Device for selecting a training and / or usage recommendation and / or a characterization
A computer-implemented device integrates scepter, surprise bags, and tuning forks with unique memory assignments to provide personalized training and characterization, addressing the lack of comprehensive integration in existing systems, enhancing user engagement and understanding through tailored recommendations.
Patent Information
- Application Number
- DE202022003340
- Authority / Receiving Office
- DE · DE
- Patent Type
- Utility models
- Current Assignee / Owner
- Filing Date
- 2022-05-04
- Publication Date
- 2026-04-30
- Estimated Expiration
- 2032-05-31
AI Technical Summary
Existing systems lack a comprehensive and efficient method for selecting, displaying, and processing training and usage recommendations based on specific personality traits or characteristics, particularly through the use of elements like scepter, surprise bags, and tuning forks, which are not effectively integrated into existing training and characterization devices.
A computer-implemented device that integrates elements such as scepter, surprise bags, and tuning forks, assigning each to a unique memory location, and processes these elements using a processor to provide contextual training and usage recommendations, displayed on a screen, utilizing binary language for memory allocation.
Enables effective and personalized training and characterization by leveraging the unique traits of each element, providing tailored recommendations that address individual strengths and weaknesses, enhancing user engagement and understanding.
Smart Images
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Abstract
Description
[0001] The present invention relates to a device for selecting a training and / or usage recommendation and / or a characterization according to the preamble of claim 1.
[0002] According to at least one embodiment, the device for selecting a training and / or usage recommendation and / or a characterization comprises, firstly, providing and / or contextually inserting at least one element of a selection of a training and / or usage recommendation and / or a characterization, displaying the training and / or usage recommendation and / or a characterization by means of a display device, in particular a screen, and processing the training and / or usage recommendation and / or a characterization by at least one processor element, wherein the provision and / or the contextual insertion is based on exactly one element selected from a group consisting of the elements scepter, surprise bags, paragraph and tuning fork type.
[0003] According to at least one embodiment, the selection can be carried out using a selection element, for example a pen, a mouse or similar.
[0004] According to at least one embodiment, each element of the group is assigned to at least one memory location on a memory element of the representation means, preferably uniquely assigned.
[0005] According to at least one embodiment, the then allocable memory space is at least partially filled with a text based on a binary language.
[0006] According to at least one embodiment, the present invention is a computer-implemented device for selecting a training and / or usage recommendation and / or a characterization.
[0007] According to at least one embodiment, the method for selecting a training and / or usage recommendation and / or a characterization comprises, firstly, providing and / or contextually inserting at least one element of a selection of a training and / or usage recommendation and / or a characterization, secondly, displaying the training and / or usage recommendation and / or a characterization by means of a display device, in particular a screen, and thirdly, processing the training and / or usage recommendation and / or a characterization by at least one processor element, wherein the provision and / or the contextual insertion is based on exactly one element selected from a group consisting of the elements scepter, surprise bags, paragraph, tuning fork type
[0008] The invention described here will be explained in more detail below with reference to the figures.
[0009] The figures all show a device 1000 or a method 100 for selecting a training and / or usage recommendation and / or a characterization.
[0010] The Fig. 1 represents that the present device 1000 comprises the provision and / or contextual insertion of at least one element of a selection of a training and / or usage recommendation and / or a characterization, as well as the display of the training and / or usage recommendation and / or a characterization by means of a display means, in particular a screen, and the processing of the training and / or usage recommendation and / or a characterization by at least one processor element.
[0011] At the Fig. 1. The provisioning and / or contextual insertion is based on exactly one element, namely the scepter 1.
[0012] In detail, therefore, the Fig. 1 can be deduced that the depicted scepter 1, for example, possesses the following properties: Strengths: Doer, assertive, gets things done, self-confident, open, direct, honest, committed, ambitious, strong will, fully committed, goal-oriented. Weaknesses: arrogant, bulldozer, aggressive. T-shirt: Get to the point - now. Motivation: Results, power, influence, success, material possessions. Stressors: Processes that are too slow, emotional energy, beating around the bush. Compliments: You're strong!, You can do it!, praise for a result, possibly also for something material (possessions). Insults: You are weak. The result you achieved is not good. You can't... Self-understanding: I'm OK. You're OK. And if not, that's OK too. Key word: I know.
