Sound Demixing Challenge 2023 Music Demixing Track Technical Report: TFC-TDF-UNet v3

In this report, we present our award-winning solutions for the Music Demixing Track of Sound Demixing Challenge 2023. First, we propose TFC-TDF-UNet v3, a time-efficient music source separation model that achieves state-of-the-art results on the MUSDB benchmark. We then give full details regarding our solutions for each Leaderboard, including a loss masking approach for noise-robust training. Code for reproducing model training and final submissions is available at github.com/kuielab/sdx23.Comment: 5 pages, 4 table

Spatial Clustering based Meteorological Fields Construction for Regional Vulnerability Assessment

Chemical accidents have affected the social-environmental system. For the regional vulnerability assessment, which is the baseline work to assess the impact on the environment, a meteorological field is needed to determine how chemicals from multiple adjacent companies are propagated. In this study, we present the method of meteorological field based on the spatial cluster which is the main component of vulnerability assessment on regional chemical accident scenario. To integrate spatially dense chemical companies into a cluster, we adopt spatial clustering algorithms. Experiment result shows that DBSCAN-based approach reduces 80.5% total area of the meteorological field against brute-force algorithm, and shows good performance on the average of the overlap ratio, and utility ratio for clustering results

PEI-Functionalized Carbon Nanotube Thin Film Sensor for CO2 Gas Detection at Room Temperature

In this study, a polyethyleneimine (PEI)-functionalized carbon nanotube (CNT) sensor was fabricated for carbon dioxide detection at room temperature. Uniform CNT thin films prepared using a filtration method were used as resistive networks. PEI, which contains amino groups, can effectively react with CO2 gas by forming carbamates at room temperatures. The morphology of the sensor was observed, and the properties were analyzed by scanning electron microscope (SEM), Raman spectroscopy, and fourier transform infrared (FT-IR) spectroscopy. When exposed to CO2 gas, the fabricated sensor exhibited better sensitivity than the pristine CNT sensor at room temperature. Both the repeatability and selectivity of the sensor were studied

A 1-v 4.6-mw/channel fully differential neural recording front-end ic with current-controlled pseudoresistor in 0.18-mm cmos

This paper presents a fully differential implantable neural recording front-end IC for monitoring neural activities. Each analog front-end (AFE) consists of a low-noise amplifier (LNA), a variable gain amplifier (VGA), and a buffer. The output signal of the AFE is digitized through a successive approximation register analog-to-digital converter (SAR ADC). The LNA adopts the current-reuse technique to improve the current efficiency, achieving the power consumption as low as 0.95 mW. The implemented LNA has the gain of 40 dB, the low-pass cutoff frequency of 10 kHz, and the high-pass cutoff frequency of sub-1 Hz which is realized using the current-controlled pseudoresistor. The VGA controls the gain from 21.9 dB to 33.9 dB for efficient digitization while consuming the power of 0.35 mW. The buffer drives the capacitive DAC of the ADC and consumes the power of 3.28 mW. The fabricated AFE occupies the area of 0.11 mm 2 /Channel and consumes 4.6 mW/Channel under 1-V supply voltage. Each channel achieves the input-referred noise of 2.88 mV rms , the NEF of 2.38, and the NEF 2 V DD of 5.67. The front-end IC is implemented in a standard 1P6M 0.18-mm CMOS process. © 2019, Institute of Electronics Engineers of Korea. All rights reserved.1

Turbulence Dynamo in the Stratified Medium of Galaxy Clusters

The existence of microgauss magnetic fields in galaxy clusters has been established through observations of synchrotron radiation and Faraday rotation. They are conjectured to be generated via small-scale dynamo by turbulent flow motions in the intracluster medium (ICM). The microgauss magnetic fields of giant radio relics, show structures of synchrotron polarization vectors, organized over scales of megaparsecs, challenging the turbulence origin of cluster magnetic fields. Unlike turbulence in the interstellar medium, turbulence in the ICM is subsonic. And it is driven sporadically in highly stratified backgrounds, when major mergers occur during the hierarchical formation of clusters. To investigate quantitatively the characteristics of a turbulence dynamo in such an ICM environment, we performed a set of turbulence simulations using a high-order-accurate, magnetohydrodynamic (MHD) code. We find that turbulence dynamo could generate the cluster magnetic fields up to the observed level from the primordial seed fields of 10(-15) G or so within the age of the universe, if the MHD description of the ICM could be extended down to kiloparsec scales. However, highly organized structures of polarization vectors, such as those observed in the Sausage relic, are difficult to reproduce through the shock compression of turbulence-generated magnetic fields. This implies that the modeling of giant radio relics may require pre-existing magnetic fields organized over megaparsec scales

Adaptive Group Scheduling Mechanism using Mobile Agents in Peer-to-Peer Grid Computing Environment

A peer to peer grid computing is an attractive computing paradigm for high throughput applications. However, both volatility due to autonomy of volunteers (i.e., resource providers) and heterogeneous properties of volunteers are challenging in a scheduling procedure. Therefore, it is necessary to develop a scheduling mechanism to adapt to a dynamic peer to peer grid computing environment. In this paper, we propose a Mobile Agent based Adaptive Scheduling Mechanism (MAASM). The MAASM classifies and constructs volunteer groups to perform a scheduling mechanism according to properties of volunteers such as volunteer autonomy failures, volunteer availability, and volunteering service time. In addition, the MAASM exploits a mobile agent technology to adaptively conduct different scheduling, fault tolerance, and replication algorithms suitable for each volunteer group. Furthermore, we demonstrate that the MAASM improves the performance by evaluating our scheduling mechanism i

