Abstract: An imaging tool, including: a drive shaft including a proximal end and a distal end; an optical waveguide including a proximal end and a distal end, the proximal end of the optical waveguide being disposed within the proximal end of the drive shaft, and the distal end of the optical waveguide extending beyond the distal end of the drive shaft; and an optical probe head coupled to the distal end of the optical waveguide.

Abstract: A multifunctional floating breakwater includes: a plank platform, a first buoy, a second buoy, a first wave baffle, a second wave baffle, a first arc breast wall, a second arc breast wall, upper inclined supports, lower inclined supports and a net cage. The multifunctional floating breakwater integrates a floating breakwater and a wave-energy power generation device, which can not only maintain good stability of the water surface in a harbor, but also generate electric energy, and allow for aquaculture and other activities as well, and has advantages of being movable and not limited by water depth and geology. In addition, the invention has a simple structure, easy production and maintenance, no pollution to the marine environment and therefore wide application prospects.

Abstract: A measuring device for wave energy conversion performance of a comb-typed permeable breakwater with arcuate walls is provided. The measuring device includes four parts: the comb-type permeable breakwater with arcuate walls, a wave height measuring instrument and pressure sensor fixing and adjusting apparatus, a wave height measuring instrument data collecting and processing apparatus and a pressure sensor data collecting and processing apparatus. The comb-typed permeable breakwater includes combined arc-shaped caissons, partition plates, a back plate, a fixing bottom plate and fixing screws. The wave height measuring instrument data collecting and processing apparatus processes data collected by a wave height measuring instrument and outputs for display. The pressure sensor data collecting and processing apparatus analyzes data collected by a pressure sensor and outputs for display. The measuring device has a stable structure, convenient operation and high experimental accuracy.

Abstract: A multifunctional floating breakwater includes: a plank platform, a first buoy, a second buoy, a first wave baffle, a second wave baffle, a first arc breast wall, a second arc breast wall, upper inclined supports, lower inclined supports and a net cage. The multifunctional floating breakwater integrates a floating breakwater and a wave-energy power generation device, which can not only maintain good stability of the water surface in a harbor, but also generate electric energy, and allow for aquaculture and other activities as well, and has advantages of being movable and not limited by water depth and geology. In addition, the invention has a simple structure, easy production and maintenance, no pollution to the marine environment and therefore wide application prospects.

Abstract: A measuring device for wave energy conversion performance of a comb-typed permeable breakwater with arcuate walls is provided. The measuring device includes four parts: the comb-type permeable breakwater with arcuate walls, a wave height measuring instrument and pressure sensor fixing and adjusting apparatus, a wave height measuring instrument data collecting and processing apparatus and a pressure sensor data collecting and processing apparatus. The comb-typed permeable breakwater includes combined arc-shaped caissons, partition plates, a back plate, a fixing bottom plate and fixing screws. The wave height measuring instrument data collecting and processing apparatus processes data collected by a wave height measuring instrument and outputs for display. The pressure sensor data collecting and processing apparatus analyzes data collected by a pressure sensor and outputs for display. The measuring device has a stable structure, convenient operation and high experimental accuracy.

Abstract: This disclosure relates to industrial data services, data modeling and applications for controlling an industrial operation. In one implementation, a platform is disclosed for allocating a data modeling request to a collaborative group of experts based on a two-dimensional data modeling flow data structure and a multilayer resource allocation graph to obtain a data model for controlling the industrial operation. The two-dimensional data modeling flow data structure and the multilayer resource allocation graph are established from an industrial graph knowledgebase using various data analytics and machine learning techniques.

Abstract: An iterative classifier for unsegmented electronic documents is based on machine learning algorithms. The textual strings in the electronic document are segmented using a composite dictionary that combines a conventional dictionary and an adaptive dictionary developed based on the context and nature of the electronic document. The classifier is built using a corpus of training and testing samples automatically extracted from the electronic document by detecting signatures for a set of pre-established classes for the textual strings. The classifier is further iteratively improved by automatically expanding the corpus of training and testing samples in real-time when textual strings in new electronic documents are processed and classified.

Abstract: A customized industrial graph knowledge base for an industrial operation includes a graph database storing nodes of multiple dimensions predefined according to the nature and characteristics of the industrial operation. The nodes are extracted from baseline, domain-specific, and implementation specific industrial knowledge data sources using various analytics for structured and unstructured data. The customized industrial graph knowledge base further includes edges representing relationships between nodes that are either inter-dimensional or intra-dimensional. The importance of each node to the industrial operation is further quantified using a graph model and is included in the graph database as a composite filtering parameter.

Abstract: Direct measurement and simulation of real-time production rates of chemical products in complex chemical plants is complex. A predictive model developed based on machine learning algorithms using historical sensor data and production data provides accurate real-time prediction of production rates of chemical products in chemical plants. An optimization model based on machine learning algorithms using clustered historical sensor data and production data provides optimal values for controllable parameters for production maximization.

