CN102507966B - System and method for detecting qualities of double-blind laboratory samples based on cloud computing - Google Patents
System and method for detecting qualities of double-blind laboratory samples based on cloud computing Download PDFInfo
- Publication number
- CN102507966B CN102507966B CN201110367485.4A CN201110367485A CN102507966B CN 102507966 B CN102507966 B CN 102507966B CN 201110367485 A CN201110367485 A CN 201110367485A CN 102507966 B CN102507966 B CN 102507966B
- Authority
- CN
- China
- Prior art keywords
- sample
- encoded
- laboratory
- sent
- mark
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 18
- 239000006101 laboratory sample Substances 0.000 title abstract description 6
- 238000001514 detection method Methods 0.000 claims abstract description 45
- 238000012360 testing method Methods 0.000 claims description 33
- 238000012857 repacking Methods 0.000 claims description 12
- 238000005516 engineering process Methods 0.000 claims description 10
- 238000012545 processing Methods 0.000 claims description 9
- 238000012372 quality testing Methods 0.000 claims description 9
- 238000004519 manufacturing process Methods 0.000 claims description 8
- 239000000523 sample Substances 0.000 abstract description 137
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 239000003814 drug Substances 0.000 description 2
- 238000012797 qualification Methods 0.000 description 2
- GOLXNESZZPUPJE-UHFFFAOYSA-N spiromesifen Chemical compound CC1=CC(C)=CC(C)=C1C(C(O1)=O)=C(OC(=O)CC(C)(C)C)C11CCCC1 GOLXNESZZPUPJE-UHFFFAOYSA-N 0.000 description 2
- 235000013361 beverage Nutrition 0.000 description 1
- 239000003153 chemical reaction reagent Substances 0.000 description 1
- 239000002537 cosmetic Substances 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000003255 drug test Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000009863 impact test Methods 0.000 description 1
- 239000000902 placebo Substances 0.000 description 1
- 229940068196 placebo Drugs 0.000 description 1
- 238000011160 research Methods 0.000 description 1
Images
Landscapes
- Automatic Analysis And Handling Materials Therefor (AREA)
Abstract
The invention provides a system and a method for detecting qualities of double-blind laboratory samples based on cloud computing. The system comprises mass sample input ends, an information system disposed on a cloud platform and mass laboratory ends, and the information system on the cloud platform comprises a sample receiving end, a sample repackage marking end and a sample sending end; the sample receiving end is used for receiving sample detection applications and the samples sent by a sample input end and code-marks the samples; the sample repackage marking end is used for receiving the code-marked samples and repackage-marks the samples; and the sample sending end sends the repackage-marked samples to detection laboratories, and the background of the system transmits sample quality detection reports to detection sending people at the sample input end.
Description
Technical field
The present invention relates to laboratory sample detection technique, by a kind of detection system based on cloud computing (Cloud Computing), all kinds of samples in laboratory are carried out to quality testing, particularly, the present invention relates to a kind of double blinding sample quality detection system and method based on cloud computing.
Background technology
At present, food, skin care item etc. cause people's attention day by day with the security of the closely-related various products of the mankind.To various product collected specimens such as food, beverage and cosmetics, and it is very general to carry out the way of quality testing, and the environment that carries out this class quality testing is exactly laboratory.
Utilizing laboratory to carry out sample quality while detecting at present, is all that censorship people directly sends sample to be checked into relevant laboratory and detects, and this laboratory sends to examining report censorship people after completing detection again.In this quality testing flow process, censorship people knows which laboratory sample has sent into, laboratory testing staff knows the concrete source of sample, censorship people and laboratory even comprise that relevant third party, easily because subjective factor affects quality testing, causes the objectivity of testing result and reliability to be affected like this.
Blind Test, understand to be exactly the test of carrying out without eyes or other survey instruments, namely anomic test from letter.Blind Test in reality, refers to by the brand mark of technical finesse related products, user, in the situation that not knowing concrete brand, uses several like products by reality, carrys out the performance of each product of comparison.Blind Test can be abandoned brand factor so that user casts off prejudices, and understanding oneself the most favorite is that product or the real property of understanding test product.
But in this test process, the first, tested content and object are clearly known by test side.The second, a plurality of similar products are provided need to tested sample, increased the workload of test.In addition, for the specimen of magnanimity and test Fang Eryan, use can further the lead to errors generation of rate of artificial mark.
Summary of the invention
For overcoming above-mentioned defect of the prior art, the present invention proposes a kind of double blinding sample quality detection system and method based on cloud computing.