Group-based Dynamic Computational Replication Mechanism

A peer-to-peer grid computing is complicated by heterogeneous capabilities, failures, volatility, and lack of trust because it is based on desktop computers at the edge of the Internet. In order to improve the reliability of computation and gain better performance, a replication mechanism must adapt to these distinct features. In other words, it is required to classify volunteers into groups that have similar properties and then dynamically apply different replication algorithms to each group. However, existing mechanisms do not provide such a replication mechanism on a per group basis. As a result, they cause a high overhead and poor performance. To solve the problems, we propose a new group-based computational replication mechanism to adapt to a unstable, untrusted, dynamic peer-to-peer grid computing environment. Our mechanism can reduce the number of redundancy and therefore complete many tasks by adaptively replicating computations on the basis of the properties of volunteer group such as availability, credibility, and volunteering service time. I

A neural recording amplifier based on adaptive SNR optimization technique for long-term implantation

Long-term neural recording which can consistently provide good signal-to-noise ratio (SNR) performance over time is important for stable operation of neuroprosthetic systems. This paper presents an analysis for the SNR optimization in a changing environment which causes variations in the tissue-electrode impedance, Zte. Based on the analysis result, a neural recording amplifier (NRA) is developed employing the SNR optimization technique. The NRA can adaptively change its configuration for in situ SNR optimization. The SNR is improved by 4.69% to 23.33% as Zte changes from 1.59 MQ to 31.8 MQ at 1 kHz. The NRA is fabricated in a 0.18-μm standard CMOS process and operates at 1.8-V supply while consuming 1.6 μA It achieves an input-referred noise of 4.67 μVrms when integrated from 1 Hz to 10 kHz, which leads to the NEF of 2.27 and the NEF2VDD of 9.28. The frequency reponse is measured with a high-pass cutoff frequency of 1 Hz and a low-pass cutoff frequency of 10 kHz. The midband gain is set to 40 dB while occupying 0.11 mm2 of a chip area. © 2017 IEEE

Novel Quantum Molecular Resonance Energy Source for Laparoscopic Bipolar Vessel Sealer: An Experimental Study in Animal Model

This study is to evaluate a novel Quantum Molecular Resonance energy device as a laparoscopic bipolar vessel sealer. The majority of conventional bipolar energy-based vessel sealing devices utilize energy at frequencies between 300 kHz and 500 kHz. The use of such frequencies has disadvantages including unintended damage to surrounding tissues and excessive surgical smoke production. Here, we developed a bipolar energy source using Quantum Molecular Resonance (QMR) energy of 4–64 MHz and combined this into a laparoscopic vessel sealer. We investigate the microscopic tissue effect and surgeon’s experiences of the laparoscopic bipolar vessel sealer using a novel QMR energy source through animal experiments. QMR energy sources showed higher sealing success rates (100% vs. 66.7%) and a higher burst pressure (963 mmHg vs. 802 mmHg) of the sealed vessels compared to LigaSure™. Histological analysis showed less vessel wall injury in the QMR energy source (55.0% vs. 73.9%). In the laparoscopic setting experiments, compared to LigaSure™, QMR energy sources showed statistically significantly less smoke formation (p = 0.014), less tissue carbonization (p = 0.013), and less stickiness (p = 0.044) during sealing tissues. A novel QMR energy source for a laparoscopic bipolar vessel sealer could produce a better sealing performance and less surrounding tissue damage

Phase-controlled growth of cobalt oxide thin films by atomic layer deposition

Cobalt oxide (CoOx) thin films were deposited on thermally grown SiO2 substrates by atomic layer deposition (ALD) using bis(1,4-di-iso-propyl-1,4-diazabutadiene)cobalt (C16H32N4Co) and oxygen (O-2) as reactants at deposition temperatures ranging from 125 to 300 degrees C. X-ray diffraction (XRD) and Raman spectroscopic analysis indicated that a mixed-phase oxide consisting of CoO and Co3O4 was deposited at temperatures ranging from 125 to 250 degrees C. However, single-phase Co3O4 was deposited above the deposition temperature of 275 degrees C. Further, analyses by Rutherford backscattering spectrometry, transmission electron microscopy, and selected area electron diffraction along with XRD and Raman spectroscopy revealed that the single-phase cobalt oxide film was stoichiometric crystalline (spinel structure) with negligible N and C impurities. The optical band gap of the single-phase Co3O4 film was 1.98 eV and increased with decreasing deposition temperature. It was also shown that the mixed-phase cobalt oxide thin films could be converted into single-phase spinel Co3O4 by annealing at 350 degrees C in O-2 ambient. It was further observed that the phase of the ALD-grown cobalt oxide thin film could be controlled by controlling the precursor or reactant pulsing condition. The study revealed that pure Co3O4 phase could be grown at a relatively low temperature (250 degrees C) by using water vapor as a reactant. Therefore, this work systemically demonstrated several pathways to grow single-phase Co3O4 by ALD using a novel metalorganic cobalt precursor