Abstract: Embodiments of the present application provide a wireless communication method, a terminal device, and a network device. In the case that both a two-step random access resource and a four-step random access resource are configured on an uplink BWP, a terminal device first selects to perform two-step random access, and the terminal device can determine whether to allow switching from two-step random access to four-step random access, and thus, the flexibility of random access is achieved. The wireless communication method includes in the case that a two-step random access resource and a four-step random access resource are configured on an uplink BWP, a terminal device determines whether to allow switching from two-step random access to four-step random access.

Abstract: The present invention discloses a prediction method for system errors, applied in prediction system predicting system errors of a monitored system. The method comprises steps of: pre-processing training data formed with data points at time slots to generate corresponding features to the data points of each time slot, and extract a frequency-based feature for each time slot according to distribution of clustering, grouping or classification of the corresponding features in the previous time slot of the current time slot. Using machine learning algorithm and taking model building data coming from the corresponding features and frequency-based feature as input to build up a prediction model for predicting and alerting a future error of the monitored system.

Abstract: Disclosed is a random access problem reporting method, comprising: a terminal device determining a random access attempt threshold value according to a random access type supported by an uplink bandwidth part; and when the terminal device fails in random access, the terminal device determining, according to the relationship between the number of instances of sending a random access request and the random access attempt threshold value, whether to report a random access problem. Further disclosed are a terminal device and a storage medium.

Abstract: The present invention discloses a prediction method based on unstructured data, applied in a prediction system comprising an analyzing module and a model-building module to predict future behaviors of a user. The prediction method comprises steps of: with the analyzing module, analyzing a recording file with a natural language processing algorithm to generate at least one feature vector, wherein the recording file is related to a subject behavior in a predetermined observation period, at least one record in a form of unstructured data is stored therein, and the record comprises a time stamp and a recording text; and with the model-building module, using a surprised machine learning algorithm building a model with information corresponding to the feature vector as input for predicting future behaviors of a user, wherein the record is one of query record of domain name system, transaction record of automated teller machine, transaction record of structured query language and literal record.

Abstract: A detective method, applied in a detective system comprising an activity-or-behavior model constructor, for activity-or-behavior model construction and automatic detection of activities of a subject system, comprises steps of using an unsupervised machine learning technique, a Natural Language Processing technique (NLP) and a supervised machine learning technique. As such, an activity-or-behavior model is built for predicting the future behaviors of the subject system and automatically detecting abnormal activities or behaviors of the subject system. The activity-or-behavior model is capable to handle multidimensional sensor data input from a plurality of sensor data streams and incorporate the sensor data values and a selected temporal information about at least one sensor data stream and between different sensor data streams.

Abstract: According to one embodiment of the invention, a method for detecting driving anomalies comprises steps of: with at least one algorithm, processing raw data from On-Board Diagnostics of a car to generate time-series data, with the time series data as input, using an automatic driving behavior separating technology to identify a plurality of driving behaviors; with the driving behaviors as input, using an artificial intelligence technology to build up a driving anomaly detection model without labeling the driving behaviors; and issuing an alarm for driving anomaly identified according to an analyzing result of alarm signature of the driving behaviors.

Abstract: A cleaning tool capable of contracting to be cleaned and expanding to be used includes a mop and a cleaning barrel. The mop includes a mop head and a mop rod connected with the mop head. The mop rod is a rotary mop rod which is able to linearly move upwards or downward and be driven to rotate. A support site used for supporting the mop rod during rotation is arranged in the cleaning barrel. The mop further includes a transformation driving mechanism. The mop head includes movable plates and a base plate. The movable plates are located on the same plane as the base plate and are able to rotate relative to the base plate. A track mechanism is arranged between the movable plates and the base plate. The mop rod is able to rotate relative to the base plate to drive the transformation driving mechanism.

Abstract: An anomaly flow detection device and an anomaly flow detection method thereof are provided.

Abstract: ADMM-NN is an algorithm-hardware co-optimization framework of DNNs using Alternating Direction Method of Multipliers (ADMM). The first part of ADMM-NN is a systematic, joint framework of DNN weight pruning and quantization using ADMM. The second part is a hardware-aware optimization to facilitate hardware-level implementations. ADMM-based weight pruning and quantization accounts for (i) computation reduction and energy efficiency improvement and (ii) performance overhead due to irregular sparsity. Experimental results demonstrate that by combining weight pruning and quantization, the proposed framework can achieve 1,910× and 231× reductions in the overall model size on the LeNet-5 and AlexNet models. Favorable results are also observed on VGGNet and ResNet models. Also, without any accuracy loss, 3.6× reduction in the amount of computation can be achieved, outperforming prior work.

