallel cipher block chaining (CPCBC) block cipher mode of operation. The mode consists of two phases: extension and parallel encryption. In the extension phase, the degree of parallelism n is determined as needed. In the parallel encryption phase, n cipher blocks generated in the expansion phase are used as the initialization vectors to open n parallel encryption chains for parallel encryption. The security analysis demonstrates that CPCBC mode can enhance the resistance to byte-flipping attacks and padding oracle attacks if parallelism n is kept secret. Security has been improved when compared to the traditional CBC mode. Performance analysis reveals that this scheme has an almost linear acceleration ratio in the case of encrypting a large amount of data. Compared with the conventional CBC mode, the encryption speed is significantly faster.


4. A Study on the Analysis of Security Requirements through Literature Review of Threat Factors of 5G Mobile Communication
   DongGyun Chu, Jinho Yoo
   Vol. 20, No. 1, pp. 38-52, Feb. 2024  
   10.3745/JIPS.03.0192
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   Keywords: 5G Mobile Networks, Security Requirements, Security Threats
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   The 5G is the 5th generation mobile network that provides enhanced mobile broadband, ultra-reliable & low latency communications, and massive machine-type communications. New services can be provided through multi-access edge computing, network function virtualization, and network slicing, which are key technologies in 5G mobile communication. However, these new technologies provide new attack paths and threats. In this paper, we analyzed the overall threats of 5G mobile communication through a literature review. First, defines 5G mobile communication, analyzes its features and technology architecture, and summarizes possible security issues. Addition, it presents security threats from the perspective of user devices, radio access network, multiaccess edge computing, and core networks that constitute 5G mobile communication. After that, security requirements for threat factors were derived through literature analysis. The purpose of this study is to conduct a fundamental analysis to examine and assess the overall threat factors associated with 5G mobile communication. Through this, it will be possible to protect the information and assets of individuals and organizations that use 5G mobile communication technology, respond to various threat situations, and increase the overall level of 5G security.


5. Applications of a Deep Neural Network to Illustration Art Style Design of City Architectural
   Yue Wang, Jia-Wei Zhao, Ming-Yue Zheng, Ming-Yu Li, Xue Sun, Hao Liu, Zhen Liu
   Vol. 20, No. 1, pp. 53-66, Feb. 2024  
   10.3745/JIPS.02.0210
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   Keywords: Architectural Design, Artistic Style, Illustration for Children, Style Transfer
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   With the continuous advancement of computer technology, deep learning models have emerged as innovative tools in shaping various aspects of architectural design. Recognizing the distinctive perspective of children, which differs significantly from that of adults, this paper contends that conventional standards may not always be the most suitable approach in designing urban structures tailored for children. The primary objective of this study is to leverage neural style networks within the design process, specifically adopting the artistic viewpoint found in children's illustrations. By combining the aesthetic paradigm of urban architecture with inspiration drawn from children's aesthetic preferences, the aim is to unearth more creative and subversive aesthetics that challenge traditional norms. The selected context for exploration is the landmark buildings in Qingdao City, Shandong Province, China. Employing the neural style network, the study uses architectural elements of the chosen buildings as content images while preserving their inherent characteristics. The process involves artistic stylization inspired by classic children's illustrations and images from children's picture books. Acting as a conduit for deep learning technology, the research delves into the prospect of seamlessly integrating architectural design styles with the imaginative world of children's illustrations. The outcomes aim to provide fresh perspectives and effective support for the artistic design of contemporary urban buildings.


6. Survey on Financial Support in Chinese Language Promotion
   Xiaowen Zhang, Lu Lu
   Vol. 20, No. 1, pp. 67-75, Feb. 2024  
   10.3745/JIPS.04.0301
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   Keywords: Chinese Language, Financial Support, Office for Chinese Teaching, SWOT
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   In the promotion of Chinese language, the funding that Confucius Institutes can rely on only comes from Hanban. From 2009 to 2014, the number of new Confucius Institutes opened is much higher than before. With the increasing number of Confucius Institutes established in various countries, the funding for promoting Chinese language has limited its development. The development situation of Confucius Institutes in Australia is diversified with very rich experience. The market-oriented development of Confucius Institutes has also tried many times. The Confucius Institutes in the Lancang-Mekong region have less experience but they can learn from various experiences from Australia to provide better ideas and paths for the development of Confucius Institutes in this region and the promotion of Chinese. This paper uses the strength, weakness, opportunity, and threat (SWOT) model to analyze the market feasibility of financial support for the development of Confucius Institutes and makes certain suggestions for the promotion of Chinese language in the Lancang-Mekong region.