Abstract: The present disclosure relates to system, method and apparatuses for identifying load volatility of a power customary and a tangible computer readable medium therefor. In an embodiment of the present disclosure, the system comprises at least one processor; and at least one memory storing computer executable instructions. The at least one memory and the computer executable instructions are configured to, with the at least one processor, cause the system to determine boundary points for splitting a load curve of a power customer automatically, through performing density-based spatial clustering on data points of the load curve of the power customer; and detect tendency turning points of the load curve by means of the determined boundary points, so as to identify the load volatility of the power customer.

Abstract: A customized industrial graph knowledge base for an industrial operation includes a graph database storing nodes of multiple dimensions predefined according to the nature and characteristics of the industrial operation. The nodes are extracted from baseline, domain-specific, and implementation specific industrial knowledge data sources using various analytics for structured and unstructured data. The customized industrial graph knowledge base further includes edges representing relationships between nodes that are either inter-dimensional or intra-dimensional. The importance of each node to the industrial operation is further quantified using a graph model and is included in the graph database as a composite filtering parameter.

Abstract: This disclosure relates to industrial data services, data modeling and applications for controlling an industrial operation. In one implementation, a platform is disclosed for allocating a data modeling request to a collaborative group of experts based on a two-dimensional data modeling flow data structure and a multilayer resource allocation graph to obtain a data model for controlling the industrial operation. The two-dimensional data modeling flow data structure and the multilayer resource allocation graph are established from an industrial graph knowledgebase using various data analytics and machine learning techniques.

Abstract: A system and a method for selecting controllable parameters for equipment operation safety are provided. The system includes a memory, a display, a communication interface, and circuitry in communication with the memory, the communication interface and the display, the circuitry is configured to: identify a key safety monitoring index (KSMI) for the equipment operation safety, select a first subset of the controllable parameters according to a first regression, select a second subset of the controllable parameters from the first subset of the controllable parameters to predict the KSMI, predict the equipment operation safety for a future time, determine a safety range, and transmit the controllable parameters to be set for the equipment operation safety according to the determined safety range.

Abstract: The present disclosure relates to system, method and apparatuses for determining parameter settings for a power generation system and a tangible computer readable medium therefor. In an embodiment of the present disclosure, the system comprises at least one processor; and at least one memory storing computer executable instructions. The at least one memory and the computer executable instructions are configured to, with the at least one processor, cause the system to: divide historical power related data of the power generation system into a plurality of power load segments based on typical power load values and the number of the historical power related data; identify feasible parameter ranges for each of the plurality of power load segments; and determine optimal parameter settings for each of the plurality of power load segments, based on the identified feasible parameters ranges and correlations between system energy efficiency and relative parameters of each of the plurality of power load segments.

Abstract: Direct measurement and simulation of real-time production rates of chemical products in complex chemical plants is complex. A predictive model developed based on machine learning algorithms using historical sensor data and production data provides accurate real-time prediction of production rates of chemical products in chemical plants. An optimization model based on machine learning algorithms using clustered historical sensor data and production data provides optimal values for controllable parameters for production maximization.

Abstract: The present disclosure relates to systems and methods for measuring reading performance.

Abstract: A method and a computing device for adjusting the display of an image, where the method includes: obtaining, during a process of playing an image, a finger gesture for processing the image; determining whether the finger gesture is a finger gesture for adjusting the image, the adjusting including rotating or flipping; and adjusting the image according to the finger gesture if the finger gesture is a finger gesture for adjusting the image. After it is determined that a finger gesture for processing an image is a finger gesture for adjusting the image, the image is adjusted according to the finger gesture, and during this process, a touch screen device body does not need to be moved, which is a convenient implementing manner; moreover, the image can be rotated or flipped, supporting different operations on the image.

Abstract: A system and a method for selecting controllable parameters for equipment operation safety are provided. The system includes a memory, a display, a communication interface, and circuitry in communication with the memory, the communication interface and the display, the circuitry is configured to: identify a key safety monitoring index (KSMI) for the equipment operation safety, select a first subset of the controllable parameters according to a first regression, select a second subset of the controllable parameters from the first subset of the controllable parameters to predict the KSMI, predict the equipment operation safety for a future time, determine a safety range, and transmit the controllable parameters to be set for the equipment operation safety according to the determined safety range.

Abstract: An iterative classifier for unsegmented electronic documents is based on machine learning algorithms. The textual strings in the electronic document are segmented using a composite dictionary that combines a conventional dictionary and an adaptive dictionary developed based on the context and nature of the electronic document. The classifier is built using a corpus of training and testing samples automatically extracted from the electronic document by detecting signatures for a set of pre-established classes for the textual strings. The classifier is further iteratively improved by automatically expanding the corpus of training and testing samples in real-time when textual strings in new electronic documents are processed and classified.

Abstract: A method and system for analyzing equipment degradation for maintaining the equipment are provided. The method and system receive and store equipment and sensor data associated with operational equipment, generate a display signal to display a relationship analysis window, a residual error window, a performance condition window, and a maintenance trigger window, and evaluate a coordinated relationship between the equipment sensor data and the environmental data, determine residual errors and determine a Historical Health Condition Index (HHCI) for the operational equipment and generate a Future Health Condition Index (FHCI) from the HHCI, and generate an equipment maintenance trigger for the operational equipment by establishing a trigger threshold for maintenance.