Abstract: A device receives, from a cloud computing environment, cloud instance information associated with cloud instances in the cloud computing environment, and processes the cloud instance information, with a machine learning model, to determine containers for one or more of the cloud instances and whether cloud instances should be removed from the cloud computing environment. The device causes a first subset of the cloud instances to be removed from the cloud computing environment, based on determining which of the cloud instances should be removed, and causes the containers to be created for a second subset of the cloud instances based on determining the containers. The device receives, from the cloud computing environment, cloud container information associated with the containers created in the cloud computing environment, and causes one or more of the containers to be scaled based on the cloud container information.

Abstract: The present disclosure relates to a communication method and system for converging a 5th-Generation (5G) communication system for supporting higher data rates beyond a 4th-Generation (4G) system with a technology for Internet of Things (IoT). The present disclosure may be applied to intelligent services based on the 5G communication technology and the IoT-related technology, such as smart home, smart building, smart city, smart car, connected car, health care, digital education, smart retail, security and safety services. Accordingly, the embodiments herein disclose a method for handling a timer operation in a wireless communication system (300). The method includes receiving, by a UE (100), a signaling message from a base station (200). The signaling message includes an information about acquired COT of the base station (200). Further, the method includes indicating, by the UE (100), about the acquired COT to a MAC layer from a physical layer.

Abstract: Accordingly the embodiments herein provide a method for adaptive data transfer in a memory system (140), the method comprising: receiving at least one of a data copy request and a data transfer request to perform at least one of a data copy and a data transfer form a first memory subsystem (142) to a second memory subsystem (144). Configuring the memory system (140) in one of a first memory mode and a second memory mode based on a time required to perform at least on of data transfer and data transfer from the first memory subsystem (142) to the second memory subsystem (144) using an enhanced system model and performing at least one of data transferring and data copying from the first memory subsystem (142) to the second memory subsystem (144) in one of the first configured memory mode and the second configured memory mode.

Abstract: Accordingly, the embodiments herein disclose a method for selecting a MCS in a wireless communication system. The method includes receiving, by a UE, a list of default MCS from a base station. Further, the method includes measuring, by the UE, a CQI. Further, the method includes selecting, by the UE, at least one MCS from the list of default MCS based on the measured CQI.

Abstract: The present disclosure relates to a communication method and system for converging a 5th-Generation (5G) communication system for supporting higher data rates beyond a 4th-Generation (4G) system with a technology for Internet of Things (IoT). The present disclosure may be applied to intelligent services based on the 5G communication technology and the IoT-related technology, such as smart home, smart building, smart city, smart car, connected car, health care, digital education, smart retail, security and safety services. Embodiments herein disclose a method for performing random access channel procedure by a UE (300). The method includes determining a first measurement metric value and a second measurement metric value for one of a plurality of SSBs and a plurality of CSI-RSs. The method includes selecting one of a first set of SSBs and a first set of CSI-RSs from one of the plurality of SSBs and the plurality of CSI-RSs based on the first measurement metric.

Abstract: The present disclosure relates to a communication method and system for converging a 5th-Generation (5G) communication system for supporting higher data rates beyond a 4th-Generation (4G) system with a technology for Internet of Things (IoT). The present disclosure may be applied to intelligent services based on the 5G communication technology and the IoT-related technology, such as smart home, smart building, smart city, smart car, connected car, health care, digital education, smart retail, security and safety services. Accordingly, the embodiments herein disclose a method for handling a timer operation in a wireless communication system (300). The method includes receiving, by a UE (100), a signaling message from a base station (200). The signaling message includes an information about acquired COT of the base station (200). Further, the method includes indicating, by the UE (100), about the acquired COT to a MAC layer from a physical layer.

Abstract: The present disclosure relates to a communication method and system for converging a 5th-Generation (5G) communication system for supporting higher data rates beyond a 4th-Generation (4G) system with a technology for Internet of Things (IoT). The present disclosure may be applied to intelligent services based on the 5G communication technology and the IoT-related technology, such as smart home, smart building, smart city, smart car, connected car, health care, digital education, smart retail, security and safety services. Accordingly the embodiments herein provides a method for handling a RAR in a wireless communication system (300).

Abstract: A device receives, from a cloud computing environment, cloud instance information associated with cloud instances in the cloud computing environment, and processes the cloud instance information, with a machine learning model, to determine containers for one or more of the cloud instances and whether cloud instances should be removed from the cloud computing environment. The device causes a first subset of the cloud instances to be removed from the cloud computing environment, based on determining which of the cloud instances should be removed, and causes the containers to be created for a second subset of the cloud instances based on determining the containers. The device receives, from the cloud computing environment, cloud container information associated with the containers created in the cloud computing environment, and causes one or more of the containers to be scaled based on the cloud container information.

Abstract: The present disclosure is related to methods and compositions for treating or preventing kidney injury or failure, comprising administering an endothelin B (ETB) receptor agonist and/or an ?2 adrenergic agent.

Abstract: The present disclosure relates to a communication method and system for converging a 5th-Generation (5G) communication system for supporting higher data rates beyond a 4th-Generation (4G) system with a technology for Internet of Things (IoT). The present disclosure may be applied to intelligent services based on the 5G communication technology and the IoT-related technology, such as smart home, smart building, smart city, smart car, connected car, health care, digital education, smart retail, security and safety services. Accordingly, the embodiments herein provides a method and system method for handling a random access procedure in a Non-Terrestrial communication system (300). The method includes obtaining, by a UE (100), a default TA, a RACH resource, and a RACH configuration list. Further, the method includes selecting, by the UE (100), the default TA and the RACH resource. Further, the method includes applying, by the UE (100), the selected default TA to the random access procedure.

