Abstract: A portable electronic device includes an audio input device and a processor. The processor is configured to obtain audio input data including a noise signal having an audio feature through the audio input device, to filter the audio input data using a neural network model to generate first audio output data, and to filter the first audio output data without using the neural network model to generate second audio output data. The first audio output data has a first changed audio feature corresponding to the audio feature and the second audio output data has a second changed audio feature corresponding to the audio feature.

Abstract: A portable electronic device includes an audio input device and a processor. The processor is configured to obtain audio input data including a noise signal having an audio feature through the audio input device, to filter the audio input data using a neural network model to generate first audio output data, and to filter the first audio output data without using the neural network model to generate second audio output data. The first audio output data has a first changed audio feature corresponding to the audio feature and the second audio output data has a second changed audio feature corresponding to the audio feature.

Abstract: An apparatus and method for a sensor network, machine-to-machine (M2M) communication, machine type communication (MTC), and Internet of things (IoT) are disclosed. The disclosure may be applied to, for example, intelligent services related to the above technologies, in conjunction with smart homes, smart buildings, smart cities, smart cars or connected cars, health care, digital education, retail business, security, and safety related services. The method includes generating first image data by resizing original image data to a predetermined size, inserting watermark data into the first image data, and adding difference data corresponding to the difference between the original image data and the first image data to second image data that is image data in which the watermark data is inserted.

Abstract: An apparatus and method for a sensor network, machine-to-machine (M2M) communication, machine type communication (MTC), and Internet of things (IoT) are disclosed. The disclosure may be applied to, for example, intelligent services related to the above technologies, in conjunction with smart homes, smart buildings, smart cities, smart cars or connected cars, health care, digital education, retail business, security, and safety related services. The method includes generating first image data by resizing original image data to a predetermined size, inserting watermark data into the first image data, and adding difference data corresponding to the difference between the original image data and the first image data to second image data that is image data in which the watermark data is inserted.

Abstract: A polymer dispersed liquid crystal display device is disclosed. A polymer dispersed liquid crystal display device of the present invention includes a pair of substrates inside which electrodes are formed, respectively. The substrates are disposed to be opposite to each other and to be spaced to a cell gap. A liquid crystal polymer network and liquid crystal droplets which are phase separated from each other, are interposed between the substrates. The liquid crystal polymer network is perpendicularly arranged to the planes of the substrates regardless of presence or absence of electrical field. The liquid crystal droplets includes a plurality of liquid crystal molecules and are dispersed in the liquid crystal polymer network. The liquid crystal polymer network has a birefringe index which is similar to that of the liquid crystal.