According to an aspect of the present invention, a kind of double blinding sample quality detection system based on cloud computing has been proposed, comprise magnanimity sample input end, be deployed in infosystem on cloud platform and the laboratory end of magnanimity, wherein, the infosystem on this cloud platform comprises that sample reception end, sample repack mark end and sample is sent end with charge free; Sample reception end is used for receiving sample detection application and the sample that sample input end is sent here, and sample is carried out to coded markings; Sample repacks mark end to be had the sample of coded markings and it is repacked to processing for receiving; Sample is sent end with charge free and is sent to the sample of repack processing with charge free testing laboratory ，Gai laboratory and complete to detect and return to testing result, and system backstage sends sample quality examining report to the censorship people of sample input end.
According to a further aspect in the invention, a kind of double blinding sample quality detection method based on cloud computing has been proposed, comprise: step 10), the sample input end of censorship people by magnanimity login system Network Based submits sample detection application to, and sample is sent to sample reception end; Step 20), be deployed in sample reception termination in the infosystem on cloud platform and receive sample detection application and the sample that sample input end is sent here, and sample is carried out to coded markings; The sample repacking mark termination receipts that are deployed in the infosystem on cloud platform have the sample of coded markings and it are repacked to mark processing; Step 30), the sample being deployed in the infosystem on cloud platform is sent in the testing laboratory of holding the sample that repacking mark is processed to send magnanimity with charge free with charge free, this laboratory completes to detect returns to testing result, and system backstage sends sample quality examining report to the censorship people of sample input end.
The present invention utilizes cloud computing and database encryption technology, by the database encryption technology of infosystem, guarantee that anyone cannot find separately sample receiving terminal and sample and send the corresponding relation between the sample encoded of end with charge free, eliminated artificial subjective factor, thereby objective reliable testing result can be provided.In order to reach real double blinding effect, should there be suitable quantity in the laboratory of linking this system, therefore only have, this infosystem is deployed on cloud computing platform, just may support laboratory and the censorship people of One's name is legion.
To further improve the reliability of laboratory sample quality testing, this infosystem can also be extended to can be to laboratory personnel, instrument, the system that the Lab Factors such as reagent and specific operation process manages, as LIMS (Laboratory Information Management System), ELN (electronic leaning laboratory notebook) and LIS (laboratory information system) etc., these professional infosystems are deployed in above cloud platform and have just become respectively SaaS LIMS (claiming again LIMS-on-Demand), SaaS ELN (claim not only ELN-on-Demand) and SaaS LIS (but also claiming LIS-on-Demand), these systems are after having increased the above-mentioned sample double blinding supervisory routine with database encryption technology, can carry out better the task that double blinding sample quality detects, certainly, lower deployment cost also greatly improves thereupon.The laboratory special information system of this class based on cloud computing often needs to connect and automatically gather its data result with the various analytical and testing instruments in laboratory, is therefore also a kind of of Internet of Things.
Accompanying drawing explanation
Fig. 1 illustrates according to double blinding sample quality detection system and the testing process schematic diagram based on cloud computing of the present invention.
As shown in Figure 1, in order clearly to realize the structure of embodiments of the invention, specific structure and device have been marked in the drawings, but this is only for signal needs, be not intended to limit the invention in this ad hoc structure, device and environment, according to specific needs, those of ordinary skill in the art can adjust these devices and environment or revise, and the adjustment of carrying out or modification are still included in the scope of accompanying claim.
Embodiment
Below in conjunction with the drawings and specific embodiments, double blinding sample quality detection system and the method based on cloud computing provided by the invention is described in detail.In the following description, will a plurality of different aspects of the present invention be described, yet, for those skilled in the art, can only utilize some or all structure of the present invention or flow process to implement the present invention.For the definition of explaining, set forth specific number, configuration and order, but clearly, in the situation that there is no these specific detail, also can not implement the present invention.In other cases, in order not obscure the present invention, for some well-known features, will no longer be described in detail.
In medical domain, double-blind trial is used during for the mankind in subjects conventionally, and object is to avoid the object of test or the result of the personnel's that test subjectivity deflection impact test.In double-blind trial, the object being put to the test and researchist also do not know which object belongs to control group, and which belongs to experimental group.Only, after all data are all collected and analyzed, researchist just can know the affiliated group of experimental subjects.In drug test, often use double-blind, patient is enrolled control group and experimental group at random.Control group is given placebo, and experimental group gives real medicine.That patient or the experimenter who observes patient do not know who obtains real medicine, until research finishes.For the specimen of magnanimity and the laboratory of magnanimity, do not distribute the system that realizes double-blind at present.
