Crack tooth的問題,透過圖書和論文來找解法和答案更準確安心。 我們找到下列推薦必買和特價產品懶人包

另外網站Cracked tooth syndrome - Wikipedia也說明:Cracked tooth syndrome (CTS) is where a tooth has incompletely cracked but no part of the tooth has yet broken off. Sometimes it is described as a ...

國立臺北科技大學 機械工程系機電整合碩士班 江卓培所指導 PAVAN SAI PAGADALA的 熱擠製鋁合金6061三階齒輪之研究:有限體積模擬與實驗的比較 (2021),提出Crack tooth關鍵因素是什麼,來自於Finite Volume Method、Aluminum extrusions、Gears、SLM、Simufact Forming、Simufact Additive。

而第二篇論文國立東華大學 資訊工程學系 顏士淨所指導 黃英聰的 基於深度學習之中醫舌象辨識及研究 (2021),提出因為有 中醫、深度學習、舌象辨識、中醫體質量表、齒痕舌的重點而找出了 Crack tooth的解答。

最後網站Why You Should Never Ignore a Cracked Tooth - Apex Oral ...則補充:Treatment typically includes placing a dental crown on the cracked tooth. If the fracture effects the pulp chamber a root canal may also be ...

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Crack tooth進入發燒排行的影片

Brianna and Skyler are unboxing three National Geographic STEM Science Kits. First they dig for a real Shark Fossil from an extinct shark. Then they find a fossilized dinosaur dropping (a coprolite). Finally they crack open 2 geodes. They show you how to open a geode. What real crystals will they find? These Nat Geo kits are so fun and educational and great for home schooling.

熱擠製鋁合金6061三階齒輪之研究:有限體積模擬與實驗的比較

為了解決Crack tooth的問題,作者PAVAN SAI PAGADALA 這樣論述:

The study introduces a novel technique, bidirectional hot extrusion and uses a selective laser melting (SLM) machine with Inconel 718 alloy to additive manufacturing of a helical-spur-helical three-stage gear. An experimental investigation is carried out on Aluminum 6061 alloy by performing the Ten

sile test on the cylindrical specimen machined based on ASTM E-8M standard to compare the estimated results with the available library data. To determine the effectiveness of the introduced techniques, firstly a computer-based design followed by analysis is carried out with the help of MSC Simufact

forming and MSC Simufact additive. The analysis includes the Finite Volume Method (FVM) for the triple gear and the Powder Bed Fusion (PBF) technique for gear die. Convergence test has been performed using the FVM with Aluminum 6061 as the material based on varying mesh element size. Simulation is e

xecuted at three different temperatures 350°C, 400°C, 450°C, and numerous attempts were made to determine the optimal time and velocity for obtaining a more favorable gear profile and the computation time. With a constant optimal time of 10s and varying the mesh element size between 0.5 to 1.6 mm wi

th the input velocity of 1.75, 2.0 & 2.25 mm/s, it is observed that the die filling rate is very accurate, and crack formation on the tooth bed is minimum. The input parameters of PBF in Simufact additive such as scan velocity, laser power, beam width, and layer thickness are optimized to evaluate t

he residual stresses and distortions formed in the fabrication of gear dies which yielded satisfactory results. IFUM (Institute for forming technology and forming machines) model is employed to evaluate the material flow rate and underfilling of the gear tooth. Considering the simulation results, ex

periments are performed to fabricate the gear die using the SLM technique and the triple-gear using monodirectional hot extrusion (due to unavailability of required bidirectional hot extrusion machine setup). Surface machining is performed to the gear die to obtain a favorable gear profile closely m

atching the simulation results.

基於深度學習之中醫舌象辨識及研究

為了解決Crack tooth的問題,作者黃英聰 這樣論述:

隨著人工智慧的成熟,並在中西醫有越來越多的應用,有越來越多的技術在輔助醫師,而舌診在中醫望診中站著重要的一環,通過對舌象的細微觀察,以中醫獨特的一套系統去分析,將舌頭與臟腑聯繫瞭解病變所在,再依據體質與症狀的分類進行適當的治療。因此本論文嘗試以深度學習的方式分兩部分研究舌象,第一部分為以本論文所提出卷積神經網路模型來依據舌象辨識中醫體質量表中的平和質與否,在只保留舌體之圖片的實驗中CNN模型的準確率達80.3%;而經稍加修改的VGG16模型準確率達96.5%。第二部分為使用YOLOv4模型偵測齒痕舌與非平滑舌,將有舌頭的圖片分粗略及精細兩種版本,以亮度、色度、對比、銳度四種屬性增強進行資料擴

充後進行訓練,實驗中判斷非平滑舌的精細版本準確率達90%;判斷齒痕舌的粗略版本準確率達92%。本論文兩部分的研究中,資料集內兩種標籤的數量雖不平衡,但實驗結果表明仍有一定的表現,說明不平衡的舌頭資料集還是可以在不特別處理的情況下透過深度學習有一些作用。