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急性有氧運動對暴力行為者的抑制控制、 情緒調節、與錯誤監控之影響;The Effects of Acute Aerobic Exercise on Inhibitory Control, Emotional Modulation, and Error Monitoring in Violent Offenders
No full text[[abstract]]過去已有許多文獻指出，有氧運動對於人類大腦認知功能有著正面效益，有些研究指出急性有氧運動可以改善個體的抑制控制、情緒調節、以及錯誤監控等功能。暴力行為的產生是由先天因素與後天環境因素交互作用而導致，而過去研究發現，暴力行為者特定腦區的結構與活化程度與常人不同，並影響認知功能。本研究目的：一、檢驗急性中等強度有氧運動是否會影響抑制控制。二、檢驗急性中等強度有氧運動是否會影響情緒調節。三、檢驗急性中等強度有氧運動是否會影響錯誤監控。方法：參與者皆為男性，招募16名衝動型暴力犯罪之監獄收容人(平均年齡: 32.81±9.85)、14位非暴力犯罪之監獄收容人(平均年齡: 31.00±7.28)、及15位健康成人作為對照組(平均年齡: 22.73±2.31)。實驗設計：以對抗平衡方法，進行二個部分。一為運動介入，採30分鐘60%儲備心跳率的腳踏車運動；二為進行30分鐘運動相關書籍的閱讀控制，二部分結束後皆以情緒性停止訊號作業測量抑制控制、情緒調節、及錯誤監控的指標，包含 Go 正確率、Go 反應時間、Stop 錯誤率、停止訊號反應時間、及錯誤後減慢。同時測量事件相關電位 (ERPs)，包括P3、N2、晚期正向波 (LPP)、與錯誤關連負波 (ERN)作為抑制控制、情緒調節、與錯誤監控相關腦區活動指標。結果：(一)行為表現、運動介入過後，三組研究參與者的停止訊號反應時間有了顯著的下降，暴力組的錯誤後減慢則在運動過後顯著低於對照組。(二)ERP結果、運動介入過後，暴力組的P3振幅顯著高於非暴力組；而三組的N2、LPP、及ERN則沒有因為運動介入產生顯著變化。上述結果顯示急性有氧運動介入可能增進了三組參與者在執行抑制控制的效率，而暴力組在運動過後對於抑制歷程的注意力資源分配也有顯著的增加。但是運動對於暴力組的錯誤後減慢則有負面的影響，顯示本實驗運動介入對於暴力行為者的錯誤覺察能力與後續行為補償的大腦處理歷程並沒有正面的改善。由於實驗參與者屬特殊對象，因此本研究認為，可能運動對於不同的群體會有不同方面的效果。建議未來研究以其他介入方式或運動類型，以釐清運動對於暴力行為者的影響。另外，透過本研究結果可知，可能有氧運動可以當作除了教育與諮商輔導之外，改善暴力行為的輔助介入。
Many previous studies have suggested that aerobic exercise had positive effects on cognition. The relationships of aerobic exercise and cognitive function have been extensively examined in recent studies. Some of current research indicated that acute aerobic exercise can improve the cognition, including inhibition, emotional modulation, and error monitoring. Violent behavior is a consequence from the interaction of inborn factors and acquired environmental factors. Problems of cognition could explain the behavior of violent offenders. Purposes: First, to examine whether acute exercise can influence inhibitory control; second, to examine whether acute exercise can influence emotional modulation; third, to examine whether acute exercise can influence error monitoring. Methods: 16 violent offenders (mean age: 32.81±9.85), 14 non-violent offenders (mean age: 31.00±7.28), and 15 healthy-controls (mean age: 22.73±2.31) were recruited in the current study. Participants were asked to perform an emotional stop signal task under go, and stop with neutral and negative conditions after 30min exercise which were set as acute moderate aerobic exercise intervention, and a control session which were set as reading exercise-related books. While measuring task performance, the behavior data (i.e. go accuracy, go reaction time, stop error rate, stop signal reaction time (SSRT), and post-error slowing (pES)), and ERPs component, comprise P3, N2, LPP, and ERN were collected concurrently. Results: First, the SSRT was decreased in three groups after the exercise session but not the reading session and the pES of the violent group was lower than controls after the exercise session. Second, violent group had an increased P3 amplitude than the non-violent offender group after the exercise session. However, there were no differences on N2, LPP, and ERN amplitude after exercise. The current study suggests the ability of inhibitory control in 3 groups can be facilitated by acute exercise intervention, but the error monitoring process and the subsequent process of regulate in the violent group was disrupted by exercise. Finally, considering the particularity of our subjects, it would suggest the exercise intervention may have different effects in different subjects. It remains necessary to investigate whether different kinds of exercise or different intervention can influence violent offenders. Furthermore, this study also suggests that exercise may be able to be an auxiliary intervention in addition to education and counseling
