CN111292826A - Intelligent fitness management method and system - Google Patents
Intelligent fitness management method and system Download PDFInfo
- Publication number
- CN111292826A CN111292826A CN202010129036.5A CN202010129036A CN111292826A CN 111292826 A CN111292826 A CN 111292826A CN 202010129036 A CN202010129036 A CN 202010129036A CN 111292826 A CN111292826 A CN 111292826A
- Authority
- CN
- China
- Prior art keywords
- student
- data
- training
- human body
- coach
- 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.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/30—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Biophysics (AREA)
- Physical Education & Sports Medicine (AREA)
- Engineering & Computer Science (AREA)
- Epidemiology (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Primary Health Care (AREA)
- Public Health (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses an intelligent fitness management method and system, which comprises the following steps: inputting physical component data of the student; generating a human body model corresponding to the physical data of the student through a human body data materialization algorithm; the student reserves a professional coach according to the generated human body model; the reserved coach formulates training content through the student human body model and the data; after the training content is finished, generating a training score; the invention realizes intelligent generation of the body model through the human body data materialization algorithm, so that a coach and a student can visually see the part of the student needing to exercise, and a training plan can be accurately specified; various data are stored through the cloud storage end, and can be effectively classified and stored, so that the data can be properly managed; the coach can modify the training content in time according to the condition of the student through the information interaction between the coach and the student so as to achieve the optimal training effect.
Description
Technical Field
The invention relates to the field of fitness, in particular to an intelligent fitness management method and system.
Background
With the progress of times, people have more requirements on body health, so people going to a gymnasium for exercise are gradually increased, however, blind exercise can cause damage to the body, and therefore a professional coach is required for guidance; when a coach guides a student, the physical condition of the student needs to be comprehensively known, and if the student is guided more, optimal body analysis and teaching content customization cannot be effectively and comprehensively performed on all students, so that an effective management system and an effective management method are needed to help the coach to perform training management.
At present, the functions of the traditional body-building system are limited to inputting data, obtaining information and reserving class time; the traditional body-building system only changes the handwritten data of the name, sex, age, telephone and the like of the student into the computer input data and does not have the functions of intelligently processing the data and managing the data; the traditional fitness system cannot finish training appeal selection at the existing port, cannot finish targeted training appeal classification and planning, only records body composition data into a computer for character display, and does not have an intelligent data generation function; the content of the training plan, such as: the action, time, times and historical coaches only display pictures or characters, and cannot directly design training plans, cloud storage and screening through ports.
Disclosure of Invention
The invention aims to: aiming at the existing problems, an intelligent fitness management method and system are provided; the invention solves the problem that the body-building system can not generate the body model intelligently; the problem that the body-building system cannot process data intelligently is solved; the problem that the body-building system can not customize the training content is solved.
The technical scheme adopted by the invention is as follows:
an intelligent fitness management method, comprising: inputting physical component data of the student; generating a human body model corresponding to the physical data of the student through a human body data materialization algorithm; the student reserves a professional coach according to the generated human body model; the reserved coach formulates training content through the student human body model and the data; and generating a training score after the training content is completed.
Further, the human body data visualization algorithm is as follows: body fat rate 1.2 × BMI +0.23 × age-5.4-10.8 × gender; the BMI is the value of the weight divided by the height, and the gender value is 1 for males and 0 for females.
11. The intelligent fitness management method of claim 2, wherein the generated mannequin is generated by dividing or multiplying a body fat rate by a constant value; the constant value dynamically changes according to the height of the student, and the height of the student takes 165cm for men and 155cm for women as basic values.
Further, the student body data and the generated human body model are stored in the cloud.
Furthermore, the training content is stored in the cloud end, and trainees can check the training content through the cloud end and upload the trained body data.
Further, the trainer can adjust the training content through the physical data uploaded by the trainee after training.
Further, the training score is generated by comparing the body data input by the student for the first time with the body data after the training is completed.
