Abstract: A cable-end connector and insulation housing assembly thereof are provided. The cable-end connector is paired with a conductive cable, and the insulation housing assembly is capable of guiding the extension of the conductive cable so that extension direction of the conductive cable aligns with expectations. This allows the conductive cable to be easily organized within the electronic device, preventing unnecessary tangling and enabling electronic devices to continue evolving toward being thinner, lighter, and more compact. Additionally, the insulation housing assembly is formed by combining multiple housings. By adjusting the structure of the combined housings, the insulation housing assembly can guide the conductive cable to extend in the desired direction.

Abstract: An electrical connector, which is assembled and constructed from multiple components with conductive terminals. Therefore, the electrical connector can be customized by altering the conductive terminals of the assembled components to adjust the number and configuration of the conductive terminals, enabling the electrical connector to meet the requirements of electronic devices.

Abstract: An electrical connector, and the electrical connector is manufactured through an assembly method, enabling the assembly of conductive terminals tailored to the requirements of electronic devices, thereby achieving customized adjustment of the number of conductive terminals in the electrical connector according to the demands. Additionally, the electrical connector comprises a circuit board capable of accommodating electronic elements, ensuring that the electrical characteristics of the electrical connector meet the requirements of electronic devices.

Abstract: A system for hand movements recognition and analysis comprises an image capture module, a recognition module, and a movement analysis module. The image capture module is installed in an operational area and is configured to capture a continuous image of the at least one hand movement of an operator during an operation period. The recognition module is coupled with the image capture module and comprises a 2D joint recognition model, a joint 3D coordinate recognition model and a hand skeletal joint position global optimization model to recognize a hand joint position of the operator based on the continuous image and generate a hand joint position coordinate.

Abstract: An external movable stage system for automated cell microscopic imaging and analysis comprises a microscope and an external movable stage device. The external movable stage device is attached to the microscope and configured to assist the microscope in observing a cell sample and to avoid vibration of the microscope. The external movable stage device comprises an automatic stage module, a control module and an image positioning module. The automatic stage module comprises a stage adjustment structure and a movable stage connected to the stage adjustment structure. The control module is configured to move the movable stage in scanning manner so that all parts of the sample plate pass through the objective lens of the microscope to obtain sub-images.

Abstract: A semiconductor manufacturing system includes: a nozzle including a first channel that allows a fluid to flow through; a light source configured to emit light; and a light sensor configured to receive light, the light source and the light sensor being disposed within the first channel and opposite to each other. The semiconductor manufacturing system is configured to: emit light, by the light source, from within the nozzle toward a surface while the nozzle is dispensing the fluid; receive the light reflected from the surface by the light sensor, the emitted light and the reflected light adapted to be contained within the fluid; and examine a status of the reflected light. The emitted light and the reflected light propagate in a direction parallel to a longitudinal axis of the first channel.

Abstract: A federated learning contribution calculation method comprises the following steps: a plurality of participants collaboratively developing a federated aggregation model by federated learning method according to their own local datasets; excluding the participation of at least one first participant in all participants, and then the remained participants collaboratively developing a contribution model by federated learning method; and, comparing the value of the first contribution model and the value of the federated model to obtain the contribution of the at least one first participant. The method of the present invention is capable of calculating the contribution(s) of single participant or multiple participants in the federated learning by few additional information and few additional calculations, so as to achieve the fair profit sharing according to the contributions.

Abstract: A decision variable calculation method allowing a of reverse derivation requester to calculate decision variables based on a target result by pre-trained models provided by some participants in federated learning. The method includes the steps of providing the target result to each pre-trained model participating in this method and allowing them to reversely derive the input parameters, forming a loss function based on the difference between each pre-trained model and target result, integrating all input parameters into a total input parameter, and integrating all loss functions into a total loss function. An optimization problem is then constructed by the total input parameters and the total loss function. The solution to the optimization problem is the required decision variables.

Abstract: A method for calculating feasible process parameters of the present invention constructs an optimization model by treating a trained predictive model as a function of process parameters to be determined, wherein the objective function is to minimize the difference between the function value and the target result, subject to the conditions that the process parameters to be determined must satisfy, either individually or in relation to each other. Moreover, in order to solve the constrained optimization problem, the method with penalty function and barrier function can be used to convert the constrained optimization problem into an unconstrained optimization problem to make it more convenient to solve.

Abstract: A method for calculating decision variables is configured to calculate the unconfirmed decision variables. First, the method provides a trained predictive mode obtained by machine learning through a machine learning method on a dataset. Next, the method transforms the objective function of the trained predictive model from a constrained objective function to an unconstrained objective function. The method then solves the optimization problem of the unconstrained objective function, wherein the optimizer, trained with the trained predictive model, calculates gradients to facilitate the solution process. Additionally, the samples from the dataset used to train the trained predictive model can be utilized to determine the initial samples for solving the optimization problem. The method for calculating decision variables of the invention can also add a dummy layer in front of the trained predictive model.

Abstract: The present invention provides a method for calculating decision variables. A dummy layer is added at an input layer of a trained neural network predictive model. The dummy layer includes a plurality of artificial neurons respectively connected to a corresponding input terminal of the input layer for the trained predictive model by a newly established link. The input value of each artificial neuron is set to 1, the bias value of the activation function is set to 0, and the output of the activation function is set to 1 when the input of the activation function is 1. The initial weight value of the newly established link is selected and set, and the weight values can be considered as decision variables, wherein the weight values can have ranges or other inter-conditional restrictions.