Cloud computing is a kind of computation schema, IT resource, data and application can be offered to user as service by network.The present invention will set up an infosystem that comprises sample managing on cloud platform, this Account Dept is deployed on Cloud Server, by network, provide service for relevant magnanimity censorship people's submitted sample and the check laboratory of magnanimity, thereby the laboratory of magnanimity and censorship people are linked up, again by database encryption technology keeping apart completely for information about censorship people and relevant testing laboratory in system, allow censorship people cannot know which laboratory sample will be detected by, the specifying information of censorship people and sample source also cannot be known in laboratory simultaneously, sample completes and detects and form examining report and send to censorship people under double blinding mode.This detection method has been eliminated the intervention of artificial subjectivity, has guaranteed the objectivity of testing result.
Generally speaking, a kind of double blinding sample quality detection method based on cloud computing is provided, the method starts in a set of infosystem (hereinafter to be referred as system) based on database of cloud platform deploy, this system is come management sample and relevant quality testing report by strict database encryption technology, and can allow the laboratory that all relevant censorship people and Duo Jia have relevant qualification above jointly use this cover system at network (wide area network and the LAN (Local Area Network) that comprise Internet).
The direct login system of network input end that censorship people can provide by sample reception end is submitted sample detection application to, then sample is sent to relevant sample reception end, after sample reception end is received sample, infosystem will be employed a sample encoded (can be described as the first sample encoded) certainly, as bar code or radio frequency (RFID) code etc. carries out mark to this sample, then this sample is sent into sample repacking mark end sample is repacked to processing, eliminate if desired the markings such as producer, trade name, the place of production and date of manufacture that may leave on sample.And the prompting automatically providing according to system changes the first sample encoded into another one coding (can be described as the second sample encoded), and the sample of then this being processed is again sent to sample and sends end with charge free.
Sample is sent end with charge free and can be inquired testing laboratory's title and the address of the automatic appointment of system and directly be sent sample with charge free this laboratory by sample the second sample encoded, the corresponding sample detection result of the second sample encoded is directly inputted after completing detection in this laboratory in system by network, system backstage, by automatically produce the sample quality examining report of the first sample encoded according to the data of the second sample encoded, then sends censorship people to.
Again the Relational database encryption technology of mark end can assurance system comprise that system manager cannot inquire separately the corresponding relation of sample the first sample encoded and sample the second sample encoded interior any user.When occurring that special circumstances need to find out the first sample encoded of certain sample and the corresponding relation of the second sample encoded really, the user name and password that system needs 2 even users that have special authority to input oneself more simultaneously can be inquired about.Corresponding relation in order to ensure two sample encoded is not revealed, and can take to increase the complexity of coding and forbid there are any measures such as instrument that can record in sample repacking and mark department.
This process, because the subjective factor in sample detection and reporting process has been eliminated in " double blinding " between sample censorship people and sample detection laboratory, has been guaranteed the objectivity of testing result.
In another embodiment of the present invention, double blinding sample quality based on cloud computing detection system is provided, this system comprise sample magnanimity input end, be deployed in infosystem and magnanimity laboratory end on cloud platform, the infosystem on this cloud platform comprises that sample reception end, sample repack mark end and sample is sent end with charge free.Wherein, infosystem on this cloud platform is disposed database encryption technology and is come management sample and relevant quality testing report, and can allow the laboratory that all relevant censorship people and Duo Jia have relevant qualification use upper the sharing of network (wide area network and the LAN (Local Area Network) that comprise Internet).
Wherein, sample input end is submitted sample detection application for censorship people to by the direct login system of network input end, then sample is sent to relevant sample reception end, and receives the sample detection report that sample reception end returns.
Wherein, sample reception end is used for receiving sample detection application and sample, and uses the first sample encoded to carry out mark to sample, and this coding can be bar code or radio frequency (RFID) code.
Wherein, sample repacking mark end has the sample of the first sample encoded and it is repacked to processing for receiving.Wherein, eliminate if desired the markings such as producer, trade name, the place of production and date of manufacture that may leave on sample.The prompting that sample repacking mark end also provides automatically according to system changes the first sample encoded into another one coding (can be described as the second coding), and the sample of then this being processed is again sent to sample and sends end with charge free.
