Abstract: A Radio Access Network Intelligent Controller (RIC), a dynamic Resource Block (RB) allocation method, and a related base station. The dynamic RB configuration method include the followings. The RIC obtains network status information from multiple BSs. Based on the network status information, the RIC identifies at least one first UE among multiple UEs that is experiencing interference. The RIC sets multiple dynamic RB allocation strategies corresponding to multiple BSs based on the network status information, at least one first UE, and at least one first BS. The RIC transmits the multiple dynamic RB allocation strategies to corresponding to ones of the multiple BSs. In response to a dynamic adjustment condition being triggered, the RIC re-obtain the network status information, to update the multiple dynamic RB allocation strategies, and transmit the multiple updated dynamic RB allocation strategies to corresponding ones of the multiple BSs.

Abstract: An adjustment method for a light emitting system and a light emitting system are provided. The light emitting system comprises a plurality of light emitting elements and a control circuit. Each of the light emitting elements has a corresponding lighting setting value. The adjustment method comprises: establishing correlation values between a target color temperature, which ranges from 1000K to 12000K, and the lighting setting values; summing the correlation values to generate a total and calculating a percentage of each of the correlation values relative to the total; and setting emission power of each of the light emitting elements according to the corresponding percentage of each of the light emitting elements. The mixed light that matches the target color temperature is then provided, and the color rendering index (CRI) of the mixed light has Ra>90.

Abstract: The invention relates to a novel method for precise and early diagnosis to facilitate in time intervention for ocular surface disease (OSD). Therefore, the method is potentially useful for ocular surface disease (OSD) diagnosis in the clinical settings.

Abstract: The invention relates to a display device which comprises a light source, a grid structure and a photo interrupter. The grid structure is disposed above the light source and can move left and right relative to the light source. When the grid structure does not block the photo interrupter, the light source receives a first signal, and when the grid structure blocks the photo interrupter, the light source receives a second signal.

Abstract: A method of bandwidth part (BWP) management for a network is provided. Position information of user equipments is received. Whether interference exists between any two of the user equipments is determined based on the position information of the user equipments and the position information of the base stations to obtain an interference status of the user equipments. Interference exists between user equipment(s) of any two base stations in each of the at least one base station combination. Interference exists between a first user equipment and a second user equipment in a first base station combination. BWP resource allocation is performed based on the at least one base station combination and the interference status of the user equipments to obtain a BWP resource allocation result. The first user equipment is assigned with a first BWP frequency band and the second user equipment is assigned with a second BWP frequency band.

Abstract: The invention relates to a display device which comprises a light source, a grid structure and a photo interrupter. The grid structure is disposed above the light source and can move left and right relative to the light source. When the grid structure does not block the photo interrupter, the light source receives a first signal, and when the grid structure blocks the photo interrupter, the light source receives a second signal.

Abstract: Aspects described herein may relate to methods, systems, and apparatuses that determine one or more categories associated with a dataset, or a portion thereof. The determination may be performed based on one or more tags associated with the dataset and/or a description associated with the dataset. Further, the determination may be performed by searching an ontology based on the one or more tags and/or the description. The determination may be performed by using a machine-learning model based on the one or more tags and/or the description. Once the one or more categories associated with the dataset are determined, the one or more categories may be used as a basis for modifying the dataset and/or validating the dataset.

Abstract: Aspects described herein may relate to methods, systems, and apparatuses that determine one or more categories associated with a dataset, or a portion thereof. The determination may be performed based on one or more tags associated with the dataset and/or a description associated with the dataset. Further, the determination may be performed by searching an ontology based on the one or more tags and/or the description. The determination may be performed by using a machine-learning model based on the one or more tags and/or the description. Once the one or more categories associated with the dataset are determined, the one or more categories may be used as a basis for modifying the dataset and/or validating the dataset.

Abstract: A method of bandwidth part (BWP) management for a network is provided. Position information of user equipments is received. Whether interference exists between any two of the user equipments is determined based on the position information of the user equipments and the position information of the base stations to obtain an interference status of the user equipments. Interference exists between user equipment(s) of any two base stations in each of the at least one base station combination. Interference exists between a first user equipment and a second user equipment in a first base station combination. BWP resource allocation is performed based on the at least one base station combination and the interference status of the user equipments to obtain a BWP resource allocation result. The first user equipment is assigned with a first BWP frequency band and the second user equipment is assigned with a second BWP frequency band.

Abstract: A method for obtaining enrichment information and a controller are provided. The method includes: querying, by an enrichment information handling circuit, whether a database stores a first enrichment information corresponding to a user device in response to the enrichment information handling circuit receiving a first creation request associated with the user device from an application; triggering, by the enrichment information handling circuit, the application to subscribe to the database for enrichment information corresponding to the user device in response to determining that the database stores the first enrichment information corresponding to the user device; and pushing, by the database, second enrichment information to the application in response to presence of the second enrichment information corresponding to the user device in the database.

