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9th International Conference on Language Resources and Evaluation, LREC 2014

作者： Xavier, Clarissa Castellã De Lima, Vera Lúcia Strube PUCRS Graduate Program in Computer Science Porto AlegreRS Brazil

ISBN: (纸本)9782951740884

Open Information Extraction (Open IE) is a strategy for learning relations from texts, regardless the domain and without predefining these relations. Work in this area has focused mainly on verbal relations. In order to extend Open IE to extract relationships that are not expressed by verbs, we present a novel Open IE approach that extracts relations expressed in noun compounds (NCs), such as (oil, extracted from, olive) from "olive oil", or in adjective-noun pairs (ANs), such as (moon, that is, gorgeous) from "gorgeous moon". The approach consists of three steps: detection of NCs and ANs, interpretation of these compounds in view of corpus enrichment and extraction of relations from the enriched corpus. To confirm the feasibility of this method we created a prototype and evaluated the impact of the application of our proposal in two state-of-the-art Open IE extractors. Based on these tests we conclude that the proposed approach is an important step to fulfil the gap concerning the extraction of relations within the noun compounds and adjective-noun pairs in Open IE.

关键词： Information retrieval

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Computational design of serine hydrolases

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science (New York, N.Y.) 2025年第6744期388卷 eadu2454页

作者： Lauko, Anna Pellock, Samuel J. Sumida, Kiera H. Anishchenko, Ivan Juergens, David Ahern, Woody Jeung, Jihun Shida, Alexander F. Hunt, Andrew Kalvet, Indrek Norn, Christoffer Humphreys, Ian R. Jamieson, Cooper Krishna, Rohith Kipnis, Yakov Kang, Alex Brackenbrough, Evans Bera, Asim K. Sankaran, Banumathi Houk, K.N. Baker, David Department of Biochemistry University of Washington Seattle WA United States Institute for Protein Design University of Washington Seattle WA United States Graduate Program in Biological Physics Structure and Design University of Washington Seattle WA United States Department of Chemistry University of Washington Seattle WA United States Graduate Program in Molecular Engineering University of Washington Seattle WA United States Paul G. Allen School of Computer Science and Engineering University of Washington Seattle WA United States Medical Scientist Training Program University of Washington Seattle WA United States Howard Hughes Medical Institute University of Washington Seattle WA United States Department of Chemistry and Biochemistry University of California Los Angeles CA United States

The design of enzymes with complex active sites that mediate multistep reactions remains an outstanding challenge. With serine hydrolases as a model system, we combined the generative capabilities of RFdiffusion with an ensemble generation method for assessing active site preorganization at each step in the reaction to design enzymes starting from minimal active site descriptions. Experimental characterization revealed catalytic efficiencies (kcat/Km) up to 2.2 × 105 M-1 s-1 and crystal structures that closely match the design models (Cα root mean square deviations <1 angstrom). Selection for structural compatibility across the reaction coordinate enabled identification of new catalysts remove with five different folds distinct from those of natural serine hydrolases. Our de novo approach provides insight into the geometric basis of catalysis and a roadmap for designing enzymes that catalyze multistep transformations.

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The University's Integrated ICT Infrastructure: UTAUT2 Implementation

The University's Integrated ICT Infrastructure: UTAUT2 Imple...

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2022 IEEE Creative Communication and Innovative Technology, ICCIT 2022

作者： Akbar, Komputerio Ramadhan, Arief Abdurachman, Edi Trisetyarso, Agung Zarlis, Muhammad Bina Nusantara University Binus Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665468763

Post-pandemic and globalization have accelerated the implementation of Industry 4.0, aided by rapid technological and information advancements. Industry 4.0 has significant consequences for all institutions in developing ICT infrastructure, one of which is educational institutions. Despite the enthusiasm in all educational institutions for using ICT to improve teaching and learning, particularly in universities, integrating technology is becoming problematic. Integrating ICT infrastructure in universities is a multidimensional process involving technology and curriculum, pedagogy, institutional readiness, lecturer competence, and long-term financial planning. Because of this, it is essential to explain the adoption of technology within the scope of this study to make the most of investments made in the integrated ICT infrastructure of the university using the UTAUT2 method. © 2022 IEEE.

关键词： Industry 4.0

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Real-time monitoring system for sudden cardiac death based on container orchestration and Binary Serialization

Real-time monitoring system for sudden cardiac death based o...

