Abstract: Technologies for generating a set of models for each account, where each model is a fine-grained, unsupervised behavior model trained for each user to monitor and detect anomalous patterns are described. An unsupervised training pipeline can generate user models, each being associated with one of multiple accounts and is trained to detect an anomalous pattern using feature data associated with the one account. Each account is associated with at least one of a user, a machine, or a service. An inference pipeline can detect a first anomalous pattern in first data associated with a first account using a first user model. The inference pipeline can detect a second anomalous pattern in second data associated with a second account using a second user model.

Abstract: The invention provides a material surface treatment equipment, which is applied to a material substrate. The material surface treatment equipment includes a surface treatment device and at least one waveguide device. The surface treatment device is used to carry the material substrate to perform a surface treatment process. Each waveguide device is used for introducing electromagnetic waves to the material substrate to assist in performing the surface treatment process. Through the introduction of electromagnetic waves, the surface treatment process of the material substrate is easy to perform and can achieve the strengthening effect.

Abstract: An electronic device is provided. The electronic device includes sensing electrodes, reference electrodes, and amplifiers. The sensing electrodes are configured to obtain a first physiological signal and a second physiological signal different from the first physiological signal. The reference electrodes are configured to obtain a first reference signal and a second reference signal different from the first reference signal. The amplifiers are coupled to the plurality of sensing electrodes and the plurality of reference electrodes, and are configured to: subtract the first reference signal from the first physiological signal to generate a first data signal; subtract the second reference signal from the first physiological signal to generate a second data signal; subtract the first reference signal from the second physiological signal to generate a third data signal; and subtract the second reference signal from the second physiological signal to generate a fourth data signal.

Abstract: Technologies for generating a set of models for each account, where each model is a fine-grained, unsupervised behavior model trained for each user to monitor and detect anomalous patterns are described. An unsupervised training pipeline can generate user models, each being associated with one of multiple accounts and is trained to detect an anomalous pattern using feature data associated with the one account. Each account is associated with at least one of a user, a machine, or a service. An inference pipeline can detect a first anomalous pattern in first data associated with a first account using a first user model. The inference pipeline can detect a second anomalous pattern in second data associated with a second account using a second user model.

Abstract: A vehicle seat assembly, suitable for vehicles such as locomotives and the like, includes a main cushion body and a lifting cushion. The main cushion body has a sliding cushion connected to a vehicle body with a sliding structure. The lifting cushion is connected to the vehicle body with a linkage mechanism. The lifting cushion is moved into a carriage when the sliding cushion is in a first position, and when the sliding cushion slides laterally into a second position to form a space portion, the lifting cushion can be lifted from the carriage and moved into the space portion and then positioned, or can be lowered into the carriage again, so that the sliding cushion can be moved back to the first position, thereby allowing the user to adjust seat cushion length according to their needs.

Abstract: Disclosed is an improved approach for managing security alerts to automatically isolate malicious security alerts from benign alerts using an ensemble model of pattern recognition techniques. In some embodiments, the approach provides for automatically isolating security alerts of malicious attack from security alerts that correspond to undesirable, yet benign, activity in computer networks, cloud infrastructures and SAAS applications. Specifically, the approach provides for qualitative contextual assessments of these alerts using an ensemble of models. These ensemble models leverage a history of security events on a computer network, cloud infrastructure and SAAS applications to determine a level of relevance for received alerts and determine, based on that level of relevance, how or if they should be presented to an administrator.

Abstract: The invention provides a material surface treatment equipment, which is applied to a material substrate. The material surface treatment equipment includes a surface treatment device and at least one waveguide device. The surface treatment device is used to carry the material substrate to perform a surface treatment process. Each waveguide device is used for introducing electromagnetic waves to the material substrate to assist in performing the surface treatment process. Through the introduction of electromagnetic waves, the surface treatment process of the material substrate is easy to perform and can achieve the strengthening effect.

Abstract: Technologies for generating a set of models for each account, where each model is a fine-grained, unsupervised behavior model trained for each user to monitor and detect anomalous patterns are described. An unsupervised training pipeline can generate user models, each being associated with one of multiple accounts and is trained to detect an anomalous pattern using feature data associated with the one account. Each account is associated with at least one of a user, a machine, or a service. An inference pipeline can detect a first anomalous pattern in first data associated with a first account using a first user model. The inference pipeline can detect a second anomalous pattern in second data associated with a second account using a second user model.

Abstract: A method for treating sleeping or movement disorder is provided. The method includes the operations as follows. A brainwave of a patient with sleeping or movement disorder is recorded. An onset of a STW oscillation episode from the brainwave is identified, wherein the STW oscillation episode is a STW signal having an oscillation frequency in a range of from about 2 Hz to about 4 Hz. a first stimulation is delivered to the patient when the onset of the STW oscillation episode is identified from the brainwave. The first stimulation is adapted according to a measurable feature of the STW oscillation episode. A system for treating sleeping or movement disorder is also provided.

Abstract: A method for treating movement disorders is provided. The method includes the following operations. A central nervous signal of a patient with movement disorders is recorded. A first stimulation is delivered from a stimulator to the patient when an oscillation episode in a range of from about 3 Hz to about 20 Hz is observed in the central nervous signal. The first stimulation is adapted according to a measurable feature of the oscillation episode. The system for treating movement disorders is also provided.

