检索结果-内蒙古大学图书馆

44th Annual Meeting of the cognitive science Society: cognitive Diversity, CogSci 2022

作者： Gok, Sebahat Goldstone, Robert L. Program in Cognitive Science Department of Instructional Systems Technology Indiana University 1101 E. 10th Street BloomingtonIN47405 United States

Reasoning about sampling distributions is notably challenging for humans. It has been argued that the complexity involved in sampling processes can be facilitated by interactive computer simulations that allow learners to experiment with variables. In the current study, we compared the effects of learning sampling distributions through a simulation-based learning (SBL) versus direct instruction (DI) method. While both conditions resulted in similar improvement in rule learning and graph identification, neither condition improved more distant transfer of concepts. Furthermore, the simulation-based learning method resulted in unintuitive and surprising kinds of misconceptions about how sample size affects estimation of parameters while the direct instruction group used correct intuitive judgments more often. We argue that similar perceptual properties of different sampling processes in the SBL condition overrode learners' intuitions and led them to make conceptual confusions that they would not typically make. We conclude that conceptually important differences should be grounded in easily interpretable and distinguishable perceptual representations in simulation-based learning methods. © 2022 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY)

关键词： Learning systems

来源：评论

学校读者我要写书评

暂无评论

The Role of Social Media in Nourishing Digital Ambidexterity Among MSMEs: Rasch Model View 7

The Role of Social Media in Nourishing Digital Ambidexterity...

引用

7th International Conference on Information Management and Technology, ICIMTech 2022

作者： Herlina, Maria Grace Iskandar, Karto Rinaldi, Banu BINUS Business School Undergraduate Program Bina Nusantara University Management Department Jakarta11480 Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Bina Nusantara University Business Creation Program Management Department BINUS Business School Undergraduate Program Jakarta11480 Indonesia

ISBN: (数字)9781665450904

ISBN: (纸本)9781665450904

Indonesians have a keen understanding of technology. However, just 7.4% of all Indonesian MSMEs use digital channels. Even though only a small percentage of MSMEs have used them, the adoption rate has been impressive. Using Rash Model Analysis, the results show that social media experiences substantially impact Indonesian MSMEs' digital ambidexterity. The study's findings imply that small and medium-sized businesses (SMEs) should prioritize their social media experience to anticipate change. To maximize their digital ambidexterity, MSMEs must access sufficient digital environments. A foundation has been laid for future research into the digitalization of small and medium-sized businesses. Small and medium-sized businesses (SMEs) can take advantage of Indonesia's high social media use, which presents several opportunities. © 2022 IEEE.

关键词： Social networking (online)

来源：评论

学校读者我要写书评

暂无评论

Forecasting dining times in a full-service Thai hotpot restaurant Using Random Forest Classifier 23

Forecasting dining times in a full-service Thai hotpot resta...

引用

8th International Conference on Mathematics and Artificial Intelligence, ICMAI 2023

作者： Kongnim, Pongjit Cooharojananone, Nagul Chavarnakul, Thira Technopreneurship and Innovation Management Program Graduated School Chulalongkorn University Thailand Department of Mathematics and Computer Science Chulalongkorn University Thailand Department of Commerce Chulalongkorn Business School Chulalongkorn University Thailand

ISBN: (纸本)9781450399982

In the foodservice industry, time is a crucial factor that impacts both consumers and management. Machine learning (ML) is increasingly used to improve the quality of services through prediction. In this study, we aim to develop a model for predicting meal duration using Random Forest Classification algorithm. The study uses data from the Point-of-Sale (POS) system of a full-service Thai hotpot restaurant, with a focus on two commercial areas in Bangkok. The variables that we used include the branch, the number of customers, the number of items, the day of the week, and the time of the day. As a result, the overall accuracy of the model was 86% and the F1-score was 0.81. The discussion of the potential use of this approach in connection with the existing system in a restaurant could also be beneficial, aiding the restaurant in planning management more efficiently and gaining a better understanding of consumer behavior. This study will discuss the results of the model along with additional perspectives for future work. © 2023 Copyright held by the owner/author(s)

关键词： Consumer behavior

来源：评论

学校读者我要写书评

暂无评论

The Influence of Leadership and Lecturer Commitment on Civic Education through Online Teamwork 6

The Influence of Leadership and Lecturer Commitment on Civic...

