Abstract: An antenna, an antenna apparatus, and a terminal are provided. The antenna includes a feeding point, a feeding stub, and a coupling stub. The feeding stub is electrically connected to the feeding point. The coupling stub is coupled to the feeding stub. The coupling stub includes at least two grounding points By selecting different grounding combinations of the at least two grounding points of the coupling stub, an antenna clearance area does not need to be increased while multi-frequency coverage of the antenna is implemented.

Abstract: Provided is a method for treatment of liver cancer and inhibition of metastasis with CXCR4-targeted nanoparticle. A CXCR4 antagonist is used as a targeting molecule to modify a lipid carrier for the formation of nanoparticle carrying an anti-angiogenesis drug or an anti-angiogenic nucleotide. Such nanoparticle can enhance the accumulation and uptake of the drug and nucleotide in liver cancer cells as well as sensitize the liver cancer cells to treatment of said drug and nucleotide, providing a synergistic suppression of angiogenesis and tumor progression. Furthermore, the CXCR4-targeted nanoparticle can effectively inhibit metastasis of liver cancer. The pharmaceutical composition is an injectable composition; hence, is suitable for clinical application for the treatment of liver cancer.

Abstract: A device for performing a cooperative function with another device is provided. The device includes a communication unit; and a controller that determines whether the other device is in a surrounding area of the device based a signal received through the communication unit, selects one cooperative function from among a plurality of cooperative functions according to a relative position of the device with respect to the other device and performs the selected cooperative function with the other device.

Abstract: A method of notifying an operation state change of a device is provided. The method includes receiving a message by a first device; identifying, by the first device, that a second device is currently connected to the first device through a network; and transmitting, by the first device, information regarding the message to the second device. The information is displayed on a display unit of the second device.

Abstract: The invention provides immune regulatory oligonucleotides (IRO) as antagonist of TLRs and methods of use thereof. These IROs have unique sequences that inhibit TLR-mediated signaling in response to a TLR ligand or TLR agonist. The methods may have use in the prevention and treatment of cancer, an autoimmune disorder, airway inflammation, inflammatory disorders, infectious disease, skin disorders, allergy, asthma or a disease caused by a pathogen.

Abstract: The claimed subject matter includes a system and method for recognizing mixed speech from a source. The method includes training a first neural network to recognize the speech signal spoken by the speaker with a higher level of a speech characteristic from a mixed speech sample. The method also includes training a second neural network to recognize the speech signal spoken by the speaker with a lower level of the speech characteristic from the mixed speech sample. Additionally, the method includes decoding the mixed speech sample with the first neural network and the second neural network by optimizing the joint likelihood of observing the two speech signals considering the probability that a specific frame is a switching point of the speech characteristic.

Abstract: A method is disclosed herein that includes an act of causing a processor to access a deep-structured, layered or hierarchical model, called a deep convex network, retained in a computer-readable medium, wherein the deep-structured model comprises a plurality of layers with weights assigned thereto. This layered model can produce the output serving as the scores to combine with transition probabilities between states in a hidden Markov model and language model scores to form a full speech recognizer. Batch-based, convex optimization is performed to learn a portion of the deep convex network's weights, rendering it appropriate for parallel computation to accomplish the training. The method can further include the act of jointly substantially optimizing the weights, the transition probabilities, and the language model scores of the deep-structured model using the optimization criterion based on a sequence rather than a set of unrelated frames.

Abstract: A content providing method of an electronic apparatus communicably connected with an external apparatus is provided. The method includes receiving a command for transferring content to the external apparatus; checking whether the content includes information indicating that the content is transferable to the external apparatus, the information being set by determining, based on a meta data included in the content, whether a predetermined condition is satisfied; and transferring the content, based on the checked information, to the external apparatus.

Abstract: A method of generating interaction activity information including connecting a second apparatus to a first apparatus capable of communicating with each other, receiving first information about a function that is capable of being performed in the first apparatus, from the first apparatus, and generating second information about a function that is used interactively between the first apparatus and the second apparatus, based on the first information.

Abstract: The present invention is related to a method for ameliorating liver fibrosis in a subject. The present invention utilizes copolymers of polyethylene glycol and poly (D, L-lactide-co-glycolide) to form nanoparticle composition containing tyrosine kinase inhibitor, such as Sorafenib. The use of nanoparticle composition is non-toxic and can increase the stability and decrease the release of drug in blood circulation. The pharmaceutical composition is in an injectable form. The nanoparticle composition containing tyrosine kinase inhibitor of the present invention can effectively ameliorate liver fibrosis including decreasing extracellular matrix accumulation, suppressing hepatic stellate cell activity, shrinking of abnormal blood vessel, and lowering microvascular density in fibrotic liver; hence is suitable for clinical application for the treatment of liver fibrosis.