Abstract: A method for calculating feasible process parameters to achieve a given process result and the method comprises the following steps of: providing a trained prediction model, obtained by machine learning of a dataset by a machine learning method, wherein the dataset comprises a plurality of samples, each of the samples comprises a plurality of sample parameters, and the trained predictive model is configured to input a plurality of input parameters and generate a prediction result corresponding to the input parameters; setting an expected result as the prediction result of the trained predictive model and providing at least one confirmed input parameters of the input parameters; and comparing the expected result, the at least one confirmed input parameters, and the sample parameters of the samples in the dataset by a reverse derivation algorithm to determine at least one non-confirmed input parameters of the input parameters.

Abstract: A method of manufacturing a semiconductor device includes: receiving a workpiece on which the semiconductor device is manufactured; causing a nozzle to dispense a fluid toward a surface of the workpiece external to the nozzle, wherein the nozzle includes a first channel and a second channel that allow the fluid to flow through; emitting light, by a light source, from within the nozzle toward the surface while the nozzle is dispensing the fluid; receiving light reflected from the surface by a light sensor, the light source and the light sensor being disposed within the nozzle and opposite to each other, and the emitted light and the reflected light adapted to be contained within the fluid; and examining a status of the reflected light. The emitted light and the reflected light propagate in a direction parallel to a longitudinal axis of each of the first channel and the second channel.

Abstract: An electrical connector, wherein the electrical connector can offer sufficient wiring space for the accompanying conductive cables, thereby reducing the stacking height of the conductive cables during wiring to ensure that the electrical connector and its accompanying conductive cables occupy internal space within electronic devices at expected height dimensions. Additionally, the provided electrical connector can guide the conductive cables to extend outward laterally, enabling the conductive cables to extend laterally within electronic devices to facilitate the organization of conductive cables within electronic devices and even helps avoid unnecessary tangling of conductive cables within electronic devices, allowing electronic devices to continue advancing towards thinner designs.

Abstract: A computing in memory accelerator for applying to a neural network includes a memory, a data buffer unit, a pooling unit, a loss computing unit, a first macro circuit, a second macro unit, a third macro unit, and a multiplexer. The memory is used for saving data. The data buffer unit is coupled to the memory and used to buffer data outputted from the memory. The pooling unit is coupled to the memory and used to pool data for acquiring a maximum pooling value. The loss computing unit is coupled to the memory and used to compute output loss. The first macro circuit, the second macro unit, and the third macro unit are coupled to the data buffer unit. The multiplexer is coupled to the pooling unit, the first macro circuit, the second macro unit, and the third macro unit and used to generate output data.

Abstract: NFT transaction method and system relating to biological feature include: receiving, at a biological asset module of an NFT transaction system, a biological cell or tissue from a provider; obtaining, at the biological asset module, the biological feature from the biological cell or tissue; producing, at a digital asset module of the NFT transaction system, a digital creation based on the biological feature; minting, at the digital asset module, a to-be-traded NFT corresponding to the digital creation; evaluating and updating, at a transaction module of the NFT transaction system, a market price of the to-be-traded NFT based on a market condition of the biological feature; and conducting a first transaction matchmaking for the to-be-traded NFT on a virtual transaction platform based on the market price.

Abstract: A method of manufacturing a semiconductor device includes: receiving a workpiece on which the semiconductor device is manufactured; causing a nozzle to dispense a fluid toward a surface of the workpiece external to the nozzle, wherein the nozzle includes a first channel and a second channel that allow the fluid to flow through; emitting light, by a light source, from within the nozzle toward the surface while the nozzle is dispensing the fluid; receiving light reflected from the surface by a light sensor, the light source and the light sensor being disposed within the nozzle and opposite to each other, and the emitted light and the reflected light adapted to be contained within the fluid; and examining a status of the reflected light. The emitted light and the reflected light propagate in a direction parallel to a longitudinal axis of each of the first channel and the second channel.

Abstract: A method of monitoring a fluid includes: applying the fluid from within a nozzle to a surface of a wafer outside of the nozzle; emitting light, by a light source, from the nozzle to the surface; receiving light reflected from the surface by a light sensor and causing the reflected light to propagate into the nozzle; and determining whether a variation of the fluid occurs according to the reflected light.

Abstract: The present invention discloses a three-dimensional cell spheroid with high proliferation activity, and the cell spheroid is obtained by ejecting a cell aggregate through a needle with a needle gauge of less than 30G. The present invention further provides the producing method and the use for the cell spheroid.

Abstract: A method of performing mass spectrometric analyses, comprises: (a) passing a stream of ions through a quadrupole mass analyzer; (b) intercepting a flux of ions emitted from an exit aperture of the quadrupole mass analyzer at a front face of a stack of multichannel plates and emitting a flux of electrons in response to the intercepted flux of ions at a rear face of the stack of multichannel plates; (c) intercepting the flux of electrons at a front surface of a scintillator comprising a phosphorescent material and emitting a flux of photons in response to the intercepted flux of ions at a rear surface of the scintillator; (d) receiving the flux of photons at a photo-imager; and (e) repositioning at least one of the scintillator and the stack of microchannel plates during the execution of one or more of the steps (a) through (d).