DSpace collection: 會議論文

Balancing Personalization and Privacy in AI Advertising: An S-O-R Framework of Consumer Perception, Brand Attitude, and Purchase Intention

Tue, 23 Jun 2026 04:06:25 GMT

title: Balancing Personalization and Privacy in AI Advertising: An S-O-R Framework of Consumer Perception, Brand Attitude, and Purchase Intention abstract: The rapid integration of Artificial Intelligence (AI) into digital marketing strategies has revolutionized the advertising landscape, enabling unprecedented levels of personalization and automated content generation. However, this technological shift introduces complex paradoxes regarding consumer trust, perceived authenticity, and data privacy. This study addresses the need for a comprehensive understanding of consumer responses to AI-generated advertising in emerging markets. Drawing on the Stimulus–Organism–Response (S–O–R) framework, this research empirically examines how Thai consumers process various AI-related advertising stimuli and how these perceptions shape their brand attitudes and purchase intentions. The conceptual model positions seven key advertising characteristics—AI source perception, trust in AI, perceived authenticity, perceived personalization, ad relevance, ad value, and privacy concern—as external stimuli. Brand attitude functions as the central organismic mediator, while purchase intention serves as the behavioral response. To capture individual differences in decision-making, product involvement is examined as a moderating variable. Data were collected via a structured questionnaire from 405 digitally active Thai consumers and analyzed using multiple regression. The empirical results indicate that consumer evaluations are primarily driven by higher-order integrative judgments rather than by isolated technological cues. Specifically, perceived authenticity and advertising value were identified as the most significant predictors of favorable brand attitudes. Interestingly, privacy concerns did not exert a significant negative influence, suggesting that, in general consumer contexts, the perceived utility of the advertisement may mitigate potential data anxieties. Furthermore, moderation analysis revealed that product involvement negatively moderates the relationship between brand attitude and purchase intention, implying that AI-driven brand building is particularly effective for low-involvement product categories. These findings offer actionable insights for marketers, suggesting a strategic pivot from emphasizing AI technology to delivering authentic, high-value content.

Exploring the Impact of Interactivity and Trust on Consumer Purchase Intention in Live Shopping Based on the SOR Theory: A Case Study of TikTok

Fri, 20 Mar 2026 04:07:06 GMT

title: Exploring the Impact of Interactivity and Trust on Consumer Purchase Intention in Live Shopping Based on the SOR Theory: A Case Study of TikTok

探討社群媒體環境中消費者購買決策情感架構之研究

Fri, 20 Mar 2026 04:07:03 GMT

title: 探討社群媒體環境中消費者購買決策情感架構之研究

Entrepreneurship Education in Tourism: Fostering Thinking Skills, Creativity, and Entrepreneurial Intentions

Fri, 20 Mar 2026 04:06:58 GMT

title: Entrepreneurship Education in Tourism: Fostering Thinking Skills, Creativity, and Entrepreneurial Intentions

VR Event Marketing and Technology Readiness in Asia: Bridging Virtual and Real Experiences in Event Tourism

Fri, 20 Mar 2026 04:06:54 GMT

title: VR Event Marketing and Technology Readiness in Asia: Bridging Virtual and Real Experiences in Event Tourism

AI-Driven Healthcare Decision Support System: Utilizing Machine Learning and Sentiment Analysis to Interpret Patient Feedback

Fri, 20 Mar 2026 04:06:48 GMT

title: AI-Driven Healthcare Decision Support System: Utilizing Machine Learning and Sentiment Analysis to Interpret Patient Feedback abstract: With medical digitalization, online patient reviews have become crucial for evaluating healthcare quality. Traditional surveys face limitations in sample size and response rate, hindering real-time patient satisfaction assessment. This study develops an AI-driven Healthcare Decision Support System (AI-DSS) using NLP and ML to analyze patient reviews from NTUH and TVGH, identifying key satisfaction factors. Using BERT for sentiment analysis and text mining, feedback is categorized into five dimensions: facility environment, waiting time, staff attitude, medical procedures, and treatment outcomes. Multiple linear regression quantifies their impact on satisfaction, while a ChiSquare Test compares hospital performance. Results show waiting time and staff attitude as critical factors, with significant differences in the facility environment and staff attitude (p < 0.001). This study confirms AI's role in real-time satisfaction monitoring and data-driven healthcare improvements