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2021 International Symposium on Electronics and Smart Devices, ISESD 2021

作者： Surantha, Nico Wincent Muhamad Isa, Sani BINUS Graduate Program - Master of Computer Science Bina Nusantara University Computer Science Department Jakarta Indonesia

ISBN: (纸本)9781665441469

Sudden Cardiac Death (SCD) is happening because the heart stops pumping the blood to the brain, lungs, et cetera, which will cause death within an hour. With this high risk and low survivability rate, real-time Internet of Things (IoT) monitoring systems have become a solution to tackle this problem. The system needs to be accessible at any time and condition by multiple users who bring up the needs of the availability and scalability of the system. Some research had been conducted on IoT monitoring system but still the result of availability and scalability not acceptable for a real-life scenario. The purpose of this research is to propose an architecture for a real-time IoT monitoring system for sudden cardiac death by using Kubernetes as the container orchestration and ProtocolBuffers as the Binary Serialization. The result shows us applying Kubernetes and ProtocolBuffers gives a good result with 100% successfully stored data and 50.5s end-to-end Execution time for 50000 requests which reflect a high availability and fast system. © 2021 IEEE.

关键词： Containers

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Abstractive Indonesian News Summarization Using BERT2GPT 7

Abstractive Indonesian News Summarization Using BERT2GPT

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7th International Conference on Information Technology, Information Systems and Electrical Engineering, ICITISEE 2023

作者： Nasari, Maulin Maulina, Ayu Girsang, Abba Suganda Computer Science Bina Nusantara University Binus Graduate Program Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350382266

This study examines the necessity of employing BERT2GPT for single-document summarization in the current age of escalating digital data. The primary focus of this work is on the abstractive technique, which tries to generate versatile summaries that surpass the primary sentences of the original content. This study employs two models, namely BERT and GPT -2, for the purpose of the summarization system. The paper introduces the BERT2GPT model, which merges the bidirectional characteristics of BERT with the generative powers of GPT. The findings indicate that the BERT2GPT method successfully catches significant information and linguistic nuances, hence enhancing the quality of the generated summaries. The corresponding average values for Rl, R2, and RL are 0.62, 0.56, and 0.60, respectively. © 2023 IEEE.

关键词： Abstractive Summarization BERT2GPT single-document summarization

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Clustering Steam User Behavior Data using K-Prototypes Algorithm

Clustering Steam User Behavior Data using K-Prototypes Algor...

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International Conference on Engineering, Technology and Innovative Researches 2019, ICETIR 2019

作者： Ranti, Kiefer Stefano Salim, Kelvin Girsang, Abba Suganda Computer Science Department BINUS Graduate Program Master of Computer Science Bina Nusantara University Jakarta Indonesia

The use of user telemetry to gather player behavioral data on video games can be very beneficial to game developers with a certain business model. With the help of user telemetry in game development, it can provide access to data on user behavior from installed game clients platform such as Steam. These behavioral data can be used to find out the Steam user behavioral patterns on playtime distributions that can be studied by developers in order to have a deeper understanding of the behaviors of their players. In this study, the data are clustered using the k-prototypes algorithm, a combination of k-means and k-modes algorithm that can be used to cluster mixed attributes. The result shows that the clusters represent the types and preferences of the players. © 2019 IOP Publishing Ltd. All rights reserved.

关键词： Software design

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On using Euler's Factorization Algorithm to Factor RSA Modulus 4

On using Euler's Factorization Algorithm to Factor RSA Modul...

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4th International Conference on Computing and Applied Informatics 2019, ICCAI 2019

作者： Budiman, M.A. Zarlis, M. Sitompul, O.S. Mawengkang, H. Graduate Program of Computer Science Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia

The RSA public key cryptosystem was among the first algorithms to implement the Diffie-Hellman key exchange protocol. At the core of RSA's security is the problem of factoring its modulus, a very large integer, into its prime factors. In this study, we show a step-by-step tutorial on how to factor the RSA modulus using Euler's factorization algorithm, an algorithm that belongs to the class of exact algorithms. The Euler's factorization algorithm is implemented in Python programming language. In this experiment, we also record the relation between the length of the RSA moduli and its factorization time. As a result, this study shows that the Euler's factorization algorithm can be used to factor small modulus of RSA, the correlation between the factoring time and the size of RSA modulus is directly proportional, and better selection of some Euler's parameters may lead to lower factoring time. © Published under licence by IOP Publishing Ltd.

关键词： Factorization

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Risk Assessment Analysis on Mobile Banking Using Cobit 5 Framework

Risk Assessment Analysis on Mobile Banking Using Cobit 5 Fra...