Abstract: A method for obtaining enrichment information and a controller are provided. The method includes: querying, by an enrichment information handling circuit, whether a database stores a first enrichment information corresponding to a user device in response to the enrichment information handling circuit receiving a first creation request associated with the user device from an application; triggering, by the enrichment information handling circuit, the application to subscribe to the database for enrichment information corresponding to the user device in response to determining that the database stores the first enrichment information corresponding to the user device; and pushing, by the database, second enrichment information to the application in response to presence of the second enrichment information corresponding to the user device in the database.

Abstract: Aspects described herein may relate to methods, systems, and apparatuses that determine one or more categories associated with a dataset, or a portion thereof. The determination may be performed based on one or more tags associated with the dataset and/or a description associated with the dataset. Further, the determination may be performed by searching an ontology based on the one or more tags and/or the description. The determination may be performed by using a machine-learning model based on the one or more tags and/or the description. Once the one or more categories associated with the dataset are determined, the one or more categories may be used as a basis for modifying the dataset and/or validating the dataset.

Abstract: Aspects described herein may relate to methods, systems, and apparatuses that determine one or more categories associated with a dataset, or a portion thereof. The determination may be performed based on one or more tags associated with the dataset and/or a description associated with the dataset. Further, the determination may be performed by searching an ontology based on the one or more tags and/or the description. The determination may be performed by using a machine-learning model based on the one or more tags and/or the description. Once the one or more categories associated with the dataset are determined, the one or more categories may be used as a basis for modifying the dataset and/or validating the dataset.

Abstract: Aspects described herein may relate to methods, systems, and apparatuses that process one or more tags associated with a dataset and index the dataset based on the processing of the one or more tags. Processing a tag may include, for example, tokenizing the tag, mapping or expanding abbreviations included within the tag, and otherwise mapping or expanding elements of the tag based on alphanumeric characteristics. Additionally, as part of processing the tag, a number of potential tags may be determined. An ontology may be searched to determine whether any of the potential tags are also found within the ontology. The dataset may be indexed into a searchable index based on any of the potential tags that are found within the ontology.

Abstract: Aspects described herein may relate to methods, systems, and apparatuses that determine one or more categories associated with a dataset, or a portion thereof. The determination may be performed based on one or more tags associated with the dataset and/or a description associated with the dataset. Further, the determination may be performed by searching an ontology based on the one or more tags and/or the description. The determination may be performed by using a machine-learning model based on the one or more tags and/or the description. Once the one or more categories associated with the dataset are determined, the one or more categories may be used as a basis for modifying the dataset and/or validating the dataset.

Abstract: Aspects described herein may relate to methods, systems, and apparatuses that process one or more tags associated with a dataset and index the dataset based on the processing of the one or more tags. Processing a tag may include, for example, tokenizing the tag, mapping or expanding abbreviations included within the tag, and otherwise mapping or expanding elements of the tag based on alphanumeric characteristics. Additionally, as part of processing the tag, a number of potential tags may be determined. An ontology may be searched to determine whether any of the potential tags are also found within the ontology. The dataset may be indexed into a searchable index based on any of the potential tags that are found within the ontology.

Abstract: Aspects described herein may relate to methods, systems, and apparatuses that process one or more tags associated with a dataset and index the dataset based on the processing of the one or more tags. Processing a tag may include, for example, tokenizing the tag, mapping or expanding abbreviations included within the tag, and otherwise mapping or expanding elements of the tag based on alphanumeric characteristics. Additionally, as part of processing the tag, a number of potential tags may be determined. An ontology may be searched to determine whether any of the potential tags are also found within the ontology. The dataset may be indexed into a searchable index based on any of the potential tags that are found within the ontology.

Abstract: A method for generating a data-bearing image is implemented by an encoding system including a halftoning module and an encoding module that stores encoding rules associated with respective codes. In the method, the halftoning module converts a grayscale image into a halftone image having a plurality of image cells each consisting of a plurality of dots, at least one of which is a first-tone dot and each of the rest of which is a second-tone dot. Afterward, the encoding module generates a data-bearing halftone image encoded with at least one of the codes by maintaining or changing the number of the first-tone dots in one of the image cells based on one of the encoding rules associated with the at least one of the codes.

Abstract: A method for generating a data-bearing image is implemented by an encoding system including a halftoning module and an encoding module that stores encoding rules associated with respective codes. In the method, the halftoning module converts a grayscale image into a halftone image having a plurality of image cells each consisting of a plurality of dots, at least one of which is a first-tone dot and each of the rest of which is a second-tone dot. Afterward, the encoding module generates a data-bearing halftone image encoded with at least one of the codes by maintaining or changing the number of the first-tone dots in one of the image cells based on one of the encoding rules associated with the at least one of the codes.

Abstract: An encoding system converts a grayscale image into an original halftone image according to a predetermined threshold matrix, determines carrier cells from the original halftone image according to reference dot patterns having rotationally asymmetric first-tone patterns, converts the carrier cells into encoded cells according to to-be-embedded codes and rotational states of corresponding asymmetric first-tone patterns, and optimizes non-carrier cells and encoded cells using a direct binary search technique to visually approach the grayscale image.