Positivity and tameness in rank 2 cluster algebras

We study the relationship between the positivity property in a rank 2 cluster algebra, and the property of such an algebra to be tame. More precisely, we show that a rank 2 cluster algebra has a basis of indecomposable positive elements if and only if it is of finite or affine type. This statement disagrees with a conjecture by Fock and Goncharov.     

A Short Note on Containment of Cores

We show that the operation of taking the core of an ideal does not preserve inclusions.     

Blockchain Network Based Topic Mining Process for Cognitive Manufacturing

Wireless Personal Communications - Cognitive manufacturing has brought about an innovative change to the 4th industrial revolution based technology in combination with blockchain distributed...     

Associative Feature Information Extraction Using Text Mining from Health Big Data

Wireless Personal Communications - With the development of big data computing technology, most documents in various areas, including politics, economics, society, culture, life, and public health,...     

Performance Evaluation of Silence-Feature Normalization Model using Cepstrum Features of Noise Signals

Speech enhancement algorithms play an important role in speech signal processing. Over the past several decades, many algorithms have been studied for speech enhancement. A speech enhancement algorithm uses a noise removal method and a statistical model filter to analyze the speech signal in the frequency domain. Spectral subtraction and Wiener filters have been used as representative algorithms. These algorithms have excellent speech enhancement performance, but suffer from deterioration in performance due to specific noise or low signal-to-noise ratio (SNR) environments. In addition, according to estimations of erroneous noise, a noise existing in a voice signal is maintained so that a spectrum corresponding to a voice signal is distorted, or a frame corresponding to a voice signal cannot be retrieved, and voice recognition performance deteriorates. The problem of deterioration in speech recognition performance arises from the difference between speech recognition and training model. We use silence-feature normalization model as a methodology to improve the recognition rate resulting from the difference in the noisy environments. Conventional silence-feature normalization has a problem in that the silent part of the energy increases, which affects recognition performance due to unclear boundaries categorizing the voice. In this study, we use the cepstrum feature of the noise signals in the silence-feature normalization model to improve the performance of silence-feature normalization in a signal with a low SNR by setting a reference value for voiced and unvoiced classification. As a result of recognition rate confirmation, the recognition rates improve in performance, compared with other methods.     

Rigid reflections and Kac-Moody algebras

Given any Coxeter group, we define rigid reflections and rigid roots using non-self-intersecting curves on a Riemann surface with labeled curves. When the Coxeter group arises from an acyclic quiver, they are related to the rigid representations of the quiver. For a family of rank 3 Coxeter groups, we show that there is a surjective map from the set of reduced positive roots of a rank 2 Kac-Moody algebra onto the set of rigid reflections. We conjecture that this map is bijective.     

Integration of field effect transistor-based biosensors with a digital microfluidic device for a lab-on-a-chip application

A new platform for lab-on-a-chip system is suggested that utilizes a biosensor array embedded in a digital microfluidic device. With field effect transistor (FET)-based biosensors embedded in the middle of droplet-driving electrodes, the proposed digital microfluidic device can electrically detect avian influenza antibody (anti-AI) in real time by tracing the drain current of the FET-based biosensor without a labeling process. Digitized transport of a target droplet enclosing anti-AI from an inlet to the embedded sensor is enabled by the actuation of electrowetting-on-dielectrics (EWOD). A reduction of the drain current is observed when the target droplet is merged with a pre-existing droplet on the embedded sensor. This reduction of the drain current is attributed to the specific binding of the antigen and the antibody of the AI. The proposed hybrid device consisting of the FET-based sensor and an EWOD device, built on a coplanar substrate by monolithic integration, is fully compatible with current fabrication technology for control and read-out circuitry. Such a completely electrical manner of inducing the transport of bio-molecules, the detection of bio-molecules, the recording of signals, signal processing, and the data transmission process does not require a pump, a fluidic channel, or a bulky transducer. Thus, the proposed platform can contribute to the construction of an all-in-one chip.