methods to identify and termination of unzerkleinerbaren fremdkoerpern from vorzerkleinertem rohgut

• 1. 一种蛇颈换热器 [P] . 中国专利： CN109442761B . 2020.11.06
• 2. 一种蛇颈换热器 [P] . 中国专利： CN109442761A . 2019-03-08
• 3. methods to identify and termination of unzerkleinerbaren fremdkoerpern from vorzerkleinertem rohgut [P] . 德国专利： DE000001148850A . 1963-05-16

  机译： 于蛇颈菜中蛇颈蕨的鉴定和终止方法

• 4. methods to identify and termination of unzerkleinerbaren fremdkoerpern from vorzerkleinertem rohgut [P] . 德国专利： DE1148850B . 1963-05-16

  机译： 于蛇颈菜中蛇颈蕨的鉴定和终止方法

• 5. methods to identify and termination of unzerkleinerbaren fremdkoerpern from vorzerkleinertem rohgut [P] . 德国专利： DE000001151429A . 1963-07-11

  机译： 于蛇颈菜中蛇颈蕨的鉴定和终止方法

• 1. Identifying Extreme Rainfall Events Using Functional Outliers Detection Methods [J] . Mohanned Abduljabbar Hael, Yongsheng Yuan 数据分析和信息处理（英文） . 2020,第004期
• 2. An Adjoint-Free CNOP-4DVar Hybrid Method for Identifying Sensitive Areas in Targeted Observations: Method Formulation and Preliminary Evaluation [J] . Xiangjun TIAN, Xiaobing FENG 大气科学进展（英文版） . 2019,第007期
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• 4. Comparison of two classification methods to identify grain size fractions of aeolian sediment [J] . YanZai Wang, YongQiu Wu, MeiHui Pan, 寒旱区科学（英文版） . 2018,第005期
• 5. A Comparison of 3D Methods for Identifying the Stance Phase in Treadmill Running for Both Rearfoot and Forefoot Runners [J] . Dorian Deflandre, Cedric Schwartz, Jean-Pierre Weerts, 运动科学：英文版 . 2016,第003期
• 6. Identifying Dominant Factor of EMI of Asymmetrical Differentia-Paired Lines with Different Termination Condition [C] . Yoshiki KAYANO, Hiroshi INOUE 電磁環境研究会;マグネティックス研究会 . 2016
• 7. Application of FDTD in hybrid methods for EM scattering analysis of cavities with complex terminations [D] . Chia, Tse Tong 1994
• 8. Soil pH nitrogen phosphatase and urease activities in response to cover crop species termination stage and termination method [O] . Adewole Tomiwa Adetunji, Bongani Ncube, Andre Harold Meyer, 2021
• 9. ABSTRACT Various body parts or organs can be analysed to identify the different diseases in the human body. Fingernail analysis is one of the ways to identify disease in the human body. Nails are the body part which are farthest from the heart and therefore receive oxygen at last. As a result the nails are the first who show the symptoms of a disease in the human body. Fingernails can be easily captured for diagnosis and there are no heavy equipment or no specific conditions required to use nail image for disease diagnosis, like in other tests and scanning processes. Human nails deliver beneficial information about complaints or any nutritive imbalances in the human body depending upon their shape, texture and colour. In human beings, numerous systemic and skin diseases can be easily analyzed through careful examination of nails of both the limbs. A lot of nail illnesses have been found to be primary signs of numerous underlying systemic illnesses. The colour, texture or shape changes in nails are signs of many diseases mainly affecting nails. Considering all these properties of nails a system is proposed that uses digital image processing (DIP) methods for identifying such changes in the human nail to get more precise results and predict numerous diseases effortlessly. With the emerging Internet of Things (IOT) concept the generated report is made available remotely, this will help users to reduce transportation efforts. As the system has to deal with large and private data, the security of data must be ensured. To keep the data confidential, the Blockchain concept which is one of the most emerging concepts in the field of data management is used. The paper contains the implementation of the digital image processing for feature extraction of nail images, usage of IOT (ThingSpeak cloud) for data storage and implementation of Blockchain to keep the system secured and theft free. KEY WORDS: Int ernet of thin gs (IOT), Image proc essin g, Thin gSpeak, RG B vavalues, Mean pi xel vavalues, Bloc kchain , Hash key. Disease Diagnostic System: Abnormalities in Human Nail [O] . Pranav S. Wazarkar 2020
• 10. Methods for Identifying High Collision Concentration Locations (HCCL) for Potential Safety Improvement Phase II: Evaluation of Alternative Methods for Identifying HCCL [R] . Srinivasan, R., Lyon, C., Persaud, B., 2011

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