Abstract: A computer device and a method of identifying whether container behavior thereof is abnormal are provided. The computer device detects container behavior of a container in a time interval, and identifies whether the container behavior of the container is abnormal according to a container behavior identification module, thereby determining whether there is an intrusion. In addition, a decoy container can be installed in the computer device to attract attacking or invading from a third party so as to reduce the risk of the container being attacked, and the container behavior identification module can be updated according to the container behavior of the decoy container.

Abstract: A system and method for simulating facial expression of a virtual facial model are provided. The system stores a plurality of three-dimensional facial models corresponding to a plurality of preset sentiments one-to-one. The system identifies a present sentiment according to an acoustic signal and selects a selected model from the three-dimensional facial models according to the present sentiment, wherein the preset sentiment corresponding to the selected model is same as the present sentiment. The system predicts an upper half face image according to a lower half face image, combines the lower half face image and the upper half face image to form a whole face image, and generates a plurality of feature relationships by matching the facial features of the whole face image with the facial features of the selected model so that a virtual facial model can simulate an expression based on the feature relationships.

Abstract: A user equipment and cell re-selection estimation method thereof for use in a NB-IoT communication system are provided. The user equipment selects a cell re-selection criterion according to a user equipment status, and determines whether a serving RSRP value of a serving base station is greater than a re-selection threshold value based on the cell re-selection criterion. The user equipment performs cell re-selection when the serving RSRP value is greater than the re-selection threshold value. The user equipment does not perform the cell re-selection when the serving RSRP value is not greater than the re-selection threshold value.

Abstract: A dispatching method and system based on multiple levels of steady state production rate in working benches are provided. The dispatching method includes the following steps: receiving a plurality of real-time streaming data regarding a plurality of products being produced by a plurality of productive working benches; grouping the production rate values comprised in each real-time streaming data according to a first data binning technique, so as to produce a first steady state production rate value corresponding to each real-time streaming data; grouping the production rate values comprised in each real-time streaming data according to a second data binning technique, so as to produce a second steady state production rate value corresponding to each real-time streaming data; and determining a dispatching message of a to-be-produced product according to a portion of the first steady state production rate values and a portion of the second steady state production rate values.

Abstract: An apparatus and method for determining a target adjustment route for a preset control condition set of a production line are provided. The apparatus establishes at least one candidate adjustment route for the preset control condition set according to the historical control condition sets. Each candidate adjustment route includes at least one adjustment control condition set arranged in an adjustment order. Each adjustment control condition set is one of the historical control condition sets. Within the same candidate adjustment route, the historical yield related values corresponding to the adjustment control condition sets are all greater than the preset yield related value and increase in the adjustment order. Within the same candidate adjustment route, the numbers of the adjustment control condition(s) included in the adjustment sets increase in the adjustment order. The apparatus selects one of the candidate adjustment route(s) as the target adjustment route.

Abstract: A system and method for identifying application layer behavior are disclosed. In order to detect intrusion into an industrial control system, the system and method determine a current status of application layer behavior of the industrial control system by analyzing a current packet which is propagated between a master device and a slave device in the industrial control system, and identify whether the current status of the application layer behavior is normal according to a normal behavior status list.

Abstract: The present disclosure provides a multimedia interacting system. The multimedia interacting system comprises a first display device, a second display device, and a server. The server communicatively connects with the first display device and the second display device. The server is configured to receive a first playback time that the first display device plays a first tour video; obtain an unsheltered area associated with the first tour video based on the first playback time; obtain a second tour video corresponding to the unsheltered area; and transmit an interacting data to the first display device and the second display device if the second display device plays the second tour video.

Abstract: A monitor apparatus, method, and non-transitory computer readable storage medium thereof are provided. The monitor method is adapted for an electronic computing apparatus, wherein the electronic computing apparatus stores a smart contract and a blockchain ledger of a blockchain system. The monitor method periodically executes the following steps: (a) obtaining a piece of behavior information of a first electronic apparatus at a time point, (b) retrieving, via the smart contract, a plurality of pieces of previous behavior information within a time interval from the blockchain ledger, wherein the time interval is defined by the time point, and each piece of previous behavior information corresponds to one of a plurality of second electronic apparatuses and the first electronic apparatus, (c) determining a legality of the piece of behavior information according to the pieces of previous behavior information, and (d) writing the behavior information into the blockchain ledger.

Abstract: An object detection and tracking method and system are provided. The object detection and tracking method includes the following steps: (i) selecting one of a plurality of frames of a video as a current frame, (ii) searching in an object tracker searching area of the current frame to generate a current object tracker, (iii) searching in each auxiliary tracker searching area of the current frame to individually generate a current auxiliary tracker, (iv) when the current object tracker is located at a block different from the blocks located by the generated object trackers, generating a new auxiliary tracker at the central position of the current frame, and (v) repeating the above steps until all the frames have been processed.

Abstract: An abnormal behavior detection model building apparatus and an abnormal behavior detection model building method thereof are provided. The abnormal behavior detection model building apparatus analyzes the parts of speech of a plurality of program operation sequences in a plurality of program operation sequence data associated with abnormal behaviors to generate a plurality of word vectors and cluster the word vectors. Based on the result of the clustering, the abnormal behavior detection model building apparatus obtains a feature vector of each of the program operation sequence data, and perform a supervised learning for a classification algorithm by using the feature vectors so as to build an abnormal behavior detection model.