企業員工採用雲端服務遵守資訊安全議題之研究;Investigation of the employee to use cloud services complying with Information Security
No full text[[abstract]]雲端服務是一種新型態的運作模式及應用服務，企業員工有效採用雲端服務將替企業節省許多營運成本。隨著企業對雲端服務的倚賴程度愈深，所面對的資訊安全威脅就愈多。企業員工個人在採用雲端服務時對於是否遵守資訊安全規範之行為，對企業保護資訊安全之控制來說具有重大影響。 本研究整合技術、組織及個人觀點，從員工採用的雲端服務模式、組織規模、嚇阻效用、組織公民行為及個人創新等方面，來探討企業員工採用雲端服務遵守資訊安全的意向。瞭解員工在採用雲端服務時，遵守資訊安全之考量與行為，藉以提供企業在制定相關資訊安全規範及政策之參考。 本研究結果顯示，在技術構面中，雲端服務與遵守資訊安全意向具有正向影響；在組織構面中，組織規模與遵守資訊安全意向具有正向影響，及嚇阻效用與遵守資訊安全意向具有正向影響；個人構面中，個人創新與遵守資訊安全意向具有正向影響，及組織公民行為與遵守資訊安全意向具有正向影響。
Cloud service is a new type of operation and application, it could be saving a lot of operating costs for enterprise. As the cloud service is used by the enterprise, the more information security threats are faced. Employee has a significant affection on the compliance with information security practices and the control of corporate information security. This research integrates the technical, organizational and personal views to explore the intentions of employees using cloud services to comply with information security from organizational scale, deterrent effect, personal innovation and organizational citizenship behavior. Understand the use of cloud services by employees to comply with information security considerations and behavior, in order to provide enterprises in the development of relevant information security norms and policy reference. The results of this study show that the use of cloud services in the technical structure of the surface will positively affect the compliance of information security practices of the employee. Organizational scale and deterrent effect will positively affect compliance with information security the intention of the will in the organizational structure of the surface. Organizational citizenship behavior will positively affect compliance with information security the intention of the will in the personal structure of the surface
應用多視角三維點雲對位於齒模重建之研究;Application of Multi-Angle Registration to Digital Dental Cast
No full text[[abstract]]數位牙醫，是以科技輔助牙醫為患者進行矯正，藉由三維影像處理技術，經過掃描、點資料對位、點資料建模，將石膏齒模數位化重建，能夠簡化假牙的製作過程，以及幫助牙醫師做進一步的診斷，實現數位牙醫的目標。在本研究中，提出一系列藉由石膏齒模取得數位齒模的方法，利用投影結構光搭配CCD，針對不同視角的石膏牙齒模型掃描多筆表面數據，根據掃描出的點資料空間關係，辨別出主要的齒模部份並濾除其餘雜訊，接著對影像進行簡化加速其執行效率，以疊代最近點演算法(ICP)計算點資料間的轉換關係，將多筆點雲做對位，使用移動最小平方法整合因重複疊合而產生誤差的點資訊，最後經由Poisson重建出表面的網格，將無序的抽象點數據建構為實體模型，精準的將實體齒模以數位化的方式呈現。同時比較了不同掃描角度之間的差異，透過本研究的方法，能夠以少次的掃描，建構出完整的數位齒模。
In this study, we used the techniques of three-dimensional image scanner and image registration to display the general dental cast in the way of digitizing. And we focused on image registration in this case. At first, we utilized Statistical Analysis Techniques to eliminate noise from the sets of multi-view dental cast of point cloud data. Then The image registration region we adopted ICP (Iterative closest point) algorithm to calculate the correspondent with the sets of point cloud. Then we overlapped two adjacent dental cast images from a series of image sequence several times to get the complete image information. Finally, we visualized the disorderly sets of abstract-pointed data through the Triangular Meshes. The purpose of the proposed method want to increase the accuracy and availability when dentists run diagnostics on the teeth. Therefore, dentists would be easier to communicate with the patients for solving the problems
瞭解消費者電子口碑之採用;Understanding the Consumer Adoption of Electronic Word-of-Mouth
No full text[[abstract]]電子口碑不論在學術方面或是商業活動方面已經被多方的探討，許多研究都指出了電子口碑在各方面的影響力。本研究將在社群溝通框架下，研究電子口碑相關的文獻變數，並探討哪些變數會影響消費者對電子口碑的採納。 消費者對電子口碑的認知可信度，在消費者決策制定的過程中被發現是一個重要的因素。而本研究也歸納出接收者涉入程度、接收者與傳送者關聯度、傳送者專業度、雙面訊息、口碑強度，皆會影響接收者的認知可信度，最後影響其對電子口碑之採納。
