本論文之目的在於瞭解現行核能保險之保單內容，歸納出核能事件發生後的各項損失，以建立一套台灣核能保險保費之估計模式。 該模式的建立包含以下步驟：首先，針對核能事件所造成的各項人身、財產、責任損失進行分類；其次，建立個別損失金額之評估公式。第三，對於核能電廠發生損失的機率與幅度分別進行探討。在損失機率方面，配合台灣核能電廠過去的損失經驗以及核研所之PRA（probabilistic risk assessment）模型，對於各級核能事件之發生機率進行假設。在損失幅度方面，估計各項損失項目之最大損失金額，配合各級核能事件下各項損失項目之損害比例，對於各級核能事件之損失幅度進行假設。最後，各級核能事件損失機率與損失幅度乘積之總和，即代表核能保險之危險保費；此外，加上附加費用後，即可求得適當的保費金額。 核能保險雖然是迅速且容易取得之財務補償工具，但所費不貲。整體而言，核能發電具有成本低、污染少等優點，若核能電廠能確保其安全性，並於損失發生後有足夠的財務保證，則可使核能發電的效益充分發揮。 / The aim of this article attempts to know the content of the nuclear energy insurance policy, to induce all kinds of losses after the nuclear events, and to establish an assessment model for the premium of the nuclear energy insurance in Taiwan. This model consists of the following steps: First, various kinds of personal, property, and liability losses which occurred after nuclear events are classified into different categories. Secondly, assessment formula for the loss amount is established. Third, loss frequency and loss severity for the damage of nuclear power plants are studied separately. Lastly, the result of multiplying “loss frequency” by “loss severity” stands for the risk premium for the nuclear energy insurance. Also, adding together the above results and the loading expense, the appropriate premium amount can be figured out. On the whole, utilizing nuclear energy for producing electric power possesses the advantage of being low costs and less pollution. If the nuclear power plants can ensure its safety as fully as possible, and provide adequate financial guarantees as damages occur, people will greatly benefit from the efficiency of nuclear power.

自負額之運用是保險人在承接業務時，掌控損失頻率與損失幅度的重要方法之一，適當的運用自負額可以穩定保險公司核保利潤營運績效，惟現行自負額仍有許多功能無法完全發揮，甚至造成實務上許多問題，故本文擬研究新型態自負額，以解決實務問題並發揮自負額之功能。 本文選擇以某產險公司實際理賠資料，探討新型態自負額的訂定方式對損失率結果之影響，另以問卷調查方式訪談六家保險公司核保及營業人員對於本文所述目前自負額制度優缺點及新型態自負額可行性之看法，結果顯示在問卷調查中本文所述目前自負額制度現況之優缺點及有關新型態自負額之可行性皆獲訪談者高度認同，在模擬實證上亦能達到對損失率影響不顯著之預期結果。 / Deductible is a key element for insurance companies to control loss frequency and loss severity. Appropriate deductible usage can stabilize underwriting profit for insurance companies. The constraints on present deductible conduct many problems in practice, so this paper proposes new-type deductible research to solve practical problem and develop optimal function of deductible. This article employs actual occurred loss database from one insurance company to study the impact on loss ratios with new-type deductible. Moreover, this paper also conducts qualitative interview survey approach to learn the viewpoints from underwriters and sales of six Taiwan insurance companies with merit and defect of present deductible and new-type deductible usage contained herein. The results show that merit and defect of present deductible and new-type deductible feasible contained herein is highly approved by interviewees. Besides, deductible usage is expected to have insignificant impact in increasing loss ratios through various case study simulations.

依照「強制汽車責任保險法」之規定，費率的釐定應兼採從人及從車因素，旨在使保險費率能更臻公平完整。本研究利用卡方獨立性檢定，以國內某大型產物保險公司之承保與理賠資料為依據，分析可能影響強制汽車責任保險損失之是否發生、損失次數與損失幅度的分類因素。除了法定的從人及從車因素之外，本研究亦試圖由取得之保單資料上找出其他可能影響損失的因子，並比較新制實施前後，其影響損失之分類因素的改變，做為是否應採用此分類因素為核保篩選及費率釐定之參考。 研究結果發現： （一）年餘並非為其有顯著影響力之分類因素； （二）性別、婚姻狀況與車種宜列為影響損失的重要分類因素； （三）肇事記錄與廠型對損失之影響不顧著，並非為重要分類因素； （四）車齡與排氣量並非為重要分類因素； （五）是否投保任意責任險與損失有顯著相關； （六）新制實施後，影響損失的顯著因素中，從人因素多於從車因素。 關鍵字：強制汽車責任保險、從人從車因素、損失頻率、損失幅度 / According to the“The Law of Compulsory Auto Liability Insurance”, the ratemaking should take both human factors and vehicle factors into account. The main purpose of this study is to investigate the factors which affect the loss occurrence, loss frequency and loss severity of compulsory auto liability insurance. Besides these legal factors, this paper also tries to find out other influential factors and compare the outcomes before 1998 with that after 1998. The analysis of the changes on the relevant factors helps the government and insurers to make rating and underwriting decisions. The methodology of this study is chi-square test and the empirical findings are as follows: 1.Age is not a significant risk factor. 2.Gender, marriage status and vehicle category should be considered as significant risk factors. 3. Both driving record and category has less effect on loss and thus should not be treated as important risk factors. 4.Neither vehicle-age nor exhaust volume should be considered as significant risk factors. 5.The factor of purchasing voluntary auto third party liability insurance has an important impact on loss. 6.After the new law of compulsory auto liability insurance has been practiced, it shows that human factors are more significant than vehicle factors in affecting insurance claims. Keywords: compulsory auto liability insurance, human factors and vehicle factors, loss frequency, loss severity