Abstract: A sequence recognition system comprises a prediction component configured to receive a set of observed features from a signal to be recognized and to output a prediction output indicative of a predicted recognition based on the set of observed features. The sequence recognition system also comprises a classification component configured to receive the prediction output and to output a label indicative of recognition of the signal based on the prediction output.

Abstract: The invention provides novel immune regulatory oligonucleotides (IRO) as antagonist of TLRs and methods of use thereof. These IROs have unique sequences that inhibit or suppress TLR-mediated signaling in response to a TLR ligand or TLR agonist. The methods may have use in the prevention and treatment of cancer, an autoimmune disorder, airway inflammation, inflammatory disorders, infectious disease, skin disorders, allergy, asthma or a disease caused by a pathogen.

Abstract: A mobile device and a server are provided. The mobile device displays relevant information extracted based on location information and additional information. Accordingly, by linking regional information acquired through a personal device with a location based service, the user is provided with useful contents effectively and further is provided with a new experience.

Abstract: The present disclosure provides a method of treating and/or preventing neurodegenerative diseases, such as Parkinson disease, Alzheimer disease, Huntington's disease, multiple sclerosis and amyotrophic lateral sclerosis, comprising administrating a therapeutically effective amount of a compound of formula I or a pharmaceutically acceptable salt thereof to a subject in need thereof.

Abstract: The adaptation and personalization of a deep neural network (DNN) model for automatic speech recognition is provided. An utterance which includes speech features for one or more speakers may be received in ASR tasks such as voice search or short message dictation. A decomposition approach may then be applied to an original matrix in the DNN model. In response to applying the decomposition approach, the original matrix may be converted into multiple new matrices which are smaller than the original matrix. A square matrix may then be added to the new matrices. Speaker-specific parameters may then be stored in the square matrix. The DNN model may then be adapted by updating the square matrix. This process may be applied to all of a number of original matrices in the DNN model. The adapted DNN model may include a reduced number of parameters than those received in the original DNN model.

Abstract: A device for performing a cooperative function with another device is provided. The device includes a communication unit; and a controller that determines whether the other device is in a surrounding area of the device based a signal received through the communication unit, selects one cooperative function from among a plurality of cooperative functions according to a relative position of the device with respect to the other device and performs the selected cooperative function with the other device.

Abstract: A deep tensor neural network (DTNN) is described herein, wherein the DTNN is suitable for employment in a computer-implemented recognition/classification system. Hidden layers in the DTNN comprise at least one projection layer, which includes a first subspace of hidden units and a second subspace of hidden units. The first subspace of hidden units receives a first nonlinear projection of input data to a projection layer and generates the first set of output data based at least in part thereon, and the second subspace of hidden units receives a second nonlinear projection of the input data to the projection layer and generates the second set of output data based at least in part thereon. A tensor layer, which can converted into a conventional layer of a DNN, generates the third set of output data based upon the first set of output data and the second set of output data.

Abstract: A device for performing a cooperative function with another device is provided. The device includes a communication unit; and a controller that determines whether the other device is in a surrounding area of the device based a signal received through the communication unit, selects one cooperative function from among a plurality of cooperative functions according to a relative position of the device with respect to the other device and performs the selected cooperative function with the other device.

Abstract: The invention provides immune regulatory oligonucleotides (IRO) as antagonist of TLRs and methods of use thereof. These IROs have unique sequences that inhibit TLR-mediated signaling in response to a TLR ligand or TLR agonist. The methods may have use in the prevention and treatment of cancer, an autoimmune disorder, airway inflammation, inflammatory disorders, infectious disease, skin disorders, allergy, asthma or a disease caused by a pathogen.

Abstract: Discriminative pretraining technique embodiments are presented that pretrain the hidden layers of a Deep Neural Network (DNN). In general, a one-hidden-layer neural network is trained first using labels discriminatively with error back-propagation (BP). Then, after discarding an output layer in the previous one-hidden-layer neural network, another randomly initialized hidden layer is added on top of the previously trained hidden layer along with a new output layer that represents the targets for classification or recognition. The resulting multiple-hidden-layer DNN is then discriminatively trained using the same strategy, and so on until the desired number of hidden layers is reached. This produces a pretrained DNN. The discriminative pretraining technique embodiments have the advantage of bringing the DNN layer weights close to a good local optimum, while still leaving them in a range with a high gradient so that they can be fine-tuned effectively.