Abstract: A solar powered cooler for a smart device such as a smartphone or smart tablet is provided, optionally with a device holder and a solar powered charger unit. The cooler may include an upper fan casing, an optional bottom fan casing, smart device holder, and an air passage formed between the upper fan casing and the smart device holder. The heat dissipation structure of the smart device holder for holding a smart device is disposed in the close proximity space of the smart device to provide a good heat dissipation effect by way of active cooling (forced convection) and passive cooling (natural convection) so as to enhance the heat dissipation performance of the smart device.

Abstract: A solar powered cooler for a smart device such as a smartphone or smart tablet is provided, optionally with a device holder and a solar powered charger unit. The cooler may include an upper fan casing, an optional bottom fan casing, smart device holder, and an air passage formed between the upper fan casing and the smart device holder. The heat dissipation structure of the smart device holder for holding a smart device is disposed in the close proximity space of the smart device to provide a good heat dissipation effect by way of active cooling (forced convection) and passive cooling (natural convection) so as to enhance the heat dissipation performance of the smart device.

Abstract: A solar powered cooler for a smart device such as a smartphone or smart tablet is provided. The cooler may include an upper fan casing, an optional bottom fan casing, smart device holder, and an air passage formed between the upper fan casing and the smart device holder. Also provided are one or more cooling fans drawing air into the air passage along a substantially vertical direction. One or more solar panels allows the cooler to harvest solar energy and deliver electric power to the one or more fans, or motors thereof. The solar panels are connected by one or more, e.g., a pair of, connector cables to the motor. The cooler may cool an entire bottom surface of the smart device using one or more cooling fans.

Abstract: A solar powered cooler for a smart device such as a smartphone or smart tablet is provided. The cooler may include an upper fan casing, an optional bottom fan casing, smart device holder, and an air passage formed between the upper fan casing and the smart device holder. Also provided are one or more cooling fans drawing air into the air passage along a substantially vertical direction. One or more solar panels allows the cooler to harvest solar energy and deliver electric power to the one or more fans, or motors thereof. The solar panels are connected by one or more, e.g., a pair of, connector cables to the motor. The cooler may cool an entire bottom surface of the smart device using one or more cooling fans.

Abstract: A method for discovering, locating, indexing, ranking, and clustering multimedia service providers using hierarchical communication topologies resulting in the retrieval of multimedia files by optimizing parameter sets to efficiently retrieve multimedia files. The method creates a plurity of individual parameter sets, the parameter sets comprising information sharing object parameters for describing structures, search query sets, and dynamic search spaces to be optimized and setting the population of individuals as a population of memes. The parameter sets are initially created using a hierarchical ordering based on the priority and diversity of data transmissions to build and extend individual router tables for a plurity of servers by said client machines.

Abstract: A method for a system that indexes, ranks, and clusters multimedia documents using organizing means, scoring means, and stochastic means that optimizes parameter sets comprising of object parameters. The method creates a plurality of individual parameter sets, the parameter sets comprising information sharing system object parameters for describing a model, structures, shape, design, process, search query sets, and dynamic search spaces to be optimized using selective variations, constructive variations, clustering variations, and stochastic variations. The optimizations of the search space are guided by document query terms of the search query set object parameter. The search space is defined in terms of the terminal set, function set, and fitness measures (NN computations).

Abstract: An information sharing system to solve one or more information retrieval problems is concerned with the novel, hybrid use of the stochastic optimization techniques of evolutionary computation (EC) search strategies for computer information systems such as search engines, or service oriented architectures (SOAs). The information sharing system uses stochastic optimization agents for task distribution and communication when foraging a system of stored documents for information, assessing the computational effort required to retrieve information in the form of stored documents, sharing information among stochastic optimization agent processes and processors, and extracting knowledge from the information. The field of evolutionary computation encompasses stochastic optimization techniques, such as randomized search strategies, in the form of evolutionary strategies (ES), evolutionary programming (EP), genetic algorithms (GA), classifier systems, evolvable hardware (EHW), and genetic programming (GP).