Wherein, sample sends that end is sent the sample with the second coding with charge free random appointment with charge free or according to the testing laboratory of certain regular appointment, the corresponding sample detection result of the second coding is directly inputted after completing detection in this laboratory in system by network, system backstage, by automatically produce the sample quality examining report of the first coding according to the second coded data, then sends censorship people to.
Wherein, the Relational database encryption technology of mark end can assurance system comprise that system manager cannot inquire separately the corresponding relation of the first sample encoded and the second sample encoded interior any user again.When occurring that special circumstances need to find out the first sample encoded of certain sample and the corresponding relation of the second sample encoded really, the user name and password that system needs 2 even users that have special authority to input oneself more simultaneously can be inquired about.Corresponding relation in order to ensure two sample encoded is not revealed, and can take to increase the complexity of coding and forbid there are any measures such as instrument that can record in sample repacking and mark department.
Finally it should be noted that, above embodiment is only in order to describe technical scheme of the present invention rather than present technique method is limited, the present invention can extend to other modification, variation, application and embodiment in application, and therefore thinks that all such modifications, variation, application, embodiment are in spirit of the present invention and teachings.
Claims (7)
1. the double blinding sample quality detection system based on cloud computing, comprise magnanimity sample input end, be deployed in infosystem on cloud platform and the laboratory end of magnanimity, wherein, the infosystem on this cloud platform comprises that sample reception end, sample repack mark end and sample is sent end with charge free; Sample reception end is used for receiving sample detection application and the sample that sample input end is sent here, and sample is carried out to coded markings; Sample repacks mark end and processes for receiving to have the sample of coded markings and it is repacked to mark; Sample is sent end with charge free and is sent to the sample of repack processing with charge free testing laboratory ，Gai laboratory and complete to detect and return to testing result, and system backstage sends sample quality examining report to the censorship people of sample input end;
Wherein, sample sends that end is sent the sample of repack processing with charge free random appointment with charge free or according to the testing laboratory of certain regular appointment, sample detection result corresponding to the second sample encoded directly inputted after completing detection in this laboratory in system by network, system backstage will produce the sample quality examining report of the first sample encoded automatically according to the data of the second sample encoded, then send censorship people to
Wherein, sample reception end is used the first sample encoded to carry out mark to sample, the prompting that sample repacking mark end also provides according to system changes the first sample encoded into second sample encoded, then the sample with the second sample encoded is sent to sample and sends end with charge free.
2. the double blinding sample quality detection system based on cloud computing according to claim 1, wherein, this first sample encoded is bar code or radio frequency code.
3. the double blinding sample quality detection system based on cloud computing according to claim 1, wherein, sample repacks mark end for eliminating producer on sample, trade name, the place of production or/and the date of manufacture marking.
4. the double blinding sample quality detection system based on cloud computing according to claim 1, wherein, sample input end is submitted sample detection application for censorship people to by the direct login system of network input end, sample is sent to sample reception end, and receives the sample detection report that sample reception end returns.
5. the double blinding sample quality detection system based on cloud computing according to claim 1, wherein, infosystem on this cloud platform is disposed database encryption technology and is come management sample and quality testing report, guarantees that any one user cannot check separately the corresponding relation of the first sample encoded and second sample encoded of sample.
6. the double blinding sample quality detection method based on cloud computing, comprising:
Step 10), censorship people submit sample detection application to by the sample input end login system Network Based of magnanimity, and sample is sent to sample reception end;
Step 20), be deployed in sample reception termination in the infosystem on cloud platform and receive sample detection application and the sample that sample input end is sent here, and sample is carried out to coded markings; The sample repacking mark termination receipts that are deployed in the infosystem on cloud platform have the sample of coded markings and it are repacked to mark processing;
Step 30), the sample being deployed in the infosystem on cloud platform is sent in the testing laboratory of holding the sample that repacking mark is processed to send magnanimity with charge free with charge free, this laboratory completes to detect returns to testing result, system backstage sends sample quality examining report to the censorship people of sample input end
Wherein, step 30) also comprise: sample sends that end is sent the sample of repack processing with charge free random appointment with charge free or according to the testing laboratory of certain regular appointment, the corresponding sample detection result of the second sample encoded is directly inputted after completing detection in this laboratory in system by network, system backstage will produce the sample quality examining report of the first sample encoded automatically according to the data of the second sample encoded, then send censorship people to
Wherein, sample reception end is used the first sample encoded to carry out mark to sample, the prompting that sample repacking mark end also provides according to system changes the first sample encoded into second sample encoded, then the sample with the second sample encoded is sent to sample and sends end with charge free.
7. method according to claim 6, wherein, step 20) also comprise:
Step 210), this coding is used bar code or radio frequency code;
Step 220), at sample, repacking mark end is used for eliminating and on sample, leaves producer, trade name, the place of production and/or the date of manufacture marking.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201110367485.4A CN102507966B (en) | 2011-11-18 | 2011-11-18 | System and method for detecting qualities of double-blind laboratory samples based on cloud computing |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201110367485.4A CN102507966B (en) | 2011-11-18 | 2011-11-18 | System and method for detecting qualities of double-blind laboratory samples based on cloud computing |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN102507966A CN102507966A (en) | 2012-06-20 |
| CN102507966B true CN102507966B (en) | 2014-01-29 |
Family
ID=46220072
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201110367485.4A Active CN102507966B (en) | 2011-11-18 | 2011-11-18 | System and method for detecting qualities of double-blind laboratory samples based on cloud computing |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102507966B (en) |
Families Citing this family (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105262582B (en) * | 2015-09-06 | 2018-05-04 | 山东省计算中心（国家超级计算济南中心） | A kind of method for being used in medicine double-blind trial protect blind bottom information |
| CN109063797A (en) * | 2018-08-03 | 2018-12-21 | 广东电网有限责任公司 | A sample information processing method and system |
| CN111798206B (en) * | 2020-06-24 | 2023-11-14 | 霓检有限公司 | A detection data processing method, device and equipment |
| CN111798946A (en) * | 2020-06-24 | 2020-10-20 | 霓检有限公司 | Detection data processing method, device and equipment |
| CN111798945A (en) * | 2020-06-24 | 2020-10-20 | 霓检有限公司 | A detection system, detection method and platform |
| CN117007824B (en) * | 2023-09-28 | 2024-02-09 | 常州百利锂电智慧工厂有限公司 | Automatic sampling and inspection system for lithium battery material production line |
| CN119417158B (en) * | 2024-10-31 | 2025-11-18 | 中国环境监测总站 | A method and system for generating the sample delivery relationship for environmental monitoring based on dynamic programming |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1905534A (en) * | 2006-08-03 | 2007-01-31 | 上海宝钢钢材贸易有限公司 | Data exchange system |
| CN101706848A (en) * | 2009-11-06 | 2010-05-12 | 中国网通集团宽带业务应用国家工程实验室有限公司 | Method and equipment for processing sample information |
| CN101882275A (en) * | 2010-07-15 | 2010-11-10 | 河北省首钢迁安钢铁有限责任公司 | Laboratory information-based management system for quintuple encryption in metallurgical industry |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7010448B1 (en) * | 2000-03-06 | 2006-03-07 | Bio-Rad Laboratories, Inc. | Method and structure for mitigating instrumentation differences |
| CA2311252A1 (en) * | 2000-06-09 | 2001-12-09 | Watertrax Inc. | Integrated water quality monitoring system |
-
2011
- 2011-11-18 CN CN201110367485.4A patent/CN102507966B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1905534A (en) * | 2006-08-03 | 2007-01-31 | 上海宝钢钢材贸易有限公司 | Data exchange system |
| CN101706848A (en) * | 2009-11-06 | 2010-05-12 | 中国网通集团宽带业务应用国家工程实验室有限公司 | Method and equipment for processing sample information |
| CN101882275A (en) * | 2010-07-15 | 2010-11-10 | 河北省首钢迁安钢铁有限责任公司 | Laboratory information-based management system for quintuple encryption in metallurgical industry |
Also Published As
| Publication number | Publication date |
|---|---|
| CN102507966A (en) | 2012-06-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102507966B (en) | System and method for detecting qualities of double-blind laboratory samples based on cloud computing | |
| Symeonaki et al. | A context-aware middleware cloud approach for integrating precision farming facilities into the IoT toward agriculture 4.0 | |
| Godin et al. | Challenges and limitations in the identification of acoustic emission signature of damage mechanisms in composites materials | |
| Bhandari et al. | Distributed deep neural-network-based middleware for cyber-attacks detection in smart IoT ecosystem: A novel framework and performance evaluation approach | |
| Floris et al. | Managing the quality of experience in the multimedia Internet of Things: A layered-based approach | |
| Shanmugam et al. | Risk assessment of heterogeneous IoMT devices: a review | |
| Nori-Sarma et al. | Advancing our understanding of heat wave criteria and associated health impacts to improve heat wave alerts in developing country settings | |
| Segura Garcia et al. | Spatial statistical analysis of urban noise data from a WASN gathered by an IoT system: Application to a small city | |
| Lokar et al. | Estimation of the ecological fallacy in the geographical analysis of the association of socio-economic deprivation and cancer incidence | |
| Buckley et al. | Edge structural health monitoring (E-SHM) using low-power wireless sensing | |
| Alrobaian et al. | Cybersecurity awareness assessment among trainees of the technical and vocational training corporation | |
| Li et al. | Damage detection with streamlined structural health monitoring data | |
| Abdull Sukor et al. | RSSI-based for device-free localization using deep learning technique | |
| Petroulakis et al. | NextGEM: next-generation integrated sensing and analytical system for monitoring and assessing radiofrequency electromagnetic field exposure and health | |
| Ramirez et al. | Toxicology testing in fatally injured workers: a review of five years of Iowa FACE cases | |
| Ferrer-Cid et al. | Sampling trade-offs in duty-cycled systems for air quality low-cost sensors | |
| WO2017039473A1 (en) | System and procedure for managing the process of verification of the safety of food and agricultural products | |
| Sharma et al. | Towards energy efficient wireless sensing by leveraging ambient Wi-Fi traffic | |
| Muktar et al. | Predictive modeling of signal degradation in urban VANETs using artificial neural networks | |
| Munera et al. | Dynamic reconfiguration of a RGBD sensor based on QoS and QoC requirements in distributed systems | |
| Poudel et al. | Developing a composite drought indicator using PCA integration of CHIRPS rainfall, temperature, and vegetation health products for agricultural drought monitoring in New Mexico | |
| Luo et al. | An Endogenous Security-Oriented Framework for Cyber Resilience Assessment in Critical Infrastructures | |
| Yiengprugsawan et al. | Pain and its impact on functional health: 7-year longitudinal findings among middle-aged and older adults in Indonesia | |
| Sheidaei et al. | Effect of various dynamic shear rheometer testing methods on the measured rheological properties of bitumen | |
| Casari et al. | Airmlp: A multilayer perceptron neural network for temporal correction of pm2. 5 values in turin |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20190109 Address after: 214000 Northwest corner of 7th floor, No. 1 Building, K-Park Business Center, No. 50 Xiuxi Road, Binhu District, Wuxi City, Jiangsu Province Patentee after: Unicorn detection Wuxi Ltd. Address before: 201203 Room 702, Lane 377, Chenhui Road, Zhangjiang High-tech Park, Pudong New Area, Shanghai Patentee before: Shanghai Lab Information Technologies Co.,Ltd. |
|
| CP01 | Change in the name or title of a patent holder | ||
| CP01 | Change in the name or title of a patent holder |
Address after: 214000 Northwest corner of 7th floor, No. 1 Building, K-Park Business Center, No. 50 Xiuxi Road, Binhu District, Wuxi City, Jiangsu Province Patentee after: Ni Inspection Co.,Ltd. Address before: 214000 Northwest corner of 7th floor, No. 1 Building, K-Park Business Center, No. 50 Xiuxi Road, Binhu District, Wuxi City, Jiangsu Province Patentee before: Neon inspection Wuxi Co.,Ltd. Address after: 214000 Northwest corner of 7th floor, No. 1 Building, K-Park Business Center, No. 50 Xiuxi Road, Binhu District, Wuxi City, Jiangsu Province Patentee after: Neon inspection Wuxi Co.,Ltd. Address before: 214000 Northwest corner of 7th floor, No. 1 Building, K-Park Business Center, No. 50 Xiuxi Road, Binhu District, Wuxi City, Jiangsu Province Patentee before: Unicorn detection Wuxi Ltd. |
|
| CP03 | Change of name, title or address | ||
| CP03 | Change of name, title or address |
Address after: 214000 Northwest corner of 7th floor, No. 1 Building, K-Park Business Center, No. 50 Xiuxi Road, Binhu District, Wuxi City, Jiangsu Province Patentee after: Ni Jian (Jiangsu) Technology Co.,Ltd. Country or region after: China Address before: 214000 Northwest corner of 7th floor, No. 1 Building, K-Park Business Center, No. 50 Xiuxi Road, Binhu District, Wuxi City, Jiangsu Province Patentee before: Ni Inspection Co.,Ltd. Country or region before: China |