An intelligent fitness management system comprising: the device comprises a student end, a coach end and a cloud storage end; the student end is used for inputting physical data of a student, calculating and generating a physical model, reserving a coach and checking training contents; the coach end is used for viewing body models and data of students and making and modifying training plans; the cloud storage end is used for storing physical data and training contents of students.
Further, the trainee terminal includes: the system comprises a first input module, a model generation module, a query module, a first display module and a first output module; the first input module is used for inputting physical data of a student; the model generation module is used for calculating and generating a body model according to the body data; the query module is used for querying the training content; the first display module is used for displaying the body model and the training content; the first output module is used for outputting the body data to the cloud storage end.
Further, the trainer end comprises: the second output module, the second display module and the management module; the second output module is used for sending the training content to the cloud storage end; the second display module is used for displaying physical data and a physical model of the student; the management module is used for formulating trainee training content.
In summary, due to the adoption of the technical scheme, the invention has the beneficial effects that:
1. the invention realizes intelligent generation of the body model through the human body data visualization algorithm of the student end, so that a coach and the student can visually see the part of the student needing to exercise, and can accurately specify a training plan.
2. According to the cloud storage system and the cloud storage method, various data are stored through the cloud storage terminal, and various data can be effectively classified and stored, so that the data can be properly managed.
3. The invention can lead the coach to revise the training content in time according to the condition of the student through the information interaction of the coach end and the student end so as to achieve the optimal training effect.
Drawings
The invention will now be described, by way of example, with reference to the accompanying drawings, in which:
fig. 1 is a flow chart of an intelligent fitness management method.
Fig. 2 is a block diagram of an intelligent fitness management system.
Wherein, 1-student end; 2-a training end; 3-a cloud storage end; 11-a first input module; 12-a model generation module; 13-a query module; 14-a first display module; 15-a first output module; 21-a second output module; 22-a second display module; 23-management module.
Detailed Description
All of the features disclosed in this specification, or all of the steps in any method or process so disclosed, may be combined in any combination, except combinations of features and/or steps that are mutually exclusive.
Any feature disclosed in this specification (including any accompanying claims, abstract) may be replaced by alternative features serving equivalent or similar purposes, unless expressly stated otherwise. That is, unless expressly stated otherwise, each feature is only an example of a generic series of equivalent or similar features.
Example 1
An intelligent fitness management method, as shown in fig. 1, comprises:
s1: inputting physical component data of the student;
in the above steps, the physical data of the trainee comprises age, height, weight, body fat rate, muscle, body index, basal metabolism, waist-hip ratio and the like; it should be noted that, when inputting physical data of a student, the corresponding name of the student is also needed to be input for data arrangement.
S2: generating a human body model corresponding to the physical data of the student through a human body data materialization algorithm;
in the above steps, the human body data visualization algorithm is: body fat rate 1.2 × BMI +0.23 × age-5.4-10.8 × gender; generating a human body model according to the body fat rate, wherein the BMI is a value obtained by dividing the weight by the height, namely calculating the weight/the height; the gender values are: male is 1, female is 0; when the human body model is generated, because the human body model can dynamically change according to different people, the human body model is generated by dividing or multiplying the body fat rate by a constant value; the constant value dynamically changes according to the height of the student, in this embodiment, the height of the student is based on 165cm for male and 155cm for female, and the constant changes according to the height fluctuation and mainly changes the positive and negative changes of the height into a change value, specifically:
when the male is based on 165cm of height, the height of the male is 5cm, and the height is divided by a constant value of 1.05; the height is 5cm lower and multiplied by a constant of 1.05; height 10cm, divided by constant 1.12; the height is 10cm, multiplied by a constant 1.12; height 15cm, divided by constant 1.2; the height is 15cm, multiplied by a constant 1.2; height 20cm, divided by constant 1.3; the height is 20cm, multiplied by a constant 1.3; the height is 25cm, and the height is multiplied by a constant 1.4; height 25cm, multiplied by a constant of 1.4.
