We investigated the effect of white noise on working memory performance using electroencephalography (EEG). Six healthy subjects participated in this study, and each subject performed a 2-back task under white noise a...
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ISBN:
(数字)9798350367331
ISBN:
(纸本)9798350367348
We investigated the effect of white noise on working memory performance using electroencephalography (EEG). Six healthy subjects participated in this study, and each subject performed a 2-back task under white noise and no sound conditions. After a series of EEG preprocessing, the amplitude of event-related potential (ERP) was calculated. The results indicated an increase in average accuracy and mean P300 amplitude during the white noise condition compared to without it, suggesting that white noise might enhance working memory performance. However, due to the limited number of participants, statistical power was not attained. In our future studies, we will perform additional experiments with more subjects.
Understanding the workings of anaerobic digestion in the production of biogas from carbon waste has been an issue for many scientists. Recently, advancement in techniques finally paved the way in providing a solution ...
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Ultra-Wide Band (UWB) is a wireless technology that utilizes frequencies with a wide bandwidth to provide coverage and positioning with centimeter-level accuracy. This technology has been widely applied in various fie...
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ISBN:
(数字)9798350368086
ISBN:
(纸本)9798350368093
Ultra-Wide Band (UWB) is a wireless technology that utilizes frequencies with a wide bandwidth to provide coverage and positioning with centimeter-level accuracy. This technology has been widely applied in various fields, such as activity recognition, indoor localization, and through-wall radar. One of the main advantages of UWB is its ability to determine the location of objects with an accuracy of up to 10 cm, making it ideal for tracking moving assets in complex and space-sensitive environments. In this study, a UWB-based positioning system uses a minimum of three anchors and one tag to measure the distance between devices. However, some conditions can reduce the measurement accuracy. To overcome this, this study proposes the use of the Support Vector Regression (SVR) algorithm to improve the accuracy of the system’s positioning. SVR is a regression method that supports linear and non-linear regression, with the aim of finding the optimal hyperplane that minimizes prediction errors. The results of the study show that UWB combined with SVR can provide significant accuracy, with a Mean Absolute Error (MAE) of $\mathbf{1 7} \mathbf{~ c m}$ on the X coordinate and 19 cm on the Y coordinate, and a Mean Squared Error (MSE) of 4 cm on the X coordinate and 5 cm on the Y coordinate in Line of Sight (LOS) conditions which under 20 cm. This confirms that the combination of UWB and SVR is an effective approach in improving the accuracy of indoor positioning.
Here, a microfluidic redox cycle-based chip device (MRECD) was fabricated for high-sensitive and selective electrochemical detection of dopamine (DA). Briefly, ITO electrodes, each with a 3x3 mm working area, were fab...
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A challenge in wearable technology lies in the realtime monitoring of molecular biomarkers associated with human health. Electrochemical sensors are one of the most useful tools for this purpose and are commonly used ...
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ISBN:
(数字)9798350371499
ISBN:
(纸本)9798350371505
A challenge in wearable technology lies in the realtime monitoring of molecular biomarkers associated with human health. Electrochemical sensors are one of the most useful tools for this purpose and are commonly used in health monitoring devices. Electrochemical biosensing is particularly convenient when used in user-friendly, low-cost devices for testing noninvasive body fluids such as sweat and saliva. However, achieving high selectivity and specificity in measurements depends on the complexity of the biomarker and the stability of the biomarker capture molecule. In this study, laser-scribed electrodes (LSEs) were manufactured using a CO2 laser cutter on Polyimide for the label-free classification of sweat components. Cyclic voltammetry experiments were performed on artificial human sweat and the sweat component L-Histidine. The resulting voltammogram data served as input to train a Multi-Layer Perceptron Neural Network (MLP-NN) algorithm capable of classifying L-Histidine and artificial sweat.
In this paper, we analyze the dynamic response of a MEMS device made of a microplate supported by two microcantilever beams and electrically actuated via an underneath electrode. We employ the motion-induced current m...