The notion of electronic word-of-mouth (eWOM) communication has received considerable attention in both business and academic communities. Numerous studies have been conducted to examine the effectiveness of eWOM communication. This study used the social communication framework to summarize and classify prior eWOM studies. This study also investigate what factors impact consumer adoption of eWOM. Receiver’s perceived credibility of eWOM is an important factor in the decision-making process. In this study, sender’s expertise, receiver’s involvement, rapport, sidedness and argument quality are the five key factors. Finally, this study convinced that receiver’s perceived eWOM credibility has positive effect on consumer adoption of eWOM
組織員工內外部動機對遵守資訊安全政策意向之影響;The Impact of Internal and External Motivations on Compliance Intention of Information Security Policy
No full text[[abstract]]隨著資訊技術的急速演進與進步，資訊化儼然已成這世代的主流，除了提升了作業效率，也縮短了人與人之間的溝通距離。然而資訊化帶來了便利卻也隱藏著危機，因此制定了資訊安全政策來規範組織內部同仁的資訊行為，而本研究藉以文獻彙整提出研究模式，利用內部動機與外部動機來探討組織內員工對於公司制定的資訊安全政策遵守意向。本研究以內部動機與外部動機為兩大方向，分別提出變數用以探討員工對於組織資訊安全策的遵守意向，內部動機以知覺有效性、組織認同為影響變數；外部動機以處罰嚴重性、偵測確定性以及同儕行為來加以探討。採用網路問卷調查及蒐集樣本，並挑選社群網站、相關論壇…等多個平台進行問卷發放。資料分析方法採結構化方程式，並以SmartPLS3.0作為主要系統分析工具，用以測量、結構分析及研究架構的驗證。研究結果顯示此概念模型之量測工具的信度、效度皆符合學術基本要求，而此研究則得到如下的驗證結果：(1) 知覺有效性、組織認同正向影響遵守資訊安全政策意向。(2) 處罰嚴重性、偵測確定性以及同儕行為正向影響遵守資訊安全政策意向。
With the rapid evolution and progress of information technology, Information has become the mainstream of this generation. In addition to improving operational efficiency, but also shorten the communication distance between people. However, information has brought convenience but also hidden the crisis, so developing information security policies to regulate the organization's internal peer behavior. In this study, the paper put forward a research model, using internal motivation and external motivation to explore the compliance intention within the organization for the company's information security policies.Using network questionnaire and collecting samples, and the data analysis method is adopts Structured Equations Modeling and SmartPLS3.0 as the main system analysis tools. After analyzing the 255 valid responses, we could draw the following conclusions:(1) Perceived effectiveness and organizational identity are positively impacting compliance with information security policy.(2) Penalty severity, detective certainty, and peer behavior are positively impacting compliance with information security polic
以超像素為基礎之影像分割與區域合併;Superpixel-based Image Segmentation and Region Merging
No full text[[abstract]]在計算機視覺及影像處理的領域中，影像分割占了一個很重要的地位。影像?割技術雖持續?斷地被提出，然而，目前影像?割仍存有許多困難，而現今有些方法可以被應用於彩色影像之?割，大多的思維只將影像從一維空間擴充到三維色彩空間，並沒有討?色彩資?中所提供的其他相關訊息。因此，色彩空間對於影像分割也是一個很值得深入研究的主題之一。影像分割的目的，是希望能夠從影像中找出我們所感興趣的區域，或者是有意義的區域。超像素能夠取得像冗餘資訊，且降低後續處理任務複雜度，目前已受到了國內外研究者的日益關注。本研究提出一個分割方式，以SLIC超像素方法劃分影像為多個子區域，再依照本研究所提出之合併方法，結合紋理與 H、S、V、R、G和B色彩特徵進行特徵值相差最小的子區域合併，針對多物件、背景複雜與物件及背景差異性低等類型之彩色影像進行區域分割。根據實驗結果，本研究提出方式可成功分割複雜背景影像中之突出之物件。最後對本研究的方法與應用進行了結果討論和未來展望。
In the field of computer vision and image processing, image segmentation occupies a very important position.Image segmentation technology is constantly being put forward, however, the current image cutting still has many difficulties, and now some methods can be applied to the color image segmentation, most of the thinking only the image from one-dimensional space expansion to three-dimensional color space, and did not discuss other relevant information provided in color data. Therefore, the color space for image segmentation is also a very worthy of one of the topics of in-depth study.The purpose of image segmentation is to be able to find areas of interest from the image, or a meaningful area. Superpixel can achieve redundant information, and reduce the complexity of follow-up processing tasks, has been the growing concern of