Abstract: A case body structure of a luggage case includes a case top member, a case bottom member and a sidewall member that are independent components. Each of the case top member and the case bottom member is a hard structure. The sidewall member includes a wall plate and a cover plate. The wall plate includes a connecting section, two installation sections, and an installation breach defined and formed by the two installation sections. The cover plate is disposed correspondingly to the installation breach. The cover plate and the wall plate define a hollow cavity. The case top member and the case bottom member are respectively disposed at two ends of the sidewall member to enclose the hollow cavity. The cover plate selectively opens relative to the wall plate to allow an object to be placed into or taken out of the hollow cavity.

Abstract: A cleaning tool capable of contracting to be cleaned and expanding to be used includes a mop and a cleaning barrel. The mop includes a mop head and a mop rod connected with the mop head. The mop rod is a rotary mop rod which is able to linearly move upwards or downward and be driven to rotate. A support site used for supporting the mop rod during rotation is arranged in the cleaning barrel. The mop further includes a transformation driving mechanism. The mop head includes movable plates and a base plate. The movable plates are located on the same plane as the base plate and are able to rotate relative to the base plate. A track mechanism is arranged between the movable plates and the base plate. The mop rod is able to rotate relative to the base plate to drive the transformation driving mechanism.

Abstract: The present invention discloses a method of removing iron ions from a solution containing neodymium, praseodymium, dysprosium and iron, in which glucose is added into an acid solution containing neodymium, praseodymium, dysprosium and iron, at a molar ratio of iron/glucose at 0.2-2, and mixed evenly, and the solution is then hydrothermal treated, and after that an iron-containing precipitate is formed at the bottom, and the residual concentration of iron in the supernatant is less than 20 mg/L, and the retention rate of the rare earth elements is more than 97%.

Abstract: A case body structure of a luggage case includes a case top member, a case bottom member and a sidewall member that are independent components. Each of the case top member and the case bottom member is a hard structure. The sidewall member includes a wall plate and a cover plate. The wall plate includes a connecting section, two installation sections, and an installation breach defined and formed by the two installation sections. The cover plate is disposed correspondingly to the installation breach. The cover plate and the wall plate define a hollow cavity. The case top member and the case bottom member are respectively disposed at two ends of the sidewall member to enclose the hollow cavity. The cover plate selectively opens relative to the wall plate to allow an object to be placed into or taken out of the hollow cavity.

Abstract: A double-sided mop according to this invention, being provided to solve the problems of a conventional mop on poor floor mopping quality, includes a mop pole, a mop head connecting to the mop pole, and a cleaning cloth provided on the surface of mop head. The mop head includes a mounting plate, a first panel, a second panel, a hinged shaft, a universal joint, and an elastic part, in which the mounting plate is provided between the first panel and the second panel, the mounting plate is hinged and connects to the hinged shaft together with the first panel and the second panel, the elastic part applies a force to clamp the first panel and the second panel, the universal joint is installed on the mounting plate by rotation, and the mop pole connects to the universal joint.

Abstract: According to one embodiment of the invention, a detective method, applied in a detective system comprising a activity-or-behavior model constructor, for activity-or-behavior model construction and automatic detection of activities of a subject system, comprising steps of: using an unsupervised machine learning technique to preprocess and analyze raw sensor data obtained from the monitored subject system to generate post data; with the post data as input, using a Natural Language Processing technique (NLP) to discover the activities or behaviors performed by the subject system; and with output data from the NLP technique as input, using a surprised machine learning technique to build an activity-or-behavior model for predicting the future behaviors of the subject system and automatically detecting abnormal activities or behaviors of the subject system; wherein the activity-or-behavior model is capable to handle multidimensional sensor data input from a plurality of sensor data streams and incorporate the senso

Abstract: A flat mop includes a mop head, a bridge seat, a mop handle and a pivot connecting member. The mop head includes a guide track, which is installed with the bridge seat therein and includes at least two positioning points. The bridge seat includes a base, an abutment elastic body installed at the base, a sliding body disposed correspondingly to the abutment elastic body and stopped at one of the positioning points when the bridge seat displaces levelly relative to the mop head to limit the movement of the bridge seat, and two locking portions respectively located at two opposite sides of the base. The mop handle includes a movement space for allowing the bridge seat to move therein, and a positioning portion disposed correspondingly to the movement space and fastening with one of the locking portions after the bridge seat moves relative to the mop handle.

Abstract: A sweeper machine comprises a support frame, a machine body, and a garbage collection case. The support frame includes two fixing arms. The machine body is disposed between and mounted to the two fixing arms. The garbage collection case is inserted to the rear side of the machine body. Each fixing arm includes a driving wheel. The machine body includes a body casing and a roll brush. The roll brush is disposed inside the body casing. The body casing includes an opening. The lower part of the roll brush is exposed from the opening. Two first connection holes are respectively formed on two ends of the body casing. Each driving shaft extends out of the fixing arm and penetrates one connection hole. Two ends of the roll brush are respectively firmly connected with the two driving shafts separately penetrating the two first connection holes.