201 results about "Observation period" patented technology

Among other things, one or more techniques and/or systems are disclosed for identifying a proximate beacon to a mobile device. One or more first received signal strengths (RSSs), relative to the mobile device, may be received and used to determine a first average signal strength (RSS) and a first average RSS deviation for a first beacon during an observation period. An average RSS deviation for the observation period can be determined using the first average RSS deviation (e.g., and other average RSS deviations). If the average RSS deviation meets a desired deviation threshold, the first beacon may be identified as the proximate beacon. In this manner, if the user of the mobile device consents to the same, the user may be provided with relevant information (e.g., advertisements) on the mobile device while in a locale (e.g., store) corresponding to the (known) location of the beacon, for example.

The invention relates to a target localization and tracking system and a method. The system comprises a plurality of cluster localization modules and command control modules, each cluster localizationmodule comprises a plurality of sensor nodes and cluster head nodes, and each cluster head node comprises an initialization module, a particle filtration module, a particle weight calculation module,a re-sampling determination module and an estimation target state module. The method which combines Kalman and particle filtration is adopted for realizing the passive localization of a target, and the computation speed is far lower than the particle filtration method on the basis of realizing high-precision localization; the localization and the track of the target is finally realized by adopting multiple sensors and being based on the observation of the direction of the target, thereby being capable of overcoming the constraint that the traditional machine-mounted or ship-mounted single station system must carry out motorization during the observation period, having no need of observing the motorization of a platform, improving the flexibility of target localization, greatly increasingthe area of a region of target monitoring localization, avoiding the shortcoming of existence of localization blind regions and having very high effectiveness, accuracy and feasibility.

A method for dynamically allocating network resources while transferring multimedia at variable bit-rates in a network extracts first content features from the multimedia to determine renegotiation points and observation periods. Second content features and traffic features are extracted from the multimedia bit stream during the observation periods. The second content features and the traffic features are combined in a neural network to predict the network resources to be allocated at the renegotiation points.

A method for multi-user detection includes receiving a complex input signal due to a superposition of waveforms encoding symbols in a real-valued constellation, which are transmitted respectively by a plurality of transmitters in a common frequency band. The complex input signal is sampled at sampling intervals over the duration of an observation period to provide a sequence of complex samples. The sequence of complex samples is processed to determine soft decision values corresponding to the symbols transmitted by the plurality of the transmitters in the observation period, while constraining the soft decision values to be real values. The soft decision values are then projected onto the constellation to estimate the transmitted symbols.

A terminal synchronization method and apparatus for use in a wireless communication system are provided. A synchronization method includes configuring, at the terminal, a synchronization signal reference time depending on whether a synchronization signal is received in an initial observation period as long as at least two frames, monitoring to receive the synchronization signal in an alternation period of a transmission period and a reception period, the alternation period following the initial observation period, updating the reference time depending on whether the synchronization signal is received in the reception period, transmitting the synchronization signal at the updated reference time in the transmission period, and updating the reference time depending on whether the synchronization signal is received in a dedicated observation period following the alternation period. The synchronization apparatus and method are advantageous in that synchronization is obtained without assistance of a base station, an Access Point (AP), etc.

The invention relates to an application layer distributed denial of service (DDoS) attack detection method and defensive system and relates to network safety, in particular to application layer DDoS attack detection and defend. The invention provides a detection method and the defensive system based on user click sequence forecasting. Firstly, a page table uniform resource locator (URL) of a website is extracted, a clustering algorithm is utilized to conduct clustering, page table classification Vj and a user click sequence of the website are obtained, then the user click sequence is utilized to construct a random wandering image, a next observation period click sequence of a user is calculated through a process of random wandering, at last, similarity of a predict sequence and a click sequence is calculated, and abnormity of the user click sequence is judged through training threshold. The application layer DDoS attack detection method and defensive system can effectively detect attacking of an application layer, particularly stimulate an attack request of normal user behavior, and can be widely applied to safe defend of a data center website server.

The invention discloses a method and apparatus for obtaining active user data of target product. The method comprises: obtaining the search data in a plurality of periods of a target product in a third-party data platform; determining the correlation between the search data and the newly increased user number in the same period of a basic product so as to determine the predicted newly increased user number in the same period of the target product; according to the user remaining rate of the basic product in previous periods, fitting a remaining curve; based on the remaining curve and the newly increased user number in the observation period, obtaining the predicted active user number of the target product in the observation period; combining a preset algorithm, obtaining the active user number of the target product in the observation period; based on the correlation among the remaining user number, the newly increased user number, the active user number and the daily active user number, creating a daily active user number prediction model; and combining the already known corresponding data of the target product to output the daily active user number of the target product so as to realize the quantified monitoring on the daily active user number. With the method proposed by the invention, it is possible to realize the quantified monitoring on the daily active user number.