連接虛擬與現實世界：VR 展覽活動行銷對參與度和滿意度的影響

Fri, 20 Mar 2026 04:06:40 GMT

title: 連接虛擬與現實世界：VR 展覽活動行銷對參與度和滿意度的影響

Enhancing regional revitalization through AI-guided co-creation: The role of place attachment and emotional cohesion in tourist behavioral loyalty

Fri, 20 Mar 2026 04:06:37 GMT

title: Enhancing regional revitalization through AI-guided co-creation: The role of place attachment and emotional cohesion in tourist behavioral loyalty

Driving Green Food Choices: The Interplay of Self-Identity, Cognitive Engagement, and Emotional Involvement

Fri, 13 Mar 2026 04:07:21 GMT

title: Driving Green Food Choices: The Interplay of Self-Identity, Cognitive Engagement, and Emotional Involvement

瞭解大學成為關係人口的關鍵因素-以地方創生觀點為例

Fri, 13 Mar 2026 04:07:16 GMT

title: 瞭解大學成為關係人口的關鍵因素-以地方創生觀點為例

以社會交換理論探討大淡水地區居民與學生之共創價值和顧客公民行為

Fri, 13 Mar 2026 04:07:11 GMT

title: 以社會交換理論探討大淡水地區居民與學生之共創價值和顧客公民行為

The Relationships of Co-Creation between Tamsui and Traveler

Fri, 13 Mar 2026 04:07:07 GMT

title: The Relationships of Co-Creation between Tamsui and Traveler

Risk management and legal compliance: An exploratory study of BNP Paribas’s Provence Mediterranean business and finance trade center

Fri, 06 Mar 2026 04:09:03 GMT

title: Risk management and legal compliance: An exploratory study of BNP Paribas’s Provence Mediterranean business and finance trade center abstract: The financial service industry nowadays, especially banks and non-bank financial intermediaries, are facing intense scrutiny. Due to this, the banking sector places a significant emphasis on risk management and legal compliance, focusing on intricate international regulations. This involves a structured process of identifying, assessing, controlling, and monitoring risks to minimize potential losses and optimize the opportunities available. In face of increasingly stringent international regulations and growing stakeholder expectations, banks must safeguard their integrity, reputation, and financial stability. These complexities have compelled banks to establish robust risk management frameworks and ensure adherence to legal and regulatory standards. BNP Paribas is a leading French bank with a significant international presence and will be the subject to this research. This research objective is to evaluate the impact of international banking regulations on risk management and compliance. A qualitative approach is done by combining in-depth interviews with business managers as well as risk and compliance officers within a Business and Finance Center along with participant observations and internal documents. Through this research, it demonstrates the effective risk management through activity diversification and the use of high-performance tools. Another factor is compliance, which plays a vital role in operational compliance within the Business and Finance Center which is shown by recruiting a compliance team with a commercial background, improving communication between business and compliance managers, and developing dedicated compliance tools. In conclusion, this thesis emphasized the significance of risk management and legal compliance in the banking sector, shedding light on the specific practices and challenges faced by BNP Paribas’s Business and Finance Center. The results demonstrates that operational risk can be attributed to management errors due to inadequate implementation of control systems. It also confirms that diversification of banking activities serves as an advantage during crises. It also shows that the impact of compliance on professional activities varies according to the type of business that is done as some may be more impacted compared to the others. Lastly, the use of risk management tools and awareness-raising training shows a positive impact due to the usefulness of these approaches particularly towards new employees. In conclusion, the outcomes of this study offer valuable insights for risk management and compliance professionals, as well as other stakeholders in the banking sector seeking to strengthen their practices in these critical areas.