7. Empirical Research on the Relationship between the Futures and Spot Prices of Cotton in China
   Lin Wang Guixian Tian
   Vol. 20, No. 1, pp. 76-84, Feb. 2024  
   10.3745/JIPS.04.0302
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   Keywords: Cotton Futures Price, Cotton Spot Price, Spot Market, VAR
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   This study constructed a VAR model with cotton futures and spot price data from April 30, 2009 to November 16, 2022, for empirical analysis utilizing the Granger causality test to analyze the dynamic relationship between cotton futures and spot market prices in China. The impulse response function and variance decomposition analysis showed that the cotton spot prices at flowering have a causal relationship with each other; in terms of mutual influence and impact, futures prices are higher than spot prices. Finally, it proposed countermeasures and suggestions from the perspective of establishing a standardized cotton spot market, improving the laws and regulations of the cotton futures market and trading system, and optimizing the structure of investment subjects.


8. TPS Analysis, Performance Indicator of Public Blockchain Scalability
   Hyug-Jun Ko, Seong-Soo Han
   Vol. 20, No. 1, pp. 85-92, Feb. 2024  
   10.3745/JIPS.04.0304
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   Keywords: Bitcoin, Blockchain, EOS.IO, Ethereum, TPS
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   In recent years, Bitcoin and Ethereum have witnessed a surge in trading activity, driven by venture capital investment and funding through initial coin offerings (ICOs) and initial exchange offerings (IEOs). This heightened interest has led to kickstarting a vibrant ecosystem for blockchain development. The total number of cryptocurrencies listed on CoinMarketCap.com has reached 2,274 highlights how dynamic and wide blockchain development landscape has grown. In blockchain development, new blockchain projects are being created by forking blockchains inspired by major cryptocurrencies such as Bitcoin and Ethereum. These projects aim to address the perceived shortcomings and improve existing technologies. Altcoins, representing these alternative cryptocurrencies, are an ongoing industry effort to improve performance and security with enhancement proposals such as Bitcoin Improvement Proposals (BIP), Ethereum Improvement Proposals (EIP), and EOSIO Enhancement Proposals (EEP). With competitive attempts to improve blockchain performance and security, an ongoing performance race between various blockchains has taken shape, each claiming its own performance advantages. In this paper, we describe the transactions contained in the blocks of each representative blockchain, and find the factors that affect the transactions per second (TPS) through transaction processing and block generation processes, and suggest their relationship with scalability.


9. The Determinants and their Time-Varying Spillovers on Liquefied Natural Gas Import Prices in China Based on TVP-FAVAR Model
   Ying Huang, Yusheng Jiao
   Vol. 20, No. 1, pp. 93-104, Feb. 2024  
   10.3745/JIPS.01.0098
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   Keywords: Aggregate Demand, Crude Oil Market, Financial Speculation, Liquefied Natural Gas Import Prices, MarketFundamentals, TVP-FAVAR Model
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   China is playing more predominant role in the liquefied natural gas (LNG) market worldwide and LNG import price is subject to various factors both at home and abroad. Nevertheless, previous studies rarely heed a multiple of factors. A time-varying parameter factor augmented vector auto-regression (TVP-FAVAR) model is adopted to discover the determinants of China’s LNG import price and their dynamic impacts from January 2012 to December 2021. According to the findings, market fundamentals have a greater impact on the import price of natural gas in China than overall economic demand, financial considerations, and world oil prices. The primary determinants include domestic gas consumption, consumer confidence and other demand-side information. Then, there are diverse and time-varying spillover effects of the four common determinants on the volatility of China's LNG import price at different intervals and time nodes. The price volatility is more sensitive and longlasting to domestic natural gas pricing reform than other negative shocks such as the Sino-US trade war and the COVID-19 pandemic. The results in this study further proves the importance of domestic natural gas market liberalization. China ought to do more to support the further marketization of natural gas prices while working harder to guarantee natural gas supplies.