[0013] In the Fig. Figure 2 shows the element Paragraph 2, where the selection can be made using a selection element, for example a pen, a mouse or similar. Each element of the group is therefore assigned to at least one memory location on a memory element of the representation device, preferably uniquely assigned.
[0014] For example, paragraph 2 shown here has the following characteristics: Strengths: thorough and precise, patient, solves problems in a structured and efficient manner, thinks everything through carefully, improves processes, analytical, knowledgeable, knows details. Weaknesses: cold, lazy when not motivated, very critical. T-shirt: Solve the problem like a puzzle. Motivation: Efficiency, predictability, accuracy, order Stressors: lack of rules, changes, mistakes and inaccuracies, silly people, chaos Compliments: You thought that through well. (Logic), Good overview, you know a lot. (Only accepts compliments from people he / she respects) Insults: This could have been resolved more quickly / effectively. This is wrong / illogical or poorly thought out. Self-image: I'm OK. You're not. Keyword: I think.
[0015] Fig. Figure 3 shows the computer-implemented device 1000 for selecting a training and / or usage recommendation and / or a characterization, wherein the memory space that can then be allocated is at least partially filled with a text based on a binary language.
[0016] The pictured surprise bag 3, for example, expresses the following properties: Strengths: creative, networker, spontaneous, flexible, creates a good atmosphere, funny, visionary, adapts quickly to new situations, entertaining, optimistic Weaknesses: blabbers, unpredictable, unreliable, lacks boundaries, is unprofessional, overreacts T-shirt: Say what you want - and smile! Motivation: People, play and fun, personal recognition. Stressors: Rigid rules (feeling restricted), sitting still, too much theory, being ignored. Compliments: Personal praise, YOU are... (appearance, character, charisma). Insults: Nobody cares about your opinion, you are unpopular, you (personally) are... Self-perception: Am I OK? You are OK. Keyword: I imagine.
[0017] The Fig. It can be seen from paragraph 4 that the method 100 for selecting a training and / or usage recommendation and / or a characterization comprises, firstly, the provision and / or contextual insertion of at least one element of a selection of a training and / or usage recommendation and / or a characterization, and secondly, the display of the training and / or usage recommendation and / or a characterization by means of a display device, in particular a screen, and thirdly, the processing of the training and / or usage recommendation and / or a characterization by at least one processor element, wherein the provision and / or the contextual insertion is based on exactly one element.
[0018] In detail, the Fig. 4 can be seen to indicate that the tuning fork 4 shown has, for example, the following properties: Strengths: empathetic, recognizes what others think, feel and need, helpful, creates harmony and quickly makes people feel comfortable. Weaknesses: doesn't stand up for his opinion, vulnerable. T-shirt: Give me time and listen to me. Motivation: Harmony, security, well-being Stressors: General pressure, deadlines, working too fast, physical energy. Compliments: You helped me a lot. You understand what I / others need. You are kind. Compliments for children or animals Insults: You're making me feel bad. You're only out for yourself, you only care about yourself. You didn't really care. Self-perception: Am I okay? Are you okay (or should I help you)? Keyword: I feel. Reference symbol list 1 scepter Paragraph 2 3 surprise bags 4 tuning forks 100 procedures 1000 devices
Claims
[1] Device (1000) for selecting a training and / or usage recommendation and / or a characterization, comprising - Providing and / or contextually inserting at least one element of a selection of a training and / or usage recommendation and / or a characterization, - Presentation of the training and / or usage recommendation and / or a characterization by means of a presentation device, in particular a screen, - Processing of the training and / or usage recommendation and / or a characterization by at least one processor element, characterized by , that the provisioning and / or contextual insertion is based on exactly one element, which is selected from a group consisting of the elements scepter (1), surprise bag (3), paragraph (2) and tuning fork type (4). [2] Device (1000) according to claim 1, characterized by , that selection using a selection element, for example a pen, a mouse or similar, is feasible. [3] Device (1000) according to claim 1 or 2, characterized by , that each element of the group has at least one memory location on a memory element of the representation means, preferably uniquely assigned. [4] Device (1000) according to claim 3, characterized by , that the then allocable storage space is at least partially filled with text based on a binary language. [5] Computer-implemented device (1000) for selecting a training and / or usage recommendation and / or a characterization according to claim 1.