A study of effectual market creation in the cross-border e-commerce of SMEs: The case of eBay in Vietnam

Fri, 06 Mar 2026 04:09:01 GMT

title: A study of effectual market creation in the cross-border e-commerce of SMEs: The case of eBay in Vietnam abstract: This study investigates the impact of effectual market creation on the international performance of SMEs engaged in cross-border business in Vietnam. The study adapts a previous model from a former research to the Vietnamese. The results of the study were surprising and revealed two main findings. Firstly, found that effective market development had a direct negative influence on international performance. What are the specific impacts that need to be researched in the future, maybe can take a look: resource allocation, market structure, cultural and regulatory challenges, habits of domestic development. Secondly, the researchers found that effective market development had a positive indirect effect on international performance through mediators which were international networking, international marketing analytics, and logistics solutions. Overall, when considering the total effect, the researchers found that the impact of effective market creation on international performance remained positive. This means that despite the direct negative influence, the combined effect of effective market development and its mediations had an overall positive impact on international performance. The findings offer a new perspective for SMEs entering the global market, particularly those who want to doing business on eBay. The study suggests that the effectuation-based model can be applied to analyze various digital endeavors in the international marketplace.

The influence of cultural diversity on technology adoption: A multi-case study of smart retail companies in Haiti

Fri, 06 Mar 2026 04:08:58 GMT

title: The influence of cultural diversity on technology adoption: A multi-case study of smart retail companies in Haiti abstract: This paper investigates the influence of cultural diversity on technology adoption within the context of smart retail companies in Haiti. Employing a multi-case study approach, the research explores how various cultural factors impact the adoption and implementation of technology in the retail sector. Drawing upon Hofstede's cultural dimensions theory and relevant literature on technology adoption, the study examines the attitudes, behaviors, and challenges encountered by smart retail companies in Haiti. Through in-depth interviews, and analysis of company practices, the research identifies key cultural drivers and barriers affecting technology adoption, including communication styles, perceptions of innovation, and organizational structures. The findings contribute to both theoretical understanding and practical implications for enhancing technology adoption strategies in culturally diverse contexts, offering insights to inform decision-making and policy development in the Haitian retail industry and beyond.

The influence of cultural intelligence on job performance: The mediating roles of cross-cultural adaptation and the moderating roles of cross-cultural communication—A case study of Taiwanese companies entering the Indian market

Fri, 06 Mar 2026 04:08:54 GMT

title: The influence of cultural intelligence on job performance: The mediating roles of cross-cultural adaptation and the moderating roles of cross-cultural communication—A case study of Taiwanese companies entering the Indian market abstract: This thesis explores how cultural intelligence (CQ) enhances job performance among Taiwanese expatriates in India, emphasizing the mediating role of cross-cultural adaptation (CCA) and the moderating influence of cross-cultural communication (CCC). Employing structural equation modeling for analysis, the study reveals that the cognitive, metacognitive, motivational, and behavioral dimensions of CQ positively influence CCA, thereby contributing to improved job performance. Furthermore, effective CCC enhances the relationship between CCA and job performance, underscoring communication's pivotal role in achieving success in global business environments. The study underscores the importance for Taiwanese companies to invest in CQ training and enhance cross-cultural communication competencies to facilitate smoother adaptation and enhance job performance within India's diverse market. While focused on Taiwanese firms in India, the research offers valuable insights applicable to other cultural contexts and industries. Future studies could broaden the scope to different nations and explore additional moderating factors, aiming to deepen our understanding of how CQ interacts with job performance across various international settings.

The influence of green marketing on brand loyalty with the mediating role of customer perception and the moderating effect of green practices: A case study of bottled water brands in Thailand

Thu, 05 Mar 2026 04:10:58 GMT

title: The influence of green marketing on brand loyalty with the mediating role of customer perception and the moderating effect of green practices: A case study of bottled water brands in Thailand abstract: This quantitative study investigates the influence of green marketing strategies on brand loyalty in the Thai bottled water market. Specifically, it focuses on the Namthip, Sprinkle Water, Purra Water, Singha Water, and Crystal Water brands. By examining consumer perceptions of green marketing and their brand loyalty towards these brands, the study aims to provide empirical support for optimizing marketing strategies. The research employs a survey methodology to collect data from Thai consumers. The sample size is 336 respondents in total, distributed through social media platforms. The questionnaire includes measures of such as, green marketing, customer perceptions, brand loyalty, and demographic characteristics. Statistical analysis techniques, such as regression analysis, is applied to assess the correlations of investigated constructs. Green marketing initiatives through green advertisement, eco-friendly packaging, and carbon footprint labeling had positive impact to customer perception. Customer perception positively impact brand loyalty while also mediates the correlation between green marketing and brand loyalty. However, green practice’s impact between customer perception and brand loyalty is not significant. The findings of this study provide a better comprehend the effectiveness of green marketing in fostering brand loyalty in the Thai bottled water industry. Additionally, the results may provide valuable recommendations for businesses aiming to enhance their sustainability efforts and build stronger relationships with consumers.

Predicting students’usage intention of personal carbon passbook by using artificial neural network method

Thu, 05 Mar 2026 04:10:54 GMT

title: Predicting students’usage intention of personal carbon passbook by using artificial neural network method abstract: As the impacts of climate change intensify, global attention to environmental protection and carbon emission reduction continues to grow. In response to this trend, Taiwan is actively implementing various energy-saving and carbon-reduction policies. Among these, the concept of the personal Carbon Passbook is gradually emerging, aiming to encourage individuals to reduce carbon emissions through daily actions. This study references the Unified Theory of Acceptance and Use of Technology (UTAUT) to design a questionnaire survey, targeting undergraduate to doctoral students to explore the factors influencing their willingness to use the Carbon Passbook. Artificial Neural Networks (ANN) are then employed for analysis and prediction. The research results show that when predicting with complete constructs, the accuracy and weighted average F1-Score are 0.87 and 0.88, respectively. After removing different constructs, both accuracy and the weighted average F1-Score decrease, especially when the Facilitating Conditions (FC) construct is removed, indicating that facilitating conditions have a significant impact on students' willingness to use the Personal Carbon Passbook. Based on these results, it is recommended that managers prioritize enhancing relevant technical support and basic resources when promoting the Personal Carbon Passbook. This ensures that students can use the Personal Carbon Passbook conveniently, effectively increasing their willingness to use it. This study reveals the key factors influencing students' intention to use the Carbon Passbook and provides targeted suggestions, hoping to encourage more young people to actively participate in carbon reduction activities and contribute to achieving the global net-zero emission goal.

Cubicpower Agentic Mixture of Experts(AMoE) Framework for Fine-Tuning NLP Tasks Without GPUs

Thu, 27 Nov 2025 04:05:54 GMT

title: Cubicpower Agentic Mixture of Experts(AMoE) Framework for Fine-Tuning NLP Tasks Without GPUs abstract: The rise of Green AI emphasizes minimizing the environmental footprint of AI systems. This paper explores a no-GPU agentic architecture for fine-tuning NLP tasks. It presents our initial experiments applying these no-GPU algorithms in pretraining and fine-tuning tasks on our CubicPower agentic mixture of experts (AMoE) framework, with the aim of contributing to more sustainable AI development. In contrast to the training procedures of neural networks, which consume significant power, the AMoE framework’s primary contribution toward power savings is that it requires no training process. We explore non-neural-network methods for solving NLP tasks and employ similarity measures to match predefined patterns for use in a RAG database.