In this paper, we analyze the dynamic response of a MEMS device made of a microplate supported by two microcantilever beams and electrically actuated via an underneath electrode. We employ the motion-induced current method to capture its dynamic response under varying pressure. We show the potential use of the MEMS device as a pressure sensor by leveraging squeeze-film damping and other nonlinear dynamic phenomena associated with its motion. The present study reveals the possible tuning of the MEMS device to operate in analog and binary modes. Analog-based detection is achieved within the low pressure range of 2.2-52 mbar. We also demonstrate the use of the MEMS device in binary mode, acting as a pressure switch, with a capability to detect low pressures down to sub-millibars.
Ethyl lactate is a biodegradable and non-toxic ester with market growth potential, being used in different fields of industry. In this work, aiming to reduce the production cost of this solvent, seeking to make it eve...
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Thanks to the high energy efficiency achieved by approximate circuits, the exploration of approximate solutions for a wide of applications is the focus of academic and industrial research. However, defining the most a...
Thanks to the high energy efficiency achieved by approximate circuits, the exploration of approximate solutions for a wide of applications is the focus of academic and industrial research. However, defining the most appropriate approximation considering the power consumption and accuracy trade-off can be exhaustive. This paper proposes a novel approach to estimate the synthesis results for approximate adders (AxA) with different bit-width and approximation levels based on a database and simple mathematical operations to reduce the synthesis process complexity during an approximate circuit development. We implement the proposed approach to estimate the synthesis results for the Copy, Error-Tolerant Adder I (ETA-I), Lower-part-or (LOA), and Truncation (Trunc) AxAs. Comparing our estimation with real synthesis results obtained by an industrial synthesis tool, we prove the approach’s efficiency by presenting an average error on the estimated parameters (area, power and delay) less than 10% in the worst case. In addition, our approach reduces by more than 25 times the number of synthesis runs when estimating the synthesis results for all circuits in the bit width range of 2 to 64 with all possible approximation levels.
This article aims to explain the use of the intelligent technique known as Arithmetic Optimization Algorithm for generating synthetic series for hydroelectric plants which belong to the Brazilian interconnected system...
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ISBN:
(数字)9798350379730
ISBN:
(纸本)9798350379747
This article aims to explain the use of the intelligent technique known as Arithmetic Optimization Algorithm for generating synthetic series for hydroelectric plants which belong to the Brazilian interconnected system. Thus, the metaheuristic is responsible for determining the best coefficients as well as the optimal order for each month which may represent historical data based on an optimization problem whose objective function is to minimize the standard deviation of errors between the real and estimated water inflow values. Finally, with the optimal coefficients and order, the next step is to generate synthetic flow series considering a period of five years ahead, guaranteeing forecasts of inflow energy which are coherent with the historical data. The simulations were carried out considering Itaipu, Belo Monte, Tucuruí and Comp PAF-MOX hydroelectric plants whose results show the applicability of the Arithmetic Optimization Algorithm for generating flow scenarios allowing a convincing energy planning.
In the realm of safety-critical Automotive System-on-Chip (SoC) design, memory functionality plays a crucial role in determining overall die yield due to its sizable footprint on the chip. Therefore, efficient methodo...
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ISBN:
(数字)9783981926385
ISBN:
(纸本)9798350348606
In the realm of safety-critical Automotive System-on-Chip (SoC) design, memory functionality plays a crucial role in determining overall die yield due to its sizable footprint on the chip. Therefore, efficient methodologies for both post-manufacturing offline testing and real-time monitoring are essential to provide timely diagnostic feedback. This paper proses a real-time memory diagnostic data compression technique Pattern-Adaptive Two-Stage Bloom Filter (PA-2SBF) for automotive System-on-Chip (SoC) applications. PA-2SBF is designed to address the challenge of false positives incorporating frequently encountered failure patterns. Bloom filters, a probabilistic data structure renowned for their space-efficiency and quick approximate membership queries, are employed to expedite fault memory diagnosis information lookup and compression. Furthermore, failure patterns are considered to mitigate the false positive rate inherent in Bloom filters. The paper also presents a strategy for leveraging the compressed diagnostic information during run-time. Specifically, it exploits the quick lookup feature of Bloom filter to prohibit CPU access to defective memory regions, enhancing overall system reliability.
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