Abstract: A method (700) for predicting, for each device included in a set of devices, whether the device will change state at a particular future point in time. The method includes, for a first device within the set of devices, obtaining a first state value indicating the current state of the first device. The method also includes, for a second device within the set of devices, obtaining a second state value indicating the current state of the second device. The method also includes forming an input vector, the input vector comprising the first state value, the second state value, and a temporal feature (e.g., a set of one or more time values indicating the current time). The method also includes inputting the input vector into a trained machine learning (ML) model.

Abstract: A response handling arrangement comprises a response prioritizing device (26) with processing circuitry configured to obtain event data (ED) and/or status data (SD) in the communication network concerning a user, where the obtaining is triggered by the user initiating a connection to a response device (24) of the communication network, apply the event data (ED) and/or status data (SD) in a response selecting model (78) of a trained machine learning module (74), and obtain an indication (I) of a type of response to the user from the response selecting model of the trained machine learning module (74) based on the applied event data (ED) and/or status data (SD) for allowing a real-time response of the response type to be made to the user by the response device (24).

Abstract: A drive device for an electric truck provided with double-tires, the drive device including drive units provided to each of the double-tires on left and right sides of the electric truck, each of the drive units including a drive unit housing integrally accommodating a motor that generates drive power, a reducer that reduces a rotation speed of the motor, and a final gear that is connected to the reducer and transfers the drive power of the motor to a drive shaft of the double-tire. The drive device further including suspension parts one integrally integrated with above the final gear in the drive unit housing of each of the drive units and steering gear parts one integrally integrated with above each of the suspension parts and being configured to be steerable the double-tire.

Abstract: A drive device for an electric truck includes drive unit housings provided to each of drive wheels on left and right sides of the electric truck, each of the drive unit housings integrally accommodating a motor that generates drive power, a reducer that reduces a rotation speed of the motor, and a final gear that is connected to the reducer and transfers the drive power of the motor to the drive wheel. The drive device further includes suspension parts one provided over the final gear in each of the drive unit housings, steering gear parts one being provided over each of the suspension parts, pairs of hinge parts, and pairs of body-connecting parts, one of the pairs connecting each of the steering gear parts to a vehicle body of the electric truck through each of the pairs of hinge parts.

Abstract: An electric truck includes drive units being provided to each of driving wheels on left and right sides of the electric truck, each of the drive units transmitting a driving force of a motor to each of the driving wheels, a body frame casing including a pair of mounting frame bodies extending in a vehicle width direction of the electric truck and being arranged apart in a vehicle front-rear direction and a pair of cross members connecting the pair of mounting frame bodies, and body-connecting parts connecting each of a vehicle front side and a vehicle rear side of each of the drive units arranged in a frame of the body frame casing to each of the mounting frame bodies. The pair of drive units are arranged so as to be adjacent to each other in the vehicle width direction inside the frame of the body frame casing.

Abstract: A drive device for an electric truck provided with double-tires, the drive device including drive units provided to each of the double-tires on left and right sides of the electric truck, each of the drive units including a drive unit housing integrally accommodating a motor that generates drive power, a reducer that reduces a rotation speed of the motor, and a final gear that is connected to the reducer and transfers the drive power of the motor to a drive shaft of the double-tire. The drive device further including suspension parts one integrally integrated with above the final gear in the drive unit housing of each of the drive units and steering gear parts one integrally integrated with above each of the suspension parts and being configured to be steerable the double-tire.

Abstract: The present disclosure relates to a method performed in an operator network providing data network connectivity to Machine-to-Machine (M2M) devices, for charging of a service session involving a plurality of the M2M devices. The method comprises, from each of the plurality of M2M devices involved in the service session, receiving a service message comprising a service identifier (SID) corresponding to the service session. The method also comprises, by means of the received SID from each of the plurality of M2M devices, determining the number of M2M devices involved in the service session. The method also comprises, based on the determined number of M2M devices, calculating a charging rate for the service session. The method also comprises using the calculated rate, charging the service session.

Abstract: A response handling arrangement comprises a response prioritizing device (26) with processing circuitry configured to obtain event data (ED) and/or status data (SD) in the communication network concerning a user, where the obtaining is triggered by the user initiating a connection to a response device (24) of the communication network, apply the event data (ED) and/or status data (SD) in a response selecting model (78) of a trained machine learning module (74), and obtain an indication (I) of a type of response to the user from the response selecting model of the trained machine learning module (74) based on the applied event data (ED) and/or status data (SD) for allowing a real-time response of the response type to be made to the user by the response device (24).

Abstract: A method of allocating radio resources in a cellular network by a network node associated with a destination cell. Prior to a handover of a moving user equipment (UE) from an originating cell to the destination cell, receiving a moving user resource requirement and a predicted handover time for the moving UE, estimating a total resource requirement comprising a sum of the moving user resource requirement and an initial resource requirement comprising a sum of resource requirements of other UEs in the destination cell, determining whether a capacity of the destination cell is sufficient to provide for the total resource requirement.

