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2024 International Conference on High Performance computing in Asia-Pacific Region Workshops, HPC Asia 2024 Workshops

作者： Fukazawa, Keiichiro Takahashi, Riki Academic Center for Computing and Media Studies Kyoto University Japan Graduate School of Informatics Kyoto University Japan

ISBN: (纸本)9798400716522

At the Supercomputer System of Academic center for computing and Media Studies Kyoto University, the fourth-generation Xeon (code-named Sapphire Rapids) is employed. The system consists of two subsystems—one equipped solely with high-bandwidth memory, HBM2e, and the other with a large DDR5 memory capacity. Using benchmark applications, a performance evaluation of systems with each type of memory was conducted. Additionally, the study employed a real application, the electromagnetic fluid code, to investigate how application performance varies based on differences in memory characteristics. The results confirm the performance improvement due to the high bandwidth of HBM2e. However, it was also observed that the efficiency is lower when using HBM2e, and the effects of cache memory optimization are relatively minimal. © 2024 Copyright held by the owner/author(s).

关键词： Sapphire

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Doubly Optimal Parallel Wire Cutting without Ancilla Qubits

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PRX Quantum 2024年第4期5卷 040308页

作者： Hiroyuki Harada Kaito Wada Naoki Yamamoto Department of Applied Physics and Physico-Informatics Quantum Computing Center

A restriction in the quality and quantity of available qubits presents a substantial obstacle to the application of near-term and early fault-tolerant quantum computers in practical tasks. To confront this challenge, some techniques for effectively augmenting the system size through classical processing have been proposed; one promising approach is quantum circuit cutting. The main idea of quantum circuit cutting is to decompose an original circuit into smaller subcircuits and combine outputs from these subcircuits to recover the original output. Although this approach enables us to simulate larger quantum circuits beyond physically available circuits, it needs classical overheads quantified by two metrics: the sampling overhead in the number of measurements to reconstruct the original output, and the number of channels in the decomposition. Thus, it is crucial to devise a decomposition method that minimizes both of these metrics, thereby reducing the overall execution time. This paper studies the problem of decomposing the n-qubit identity channel, i.e., n-parallel wire cutting, into a set of local operations and classical communication; then we give an optimal wire-cutting method composed of channels based on mutually unbiased bases that achieves minimal overheads in both the sampling overhead and the number of channels, without ancilla qubits. This is in stark contrast to the existing method that achieves the optimal sampling overhead yet with ancilla qubits. Moreover, we derive a tight lower bound on the number of channels in parallel wire cutting without ancilla systems and show that only our method achieves this lower bound among the existing methods. Notably, our method shows an exponential improvement in the number of channels, compared to the aforementioned ancilla-assisted method that achieves optimal sampling overhead. Our work significantly alleviates the additional overheads for the wire-cutting method and may provide essential components for the early

关键词： Quantum algorithms Quantum circuits Quantum information theory

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Evaluating Subtle Positive–Negative Facial Expression Transitions for Monitoring Changes in Personal Internal States 21st

Evaluating Subtle Positive–Negative Facial Expression Trans...

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21st Pacific Rim International Conference on Artificial Intelligence, PRICAI 2024

作者： Zhang, Junyao Shimonishi, Kei Ueda, Hirotada Kondo, Kazuaki Nakamura, Yuichi Graduate School of Informatics Kyoto University Kyoto Japan Academic Center for Computing and Media Studies Kyoto University Kyoto Japan

