Abstract: Power flow in an electric power network is optimized during multiple time periods of operation of the electric power network by solving an optimization problem represented by an objective function by first initializing variables and constraints of a branch and bound (BB) tree, wherein nodes in the BB tree represent feasible regions of the optimization problem. Upper and lower bounds on the objective function are solved using the BB tree. A lowest upper bound and a lowest upper bound are updated. If difference between the lowest lower bound and the lowest upper bound is less than a threshold, the power flow is outputted based on the lowest lower bound and the lowest upper bound.

Abstract: A unit commitment problem is solved for a set of generators with a set of configurations having a set of 2N.T schedules, wherein N is a number of generators i and T is a number of decision time steps. A reduced set of configurations is determined, and then a functional metric to measure a similarity of all possible pairs of the configurations is defined. Dynamic programming is applied to the reduced set of configurations using the similarity metric to determine an optimal configuration.

Abstract: A heating, ventilation and air-conditioning (HVAC) system for a building is optimized while maximizing a comfort of occupants and minimizing energy consumption. The building is modeled as a network of nodes and edges, wherein the nodes represent rooms, and the edges represent walls. Dynamics of temperatures and humidity in the rooms and the temperature of the walls and the building are modeled using differential equations and the network. The comfort of the occupants is modeled by a predicted mean vote (PMV). The minimizing is formulated as an optimal control problem, which is discretized using an integration technique to obtain a finite dimensional optimization problem. Then, the finite dimensional optimization problem is solved using sparse linear algebra until convergence.

Abstract: An optimal conditional operational schedule for a set of power generators is determined by constructing states and transitions of a factored Markov decision process (fMDP) from a target electrical demand and generator variables. A cost function for the fMDP is constructed based on the electrical demand, the generator variables, and a risk coefficient. Then, the fMDP is solved to obtain the optimal conditional operational schedule.

Abstract: A continuous dynamical system is converted to a Markov decision process (MDP) with discrete states. A predetermined number of continuous states of the continuous system is selected, wherein each continuous state corresponds to one discrete state of the MDP. Delaunay triangulation is applied to the continuous states to produce a set of triangles, wherein vertices of each triangle represent the continuous states. For each discrete state, a next discrete state y=ƒ(x, a) is determined, wherein x represents the continuous state corresponding to the discrete state, a is a control action, and ƒ is a non-linear transition function for the continuous. A particular triangle containing the next discrete state y is identified, and the next discrete state y is expressed as probabilities of transitioning to the discrete states corresponding to the continuous states x represented by the vertices of the particular triangle.

Abstract: A unit commitment problem is solved for a set of generators with a set of configurations having a set of 2N.T schedules, wherein N is a number of generators i and T is a number of decision time steps. A reduced set of configurations is determined, and then a functional metric to measure a similarity of all possible pairs of the configurations is defined. Dynamic programming is applied to the reduced set of configurations using the similarity metric to determine an optimal configuration.

Abstract: An average environmental condition for a specified target date and time is determined by indexing a database of time series data to retrieve the environment condition for each day and time where an orbital position of the earth with respect to the sun is nearest to the orbital position of the earth on the target date and time. The average environmental condition is then determined from the retrieved environmental conditions.

Abstract: Embodiments of the invention describe a method for classifying data in a system with limited memory. The method applies exemplar learning (EL) procedures to a training data set to produce an exemplar data set adapted to the size of the memory. The EL procedure is selected form a group consisting of an entropy based exemplar learning (EBEL) procedure and an AUC-based exemplar learning (ABEL) procedure. The exemplar data set is used to classify acquired by the system data.

Abstract: A continuous dynamical system is converted to a Markov decision process (MDP) with discrete states. A predetermined number of continuous states of the continuous system is selected, wherein each continuous state corresponds to one discrete state of the MDP. Delaunay triangulation is applied to the continuous states to produce a set of triangles, wherein vertices of each triangle represent the continuous states. For each discrete state, a next discrete state y=f(x, a) is determined, wherein x represents the continuous state corresponding to the discrete state, a is a control action, and f is a non-linear transition function for the continuous. A particular triangle containing the next discrete state y is identified, and the next discrete state y is expressed as probabilities of transitioning to the discrete states corresponding to the continuous states x represented by the vertices of the particular triangle.

Abstract: An average environmental condition for a specified target date and time is determined by indexing a database of time series data to retrieve the environment condition for each day and time where an orbital position of the earth with respect to the sun is nearest to the orbital position of the earth on the target date and time. The average environmental condition is then determined from the retrieved environmental conditions.

