Abstract: Apparatus and associated methods relate to an inventory management system having a machine learning engine trained to (a) dynamically predict a demand amount of the inventory in response to a set of near-future data and (b) generate a signal to order the amount of inventory as needed. In an illustrative example, the machine learning engine may be trained by a hotel's historical room booking data, the hotel's historical occupancy data, and corresponding inventory consumption data stored in a database. Various embodiments may enable, for example, the hotel to have better management on the status of inventories at various stages. For example, sufficient inventory may be available. In addition, providing the proper amount of inventory may also advantageously reduce the cost spent on unused products.

Abstract: Apparatus and associated methods relate to an inventory management system having a machine learning engine trained to (a) dynamically predict a demand amount of the inventory in response to a set of near-future data and (b) generate a signal to order the amount of inventory as needed. In an illustrative example, the machine learning engine may be trained by a hotel's historical room booking data, the hotel's historical occupancy data, and corresponding inventory consumption data stored in a database. Various embodiments may enable, for example, the hotel to have better management on the status of inventories at various stages. For example, sufficient inventory may be available. In addition, providing the proper amount of inventory may also advantageously reduce the cost spent on unused products.

Abstract: Apparatus and associated methods relate to an inventory management system having a machine learning engine trained to (a) dynamically predict a demand amount of the inventory in response to a set of near-future data and (b) generate a signal to order the amount of inventory as needed. In an illustrative example, the machine learning engine may be trained by a hotel's historical room booking data, the hotel's historical occupancy data, and corresponding inventory consumption data stored in a database. Various embodiments may enable, for example, the hotel to have better management on the status of inventories at various stages. For example, sufficient inventory may be available. In addition, providing the proper amount of inventory may also advantageously reduce the cost spent on unused products.

Abstract: Apparatus and associated methods relate to an inventory management system having a machine learning engine trained to (a) dynamically predict a demand amount of the inventory in response to a set of near-future data and (b) generate a signal to order the amount of inventory as needed. In an illustrative example, the machine learning engine may be trained by a hotel's historical room booking data, the hotel's historical occupancy data, and corresponding inventory consumption data stored in a database. Various embodiments may enable, for example, the hotel to have better management on the status of inventories at various stages. For example, sufficient inventory may be available. In addition, providing the proper amount of inventory may also advantageously reduce the cost spent on unused products.

Abstract: Techniques, systems, and devices are disclosed for non-invasive monitoring and imaging of nuclear fuel inside a nuclear reactor using muon detector arrays. In one aspect, these detector arrays are placed outside the reactor vessel or building for investigating the reactors without access to the cores, therefore the imaging process is non-invasive. In some implementation, these detector arrays measure both muon scattering and absorption to enable imaging and characterizing not only the very high-Z fuel materials, but also other materials in the reactor, thereby obtaining a more complete picture of reactor status. When applied to damaged reactors, the disclosed proposed techniques, systems, and devices, through the process of providing an image, can reveal the presence (or absence) of damage to fuel rod assemblies or puddles of molten fuel at the bottom of the containment vessel, thus providing crucial information to guide decisions about remedial actions.

Abstract: Systems and methods are presented for providing a psychological analysis of financial products in an investor's financial portfolio. In some example embodiments, a method is presented. The method may include accessing, in a device comprising one or more processors, a psychometric data of a financial product, the psychometric data quantifying a decision-making tendency used in managing the financial product.

Abstract: Systems and methods are presented for providing a psychological analysis of financial products in an investor's financial portfolio. In some example embodiments, a method is presented. The method may include accessing, in a device comprising one or more processors, a psychometric data of a financial product, the psychometric data quantifying a decision-making tendency used in managing the financial product.

Abstract: Systems and methods are presented for finding similar funds to a target fund in an investor's financial portfolio. In some embodiments, a method is presented. The method may include accessing target fund characteristics data describing former characteristics of a target fund.

Abstract: Techniques, systems, and devices are disclosed for non-invasive monitoring and imaging of nuclear fuel inside a nuclear reactor using muon detector arrays. In one aspect, these detector arrays are placed outside the reactor vessel or building for investigating the reactors without access to the cores, therefore the imaging process is non-invasive. In some implementation, these detector arrays measure both muon scattering and absorption to enable imaging and characterizing not only the very high-Z fuel materials, but also other materials in the reactor, thereby obtaining a more complete picture of reactor status. When applied to damaged reactors, the disclosed proposed techniques, systems, and devices, through the process of providing an image, can reveal the presence (or absence) of damage to fuel rod assemblies or puddles of molten fuel at the bottom of the containment vessel, thus providing crucial information to guide decisions about remedial actions.

Abstract: A machine may be configured as a recommendation machine that makes one or more recommendations to one or more users. The machine may provide a recommendation based on one or more psychometric profiles that correspond to a user, a product, a manager for the product, or any suitable combination thereof. The user may be a potential buyer of the product, and the manager for the product may fully or partially manage the product and consequently affect the value of the product. The user's psychometric profile may describe market understanding and risk tolerance possessed by the user, and the manager's psychometric profile may describe market understanding and risk tolerance held by the manager. Such psychometric profiles may be used to make recommendations of products. In addition, a psychometric profile for the product itself may be used in the making of such recommendations.

Abstract: A machine may be configured as a recommendation machine that makes one or more recommendations to one or more users. The machine may provide a recommendation based on one or more psychometric profiles that correspond to a user, a product, a manager for the product, or any suitable combination thereof. The user may be a potential buyer of the product, and the manager for the product may fully or partially manage the product and consequently affect the value of the product. The user's psychometric profile may describe market understanding and risk tolerance possessed by the user, and the manager's psychometric profile may describe market understanding and risk tolerance held by the manager. Such psychometric profiles may be used to make recommendations of products. In addition, a psychometric profile for the product itself may be used in the making of such recommendations.

Abstract: The present invention, foreign language teaching tool (FLTT), is a language translation tool that slowly introduces the student to different words in the foreign language while the student is reading a familiar text. The preferred embodiment of FLTT is on an e-book, but FLTT can be adapted to printed hard-copy texts. FLTT starts with an original text in the student's native language and analyzes and translates the original text using a primary translation process. In the primary translation process, the original text is broken down into different grammatical units and then translated using a commercial computer translation package. A bilingual literature specialist then reviews the translated text and makes any necessary corrections in order to preserve the literary quality of the original text.

Abstract: The present invention, foreign language teaching tool (FLTT), is a language translation tool that slowly introduces the student to different words in the foreign language while the student is reading a familiar text. The preferred embodiment of FLTT is on an e-book, but FLTT can be adapted to printed hard-copy texts. FLTT starts with an original text in the student's native language and analyzes and translates the original text using a primary translation process. In the primary translation process, the original text is broken down into different grammatical units and then translated using a commercial computer translation package. A bilingual literature specialist then reviews the translated text and makes any necessary corrections in order to preserve the literary quality of the original text.