The Impact of Consumer Confidence, Trading Volume, and Exchange Rates on Stock Prices in Indonesia: Mediating Effects of ESG Risk Ratings and Inflation

Mon, 08 Sep 2025 04:05:42 GMT

title: The Impact of Consumer Confidence, Trading Volume, and Exchange Rates on Stock Prices in Indonesia: Mediating Effects of ESG Risk Ratings and Inflation abstract: This study examines the complex interplay between macroeconomic factors, ESG (Environmental, Social, and Governance) risk ratings, and stock price performance within the Indonesian stock market. We conducted an empirical analysis of 77 Indonesian companies listed on both the Indonesia Stock Exchange (IDX) and CSRHub from 2019 to 2023. We used a panel regression model to assess the direct effects of key variables and employed Sobel, Aroian, and Goodman tests to evaluate potential mediating effects. The findings reveal that while ESG risk ratings significantly influence stock prices, consumer confidence index, stock trading volume, exchange rates, and inflation do not exert a direct impact. Although these macroeconomic factors do influence inflation and ESG risk ratings, the study concludes that neither of these variables mediates the relationship between consumer confidence, trading volume, exchange rates, and stock prices. These findings offer valuable insights for investors and policymakers, highlighting the growing importance of ESG considerations in investment decisions and long-term value creation in the Indonesian emerging market.

Forecasting Renewable Energy Generation Using Random Forest Analysis

Mon, 08 Sep 2025 04:05:39 GMT

title: Forecasting Renewable Energy Generation Using Random Forest Analysis abstract: Renewable energy forecasting is critical for sustainable energy development and grid stability. This study applies a Random Forest model to analyze the contribution of different renewable energy sources to total energy generation in Taiwan. The results indicate that geothermal and solar energy have the highest impact, while offshore wind, onshore wind, and conventional hydropower contribute less significantly. This analysis aligns with previous research and highlights the necessity of optimizing renewable energy strategies. By leveraging machine learning techniques, policymakers can gain deeper insights into renewable energy trends and make data-driven decisions to enhance energy security and efficiency. The study also suggests that further improvements in wind energy forecasting could contribute to better grid stability. Future research could explore hybrid machine learning approaches to refine predictive accuracy and model robustness.

Research on the application of artificial intelligence in restaurant management of Donghua hot pot

Wed, 18 Jun 2025 04:05:51 GMT

title: Research on the application of artificial intelligence in restaurant management of Donghua hot pot

Utilizing Big Data Statistical Analysis for Construction Progress Management

Wed, 18 Jun 2025 04:05:49 GMT

title: Utilizing Big Data Statistical Analysis for Construction Progress Management

使用文字探勘及情感分析探討醫療體系服務之滿意度研究

Tue, 12 Nov 2024 04:05:41 GMT

title: 使用文字探勘及情感分析探討醫療體系服務之滿意度研究

TANET 2024-Contrastive Learning Recommendation Systems with Time-Variant Objectives

Mon, 28 Oct 2024 04:05:46 GMT

title: TANET 2024-Contrastive Learning Recommendation Systems with Time-Variant Objectives abstract: Recommendation systems have seen significant advancements with the application of machine learning techniques, yet challenges remain in maintaining optimal performance throughout training. Contrastive learning, while effective in enhancing user and item representations, often suffers from performance degradation over time. In this paper, we present a novel approach that incorporates time-variant objectives (TVO) to address this issue. By integrating a scheduler with various time-variant functions into the contrastive learning framework, we dynamically balance the recommendation loss and contrastive loss during training. This method stabilizes model performance and mitigates the typical decline observed in traditional approaches. Our experimental results show that the TVO-enhanced model achieves more reliable and precise recommendations compared to existing methods. This approach offers a promising solution for improving the consistency and accuracy of contrastive learning-based recommendation systems. Keywords: Recommendation Systems, Contrastive Learning, Time Variant Objectives, TVO, GCN

Investor Sentiment and Cross-Market Volatility Spillovers: Evidence from ESG-Rated Stock Indexes

Fri, 09 Aug 2024 04:06:30 GMT

title: Investor Sentiment and Cross-Market Volatility Spillovers: Evidence from ESG-Rated Stock Indexes

The Impact of Emotional Appeals and Brand Awareness on Purchase Intentions: The Mediating Role of Electronic Word-of-Mouth in Facebook Live Streaming