Over the last century, physiological signals have been broadly analyzed and processed not only to assess the function of the human physiology, but also to better diagnose illnesses or injuries and provide treatment options for patients. In particular, Electrocardiogram (ECG), blood pressure (BP) and impedance are among the most important biomedical signals processed and analyzed. The majority of studies that utilize these signals attempt to diagnose important irregularities such as arrhythmia or blood loss by processing one of these signals. However, the relationship between them is not yet fully studied using computational methods. Therefore, a system that extract and combine features from all physiological signals representative of states such as arrhythmia and loss of blood volume to predict the presence and the severity of such complications is of paramount importance for care givers. This will not only enhance diagnostic methods, but also enable physicians to make more accurate decisions; thereby the overall quality of care provided to patients will improve significantly. In the first part of the dissertation, analysis and processing of ECG signal to detect the most important waves i.e. P, QRS, and T, are described. A wavelet-based method is implemented to facilitate and enhance the detection process. The method not only provides high detection accuracy, but also efficient in regards to memory and execution time. In addition, the method is robust against noise and baseline drift, as supported by the results. The second part outlines a method that extract features from ECG signal in order to classify and predict the severity of arrhythmia. Arrhythmia can be life-threatening or benign. Several methods exist to detect abnormal heartbeats. However, a clear criterion to identify whether the detected arrhythmia is malignant or benign still an open problem. The method discussed in this dissertation will address a novel solution to this important issue. In the third part, a classification model that predicts the severity of loss of blood volume by incorporating multiple physiological signals is elaborated. The features are extracted in time and frequency domains after transforming the signals with Wavelet Transformation (WT). The results support the desirable reliability and accuracy of the system.

隨著高科技產業的興起，電子產業因應市場快速與客戶滿意度的高度需求，供應鏈物流業的快速發展，使得傳統運送模式之風險形態產生戲劇性的變化，損失頻率及損失幅度均已隨著運籌模式物流的風險由傳統運輸Door to Door構成線性的低度風險，轉變為Hub、組裝中心、物流倉庫、承攬人、次承攬人等複雜的關係方所構成，網狀物流模式的高度風險區塊。而運輸保險長期以來處於保險業者、保險經紀人的惡性競爭市場，高科技電子業基於風險成本考量，強勢壓縮保險費，使得電子業運輸保險損失率居高不下。 本研究透過個案電子公司之重大損失案例研究，歸納高科技電子業物流損失的發生原因，提出核保、理賠管理、及物流倉庫、運送人損防、管理建議供保險業界，物流業者參考。 未來，保險業面對全球運籌業物流風險經營，除積極運用核保策略，加強同業間的共保協商機制，以分散風險外，針對此特殊業務的核保應加強倉庫管理人風險查勘及物流運送人之委任規範、以達到風險預防之效果。更重要的是，保險經營者應修正，以利潤導向的經營理念代替市場佔有率的迷思，方是杜絕市場惡性競爭的根本。 關鍵字：電子業、全球運籌、供應鏈、風險管理、 損失頻率、損失幅度、核保策略、理賠管理、 損失率。 / With the blooming growth of high-tech industry, the electronic industry pursued for swiftness and clients satisfaction as well as the fast development of logistics business, risk of cargo distribution had transformed from the traditionally low-risk lineal “door to door” model to a high-risk complex structure of network composed by Hubs, Configuration Centers, warehouses, contractors, and sub-tractors. Moreover, the intense competitiveness among insurers and insurance agents as well as the cost-down strategy on cargo transit insurance premium of high-tech companies even make the loss-claim ratio have stayed high for such a long time. By studying cases of specific high-tech company claiming for great loss amount, we herby conclude several main causes of loss during transit and bring up suggestions on Underwriting, Claim Adjustment, Logistics Warehouse, Carrier Loss Prevention, and Logistics Management for your reference. In the future, in terms of risk management and diversification, we should not only aggressively adjust our underwriting strategy, enhance co-insurance policy but also strengthen investigations on the warehouse staffs and designate supplier adequate responsibilities. Besides, what’s more important is to alter the myth of being purely interest-oriented and to discard the thought of expanding market percentage by cutting prices, only then we could really make a sound foundation at the market instead of suffering malignant competition with each other. Key Word：Electronic Industry，Global Logistic，Supply Chain，Risk Management，Loss Frequency，Loss Severity，Underwriting Strategy，Claim Management，Loss Ratio。