Abstract: A device receives, from a cloud computing environment, cloud instance information associated with cloud instances in the cloud computing environment, and processes the cloud instance information, with a machine learning model, to determine containers for one or more of the cloud instances and whether cloud instances should be removed from the cloud computing environment. The device causes a first subset of the cloud instances to be removed from the cloud computing environment, based on determining which of the cloud instances should be removed, and causes the containers to be created for a second subset of the cloud instances based on determining the containers. The device receives, from the cloud computing environment, cloud container information associated with the containers created in the cloud computing environment, and causes one or more of the containers to be scaled based on the cloud container information.

Abstract: Methods for accelerated code injection detection using operating system controlled memory attributes are performed by systems and apparatuses. The methods optimize search operations for memory segments in system and virtual memories by searching for segment attributes. A set of memory segments is determined wherein each memory segment in the set includes specific attributes. The memory segments in the set are ranked for a threat level based on segment attribute. The threat level is used to determine subsequent actions including providing indications of the memory segments in the set and initiating execution of an anti-malware application. Relevant segment attributes used for the segment search can be dynamically updated in an attribute list. Segment attributes of a segment can be determined by accessing a memory manager of an operating system via an API.

Abstract: The present invention relates to method of treating chronic myeloid leukemia (CML) or drug resistant CML comprising, administering to human being or any other mammal or animal in need thereof, a therapeutically effective amount of Clofazimine (CFZ) or its pharmaceutically acceptable derivative, analogue, salt or composition; or a combination of a therapeutically effective amount of Clofazimine (CFZ) or its pharmaceutically acceptable derivative, analogue, salt or composition with a tyrosine kinase inhibitor (TKI). The invention also provides the kit for treatment of CML or drug resistant CML.

Abstract: A device receives, from a cloud computing environment, cloud instance information associated with cloud instances in the cloud computing environment, and processes the cloud instance information, with a machine learning model, to determine containers for one or more of the cloud instances and whether cloud instances should be removed from the cloud computing environment. The device causes a first subset of the cloud instances to be removed from the cloud computing environment, based on determining which of the cloud instances should be removed, and causes the containers to be created for a second subset of the cloud instances based on determining the containers. The device receives, from the cloud computing environment, cloud container information associated with the containers created in the cloud computing environment, and causes one or more of the containers to be scaled based on the cloud container information.

Abstract: The present invention relates to method of treating chronic myeloid leukemia (CML) or drug resistant CML comprising, administering to human being or any other mammal or animal in need thereof, a therapeutically effective amount of Clofazimine (CFZ) or its pharmaceutically acceptable derivative, analogue, salt or composition; or a combination of a therapeutically effective amount of Clofazimine (CFZ) or its pharmaceutically acceptable derivative, analogue, salt or composition with a tyrosine kinase inhibitor (TKI). The invention also provides the kit for treatment of CML or drug resistant CML.

Abstract: Disclosed systems and methods include configuring behavior of a machine in a physical environment based on detected interactions with the physical environment. In some cases, an electronic identification device identifies a presence of an object in the physical environment. An attribute corresponding to the identified object is determined, the attribute identifying a characteristic of a user or group or users of the physical environment. The attribute is matched to a parameter indicating an environment device and a configuration of the environment device. In some cases, the configuration is based on historical information about interactions in the physical environment, and the user characteristic. Behavior of the environment device is modified based on the configuration.

Abstract: A method for dynamically enforcing a code usage policy including mapping machine code compiled from source code to identify construct interactions in the machine code, determining whether the construct interactions identified by the mapping conform to one or more construct interaction maps in a construct interaction registry associated with a code usage policy, and generating instructions to render one or more error messages within a graphical user interface of a development environment in response to a determination that one or more of the construct interactions in the machine code fails to comply with at least one of the construct interaction maps in the construct interaction registry.

Abstract: A method for dynamically enforcing a code usage policy including mapping machine code compiled from source code to identify construct interactions in the machine code, determining whether the construct interactions identified by the mapping conform to one or more construct interaction maps in a construct interaction registry associated with a code usage policy, and generating instructions to render one or more error messages within a graphical user interface of a development environment in response to a determination that one or more of the construct interactions in the machine code fails to comply with at least one of the construct interaction maps in the construct interaction registry.

Abstract: A device receives, from a cloud computing environment, cloud instance information associated with cloud instances in the cloud computing environment, and processes the cloud instance information, with a machine learning model, to determine containers for one or more of the cloud instances and whether cloud instances should be removed from the cloud computing environment. The device causes a first subset of the cloud instances to be removed from the cloud computing environment, based on determining which of the cloud instances should be removed, and causes the containers to be created for a second subset of the cloud instances based on determining the containers. The device receives, from the cloud computing environment, cloud container information associated with the containers created in the cloud computing environment, and causes one or more of the containers to be scaled based on the cloud container information.

Abstract: Methods for accelerated code injection detection using operating system controlled memory attributes are performed by systems and apparatuses. The methods optimize search operations for memory segments in system and virtual memories by searching for segment attributes. A set of memory segments is determined wherein each memory segment in the set includes specific attributes. The memory segments in the set are ranked for a threat level based on segment attribute. The threat level is used to determine subsequent actions including providing indications of the memory segments in the set and initiating execution of an anti-malware application. Relevant segment attributes used for the segment search can be dynamically updated in an attribute list. Segment attributes of a segment can be determined by accessing a memory manager of an operating system via an API.