ISBN: (纸本)9789819601219

Predicting the internal conditions of people who have difficulties explaining their internal states because of dementia or other problems has gained increasing attention. Monitoring internal states requires precise evaluation of weak (less intense) facial expressions, which is challenging due to the significant influence of individual characteristics on facial expressions. For instance, a person may look more like they are smiling or frowning than others even when they are in a neutral state. In addition, ambiguous changes may occur. For example, subtle changes from neutral to positive facial expressions could be similar to those from neutral to negative expressions, which further complicates the evaluation of facial expressions. Conventional FER systems designed for various people with various personal differences often have difficulties in detecting and indexing such subtle changes caused by motion artifacts that exceed the displacement of feature points. In this study, we developed a personalized and customized facial expression recognition (FER) model that can monitor changes in a person’s internal state by recognizing the transitions in their daily facial expressions. The model employs image comparison to monitor a specific person. It is tailored to each individual by training it with the individual’s actual facial expressions. This model is not universal but can be adjusted to individual emotional nuances. To account for arbitrary transitions along positive–negative facial expressions, we developed a two-stage FER framework comprising three deep neural networks (DNNs). The proposed framework uses images without detecting facial feature points. The first stage performs binary classification on the input image pairs and categorizes each image as positive or negative. The second stage compares the images to predict the direction of changes, i.e., whether the expression shifts toward positive or negative. This stage is trained on transitional image pairs, focusing

关键词： Deep neural networks

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Elucidating Theory of Malaysian Data Crisis in Demystifying Dark Data Catalyst 6

Elucidating Theory of Malaysian Data Crisis in Demystifying ...

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6th IEEE Symposium on Computers and informatics, ISCI 2024

作者： Ajis, Ahmad Fuzi Md Ibrahim, Ag. Asri Ag Verma, Manoj Kumar UiTM Cawangan Johor Center of Information Science College of Computing Informatics and Mathematics Segamat Malaysia University Malaysia Sabah Faculty of Computing and Informatics Kota Kinabalu Malaysia Mizoram University Department of Library and Information Science Aizawl India

ISBN: (纸本)9798350353853

This article presents the findings of a research on the dark data phenomenon faced by Small and Medium Enterprises (SME) in Malaysia in connection to the features of dark data from SME perspectives. The dark data was found to be influenced by the data shadow in the form of grey and black data which each differentiated by the intensity of data darkness, a condition that influenced data from being found and utilized. In this study, there were 18 samples produced from Inductive Grounded & Emergent Theory Sampling, which was used to discover acceptable samples for the study, were subjected to qualitative research. Using semi-structured interviews that were recorded, transcribed, and analyzed using the Grounded Theory Methodology, data was obtained. The outcomes of the study emphasized on the emergence of Data Crisis which found to be the major factors contributing to the dark data often found in SME archives. The research demonstrates that there is a dearth of literature on dealing with dark data, indicating that dark data epistemology is still emerging. The findings indicated that the Data Crisis is a situation in which a business proprietor is confronted with the repercussions of inadequate data management. On the basis of the experiences of Malaysian SMEs, a model was proposed to elucidate the data crisis. © 2024 IEEE.

关键词： Data assimilation

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Maximizing complex features to minimize the detectability of content-adaptive steganography

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Multimedia Tools and Applications 2024年 1-19页

作者： Setiadi, De Rosal Ignatius Moses Rustad, Supriadi Andono, Pulung Nurtantio Shidik, Guruh Fajar Faculty of Computer Science Universitas Dian Nuswantoro Semarang50131 Indonesia Research Center for Quantum Computing and Materials Informatics Faculty of Computer Science Universitas Dian Nuswantoro Semarang50131 Indonesia

Content-adaptive steganography has three rules that need to be fulfilled to maximize the performance of the cost function, thereby increasing resistance to steganalysis attacks. This study proposes a combination method of image sharpening, Fuzzy edge detection, and residual weighting to maximize the performance of the three rules. Image sharpening is found to be useful for detailing complex features as required by the complexity first rule, while fuzzy edge detection is found to be effective in maximizing the spreading second rule. The clustering third rule is also implemented by customizing the cost of the pixels outside the embedding areas. Embedding simulation is applied to a modified MiPOD method, which we named MaxMiPOD, where SRM and maxSRMd2 steganalysis trials are carried out at payloads of 0.05, 0.1, 0.2, 0.3, 0.4, and 0.5 bpp. The proposed method produces a very significant performance increase of undetectability compared to the MiPOD standard and state-of-the-art methods, especially at a payload of 0.05 bpp. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Cost functions