Abstract: A charge and discharge control apparatus and method are provided. The charge and discharge control apparatus decides multiple discharge time intervals and multiple discharge power values for an energy storage according to a predicted load curve and a peak shaving threshold and decides multiple charge time intervals and multiple charge power values for the energy storage according to the predicted load curve and a customer base line. The peak shaving threshold is between a contracted capacity and a peak value of the predicted load curve. A difference between the peak value and the peak shaving threshold is not greater than a maximum discharge power of the energy storage. The customer base line is between the contracted capacity and a valley value of the predicted load curve. A difference between the customer base line and the valley value is not greater than a maximum charge power of the energy storage.

Abstract: A user equipment (UE) and a base station (BS) are provided. The UE receives an uplink transmission configuration message indicating a pre-configured radio resource pool and an uplink control configuration message indicating an uplink control radio resource in the pre-configured radio resource pool from the BS. The UE transmits an uplink control message on the uplink control radio resource and transmits an uplink data signal on an uplink data radio resource in the pre-configured radio resource pool so that the BS receives the uplink data signal according to the uplink control message.

Abstract: A transmission apparatus and a transmission data protection method thereof are provided. The transmission apparatus stores a data table, a bloom filter, a first randomization array, a plurality of second randomization arrays and an identifier of each of the second randomization arrays. The bloom filter has a plurality of independent hash functions. The transmission apparatus generates a current original datum according to the data table; inputs the current original datum to the bloom filter as a current input datum of the bloom filter to output a current bloom datum; randomizes the current bloom datum according to the first randomization array to generate a current first randomized datum; randomizes the current first randomized datum according to one of the second randomization arrays to generate a current second randomized datum; and transmits a data signal carrying the current second randomized datum and an identification datum to another transmission apparatus.

Abstract: A user equipment (UE) and a base station (BS) are provided. The UE transmits a first uplink signal to the BS based on a current data repetition transmission parameter. After receiving a dynamic indication message from the BS, the UE generates an updated data repetition transmission parameter according to the dynamic indication message. The UE transmits a second uplink signal to the BS based on the updated data repetition transmission parameter.

Abstract: A base station (BS) and a user equipment (UE) for a mobile communication system are provided. The BS transmits first downlink control information (DCI) indicating a first uplink radio resource to a UE and transmits second DCI indicating a second uplink radio resource to another UE. The second uplink radio resource has an overlapping part with the first uplink radio resource. The BS further transmits third DCI to the UE in response to the overlapping part. The third DCI indicates transmission adjustment information.

Abstract: A model building server and model building method thereof are provided. The model building server stores a model building program having a configuration combination. The model building server randomly generates a plurality of first configuration combination codes for feature categories, model algorithm categories and hyperparameters to set the configuration combination, and runs the model building program based on a first optimization algorithm to determine a first model. According to at least one determined feature category and at least one determined model algorithm category indicated by the configuration combination code corresponding to the first model, the model building server randomly generates a plurality of second configuration combination codes for features, model algorithms and hyperparameters to set the configuration combination, and runs the model building program based on a second optimization algorithm to determine an optimization model.

Abstract: An apparatus, method, and non-transitory computer readable storage medium for generating control instructions based on text are provided. The apparatus analyzes a text with at least one string to generate a text timestamp document, analyzes the at least one string to generate a plurality of pieces of emotion information, a plurality of pieces of action information, and a plurality of pieces of environment information, and decides a plurality of emotion tags and their corresponding timestamps, a plurality of action tags and their corresponding timestamps, and a plurality of environment tags and their corresponding timestamps according to a feature database. The apparatus further generates control instruction(s) and the corresponding timestamp(s) according to the emotion tags and their corresponding timestamps, the action tags and their corresponding timestamps, and the environment tags and their corresponding timestamps.

Abstract: A display system for an issue comprises an input unit, a display unit and an processing unit. The input unit receives an initial keyword corresponding to an issue. The display unit displays at least a derivative issue generated from the issue during a time period according to time-based characteristics. The processing unit coupled to the input unit and the display unit obtains tags of subject contents of web pages, and obtains a present keywords group according to co-occurrence correlation of the tags. The processing unit analyzes the correlation between the present keywords calculated based on social voice, analyzing overlap rate for the present keywords compared with the initial keywords, and compares correlation between the present keywords with correlation between the initial keywords calculated based on social voice, in order to determine whether at least one of the derivative issue is generated.

Abstract: A server and a cloud computing resource optimization method thereof for big data cloud computing architecture are provided. The server runs a dynamic scaling system to perform the following operations: receiving a task message; executing a profiling procedure to generate a profile based on an to-be-executed task recorded in the task message; executing a classifying procedure to determine a task classification of the to-be-executed task; executing a prediction procedure to obtain a plurality of predicted execution times corresponding to a plurality of computing node numbers, a computing node type and a system parameter of the to-be-executed task; executing an optimization procedure to determine a practical computing node number of the to-be-executed task; and transmitting an optimization output message to a management server to make the management server allocate at least one data computing system to execute a program file of the to-be-executed task.

Abstract: A method for transmitting reference signals includes: determining, by a wireless transmitting device, a first vector set used for calculating a first vector subspace that includes a channel frequency response vector corresponding to a subcarrier; calculating, by the wireless transmitting device, a second vector set including several second vectors derived from performing dot product operations to each vector in the first vector set with a conjugate vector of each vector in the first vector set; calculating, by the wireless transmitting device, a null space of a second vector subspace spanned by the second vector set and determining, by the wireless transmitting device, a cover code from the null space; and transmitting a first reference signal and a second reference signal which is a dot product of the first reference signal and the cover code on the subcarrier from the wireless transmitting device to a wireless receiving device.