D Young & Co LLP

An in-vehicle system includes a first display device including a first display unit provided in front of a driver's seat in a vehicle interior, a second display device including a second display unit provided closer to a passenger's seat than the first display unit in a front portion of the vehicle interior, and an information processing apparatus. In a case where the first display device accepts a luminance adjustment command of the first display unit, the information processing apparatus also adjusts luminance of the second display unit of the second display device in coordination with luminance adjustment of the first display unit.

A method includes obtaining an expert availability forecasting model including at least a first time slot, a multitude of available experts corresponding to the at least first time slot, and a predicted customer demand corresponding to the at least first time slot. An expert allocation model is generated, including a first set of available experts allocated to the at least first time slot based on the expert availability forecasting model. A first set of customers is selected, corresponding to the predicted customer demand. The first set of customers is matched to the corresponding first set of available experts in the at least first time slot, based on the expert allocation model, to obtain a customer-expert allocation schedule. The method further includes transmitting the customer-expert allocation schedule to a performance analytics dashboard. The method further includes monitoring at least one data source for at least one expert availability event.

Aspects of the present disclosure relate to automated content modality transformation. Embodiments include receiving content that corresponds to a particular modality. Embodiments further include providing the content as input to a generative machine learning model that has been trained to generate versions of provided content items that correspond to a target modality. Embodiments further include receiving, as an output from the generative machine learning model, a new version of the content that corresponds to the target modality. Embodiments further include providing the content and the new version of the content as input to a given machine learning model that is trained to generate a confidence score that indicates a likelihood that the new version is an accurate representation of the content in the target modality. Embodiments further include performing one or more actions involving the new version of the content based on the confidence score.

The present disclosure relates to a replacing method for replacing an on-vehicle battery mounted on a vehicle using a cart (20). The cart (20) includes a protrusion (25) that protrudes upward. The replacing method includes moving the cart (20) making the protrusion (25) come into contact with a guide portion (13) provided under a floor of the vehicle (10).

This disclosure describes techniques for managing multiple wireless networks providing overlapping coverage to user devices. In one example, this disclosure describes a computing system configured to collect network data associated with a first wireless network; collect network data associated with a second wireless network, wherein the first wireless network and the second wireless network have an overlapping coverage area, and wherein the first wireless network and the second wireless network are different wireless network types; identify, based on the network data associated with the first wireless network, a user device that is attached to the first wireless network and is in the overlapping coverage area, wherein the user device is also capable of attaching to the second wireless network; and predict, based on both the network data associated with the first wireless network and the network data associated with the second wireless network, a network condition impacting the user device.

The present disclosure relates to a replacing method for replacing an on-vehicle battery. The replacing method includes mounting the on-vehicle battery on a low-height cart (10) that has a height lower than a minimum ground clearance of a vehicle (30) when the on-vehicle battery is mounted, and moving the low-height cart (10) mounting the on-vehicle battery to under a floor of the vehicle (30) and replacing the on-vehicle battery.

An exhaust monitoring apparatus (100) sets a transport delay time (TL) spanning from when air passes through a portion of an intake passage (19) where an air flow meter (20) is provided to when exhaust gas derived from the air that has passed through the air flow meter (20) reaches a nitrogen oxide sensor (17). The exhaust monitoring apparatus (100) estimates an emission amount of nitrogen oxides based on an output value of the nitrogen oxide sensor (17) and an output value of the air flow meter (20) that was output earlier than a point in time at which the nitrogen oxide sensor (17) output the output value by the transport delay time (TL).

Techniques are disclosed for a network management system (NMS) that computes a channel score based on a normalized metric for a channel and assigns a channel to an access point (AP) based on the channel score). In one example, the NMS obtains data associated with at least one channel of a plurality of channels in a frequency band at a site, where the data includes a set of metrics. The NMS computes a normalized metric for each metrics of the set of metrics with respect to a threshold value representative of degraded performance of the at least one channel. The NMS computes a channel score based on a product of the normalized metrics. The NMS assigns a channel to at least one AP based on the channel score for the channel.

The present disclosure relates to a replacing method for replacing an on-vehicle battery having a protection panel (21) joined thereto. The replacing method includes, while the protection panel (21) is joined to the on-vehicle battery, replacing the on-vehicle battery by releasing the fixing between the vehicle on which the on-vehicle battery is mounted and the protection panel (21).

A vehicle control system according to the present disclosure includes: a plurality of cameras arranged side by side along a longitudinal direction of a work line, the plurality of cameras being configured to capture images of a vehicle (100) traveling on the work line from above; and a controller (200) configured to control traveling of the vehicle (100) based on the images captured by the plurality of cameras (310a, 310b). In the vehicle control system, while the vehicle (100) is caused to self-propel in a predetermined direction, a worker performs work while moving, and the plurality of cameras comprise pairs of cameras (310a, 310b) arranged side by side along the longitudinal direction of the work line, each of the pairs of cameras (310a, 310b) being configured to capture images of the vehicle (100) from diagonally upward to the left and diagonally upward to the right, respectively.