引用

6th International Conference on Digital Technology in Education, ICDTE 2022

作者： Benawa, Arcadius Pane, Murty Magda Character Building Development Center Mass Communication Program Communication Department Faculty of Digital Communication and Hotel and Tourism Bina Nusantara University Jakarta Indonesia Character Building Development Center School of Computer Science Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781450398091

This research is motivated by concerns of the education management of students, who are studying civic education. This study aimed to determine the influence of leadership and lecturer’s commitment on the effectiveness and efficiency of civic education. This research was also conducted as a reference material for lecturers to improve their effectiveness and efficiency in lecturing students who have done online teamwork for particular projects in civic education courses. The result of this study showed that there are significant influence of the leadership and lecturer’s commitment on civic education. Therefore, it is very relevant and urgent for lecturers to improve the quality of their leadership and commitment in lecturing civic education. © 2022 Association for Computing Machinery.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

The Correlation between Organizational Commitment and SECI Model Implementaton during Knowledge Sharing Activities in Online Teamwork 5

The Correlation between Organizational Commitment and SECI M...

引用

5th International Conference on Education Technology Management, ICETM 2022

作者： Pane, Murty Magda Benawa, Arcadius Character Building Development Center School of Computer Science Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Character Building Development Center Mass Communication Program Communication Department Faculty of Digital Communication and Hotel and Tourism Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781450398015

This research's objective is to get the information about the correlation between organizational commitments of the students and the knowledge sharing activities the students have done. The specific model chosen in this research for knowledge sharing is the SECI Model. It used an experimental model combined with quantitative method. It used 92 respondents from several departments and second semester. It used questionnaires for SECI Model and Organizational Commitment, and they got > 0.250 for corrected total item correlations and Cronbach alpha, so all the itmes in the questionnaires are valid and reliable. The respondents tend to choose the scale of 4 (46.965% in average), 3 (26.855% in average) and 5 (17.913% in average). The correlations between organizational commitment and every process of SECI Model are 0.366, 0.270, 0.213 and 0.707. These results show that organizational commitment of the respondents have positive linear relationships with every process of SECI Model. © 2022 ACM.

关键词： Students

来源：评论

学校读者我要写书评

暂无评论

LLM2Vec Sentence Embeddings Analysis in Sentiment Classification

LLM2Vec Sentence Embeddings Analysis in Sentiment Classifica...

引用

International Conference on Data and Software Engineering (ICODSE)

作者： Matthew Martianus Henry Nur Adhianti Hervanto Mahmud Isnan Dian Kurnianingrum Chyntia Ika Ratnapuri Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Entrepreneurship Department Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331506407

ISBN: (纸本)9798331506414

Sentiment analysis is crucial method in business intelligence to extract insights, which typically begin with sentiment classification. One of the latest frameworks for generating sentence embeddings for sentiment classification is LLM2Vec, which allows Transformer decoder-based models to generate sentence embeddings for text representation. Its capability is deemed language-agnostic, which, in this study, the framework is leveraged for Tokopedia tweet sentiment analysis to prove the claim. The base decoder models used in the LLM2Vec framework were Llama 3 8B, Llama 2 7B, Sheared Llama 1.3B, and Mistral 7B. Two BERT-based models, which are the Indonesian SBERT model and IndoBERT trained with the SimCSE approach, were employed as a comparison. The generated embeddings were classified using logistic regression, SVM, and MLP Classifier. Classifiers using embedding generated by LLM2Vec with Llama 3 8B and Mistral 7B achieves on-par performance with classifiers that utilize IndoBERT SimCSE embeddings, while classifiers using embeddings generated by LLM2Vec with Llama 2 7B and Sheared Llama 1.3B achieves much lower performance. Classifiers with Indonesian SBERT embeddings achieve the highest F1 score performance. Despite slightly lower performance, this study has proven the language-agnostic capability of LLM2Vec, especially with Llama 3 8B and Mistral 7B in colloquial Bahasa Indonesia sentiment analysis, since none of the base decoders were ever trained using the Bahasa Indonesia corpus.

关键词： Support vector machines Sentiment analysis Logistic regression Social networking (online) Blogs Transformers Encoding Decoding Business intelligence Software engineering

来源：评论

学校读者我要写书评

暂无评论

Mitigating Inappropriateness in Image Generation: Can there be Value in Reflecting the World’s Ugliness?

arXiv

引用

arXiv 2023年

作者： Brack, Manuel Friedrich, Felix Schramowski, Patrick Kersting, Kristian Germany Computer Science Department TU Darmstadt Germany Germany LAION Germany Centre for Cognitive Science TU Darmstadt Germany

Text-conditioned image generation models have recently achieved astonishing results in image quality and text alignment and are consequently employed in a fast-growing number of applications. Since they are highly data-driven, relying on billion-sized datasets randomly scraped from the web, they also reproduce inappropriate human behavior. Specifically, we demonstrate inappropriate degeneration on a large-scale for various generative text-to-image models, thus motivating the need for monitoring and moderating them at deployment. To this end, we evaluate mitigation strategies at inference to suppress the generation of inappropriate content. Our findings show that we can use models’ representations of the world’s ugliness to align them with human preferences. © 2023, CC BY.

关键词： Behavioral research

来源：评论

学校读者我要写书评

暂无评论

Proposing a visualized comparative review analysis model on tourism domain using Naïve Bayes classifier 8

Proposing a visualized comparative review analysis model on ...

引用

8th International Conference on computer science and Computational Intelligence, ICCSCI 2023

作者： Sano, Albert Verasius Dian Stefanus, Adriel Anderson Madyatmadja, Evaristus Didik Nindito, Hendro Purnomo, Agung Sianipar, Corinthias P.M. Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta11480 Indonesia Kyoto University Kyoto606-8502 Japan

This study, using the Naïve Bayes classifier, proposes a new descriptive model for conducting a comparative review analysis on the tourism domain. The proposed model seeks to improve the understanding of tourists' experiences by visually representing their opinions between various tourist destinations. The model predicts the sentiment of tourist reviews using the Naive Bayes classifier, which is then used to generate visualizations that facilitate comparative analysis. The comparison takes two tourism sites as experimental examples. The results, in terms of accuracy, show 80% and 64% for the first and the second site respectively. The study discusses the model's implementation, effectiveness, and potential applications in the tourism industry. The findings of the study suggest that the proposed model can provide valuable insights into tourist experiences and help tourism stakeholders, such as the managements of tourism sites, the future or soon coming tourists to make informed decisions based on comparative analysis. © 2023 The Authors. Published by Elsevier B.V.

关键词： Comparative review analysis Naïve Bayes classifier tourism

来源：评论

学校读者我要写书评

暂无评论

Detect Areas of Upward and Downward Fluctuations in Bitcoin Prices Using Patterned Datasets 9

Detect Areas of Upward and Downward Fluctuations in Bitcoin ...

引用

9th IEEE Information Technology International Seminar, ITIS 2023

作者： Parlika, Rizky Mustafid Rahmat, Basuki Pascasarjana School Diponegoro University Department of Doctoral Program of Information System Semarang Indonesia University of Pembangunan Nasional 'Veteran' Jawa Timur Department of Informatics Faculty of Computer Science Surabaya Indonesia

ISBN: (纸本)9798350306835

Many researchers have proposed various theories and techniques to estimate the value of Bitcoin. However, there is still a great opportunity to suggest a new approach to Bitcoin forecasting. This research will examine the concept of forming a patterned dataset to prove the hypothesis regarding the start of a bitcoin price fluctuation until the end of the fluctuation using patterned dataset pairs in conditions of price decline (moon) and in conditions of price decline (crash). Patterned datasets were initially built from data on the movement of all cryptocurrency assets on a digital cryptocurrency trading market. The Patterned Dataset is programmed based on the response of all crypto assets to changes in the price of bitcoin over time. Patterned datasets are better able to describe the conditions of the digital cryptocurrency market, along with patterns of potential increases and decreases in Bitcoin prices in particular and cryptocurrencies in general. To deepen the observations, resampling of the patterned dataset was carried out with a 4-hour timeframe using the mean, median, min, max, and sum filter functions on pairs of crash and moon conditions per month. The results show that filter functions other than sum, namely mean, median, min, and max, provide markings of fluctuation area patterns that are easier to recognize. Two hypotheses related to fluctuations were also successfully proven in this research. © 2023 IEEE.

关键词： Bitcoin

来源：评论

学校读者我要写书评

暂无评论

Performance Analysis of Distributed Database System in Cloud Computing Environment

Performance Analysis of Distributed Database System in Cloud...

引用

International Conference on Computing, Engineering, and Design (ICCED)

作者： Nicholas Prasetio Daniel Ferdinand Brandon Christopher Wijaya Maria Susan Anggreainy Afdhal Kumiawan Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department Computer Science Bina Nusantara University Jakarta Indonesia BINUS Graduate Program School of Computer Science Bina Nusantara University Jakarta Indonesia

This research discusses the performance evaluation of distributed database systems in a cloud computing environment Cloud computing environments allow data and applications to be stored and deployed on infrastructure located in different parts of the world. However, the use of distributed database systems in cloud computing environments can cause performance issues, such as complex data access and factors such as network latency, security, and scalability that affect system performance. Therefore, performance evaluation of distributed database systems is necessary to ensure effective data management across the infrastructure. The purpose of this research is to measure and understand the performance of distributed database systems in a cloud computing environment. This is important because proper performance evaluation is needed to ensure distributed database systems can operate effectively and efficiently in such environments. This research will analyze the features of distributed database systems, factors that affect performance, how to measure and compare system performance, and how to improve system performance. Analyzing the performance of distributed database systems in a cloud computing environment can help users choose the most appropriate and efficient cloud computing platform for their business needs and improve operational efficiency.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：