researchers at home and abroad. This study presents a segmentation approach to the SLIC superpixel approach and the sub-regions with the smallest of the eigenvalues of the H, S, V, R, G and B color characteristics combined with the texture are combined with the sub-regions, and the background is complex and the background is complex. Object and background difference of low type of color image for regional segmentation. According to the experimental results, this study suggests that the way to successfully segment the complex objects in complex background images.Finally, the results of this study and application of the results of the discussion and future prospects
利用關鍵字熱門程度預測學術期刊論文影響力;Predicting the Impact of Academic Journal Papers by Keyword Popularity
No full text[[abstract]]隨著網際網路逐漸蓬勃發展，現今已有許多資訊在網際網路上公開，而人們越來越依賴在網路上的各種資訊，在各領域學術期刊中，研究學者們會隨著時間及議題潮流，關注所要研究的議題，同時也會追求新穎的科技及研究方法來進行實驗，以提高實驗結果準確度。本研究主要運用期刊(Journal)、第一作者(Fisrt Author)及關鍵字熱門程度(Keyword Popularity)來預測期刊論文影響力(Journal Paper Impact)，其中，會將關鍵字相關指標數據與潛藏狄利克里分配(Latent Dirichlet Allocation, LDA)的主題機率進行搭配，產生期刊論文的各項關鍵字熱門程度，再運用資料探勘軟體Weka的決策樹(Tree)及函式分類(Functions)，前者以C4.5演算法(C4.5 Algorithm, J48)，後者分別以羅吉斯回歸(Logistic Regression, Logistic)、支援向量機(Support Vector Machine, SMO)、類神經網路(Artificial Neural Network, MultilayerPerceptron)，共四種分類技術來建樣預測模型，進而探討商管領域不同類別對於關鍵字熱門程度的影響程度，以及探討關鍵字熱門程度因子與其他相關因子(期刊、作者)對於該領域的期刊論文影響程度。
With the Internet gradually flourish, there are a lot of information published on the Internet now, and then people are deeply dependent on the variety of information. In the academic journals in the various fields, researchers will follow the trend of time and topics, and focus on the topics which they would like to experiment. At the same time, they also pursue innovative technologies and new research methologies to experiment and improve the accuracy of experimental results. This study mainly uses the journal, the first author and the keyword popularity to predict the journal paper impact. It takes the related keywords information are meatched with the topic probability of Latent Dirichlet Allocation (LDA), and then it calculates the keyword popularity of each paper. This study uses tree and functions of the data mining software – Weka, there are four classification techniques to build predictive models, the former is C4.5 Algorithm (J48); the later are Logistic Regression (Logistic), Support Vector Machine (SMO), and Artificial Neural Network (MultilayerPerceptron), and then this study explores the different categories of the impact on the keyword popularity in the business and management field, and also explores the keyword popularity factors and other related factors (journal and author) of the impact on the journal paper impact in this field
影響採用RWD設計網頁意圖之因素;Factors Affecting the Intention of Designing Web Pages Using RWD
No full text[[abstract]]隨著行動上網的資訊普及，許多行動裝置如智慧型手機、平板電腦等行動設備，已經成為許多人生活與工作無法欠缺的工具。為滿足不同載具與螢幕解析度的適當內容呈現，採用響應式網頁設計技術已成為設計師主要的設計工具之一。本研究以科技接受模式與任務-科技適配理論整合模式，來探討網頁設計師對於響應式網頁設計技術的任務適配與採用意願的程度。我們採用問卷調查方式，以國內網頁設計師作為研究對象進行實證研究。 171份有效門卷經結構方程式模式進行資料分析後發現：知覺有用性、知覺易用性、和轉換成本對使用態度有正向影響，使用態度對使用圖有正向影響。
With mobile Internet access, many mobile devices such as smart phones, tablet PCs, and other mobile devices have become tools for many people in their everyday lives. To meet the appropriate content of different devices and screen resolutions, Responsive Web Design (RWD) technology has become an important design tool. In this study, we explored the factors influencing web designers’ decision on adopting RWD based on Technology Acceptance Model and Task-Technology Fit Model. A questionnaire survey was conducted and 171 validate responses were collected. Structural equation modeling technique was employed for data analysis and the results showed that perceived usefulness, perceived ease of use, and perceived cost had positive impacts on attitude, and attitude had a positive impact on adoption intention