Abstract: The present disclosure relates to a method related to an online charging system for a cellular radio communication system. The method includes obtaining a notification that a refill action of a user account for the communication system is pending. The notification includes an identifier (vid) of a refill resource for the refill action. The method also includes inspecting a refill database updated by an account management function of the online charging system to determine whether the refill resource identifier is included therein, indicating whether or not the user account has been refilled based on the refill resource.

Abstract: The present disclosure relates to a method performed in an operator network providing data network connectivity to Machine-to-Machine (M2M) devices, for charging of a service session involving a plurality of the M2M devices. The method comprises, from each of the plurality of M2M devices involved in the service session, receiving a service message comprising a service identifier (SID) corresponding to the service session. The method also comprises, by means of the received SID from each of the plurality of M2M devices, determining the number of M2M devices involved in the service session. The method also comprises, based on the determined number of M2M devices, calculating a charging rate for the service session. The method also comprises using the calculated rate, charging the service session.

Abstract: The present disclosure relates to a method related to an online charging system for a cellular radio communication system. The method includes obtaining a notification that a refill action of a user account for the communication system is pending. The notification includes an identifier (vid) of a refill resource for the refill action. The method also includes inspecting a refill database updated by an account management function of the online charging system to determine whether the refill resource identifier is included therein, indicating whether or not the user account has been refilled based on the refill resource.

Abstract: The present disclosure relates to a method performed by a network element in an operator network for assessing a quality of experience (QoE) of a service for a radio device. The method comprises receiving a first value of a key performance indicator (KPI) of the service from the radio device. The method also comprises receiving a second value of the KPI from the operator network serving the radio device. The method also comprises comparing the first and the second values of the KPI, and determining any deterioration of the QoE over the operator network, based on said comparing. The present disclosure also relates to a method of the radio device as well as to the network element and the radio device.

Abstract: A method of allocating radio resources in a cellular network by a network node associated with a destination cell. Prior to a handover of a moving user equipment (UE) from an originating cell to the destination cell, receiving a moving user resource requirement and a predicted handover time for the moving UE, estimating a total resource requirement comprising a sum of the moving user resource requirement and an initial resource requirement comprising a sum of resource requirements of other UEs in the destination cell, determining whether a capacity of the destination cell is sufficient to provide for the total resource requirement.

Abstract: A method and a control node for handling incoming communication directed to a first wireless device when a user of the first wireless device is driving a vehicle. The control node detects a second wireless device that is present in the vehicle. When an incoming communication directed to the first wireless device is received, the control node forwards the incoming communication to the second wireless device, to enable a user of the second wireless device to act upon the incoming communication. Thereby, the first wireless device will not emit any sound or vibration and its user will not be distracted and tempted to look at the device and/or respond to the communication. The control node may be implemented in the first wireless device, a network node or a vehicle node.

Abstract: A stream processing handling arrangement provides a number of data handling blocks, selectable for forming a work flow. The blocks comprise data processing blocks. The arrangement receives selections of data handling blocks, block parameter settings and workflow property objectives, and compares the objectives with corresponding stream processing framework capabilities. The arrangement determines a stream processing framework for the work flow, provides a number software module groups, each corresponding to a different framework and comprising software modules corresponding to the data handling blocks, and chooses a group corresponding to the determined stream processing framework. The arrangement selects, in this group, software modules corresponding to the selected blocks and constructs an application using the selected software modules.

Abstract: The present disclosure relates to a method performed by a network node configured for making automatic predictions in a telecommunication network. The method comprises obtaining a first value of a first key performance indicator (KPI) for a first network entity (NE) in the telecommunication network. The method also comprises obtaining a second value of a second KPI for a communication route between said first NE and a second NE. The method also comprises predicting, automatically and based on the obtained first and second values, that an alarm will be triggered at the second NE.

Abstract: The present disclosure relates to a method performed by a network element in an operator network for assessing a quality of experience (QoE) of a service for a radio device. The method comprises receiving a first value of a key performance indicator (KPI) of the service from the radio device. The method also comprises receiving a second value of the KPI from the operator network serving the radio device. The method also comprises comparing the first and the second values of the KPI, and determining any deterioration of the QoE over the operator network, based on said comparing. The present disclosure also relates to a method of the radio device as well as to the network element and the radio device.

Abstract: A method for propagating user preference information in a communications network, in which the user preference information may be available for a subset of users within the network. The method comprises generating individual user attribute vectors, based on user historical data and estimating user preference information. The method further comprises defining a community structure for the network and generating a stacked representation for users, the representation comprising the user attribute vector augmented with an aggregated vector of estimated user preferences of members of the user's community. The method further comprises learning a function relating the stacked representation to user preference, using the subset of users, and applying the learned function to users outside the subset.

Abstract: The present disclosure relates to a method performed by a network node configured for making automatic predictions in a telecommunication network. The method comprises obtaining a first value of a first key performance indicator (KPI) for a first network entity (NE) in the telecommunication network. The method also comprises obtaining a second value of a second KPI for a communication route between said first NE and a second NE. The method also comprises predicting, automatically and based on the obtained first and second values, that an alarm will be triggered at the second NE.