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Lag Sequential Analysis for Identifying Blended Learners’ Sequential Patterns of e-Book Note-taking for Self-Regulated Learning

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Educational Technology and Society 2023年第2期26卷 63-75页

作者： Yang, Christopher C. Y. Ogata, Hiroaki Graduate School of Informatics Kyoto University Japan Academic Center for Computing and Media Studies Kyoto University Japan

Blended learning (BL) is regarded as an effective strategy for combining traditional face-to-face classroom activities with various types of online learning tools (e.g., e-books). An effective feature of e-books is the ability to use digital notes. When e-books are used in BL, the strategic adoption of note-taking provides benefits that influence the learners’ progress for self-regulated learning (SRL) and course achievements. However, learners tend to be unsure about how note-taking is performed using online learning materials and lack knowledge of effective strategies for SRL. Furthermore, few studies have investigated blended learners’ sequential patterns of e-book note-taking for SRL. Thus, in this paper, an exploratory study was conducted in an undergraduate course that implemented the BL design. The learning task for the blended learners in the present study was to study the learning material using BookRoll, an e-book system, during in-class and out-of-class learning sessions. Lag sequential analysis of the e-book learning behavior data was conducted to identify the blended learners’ sequential behaviors of e-book note-taking for the cognitive strategy use of SRL. Moreover, the difference between higher and lower-achievement blended learners in terms of their sequential behaviors of e-book note-taking for SRL was revealed. This study can help educators provide evidence-based educational feedback to learners regarding the identified sequential patterns of e-book note-taking that can be applied as effective strategies for promoting the cognitive strategy use of SRL and improvement of course achievement in BL. © 2023,Educational Technology and Society. All Rights Reserved.

关键词： Blended learning Lag sequential analysis Note-taking Self-regulated learning Sequential pattern

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Automatic Construction of a Large-Scale Corpus for Geoparsing Using Wikipedia Hyperlinks 30

Automatic Construction of a Large-Scale Corpus for Geoparsin...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Ohno, Keyaki Kameko, Hirotaka Shirai, Keisuke Nishimura, Taichi Mori, Shinsuke Graduate School of Informatics Kyoto University Japan Academic Center for Computing and Media Studies Kyoto University Japan LY Corporation Japan

ISBN: (纸本)9782493814104

Geoparsing is the task of estimating the latitude and longitude (coordinates) of location expressions in texts. Geoparsing must deal with the ambiguity of the expressions that indicate multiple locations with the same notation. For evaluating geoparsing systems, several corpora have been proposed in previous work. However, these corpora are small-scale and suffer from the coverage of location expressions on general domains. In this paper, we propose Wikipedia Hyperlink-based Location Linking (WHLL), a novel method to construct a large-scale corpus for geoparsing from Wikipedia articles. WHLL leverages hyperlinks in Wikipedia to annotate multiple location expressions with coordinates. With this method, we constructed the WHLL corpus, a new large-scale corpus for geoparsing. The WHLL corpus consists of 1.3M articles, each containing about 7.8 unique location expressions. 45.6% of location expressions are ambiguous and refer to more than one location with the same notation. In each article, location expressions of the article title and those hyperlinks to other articles are assigned with coordinates. By utilizing hyperlinks, we can accurately assign location expressions with coordinates even with ambiguous location expressions in the texts. Experimental results show that there remains room for improvement by disambiguating location expressions. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Location

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Enhancing semantic interoperability across materials science with HIVE4MAT 1

Enhancing semantic interoperability across materials science...