Fri, 09 Aug 2024 04:06:27 GMT

title: The Impact of Emotional Appeals and Brand Awareness on Purchase Intentions: The Mediating Role of Electronic Word-of-Mouth in Facebook Live Streaming

以資訊計量學探討平台經濟及數位政府議題之研究：運用科學知識圖譜分析科學體系結構之脈絡

Fri, 09 Aug 2024 04:06:23 GMT

title: 以資訊計量學探討平台經濟及數位政府議題之研究：運用科學知識圖譜分析科學體系結構之脈絡

以資訊計量學探討開放資料之研究

Fri, 09 Aug 2024 04:06:20 GMT

title: 以資訊計量學探討開放資料之研究

Driving Green Food Choices: The Interplay of Self-Identity, Cognitive Engagement, and Emotional Involvement

Wed, 31 Jul 2024 04:12:55 GMT

title: Driving Green Food Choices: The Interplay of Self-Identity, Cognitive Engagement, and Emotional Involvement

Perception of Sustainable Change Strategy and Resistance to Change: A Moderated Mediation Model

Tue, 09 Apr 2024 04:05:31 GMT

title: Perception of Sustainable Change Strategy and Resistance to Change: A Moderated Mediation Model

以BERT語言模型及價值信念規範理論探討平台經濟下之綠色消費消費者評論

Wed, 21 Feb 2024 04:06:30 GMT

title: 以BERT語言模型及價值信念規範理論探討平台經濟下之綠色消費消費者評論 abstract: 近年來因綠色消費逐漸受到政府、企業、組織及消費者的重視，然而徹底推動並落實綠色消費並不容易。人們的價值觀、信念、個人規範和環境行為之間的關係會影響環境，因而本研究為瞭解支持綠色購物計畫的消費者真實想法及感受，進而瞭解推動綠色消費的重要成功關鍵因素及管理意涵。本研究以價值信念規範理論為基礎，提出價值信念規範及綠色行研究模型（Value-belief-norm and green behavior research model，VBNG model），探討於因果鏈中消費者所採取綠色行為之動機。並以平台綠色消費者為例，以目前提供綠色消費的品牌為基礎，使用爬蟲技術及自然語言處理，擷取 Facebook 及 IG 社群媒體平台上與綠色消費、環保消費等字詞相關之貼文及討論，以 BERT（Bert-base-chinese）語言模型分析其語意及情緒，建立情緒、面向、面向情緒等三個分類系統，使企業更加瞭解消費者真實想法及回饋，進而優化平台的綠色消費服務品質。本研究以二階段進行：(1)以價值信念規範及綠色行研究模型構面面向進行多標籤分類，(2)評論情緒的多類別分類及各面向情緒的多輸出分類。實驗系統以 BERT 預訓練語言模型搭配遷移學習，並評估其多類別、多標籤、多輸出分類系統之準確度，最後並以嚴格準確率作為評估指標。

IMP2023-圖文組特徵設計與分類互轉方法

Mon, 11 Dec 2023 04:06:01 GMT

title: IMP2023-圖文組特徵設計與分類互轉方法 abstract: 本文所追尋的是文字和影像一起處理的方法,就是找出圖文特徵值。我們可以讓影像和文字間做一個連結,那麼以後就能夠先不用做分類,而是直接找影像或文字,再連結到另一方去,之後再去做分類的判別。同時若是日後個別影像和文字有所變動,我們也希望只抽換變動部分即可,不需重新加以訓練。可用文字查詢圖文特徵,也可用影像查詢圖文特徵,再找出資料集中哪個圖文組和它最相近。圖文特徵向量可和圖文特徵矩陣算出相似度,不同圖文特徵間也可計算相似度。文字特徵權重越大文字特徵影響力越強,會發現相同關鍵字。文字特徵權重越小影像特徵影響力就越強,色調亮度格局會較像。使用hash會讓文字詞袋向量大小縮小很多。但缺點是不同字共用同一個位置,會造成誤差。