Abstract: A method for a system that indexes, ranks, and clusters multimedia documents using assessment means, scoring means, stochastic means, and organizing means that optimizes parameter sets comprising of object parameters. The method creates a plurality of individual parameter sets, the parameter sets comprising information sharing system object parameters for describing a model, structures, shape, design, process, search query sets, and dynamic search spaces to be optimized using selective variations, constructive variations, clustering variations, and stochastic variations. The optimizations are guided by document query terms of the search query set object parameter that are initially optimized by assessment means, scoring means, stochastic means, and organizing means that lead to selective variations, constructive variations, clustering variations, and stochastic variations of the parameter sets.

Abstract: A method is described for applying distributed stochastic optimization techniques of evolutionary computation using a plurality of servers and a plurality of clients machines being connected via a computer network such as the Internet. The stochastic optimization techniques of evolutionary computation seek to optimize a populations of individuals against one or more predetermined fitness criteria when applied to solving solve the network routing problem coupled with one or more information retrieval problems. The field of evolutionary computation encompasses stochastic optimization techniques, such as randomized search strategies, in the form of evolutionary strategies (ES), evolutionary programming (EP), genetic algorithms (GA), classifier systems, evolvable hardware (EHW), and genetic programming (GP). The stochastic optimization component objectives of the multimedia resource discovery and retrieval systems includes maximization of resource utilization and of overall LAN throughput.

Abstract: A method for a system that indexes, ranks, and clusters multimedia documents using organizing means, scoring means, and stochastic means that optimizes parameter sets comprising of object parameters. The method creates a plurality of individual parameter sets, the parameter sets comprising information sharing system object parameters for describing a structures, search query sets, and dynamic search spaces to be optimized and setting the population of individuals as a population of memes. These parameters are required to filter, organize, and index any large-scale data set—information stored on a single computer, a local area network (LAN), and a wide area network (WAN) that encompasses the whole Internet—that may consists of constantly fluctuating information content over relatively short periods of time.

Abstract: A method for a system that indexes/ranks/clusters multimedia documents using hybrids of information retrieval algorithms and the stochastic optimization techniques of evolutionary computation (EC) that optimizes parameter sets comprising of object parameters. The method creates a plurality of individual parameter sets, the parameter sets comprising information sharing system object parameters for describing a model, structure, shape, design, process, search query set, or dynamic search space to be optimized and setting the initial population as a current (static parent) population.

Abstract: A method is described for applying distributed stochastic optimization techniques of evolutionary computation using a plurality of servers and a plurality of clients machines being connected via a computer network such as the Internet. The stochastic optimization techniques of evolutionary computation seek to optimize a populations of individuals against one or more predetermined fitness criteria when applied to solving solve the network routing problem coupled with one or more information retrieval problems. The field of evolutionary computation encompasses stochastic optimization techniques, such as randomized search strategies, in the form of evolutionary strategies (ES), evolutionary programming (EP), genetic algorithms (GA), classifier systems, evolvable hardware (EHW), and genetic programming (GP). The stochastic optimization component objectives of the multimedia resource discovery and retrieval systems includes maximization of resource utilization and of overall LAN throughput.

Abstract: An information sharing system to solve one or more information retrieval problems is concerned with the novel, hybrid use of the stochastic optimization techniques of evolutionary computation (EC) search strategies for computer information systems such as search engines, or service oriented architectures (SOAs). The information sharing system uses stochastic optimization agents for task distribution and communication when foraging a system of stored documents for information, assessing the computational effort required to retrieve information in the form of stored documents, sharing information among stochastic optimization agent processes and processors, and extracting knowledge from the information. The field of evolutionary computation encompasses stochastic optimization techniques, such as randomized search strategies, in the form of evolutionary strategies (ES), evolutionary programming (EP), genetic algorithms (GA), classifier systems, evolvable hardware (EHW), and genetic programming (GP).