基於範例影像之人臉特徵仿製;Cloning Human Facial Feature by Example
No full text[[abstract]]人臉蘊含著豐富的資訊，它可以表達出一個人的身分、年齡、身體狀況、情感。在過去幾十年來，隨著計算機視覺及機器學習等技術的快速發展，人臉辨識、人臉特徵模擬的技術，已經被廣泛的應用於真實世界中。在本篇論文中，提出一套基於範例影像之人臉特徵仿製的系統，希望在不改變主體影像的臉部結構下，將範例影像的臉部特徵，轉移至主體影像中，使主體影像能夠達到與範例影像相似的視覺效果。在此系統中，我們會先讓使用者提供兩張影像，一張為主體影像，另一張為範例影像。之後，我們採用主動形狀模型 (active shape model) 判斷出臉部及五官的輪廓，並將五官排除，只保留臉部皮膚的區域，再採用膚色偵測 (skin color detection) 從皮膚的區域中，排除非膚色的區域。最後，採用無縫隙仿製 (seamless cloning) 的技術，將範例影像中臉部皮膚紋理的區域合成至主體影像上，使主體影像與範例影像具有相同的臉部特徵，並達到相似的視覺效果。除此之外，為了解決因膚色差異大而造成的缺陷，我們額外提出了自動選取範例影像的功能，使結果影像能達到更好的合成效果。我們的系統可以透過範例影像的選取達到不同的應用，並且能夠輕易地將特徵仿製到另外一張影像上，使兩張影像擁有相同的視覺效果。
Human face contains a wealth of information, including individual's identity, age, health condition, and emotion. During the last few decades with the vigorous development of computer vision and machine learning techniques, facial feature simulation, face detection and face recognition have been widely applied in real world.In this thesis, we propose a system on cloning human facial feature based on example images. Our goal is to clone the facial feature of an example image to source image without changing the identity of source image, making source and example image have the same visual effect. In our system, Users first provide the source and example image, and then we use Active Shape Model to find the face contour and facial component shape and exclude them from example, keeping only the facial skin area. Afterward, we adopt skin color detection to remove non-skin color area from facial skin area, and retain only facial skin texture area. Finally, we apply seamless cloning to blend the facial feature of example image to source image, making two images have the same facial feature and achieve the similar visual effect. In addition to the aforementioned techniques, we also propose an automatic selection of a good example to solve the problem if skin color between the source image and example image differ greatly, making the result image achieve better visual effects.Our system can be applied to different domain via choosing the different example image, and can easily clone the facial feature of example image to source image, making the source image own the facial feature of example image and achieve the similar visual effects
協同過濾深度學習之推薦系統;Deep Learning Recommendation System With Collaborative Filtering
No full text[[abstract]]近年來隨著網路的蓬勃發展，網路上的遠距離互動已經不僅僅是使用者與使用者的對話，已經發展成由機器自動回應使用者的地步，也就是所謂的人工智慧，而近年來很火紅的深度學習演算法，在人工智慧的領域，不論是語音處理、電腦視覺與自然語言的處理等，領域都取得非常大的成就。相對來說，深度學習在推薦系統的領域上還是處於一個早期的探索階段。因此本論文提出利用深度學習的推薦系統，此種方式可以有效解決以往基於內容推薦的系統中常遇到的問題，像是冷啟動的問題等，而且有效的利用Alternating Least Squares(ALS)將用戶(User)對商品(Item)的評分兩個矩陣，充分的將數據中大量的缺失項目補足且減少矩陣維度，再利用Collaborative Filtering協同過濾技術找出用戶有相似行為的群體訊息，並根據這些訊息給用戶推薦。本論文中推薦系統能有效的解決傳統推薦系統相對不足的部分，並利用深度學習的方式，更準確的推薦用戶可能喜歡的商品。
The recommendation system is major top of discussion in the E-commerce , and Deep Learning algorithm became more than more popular , no matter Artificial Intelligence , Voice processing or Natural Language Processing , Deep Learning can be applied very success. The recommendation system field for Deep Learning is early to development . so we propose our methods , Deep learning Recommendation system with collaborative filtering , our method can solve many problems from the old recommendation system , like Dataset problem , Decision tree. And we using alternating least squares to find the item of user the score vector , and Collaborative Filtering to find the group message of similarly , recommend for the user according to the message