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1st International Workshop on Semantic Materials Science: Harnessing the Power of Semantic Web Technologies in Materials Science, SeMatS 2024

作者： Greenberg, Jane Polson, Kio McClellan, Scott Zhao, Xintong Kalinowski, Alex An, Yuan Metadata Research Center College of Computing and Informatics Drexel University 3675 Market St. PhiladelphiaPA19104 United States

HIVE4MAT is a linked data interactive application for navigating ontologies of value to materials science. HIVE enables automatic indexing of textual resources with standardized terminology. This article presents the motivation underlying HIVE4MAT, explains the system architecture, reports on two evaluations, and discusses future plans. © 2024 CEUR-WS. All rights reserved.

关键词： Simple knowledge organization system (SKOS)

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Implementation of a Mixed Triple Logistic Map and the BB84 Quantum Key Distribution for Secure Image Communication

Implementation of a Mixed Triple Logistic Map and the BB84 Q...

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2024 International of Seminar on Application for Technology of Information and Communication, iSemantic 2024

作者： Morissa, Virnika Shefira Gina Setiadi, De Rosal Ignatius Moses Universitas Dian Nuswantoro Informatics Engineering Department Semarang50131 Indonesia Universitas Dian Nuswantoro Research Center for Quantum Computing and Materials Informatics Faculty of Computer Science Semarang50131 Indonesia

ISBN: (纸本)9798350366648

In the digital era, data communication security is one of the main challenges. This research proposes a new method for secure image communication, which is a mixed triple logistic map and BB84 quantum key distribution. This approach combines the strengths of classical and quantum cryptographic systems to improve security. BB84 quantum key distribution protocol for securely distributing encryption keys. The resulting key is then processed into a hash value using the SHA-256 algorithm. These hash values are converted into ASCII values, which are used to generate three key sequences using the modified logistic map. The three key sequences are combined to form a keystream used in image encryption. Several security metrics are used to evaluate encryption security, including entropy, the Chi-Square test, and pixel correlation. The analysis results show that the encrypted image has an entropy close to eight. In addition, all chi-square values smaller than 293 indicate a uniform distribution. The correlation of nearby pixels in the encrypted image is also very low, where all values are less than 0.01, which indicates the loss of local patterns in the encrypted image. These results demonstrate that the proposed method effectively secures image communications, providing high security and resistance to conventional and quantum cryptographic attacks. © 2024 IEEE.

关键词： Quantum cryptography

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Towards Automated Evidence Extraction: A Case Study of Adapting SAM to Real-World Educational Data 31

Towards Automated Evidence Extraction: A Case Study of Adapt...

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31st International Conference on Computers in Education, ICCE 2023

作者： Okumura, Kouki Horikoshi, Izumi Koike, Kento Ogata, Hiroaki Graduate School of Informatics Kyoto University Japan Academic Center for Computing and Media Studies Kyoto University Japan

ISBN: (纸本)9786269689019

The demand for a shift from intuition- and experience-based to evidence-based education has been growing. A major challenge in realizing this transition is extracting evidence from real-world educational data. Conventionally, this data extraction process is performed by manually choosing classes for comparison. However, the selection requires expert knowledge of which classes should be compared with which indicators. In this study, we propose the use of deep learning algorithms to uncover inherent causal relationships within vast amounts of existing data. Specifically, we employ structural agnostic modeling, a causal search algorithm known for its exceptional performance on real-world data, to extract complex causal candidates in education. This approach has been referred to as "observational causal discovery." We evaluate the effectiveness of this method using real-world educational data and compare its advantages with those of conventional automatic comparison methods. Results demonstrate that the proposed method can identify various causal candidates, including those that are difficult for humans to discern, and even those without causal relationships. Different from existing methods, the proposed approach does not require selected or fixed comparative indices, thus potentially uncovering comparative indices that elude human comprehension. We anticipate that this research will enable the collection of substantial evidence from real-world educational data and promote evidence-based education. © 2023 Asia-Pacific Society for Computers in Education.

关键词： Deep learning

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