When the female takes the height of 155cm as a reference, the height of the female is 5cm, and the height is divided by a constant value of 1.05; the height is 5cm lower and multiplied by a constant of 1.05; height 10cm, divided by constant 1.1; the height is 10cm, multiplied by a constant 1.1; height 15cm, divided by constant 1.2; the height is 15cm, multiplied by a constant 1.2; height 17cm, divided by constant 1.25; the height is 17cm, multiplied by a constant 1.25; height 20cm, divided by constant 1.3; height 20cm lower, multiplied by a constant 1.3.
The calculation is carried out under the condition that the body fat ratio is not changed, and when the height of the student is a basic value, the constant is 1; in actual use, if the body fat percentage of a male is 25% and the height is 170cm, the calculation formula is as follows: if 25%/1.05 is 23.8%, intelligently generating a human model with the body fat rate of 23.8%; if the fat percentage of a male is 25% and the height is 160cm, the calculation formula is as follows: 25%. 1.05 ═ 26.2%, the human model with body fat percentage of 26.2% was generated intelligently.
S3: the student reserves a professional coach according to the generated human body model;
in the above steps, the trainee can know the part of the trainee needing to exercise through the generated human body model, and can reserve a professional coach corresponding to the requirement of the trainee according to the requirement of the trainee; for example, a trainer with a high abdominal exercise experience can be reserved, and a trainer with a high leg exercise experience can be reserved. In the embodiment, the human body model can be dragged after the human body model is generated, the human body model is changed, so that the expected human body model is achieved, and the system can appoint an exercise plan and recommend a related coach according to the expected model set by the college; all the data can be uploaded to the cloud end to be stored, so that a coach and a student can check the data at any time.
S4: the reserved coach formulates training content through the student human body model and the data;
in the above steps, the reserved coach can check the physical data and the physical model of the student through the cloud, and the coach can make exercise content according to the requirement of the student and also can make training content according to the expected physical model of the student; if the trainees cancel the training, all data of the trainees can be returned to the trainees from the cloud, and the information safety is guaranteed.
S5: and generating a training score after the training content is completed.
In the above steps, the trainees can check the training content through the cloud and carry out corresponding training according to the training content; the current body data can be uploaded every time one training stage is finished, the body model is generated again, the trainer can compare the body data and the body model twice, and exercise contents are adjusted by combining the body model expected by the trainee, so that the optimal effect is achieved. After training, the system can compare with the body model after training according to initial body model and training to generate training score for the student to directly observe the problem that training is not in place in training change and training.
According to the embodiment, the physical model is generated intelligently, so that a coach and a student can visually see the part of the student needing to exercise, and a training plan can be accurately specified; meanwhile, all data can be effectively classified and stored by storing all data to the cloud, so that the data can be properly managed.
Example 2
An intelligent fitness management system, as shown in fig. 2, comprising: student end 1, coach end 2 and cloud storage end 3.