Abstract: Disclosed is an improved approach for identifying security risks and breaches in a network by applying machine learning methods that learn resource access patterns in the network. Specifically, by observing the access pattern of the network entities (e.g. accounts, services, and hosts) from authorization requests/responses, the model through unsupervised learning, organizes the entity relationships into an ensemble of hierarchical models. The ensemble of hierarchical models can then be leveraged to create a series of metrics that can be used to identify various types of abnormalities in the access of a resource on the network. For instance, by further classifying the access request for a resource using abnormality scores into detection scenarios, the model is able to detect both an abnormality and the type of abnormality and include such information in a corresponding alarm when a security breach happens.

Abstract: A method for treating neural disorders is provided. The method includes the following operation. A stimulation is delivered to a layer of a cortex of a patient with a neural disorder, wherein the stimulation is delivered to less than all layers of the cortex of the patient. In another method for treating neural disorders, a stimulation is delivered to a cortex of a patient with a neural disorder, wherein the stimulation delivered to one of a plurality of layers of the cortex is stronger than to other layers of the cortex. The system for treating neural disorder is also provided. The system includes a stimulation signal generator and a layer-specific stimulation means. The layer-specific stimulation means is coupled to the stimulation signal generator, configured to deliver a stimulation to a specific layer of a cortex of a patient with a neural disorder.

Abstract: The application discloses an electronic device set including a modular appliance. The modular appliance includes a first power supplier, a processing device, and a connector. The power device includes a first power supply terminal, a second power supply terminal and at least one first signal terminal. The the processing device is configured to perform data acquisition and electrical stimulation on a biological subject via the at least one first signal terminal. The connector includes contacts coupled to the first electrode, the second electrode, the first power supply terminal, the second power supply terminal, and the at least one first signal terminal, respectively.

Abstract: A method for treating neural disorders is provided, The method includes the following operation. A stimulation is delivered to a layer of a cortex of a patient with a neural disorder, wherein the stimulation is delivered to less than all layers of the cortex of the patient. In another method for treating neural disorders, a stimulation is delivered to a cortex of a patient with a neural disorder, wherein the stimulation delivered to one of a plurality of layers of the cortex is stronger than to other layers of the cortex. The system for treating neural disorder is also provided. The system includes a stimulation signal generator and a layer-specific stimulation means. The layer-specific stimulation means is coupled to the stimulation signal generator, configured to deliver a stimulation to a specific layer of a cortex of a patient with a neural disorder.

Abstract: Disclosed is an improved approach for identifying security risks and breaches in a network by applying machine learning methods that learn resource access patterns in the network. Specifically, by observing the access pattern of the network entities (e.g. accounts, services, and hosts) from authorization requests/responses, the model through unsupervised learning, organizes the entity relationships into an ensemble of hierarchical models. The ensemble of hierarchical models can then be leveraged to create a series of metrics that can be used to identify various types of abnormalities in the access of a resource on the network. For instance, by further classifying the access request for a resource using abnormality scores into detection scenarios, the model is able to detect both an abnormality and the type of abnormality and include such information in a corresponding alarm when a security breach happens.

Abstract: A method for treating movement disorders is provided. The method includes the following operations. A central nervous signal of a patient with movement disorders is recorded. A first stimulation is delivered from a stimulator to the patient when an oscillation episode in a range of from about 3 Hz to about 20 Hz is observed in the central nervous signal. The first stimulation is adapted according to a measurable feature of the oscillation episode. The system for treating movement disorders is also provided.

Abstract: The present invention relates to a method for testing a retinal implant. After an implantable device for interfacing with retinal cells is provided, an external stimulus is applied to the implantable device so that the implantable device transmits a first pulse to a processing device through a wireless interface. When a conversion unit is controlled to gradually decrease an output voltage until the implantable device outputs an output voltage lower than a reference voltage, the implantable device transmits a signal different from the first pulse to the processing device through the wireless interface. The processing device determines a current value of a pixel unit according to a time difference between the first pulse and the signal.

Abstract: A conductance measurement circuit includes an operation amplifier, a bias current source, a compensation current source, and an output stage circuit. In the operation amplifier, a first input end receives a reference voltage, a second input end is coupled to a tested object, and an output end generates a compensation voltage. The bias current source provides a bias current to a bias end. The compensation current source derives the compensation current from the bias end according to the compensation voltage. The output stage circuit provides a trans-conductance value and an output end equivalent resistance, generates an output current according to the compensation voltage, and generates an output signal according to the output current and the trans-conductance value.

Abstract: The present invention relates to a method for testing a retinal implant. After an implantable device for interfacing with retinal cells is provided, an external stimulus is applied to the implantable device so that the implantable device transmits a first pulse to a processing device through a wireless interface. When a conversion unit is controlled to gradually decrease an output voltage until the implantable device outputs an output voltage lower than a reference voltage, the implantable device transmits a signal different from the first pulse to the processing device through the wireless interface. The processing device determines a current value of a pixel unit according to a time difference between the first pulse and the signal.

Abstract: The present invention discloses a demodulating method for a demodulating circuit. The demodulating method comprises a step of utilizing a wave-shaping voltage step-down circuit to perform a wave-shaping process for a modulating input signal. A separate circuit of modulating input signal is filtering data zero of the modulating input signal and reserving data one of the modulating input signal. A triggering circuit of data recover is used to start the count of data span, until the data count is completed. A data recover circuit is used to recover the data.