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2022 IEEE Creative Communication and Innovative Technology, ICCIT 2022

作者： Utamajaya, Joy Nashar Ramadhan, Arief Abdurachman, Edi Trisetyarso, Agung Zarlis, Muhammad Bina Nusantara University Binus Graduate Program - Computer Science Computer Science Department West Jakarta Indonesia

ISBN: (纸本)9781665468763

In general, public or private organizations or companies have used information-based technology as a support to improve business performance to be more effective and efficient in order to achieve a company's business goals. Banking companies include companies that use information technology such as Mobile Banking in their services. Mobile banking is a banking facility or service using mobile communication tools such as mobile phones, with the provision of facilities for banking transactions through mobile applications. Even though they have used a good SOP (Standard Operating Procedure), there are still many obstacles that occur, especially system problems and human errors. This can result in a high risk if it occurs continuously and will be fatal to the company's business processes. Therefore, COBIT 5 can be used as a benchmark for the IT assessment process on local bank mobile banking services. The purpose of the study is to determine the level of capability and strategy for improving risk management. The method used in this study is to focus on IT risk management with the COBIT 5 framework in the Evaluate Direct Monitoring (EDM) 3 domain, Align Plain Organize (APO) 12. From the results of the analysis, the calculation of the capability level is at Level 1 Performed Process with a score of 82.04%, thus the status has evidence as well as a systematic approach and this achievement is obtained significantly through the assessment of process attributes. © 2022 IEEE.

关键词： Risk management

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Fine-Tuning Fasttext Using Bayesian Optimization for Movie Review Sentiment Analysis 1

Fine-Tuning Fasttext Using Bayesian Optimization for Movie R...

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1st International Conference on Technology, Engineering, and Computing Applications, ICTECA 2023

作者： Halim, Rico Girsang, Abba Suganda Riftiarrasyid, Mohammad Faisal Binus Graduate Program Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350360554

The advancements in technology during the 20th century resulted in the onset of the digital computer era. This study investigates the relative importance of earlier algorithms in comparison to more recent ones. Various research projects suggest improving vectorization by combining conventional and modern techniques, while others suggest optimizing it through algorithmic methods. This study primarily focuses on employing Bayesian optimization to optimize hyperparameters, hence improving the performance evaluation of TF-IDF FastText sentiment classification models. This study presented four models: the initial model utilized FastText with a preprocessing step that involved removing stopwords, the second model employed Fast-Text without any optimization using Bayesian optimization, the third model utilized FastText with optimization using Bayesian optimization, and the fourth model combined FastText with TF-IDF and was further optimized using Bayesian optimization. The Support Vector Machine (SVM) technique will be employed to evaluate all of the models. The findings suggest that the model's performance stays unchanged when stopwords are eliminated (Precision, Recall, F1: 0.9007). The model demonstrates a slight enhancement through the utilization of Bayesian optimization, resulting in a 0.02% increase, reaching a final accuracy of 0.9019%. Bayesian optimization is frequently employed to improve performance. The performance of Bayesian optimization is affected by the magnitude of the learning rate, and models that do not utilize Bayesian optimization demonstrate inferior performance. Both the TF-IDF FasText model and FastText model yielded comparable outcomes, attaining an F1 score of 0.9019 after being tuned by Bayesian optimization. © 2023 IEEE.

关键词： Sentiment analysis

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Recommender System Using Transformer Model: A Systematic Literature Review 1

Recommender System Using Transformer Model: A Systematic Lit...

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1st International Conference on Information System and Information Technology, ICISIT 2022

作者： Pohan, Husni Iskandar Warnars, Harco Leslie Hendric Spits Soewito, Benfano Gaol, Ford Lumban Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (数字)9781665402002

ISBN: (纸本)9781665402002

Online transactions are significant in the pandemic era. Using online transactions can minimize the risk of physical contact with disease transmission between buyers and sellers. However, with so many choices of items, it becomes challenging for users to decide which item suits their needs. For this reason, the recommender system was created as a handy tool. Recommender systems can help provide ratings, compare with other user data, use personal transaction history, use current events, or combine the above methods. Currently, computer science experts are constantly trying to improve recommender systems. In 2017 a new method emerged that uses transformers as one of the deep learning models. The combination of recommender systems and transformers can process extensive data, create different weights for each input data, and process data without sequentially allowing parallel processing and reducing training time significantly. Many papers in various countries are continuously trying to improve this methodology. In this literature review, we try to analyze the technology used, the dataset used, and the area where the technology is implemented. In this case, we carry out collecting papers, then filtering, classifying and analyzing, and making conclusions. © 2022 IEEE.

关键词： Recommender systems

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