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人為因素分析與分類系統應用於臺鐵事故分析之研究
No full text國營臺灣鐵路股份有限公司（以下簡稱臺鐵）每年發生至少500件事故，且大多數造成事故的原因為人為因素，事故是由系統中一連串的問題所導致，當多個問題同時出現時就會發生嚴重事故，所以分析事故之觀點應由第一線人員之觀點提昇至系統之觀點，方能深入思考整個組織潛在肇因，故本研究首先將探討造成臺鐵重大行車事故之原因，找出組織對於第一線人員之影響，接著探討如何減少組織對於人員衝擊之改善方案。 本研究總共分為五個階段，第一階段首先分析運安會事故報告，發現造成臺鐵重大行車事故的原因為人員與管理層面；第二階段分析人員與管理層面之關聯，以人為因素分析與分類系統(HFACS)之為基礎，使用決策實驗室分析法結合詮釋結構模式（DEMATEL-ISM），得出組織文化與監管單位是影響事故之根源；第三階段為改善組織文化與監管單位，須建立健全與完善的通報機制，強化事故預防的安全管理，故須推動安全管理系統（Safety System Management, SMS），方能提昇鐵路運輸之安全水準，故本研究第三階段首先使用修正式德爾菲法(Modified Delphi Method)，整理安全管理系統之構面與影響因素；第四階段使用第三階段之構面與影響因素，使用決策實驗室分析（DEMATEL）排序重要程度。研究結果發現最重要的構面是規劃，此構面下重要的影響因素為安全目標與政策、重視安全的單位文化、風險評估與管理；第二重要的構面為組織與未來發展，此構面下較重要的影響因素為鐵路相關的法律、智慧鐵道相關系統；第三重要的構面為行動，此構面下較重要的因素有文件管理系統、事故事件調查與改善。 最後經由專家評估在資源有限下，各構面下之因素長期短期可行性，結果得知：在規劃構面，短期可改善的因素有安全目標與政策、風險評估與管理、安全管理系統教育訓練與資源；在執行構面，短期可改善的因素有緊急事故與防災應變、組織訊息傳達與溝通、風險衡量與管理；在查核構面，內部審查與評估、風險評估與通報系統兩因素皆為短期可改善之因素；在行動構面，短期可改善的因素是文件管理系統；在組織與未來發展構面，智慧鐵道是長期與短期皆須發展的項目，智慧鐵道是臺鐵目前準備推動之項目，故智慧鐵道將是短期長期發展之重點，投入較多資源導入智慧鐵道的同時，亦應投入相對的資源教育組織內部成員如何使用智慧鐵道與其目的，方能減少成員對於智慧鐵道認知差異。鐵路相關法律、組織協調與改善建議則為長期改善因素。中華民國運輸學會補正完畢國內台中市，台灣TW
Deep Belief-MobileNet1D: A novel deep learning approach for anomaly detection in industrial big data
No full textEarly fault or unusual behavior detection can reduce the risk of equipment failure improve performance and increase safety. Anomaly detection in industrial big data involves identifying deviations from normal patterns in large-scale datasets. This method assists in preventing equipment failures optimizing maintenance schedules and raising overall operational efficiency in industrial settings by identifying anomalous behaviors or outliers. Through the utilization of deep learning procedures, this investigation endeavours to apply are fined procedure for anomaly detection in industrial big data. Pre-processing, feature selection and Anomaly detection are three steps of a process that are used. The input data is first fed into MapReduce framework where it is divided and pre-processed. Imputation of missing data and Yeo-Jhonson transformation are then applied to eliminate noise from data. After pre-processed data is generated, it is put through a feature selection phase using Serial Exponential Lotus Effect Optimization Algorithm (SELOA). The algorithm is created newly by combining Lotus Effect Optimization Algorithm (LOA) with Exponential Weighted Moving Average (EWMA). Finally, anomaly detection is done using the features that are selected by means of Deep Belief-MobileNet1D, which combines MobileNet1D and Deep Belief Network (DBN). With a recall of 96.2 %, precision of 92.8 %, F1 score of 94.5 % and accuracy of 95.9 %, results show that the proposed strategy surpasses standard approaches. These findings demonstrate Deep Belief-MobileNet1D model's ability to detect anomalies in industrial big data.補正完畢US
Investigating Dayue: An LFG-OT approach to its subcategorization and structure
No full text連結
https://muse.jhu.edu/article/940611This paper investigates the subcategorization and structure of dayue, taking a Lexical Functional Grammar–Optimality Theory (LFG-OT) approach to account for the different uses of this word. It argues that dayue can be identified in the category of either an adverb or a preposition, depending on the function it takes and the structure it has. As an adverb, dayue modifies the clausal element or the quantifier phrase directly following it. As a preposition, dayue takes a noun phrase (NP) or an adpositional phrase as the complement, occurring in the adjunctive position. There may be ambiguities due to the subcategorization of, and the argument structure associated with, dayue, which result in the same linguistic form being generated as optimal outputs for different input meanings. However, each can be argued to correspond to a different c-structure. An LFG-OT approach is adopted in this paper to account for the structure of dayue. LFG proposes different levels of representation, and OT is involved in the theoretical model by evaluating linguistic forms according to the interaction and ranking of different kinds of linguistic constraints. Faithfulness constraints ensure faithful mappings among the lexical, functional, and syntactic levels of representation. Markedness constraints require linguistic structures to be well formed. Economy constraints pursue a concise, efficient way of expression. Alignment constraints map arguments with constituent structures.電子