Abstract: A method and system determine peak power consumption over time by a bank of elevator for servicing a set of passenger hall calls and delivery requests, and selecting elevator schedules that keep peak power consumption below a predetermined threshold. For each car in response to receiving a hall call, a set of all possible paths to service all hall calls assigned to the car are determined, in which each path includes a set of all possible segments. A peak power consumption for each possible segment is also determined. The peak power consumptions for the set of all possible segments for each time instant are added to determine a total peak power consumption for each time instant, and a particular path is selected as a schedule to operate the bank of elevator cars, if the total peak power consumption for any instant in time while operating according to the selected schedule is below a predetermined threshold.

Abstract: Embodiments of the invention describe a method for classifying data in a system with limited memory. The method applies exemplar learning (EL) procedures to a training data set to produce an exemplar data set adapted to the size of the memory. The EL procedure is selected form a group consisting of an entropy based exemplar learning (EBEL) procedure and an advanced broadband enabled learning (ABEL) procedure. The exemplar data set is used to classify acquired by the system data.

Abstract: Embodiments of the invention describe a computer-implemented method for extracting data from web pages. During a learning stage, the embodiments receive a template web page represented by a template Document Object Model (DOM) and select a record node, which is a root node of a sub-tree of the template DOM that contains data to be extracted. After that, a record node sub-tree and data field sub-paths are stored in a memory, wherein the record node is a root node of the record node sub-tree, and the data field sub-paths are relative paths of the template DOM from the record node to data field nodes. During the extraction stage, a web page represented by a DOM-tree is received and a matched sub-tree of the DOM-tree according to a structure of the record node sub-tree is identified. Next, data from the matched sub-tree according to the data field sub-paths are extracted.

Abstract: A moving object is classified by transmitting, by a linear array of transmit antenna elements, a microwave into a surveillance area. A scattered microwave backprojected from a moving object is received by a linear array of receive antenna elements. Features are extracted from the scattered microwave related to a spiral evolution of the scattered microwave. The moving object is then classified as one of a set of possible classes according to the extracted features, and an alarm signal can be generated indicating the selected class.

Abstract: A moving object is classified by transmitting, by a linear array of transmit antenna elements, a microwave into a surveillance area. A scattered microwave backprojected from a moving object is received by a linear array of receive antenna elements. Features are extracted from the scattered microwave related to a spiral evolution of the scattered microwave. The moving object is then classified as one of a set of possible classes according to the extracted features, and an alarm signal can be generated indicating the selected class.

Abstract: A method detects a change in a stream of samples acquired by a sensor. A stream of samples acquired by a sensor over time is stored sequentially in a buffer in which an oldest sample is discarded and a newest sample is stored when the buffer is full such that the buffer forms a window of samples sliding forward in time. For each new sample, the buffer is partitioned into all possible pairs of contiguous sub-windows of samples including a first sub-window and a second sub-window such that the newest sample is stored in the second sub-window of the pair. A difference is determined between the first and second sub-window of each pair of the contiguous sub-windows of samples, and a maximum difference is assigned as a merit score. A change in the stream of samples is signaled if the merit score is greater than a predetermine threshold. The change can be abrupt or gradual.

Abstract: A method detects a change in a stream of samples acquired by a sensor. A stream of samples acquired by a sensor over time is stored sequentially in a buffer in which an oldest samples is discarded and a newest sample is stored when the buffer is full, such that the buffer forms a window of samples sliding forward in time. For each new sample, the buffer is partitioned into all possible pairs of contiguous sub-windows of samples including a first sub-window and a second sub-window such that the newest sample is stored in the second sub-window of the pair. A difference is determined between the first and second sub-window of each pair of the contiguous sub-windows of samples, and a maximum difference is assigned as a merit score. A change in the stream of samples is signaled if the merit score is greater than a predetermine threshold. The change can be abrupt or gradual.

Abstract: A method schedules cars of an elevator system, the elevator system including a set of cars, and a set of hall calls. For each car, a waiting time is determined independently if the hall call is the only hall call assigned to the car. For each car, a mutual delay ?W(h|g) is determined for each possible pair of unassigned hall calls h and assigned hall calls g. The waiting time and mutual delays are summed. Then, the assignments are made to the set of cars so that the sum is a minimum.

Abstract: A business process is modeled by determining, for each possible pair of tasks in a trace of executions of N tasks corresponding to a business process, whether the tasks in each pair have an identical relation condition with every other task in the trace. A pair of tasks is identified as child task nodes of an associated parent relation node if the identical relation condition is true. A renderable workflow tree is constructed from all identified child task of the associated corresponding parent relation, nodes.

Abstract: A method schedules cars of an elevator system. Each possible assignment of a set of hall calls to a set of cars is represented by a solution vector maintained as a node in a search tree. Each solution vector is evaluated using an ESA-DP process according to an immediate policy to determine initially a best solution. A branch-and-bound process is applied to each solution vector using the initial best solution and the search tree to determine a globally optimal solution for scheduling the cars according to a reassignment policy.