The student terminal 1 is used for inputting physical data of a student, calculating and generating a physical model, reserving a coach and checking training contents; the trainee terminal 1 includes: the system comprises a first input module 11, a model generation module 12, a query module 13, a first display module 14 and a first output module 15; the first input module 11 is used for inputting physical data of a student, that is, the student or a coach can input the physical data of the student into the student terminal 1 through the first input module 11, the physical data includes height, weight, body fat ratio, muscle, body index, basal metabolism, waist-hip ratio, and the like, in this embodiment, the student can also input the physical data during training overshoot to check the training effect; the model generation module 12 is configured to generate a body model by calculation according to body data, where the generated body model is generated by calculation through a human body data materialization algorithm, and the specific algorithm is as follows: body fat rate 1.2 × BMI +0.23 × age-5.4-10.8 × gender; generating a human body model according to the body fat rate, wherein the BMI is a value obtained by dividing the weight by the height, namely calculating the weight/the height; the gender values are: male is 1, female is 0; the corresponding body model can be generated through the body fat percentage, and in practice, different people have different heights under the condition of the same body fat percentage, so that under the condition of the same body fat percentage, the height is different, the body fat percentage and a constant in the height range need to be multiplied or divided, and the current body fat mass is obtained, wherein the height has a basic height, the height is 165cm for males and 155cm for females; when the male is based on the height 165cm, the height is 5cm, and the constant is divided by 1.05; the height is 5cm lower and multiplied by a constant of 1.05; height 10cm, divided by constant 1.12; the height is 10cm, multiplied by a constant 1.12; height 15cm, divided by constant 1.2; the height is 15cm, multiplied by a constant 1.2; height 20cm, divided by constant 1.3; the height is 20cm, multiplied by a constant 1.3; the height is 25cm, and the height is multiplied by a constant 1.4; the height is 25cm, and the height is multiplied by a constant 1.4; when the female takes the height of 155cm as a reference, the height of the female is 5cm, and the height is divided by a constant value of 1.05; the height is 5cm lower and multiplied by a constant of 1.05; height 10cm, divided by constant 1.1; the height is 10cm, multiplied by a constant 1.1; height 15cm, divided by constant 1.2; the height is 15cm, multiplied by a constant 1.2; height 17cm, divided by constant 1.25; the height is 17cm, multiplied by a constant 1.25; height 20cm, divided by constant 1.3; the height is 20cm, multiplied by a constant 1.3; in the embodiment, the student can also drag the generated body model to change the body model style so as to set the body model into an ideal style, and the system can design a training plan according to the ideal body model; the query module 13 is used for querying the training content, and the trainees can check the training content at any time through the query module 13 and perform corresponding training according to the training content; the first display module 14 is used for displaying the body model and the training content, that is, after the trainee inquires the training content of the trainee, the training content can be displayed through the first display module 14 for the trainee to view; the first output module 15 is configured to output the body data to the cloud storage 3, that is, the input body data and the generated body model may be output to the cloud storage 3 for storage.
The coach terminal 2 is used for viewing body models and data of students and making and modifying training plans; the trainer end 2 comprises: a second output module 21, a second display module 22 and a management module 23; the second output module 21 is used for sending the training content to the cloud storage terminal 3, that is, the training content made by the coach according to the physical model of the student is sent to the cloud storage terminal 3 through the second output module 21, and the student can check the training content of the student through the cloud storage terminal 3; the second display module 22 is used for displaying physical data and physical models of the trainees, that is, the second display module 22 displays the physical data and physical models of the trainees uploaded to the cloud storage terminal 3 by the trainee terminal 1, so that the trainees can view and make corresponding training plans; the management module 23 is configured to formulate trainees training content, that is, after the trainee views physical data, a physical model of the trainee and a physical model expected by the trainee, the trainee can formulate specific training content in combination with a training plan generated by the system, and send the training content to the cloud storage 3 through the second output module 21 for the trainee to view.
The cloud storage end 3 is used for storing physical data and training contents of the trainees, that is, physical data, physical models and expected physical models of the trainees sent from the trainee end 1 can be stored, and training contents, training scores, training suggestions and the like sent from the trainer end 2 can be stored; meanwhile, various data can be classified and sorted through the cloud storage end 3, and data confusion is prevented.
In the embodiment, the cloud storage end 3 stores various data, so that the data is effectively managed, and the various data can be classified and sorted through the cloud storage end 3, so that data confusion is avoided; through the student end 1 and the coach end 2, a coach can visually know the physical condition of the student, and effective training content can be formulated.
According to the intelligent training system, the physical model is intelligently generated through the student end 1, so that a coach and a student can visually see the part of the student needing to exercise, and a training plan can be accurately specified; various data are stored through the cloud storage end 3, and various data can be effectively classified and stored, so that the data can be properly managed; the coach can modify the training content in time according to the condition of the student through the information interaction of the coach end 2 and the student end 1 so as to achieve the optimal training effect.