Effectively learn how to learn: a novel few-shot learning with meta-gradient memory
No full text全文連結https://www.inderscienceonline.com/doi/abs/10.1504/IJWGS.2024.137549Recently, the importance of few-shot learning has tremendously grown due to its widespread applicability. Via few-shot learning, users can train their models with few data and maintain high generalisation ability. Meta-learning and continual learning models have demonstrated elegant performance in model development. However, unstable performance and catastrophic forgetting are still two fatal issues with regard to retaining the memory of knowledge about previous tasks when facing new tasks. In this paper, a novel method, enhanced model-agnostic meta-learning (EN-MAML), is proposed for blending the flexible adaptation characteristics of meta-learning and the stable performance of continual learning to tackle the above problems. Based on the proposed learning method, users can efficiently and effectively train the model in a stable manner with few data. Experiments show that when following the N-way K-shot experimental protocol, EN-MAML has higher accuracy, more stable performance and faster convergence than other state-of-the-art models on several real datasets.電子
Remote Attestation Schemes by Using Lightweight Hardware-based Trusted Agents for Sensor Networks
No full text無線感測網路已被採用於各類商業、科學與軍事的應用中，主要可被用來監視特定區域與蒐集關鍵資料。惡意程式注入攻擊一直威脅著感測節點的安全性，並導致偽造資料的傳遞與洩漏私密資料等安全性議題。攻擊者可以將惡意程式存入一個含有軟體漏洞的感測節點之中，例如經由實體擄獲的方式。這些惡意程式更可進一步地轉換成蠕蟲並經由一個受感染的感測節點將惡意程式散播開來；最後，整個感測網路將被攻陷。在叢集式無線感測網路架構中，攻擊者透過惡意程式控制中繼站將可以攻陷整個叢集網路，因此中繼站將成為攻擊者的首要目標。一個可以抵禦上述安全威脅的檢驗機制儼然已是不可或缺的需求。
遠程證實方法可被用來驗證程式記憶體內容的完整性，驗證者可以檢驗遠程證實者是否處於預期中的正常執行環境。證實者必須提出完整性證明的依據，藉此表明它的可信度。基於軟體型式的遠程證實方法，由於建置成本較低，因此特別適用於計算資源有限的感測節點。然而，目前已有許多與其相關的安全性漏洞與實務上的限制被提出。基於硬體可信賴平台模組的遠程證實協定是另一個常見的機制，並且可以摒除基於軟體型式方法的限制。但是，可信賴平台模組將需要較高的計算代價與較高的硬體成本，因此較不適用於無線感測網路的應用中。
為了結合現有各種遠程證實方法之優點，本論文提出幾項基於輕量化硬體可信賴代理人的遠程證實方法。由於該可信賴代理人不需執行任何繁複的密碼運算並且僅需配置少量的參數儲存空間，因此特別適用於計算資源受限的小型裝置，例如無線感測器。特別值得一提的是，時間與空間兩項物理因素都被應用於本研究的提案方法中。基於時間因素之設計，遠程證實方法的程序可被確保執行於一個未被干擾的環境中，並且不受資料傳遞時導致的時間延遲所影響。基於空間因素之設計，證實者可以免於閒置記憶體空間被攻擊者利用的風險，此外還能增進記憶體利用率。實驗結果完全呈現本提案方法的有效性，效率分析也指出計算資源受限的證實者僅需消耗相對少量的能源即可完成遠程證實程序。紙本TW
Aftermath of the Fourth Taiwan Strait Crisis: Media Discourse Analysis of Taiwan and India's Perception of China's Threat
No full textThis study examines Taiwan and India’s media discourse and political elite statements from 1 July 2022 to 1 October 2023, starting from the fourth Taiwan Strait crisis in 2022. We conducted a discourse analysis of over 121,901 news texts using extensive data analysis and text-mining software. Additionally, our research team conducted expert focus group discussions with renowned think tanks and research centres in New Delhi, India. Building upon the data text analysis findings, we further explored India’s stance on the Taiwan Strait conflict, its perception of the Chinese threat and the impact of the ongoing ‘new normal’ crisis on India’s Indo-Pacific strategic layout. The aim was to uncover common security needs and intersecting interests between the two countries, considering their different national interests and geopolitical considerations.
Based on the analysis of textual mining and expert discussions, this study reveals the following: First, India is concerned about the current situation in the Taiwan Strait. Second, the current tensions in the Taiwan Strait will influence India’s strategic layout. Third, there is a growing consensus within India regarding the Chinese threat. In light of these findings, this study suggests that Taiwan and India share interests in democratic values, maritime traffic security and high-tech industry supply chains. Taiwan possesses expertise in China studies and a deep understanding of China’s military threat, while Taiwan and India possess specific technological capabilities. Based on these foundations, there are potential opportunities for further dialogue, exchange and cooperation in relevant fields between India and Taiwan.補正完畢IN