NCS2023-由MS CoCo影像資料集探索綠色AI概念流轉方法

Mon, 13 Nov 2023 04:06:33 GMT

title: NCS2023-由MS CoCo影像資料集探索綠色AI概念流轉方法 abstract: 本文利用MS CoCo影像資料集內不同類型的影像與標題，發展出文字概念流轉的想法，讓概念在相似的文字間流轉。並提出影像標題自動概念流生成辦法，使用詞袋向量與資料集詞袋矩陣來計算資料集內與句子向量最相近的句子。同時不使用機器學習及GPU，採用綠色AI演算法來試驗成果。我們也測試了MS CoCo影像資料集標題概念流轉效果，包括重複與不重複的相似句子多層概念流轉。並利用同義詞替代尋找更多概念變化的可能性。從標題句子的概念流轉，可以對應到相對的影像，產生如影片效果的影像流。利用這個自動概念流轉的方法，可以自動產生故事性的概念流。先設定故事主題與子題，再從多個子題文字中，藉由文字慢慢地流轉概念，發展出不同的段落，然後將每個句子對應到不同的關鍵格影像。最後產生關鍵格之間的格間影像，如此就能做出符合主題與子題的影片。

NCS2023-建構電腦多項式認知運算能力之設計與驗證

Mon, 13 Nov 2023 04:06:30 GMT

title: NCS2023-建構電腦多項式認知運算能力之設計與驗證 abstract: 大腦的認知就像一棵大樹的樹根，一層一層的由下向上連結彙總。所有的知識，像一張一張的小貼紙一樣，將方法記錄在裡面。我們提出過一個大腦的貼紙模型，所有的知識，像一張張的小貼紙，將方法記錄在裡面。使用時就有點像寫程式的方法呼叫。由上到下，一層一層的呼叫不同的方法。唯一的差別，就是我們現在的小貼紙，要用自然語言來描述步驟的一二三，而不是使用電腦程式來記錄。我們討論了如何讓電腦將兩種方式都具備，先建構對數學計算方法的認知，利用大腦的貼紙模型，把方法寫成貼紙。將算術由數數的方法開始，之後再寫出加減法的方法，最後到直式加法的貼紙。利用這種方式，最後就可以建構出完整的數學方法知識樹。然後再開發程式，讓電腦能夠直接計算多項式運算。我們的多項式程式架構，採取變數，項，多項式三層模組設計。多項式模組由項模組構成，而項模組又由變數模組組成。但是變數本身就可以是多項式，函數，分式或複式，所以是一種多層次的遞迴架構。能夠將複雜的計算式，計算展開之後再整理歸納。有了程式計算，再結合先前理解的認知貼紙模型，就可以讓電腦又理解方法，同時也有有效率的計算複雜數學式子的能力。

TANET2023-電資商管CubicPower科技教學機器人課程規劃設計

Mon, 13 Nov 2023 04:06:26 GMT

title: TANET2023-電資商管CubicPower科技教學機器人課程規劃設計 abstract: 我們規劃了電資商管學院的相關科技課程，希望能夠培養電子電路設計，資訊軟體開發，人工智慧，金融科技，區塊鏈以及雲端運算大數據技術的相關技術人才。針對電資商管的科技科目設計的教學機器人，列出了各科的詳細課綱規劃。整個教學機器人的運作將以概念講授，實例動手，成果測驗為教學方式。展現的方式將是網頁型的介面，把所有的課程一一列出，每個課程下面的各章節單元都有連結，一直到各單元的組成名詞項目，也都可以直接存取得到。同時並規劃教學對話機器人，要能夠回答學生的問題。未來在它的資料庫中，需要有充足的考古題樣本，以供回答。CubicPower的教學機器人，設計了不同的系統來進行教學工作。一個是知識庫，將知識有系統的寫入知識庫，讓程式能看得懂。CubicPower用半結構化的JSON來承載知識。使用LaTex格式記錄公式。建立電路圖形輸入模組以繪製電路，並產生電路連結表，以供模擬器使用。另一個是理財計算機與數學線上計算。提供數學的基本練習，與實例應用的線上計算環境。

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