A signal processing unit in a radar device calculates a change amount Y (=log(P)−log(Pb)) between a power P of a current arrival echo and a power of a previous arrival echo arrived before an observation period T_SW. A memory unit in the radar device stores, every type of objects, a probability distribution of the change amount Y calculated from the arrival echo from the object. On the basis of the calculated change amount Y and the probability distribution, the signal processing unit determines a probability Pr to obtain the change amount Y every type of object, and determines that the object having the maximum probability Pr is the object which transmits the current arrival echo.

A positioning information distribution system for distributing positioning information through a data network is described. In one embodiment, the system distributes satellite information from a global positioning system (GPS). The system includes an information processing station connected to a data network accessible by wireless communication, a receiving station including a GPS receiver, and a mobile unit including a GPS receiver and a wireless receiver. The information processing station collects GPS satellite information from the receiving station and transmits the satellite information to the mobile unit using wireless communication. Alternately, a network of receiving stations are provided. The mobile unit can obtain the satellite information from the information processing station for determining its measured position, even when the mobile unit is roaming in an urban area and is not able to observe the GPS satellites for the lengthy observation period needed to acquire the satellite information itself.

The invention discloses a credit monitoring and scoring method and system based on a behavior model. The method comprises the following steps: obtaining the original data of an account in an observation period; carrying out feature extraction on the original data of the account to obtain a prediction variable; according to the prediction variables, using the machine learning algorithm for modeling, and obtaining the prediction model of the response variables and the prediction variables; predicting an account with repayment performance according to the predicting model to obtain a default probability in the predicting period of the account; calculating the behavior score of the account according to the default probability of the account during the prediction period. The invention can increase the data changing speed, improve the applicability and generalization, and carry out accurate behavior scoring on the account.

A method of generating a dynamic call graph of an application is disclosed. The method includes collecting information on what program code pages are accessed during each sampling period, defining parts of an executable program code which are accessible during each sampling period according to the collected information, defining a set of functions within the defined parts of the executable program code, generating dynamic call graphs using the defined set of functions for each sampling period, and generating dynamic call graphs for an observation period by combining accurate dynamic call graphs of each sampling period.

An average color bar (507) representing the entire imaging period of images captured by the capsule endoscope in time series is displayed. The checked images in all captured images are displayed in a list in the checked image display column (504B), and it is calculated which time in the imaging period each checked image corresponds to, and the scale of the average color bar (507) is used to set the average color bar (507). (507) mark and display with numbers corresponding to each inspection image. As a result, the searchability of the image obtained by shooting the inside of the body is improved, and it is possible to easily identify which organ the displayed image is.

The invention discloses a reservoir water temperature change rule prototype observation method. The reservoir water temperature change rule prototype observation method is characterized by comprising a time point distribution method of reservoir water temperature change rule prototype observation and a space point distribution method of reservoir water temperature change rule prototype observation. According to method, the long-serial and large-scale prototype observation of the reservoir water temperature change rule is considered, and the synchronous link of water temperature observation periods of different hydrological, ecological and meteorological processes of a reservoir, and effective coverage of longitudinal and vertical water temperature prototype observation point location of water temperature characteristic changes of a mainstream and tributaries of the reservoir are achieved. The systematicness, representativeness and reliability of a water temperature prototype observation result are guaranteed. The reservoir water temperature change rule prototype observation method has important significance on improving the technical level and result quality of the national water temperature prototype observation work, overcoming the defects of the prior art, further improving the working levels of the national reservoir water temperature change mathematical model research, the empirical formula improvement and the computing software development research thereof and promoting the technological development of the industry.

The invention belongs to the technical field of traffic management and relates to a method for predicting road traffic flow based on global positioning system (GPS) data. The method comprises the following steps of: dividing time during which the traffic flow is required to be predicted and monitored in a day into different periods of time; in each observation period of time, monitoring the positions of taxis loaded with vehicle-mounted GPSs to acquire GPS position data in each period of time, monitoring road traffic flow data in each period of time, and counting; calculating the speed corresponding to the position of each vehicle in the GPS position data at each historical moment and the average speed of all vehicles on the whole main road; and monitoring real-time position data of each vehicle in each period of time in real time, calculating the instantaneous speed of each vehicle and the average traffic flow speed of the road, predicting future traffic flow data, and judging whether traffic jams occur or not. By the method, the capital and manpower investment of road detection equipment can be reduced, and a traffic congestion problem can be solved in an auxiliary mode.