10. Signal Processing and Development Process Based on “MOOC + SPOC + Flipped Classroom”
    Bei Qiao, Yan Mi
    Vol. 20, No. 1, pp. 105-115, Feb. 2024  
    10.3745/JIPS.04.0303
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    Keywords: Higher Education Institutions, Flipped Classrooms, MOOC, SpoC
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    The hybrid teaching approach of “MOOC + SPOC + Flipped Classroom” overcomes the constraints of time and space that are typically associated with traditional teaching methods, thus compensating for the shortcomings of traditional approaches. These changes in education are driven by the “Internet+” wave and the growing popularity of online teaching. The “MOOC + SPOC + Flipped Classroom” hybrid teaching mode can successfully compensate for the drawbacks of traditional teaching methods, thereby overcoming their restrictions. By defining relevant concepts, one can distill the key characteristics of the “MOOC + SPOC + Flipped Classroom” hybrid teaching mode. Formative assessment was employed to thoroughly evaluate the effectiveness of this teaching approach. By leveraging the advantages of massive open online course (MOOC), small private online course (SPOC), and flipped classroom, the “MOOC +SPOC + Flipped Classroom” teaching mode incorporates real-time student assessment through peer evaluation, computer-aided evaluation, and teacher evaluation. This mode promotes the simultaneous development of theoretical knowledge and practical skills, helping students to establish strong foundations while fostering their practical abilities. While the traditional teaching method remains fruitful, the convenience of today's network allows the teaching profession to continually evolve. The traditional teaching mode heavily relies on teachers, making it impossible to conduct lessons without them. However, the development of MOOC enables students to seek knowledge online from their preferred teachers, rather than solely relying on their assigned instructors.


11. SoC Virtual Platform with Secure Key Generation Module for Embedded Secure Devices
    Seung-Ho Lim, Hyeok-Jin Lim, Seong-Cheon Park
    Vol. 20, No. 1, pp. 116-130, Feb. 2024  
    10.3745/JIPS.01.0099
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    Keywords: FHE, PUF, Secure Key Generation, SoC Virtual Platform
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    In the Internet-of-Things (IoT) or blockchain-based network systems, secure keys may be stored in individual devices; thus, individual devices should protect data by performing secure operations on the data transmitted and received over networks. Typically, secure functions, such as a physical unclonable function (PUF) and fully homomorphic encryption (FHE), are useful for generating safe keys and distributing data in a network. However, to provide these functions in embedded devices for IoT or blockchain systems, proper inspection is required for designing and implementing embedded system-on-chip (SoC) modules through overhead and performance analysis. In this paper, a virtual platform (SoC VP) was developed that includes a secure key generation module with a PUF and FHE. The SoC VP platform was implemented using SystemC, which enables the execution and verification of various aspects of the secure key generation module at the electronic system level and analyzes the system-level execution time, memory footprint, and performance, such as randomness and uniqueness. We experimentally verified the secure key generation module, and estimated the execution of the PUF key and FHE encryption based on the unit time of each module.


12. Dynamic Caching Routing Strategy for LEO Satellite Nodes Based on Gradient Boosting Regression Tree
    Yang Yang, Shengbo Hu, Guiju Lu
    Vol. 20, No. 1, pp. 131-147, Feb. 2024  
    10.3745/JIPS.03.0193
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    Keywords: Gradient Boosting Regression Tree Cache Allocation, Low-Earth Orbit Satellite, inter-satellite links, Spatialand Temporal Correlation, traffic prediction
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    A routing strategy based on traffic prediction and dynamic cache allocation for satellite nodes is proposed to address the issues of high propagation delay and overall delay of inter-satellite and satellite-to-ground links in low Earth orbit (LEO) satellite systems. The spatial and temporal correlations of satellite network traffic were analyzed, and the relevant traffic through the target satellite was extracted as raw input for traffic prediction. An improved gradient boosting regression tree algorithm was used for traffic prediction. Based on the traffic prediction results, a dynamic cache allocation routing strategy is proposed. The satellite nodes periodically monitor the traffic load on inter-satellite links (ISLs) and dynamically allocate cache resources for each ISL with neighboring nodes. Simulation results demonstrate that the proposed routing strategy effectively reduces packet loss rate and average end-to-end delay and improves the distribution of services across the entire network.