The invention is not limited to the foregoing embodiments. The invention extends to any novel feature or any novel combination of features disclosed in this specification and any novel method or process steps or any novel combination of features disclosed.
Claims (10)
1. An intelligent fitness management method, comprising: inputting physical component data of the student; generating a human body model corresponding to the physical data of the student through a human body data materialization algorithm; the student reserves a professional coach according to the generated human body model; the reserved coach formulates training content through the student human body model and the data; and generating a training score after the training content is completed.
2. The intelligent fitness management method of claim 1, wherein the human body data materialization algorithm is: body fat rate 1.2 × BMI +0.23 × age-5.4-10.8 × gender; the BMI is the value of the weight divided by the height, and the gender value is 1 for males and 0 for females.
3. The intelligent fitness management method of claim 2, wherein the generated mannequin is generated by dividing or multiplying a body fat rate by a constant value; the constant value dynamically changes according to the height of the student, and the height of the student takes 165cm for men and 155cm for women as basic values.
4. The intelligent fitness management method of claim 1, wherein the trainee can set a desired physical body model through the generated human body model, and the actual trainee physical data, the generated human body model and the set desired human body model data are stored in the cloud.
5. The intelligent fitness management method of claim 1, wherein the training content is stored in a cloud, and the trainee can view the training content through the cloud and upload the trained body data.
6. The intelligent fitness management method of claim 5, wherein the trainer can adjust the training content through the physical data uploaded by the trainee after training.
7. The intelligent fitness management method of claim 1, wherein the training score is generated by comparing physical data input by the trainee for the first time with physical data after training.
8. An intelligent fitness management system, comprising: the device comprises a student end (1), a coach end (2) and a cloud storage end (3); the student terminal (1) is used for inputting physical data of a student, calculating and generating a physical model, reserving a coach and checking training contents; the trainer end (2) is used for viewing body models and data of students and making and modifying training plans; the cloud storage end (3) is used for storing physical data and training contents of students.
9. The intelligent fitness management system of claim 8, wherein the trainee end (1) comprises: the device comprises a first input module (11), a model generation module (12), a query module (13), a first display module (14) and a first output module (15); the first input module (11) is used for inputting physical data of a student; the model generation module (12) is used for generating a body model according to body data calculation; the query module (13) is used for querying the training content; the first display module (14) is used for displaying the body model and the training content; the first output module (15) is used for outputting the body data to the cloud storage end (3).
10. The intelligent fitness management system of claim 8, wherein the trainer end (2) comprises: a second output module (21), a second display module (22) and a management module (23); the second output module (21) is used for sending the training content to the cloud storage end (3); the second display module (22) is used for displaying the physical data and the physical model of the student; the management module (23) is used for formulating trainee training content.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010129036.5A CN111292826A (en) | 2020-02-28 | 2020-02-28 | Intelligent fitness management method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010129036.5A CN111292826A (en) | 2020-02-28 | 2020-02-28 | Intelligent fitness management method and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111292826A true CN111292826A (en) | 2020-06-16 |
Family
ID=71026904
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010129036.5A Pending CN111292826A (en) | 2020-02-28 | 2020-02-28 | Intelligent fitness management method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111292826A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113643789A (en) * | 2021-10-15 | 2021-11-12 | 北京京东方技术开发有限公司 | Method, device and system for generating fitness scheme information |
| CN114822143A (en) * | 2022-06-29 | 2022-07-29 | 深圳前海壹路科技有限公司 | Military training intelligent examination management system and method |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106530055A (en) * | 2016-11-11 | 2017-03-22 | 厦门钢宇工业有限公司 | Body-building method and body-building system |
| TWM563048U (en) * | 2018-03-07 | 2018-07-01 | 國立勤益科技大學 | Fitness training information system |
| CN108472533A (en) * | 2015-12-24 | 2018-08-31 | 三星电子株式会社 | Electronic equipment and the method for providing Personalized motion guidance for it |
| CN109545324A (en) * | 2018-11-05 | 2019-03-29 | 广州捷盈网络科技有限公司 | A kind of training system and its training program recommended method of fitness and weight losing |
| CN110102026A (en) * | 2019-05-13 | 2019-08-09 | 绍兴文理学院 | A kind of system and method intelligently customizing Slimming Program based on Internet of Things |
-
2020
- 2020-02-28 CN CN202010129036.5A patent/CN111292826A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108472533A (en) * | 2015-12-24 | 2018-08-31 | 三星电子株式会社 | Electronic equipment and the method for providing Personalized motion guidance for it |
| CN106530055A (en) * | 2016-11-11 | 2017-03-22 | 厦门钢宇工业有限公司 | Body-building method and body-building system |
| TWM563048U (en) * | 2018-03-07 | 2018-07-01 | 國立勤益科技大學 | Fitness training information system |
| CN109545324A (en) * | 2018-11-05 | 2019-03-29 | 广州捷盈网络科技有限公司 | A kind of training system and its training program recommended method of fitness and weight losing |
| CN110102026A (en) * | 2019-05-13 | 2019-08-09 | 绍兴文理学院 | A kind of system and method intelligently customizing Slimming Program based on Internet of Things |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113643789A (en) * | 2021-10-15 | 2021-11-12 | 北京京东方技术开发有限公司 | Method, device and system for generating fitness scheme information |
| CN113643789B (en) * | 2021-10-15 | 2022-04-01 | 北京京东方技术开发有限公司 | Method, device and system for generating fitness scheme information |
| CN114822143A (en) * | 2022-06-29 | 2022-07-29 | 深圳前海壹路科技有限公司 | Military training intelligent examination management system and method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Dawson et al. | Training with simulation improves residents’ endovascular procedure skills | |
| KR101058741B1 (en) | Study habits testing system and method | |
| US11413501B2 (en) | Method and system of planning fitness courses | |
| CN111292826A (en) | Intelligent fitness management method and system | |
| CN105069294A (en) | Calculation and analysis method for testing cognitive competence values | |
| CN108172051A (en) | A kind of PE Teaching method and apparatus | |
| US20170169718A1 (en) | Athlete mental strength assessment and conditioning system and method | |
| CN108615439A (en) | Method, apparatus, equipment and medium for formulating ability training scheme | |
| CN112289434A (en) | Medical training simulation method, device, equipment and storage medium based on VR | |
| Tekin-Dede et al. | A Rubric Development Study for the Assessment of Modeling Skills. | |
| Krutsevich et al. | Control of physical preparedness of schoolchildren using index method | |
| CN114446109A (en) | Multifunctional interactive massage teaching system | |
| Buckingham | Class size and teacher quality | |
| CN109745688A (en) | The method, apparatus and electronic equipment quantitatively calculated applied to golf swing | |
| US20170039868A1 (en) | Information processing apparatus and ability improvement assisting method | |
| US20190201744A1 (en) | Internet based asynchronous coaching system | |
| Vipinosa et al. | Productivity, Work Values, and Teaching Effectiveness of Science Teachers in Capiz State University | |
| Ayranci et al. | A study of the relationship between students' views toward a career management class and their future careers | |
| Bogamuwa | Learning style preferences of English as second language learners in the Open University English for general academic purpose (EGAP) programme | |
| JP5347078B1 (en) | Education information management computer program, education information management computer system | |
| US20220068150A1 (en) | Organization system, organization process, learning system, memorization process, concept incorporation system, concept incorporation process, and methods of use for understanding general knowledge of important and difficult information | |
| Yaneva et al. | Fitness education for students in the discipline" sport | |
| Ganaden et al. | Leadership Behaviors of Sports Coaches in Public Elementary Schools of District 2, San Felipe, Zambales, Philippines | |
| CN113934901B (en) | Information matching method, device, equipment, system and medium based on behavior cognition | |
| CN113053194B (en) | Physician training system and method based on artificial intelligence and VR technology |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |