Sensors
The dataset consists of experimental data collected in an anechoic tank, with a specific setup involving single-source transmission and reception by a 6-element circular array with a radius of 0.046 meters. The transmitted signals include common wideband signals used in underwater positioning and communication, such as chirps, single-carrier QPSK, multi-tone signals, and OFDM signals. The transmitter and receiver are located at the same depth, and the receiving array rotates 360 degrees with 30-degree intervals.
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As semiconductor devices have become increasingly miniaturized, the ability to control very small Critical Dimensions (CDs) during the etching process has become crucial through controlled plasma processes. Hence, diagnosing plasma and reflecting this in the process to enhance yield is of paramount importance. Typically, a Single Langmuir Probe (SLP) is utilized for plasma diagnostics.
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Recent semiconductor devices have embraced structural modifications, including vertical stacking, to overcome the limitations of miniaturization. Particularly, memory devices have seen improvements through the transition to 3D stack structures. To address the challenges of etching high aspect ratio contact holes, the Bosch process, which alternates between deposition of a passivation layer on the pattern wall to prevent sidewall etching and etching steps, has been utilized.
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The Partial Discharge - Localisation Dataset, abbreviated: PD-Loc Dataset is an extensive collection of acoustic data specifically curated for the advancement of Partial Discharge (PD) localisation techniques within electrical machinery. Developed using a precision-engineered 32-sensor acoustic array, this dataset encompasses a wide array of signals, including chirps, white Gaussian noise, and PD signals.
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New capabilities involving sensors, data collection, and data analysis have enabled innovations in how engineered systems are monitored and maintained. Whereas each new evolution of maintenance philosophies has relied upon the current technological state, this research examines potential future capabilities in the field of prognostics and health management (PHM). PHM algorithms for predicting the estimated time to failure for a system are based on sensor data, physical models, or a combination of both.
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A dataset comprising a total of 21 individuals has been meticulously compiled, with 9 individuals identified as exhibiting Major Depressive Disorder (MDD) based on the outcomes derived from the PHQ-9 Questionnaire. The remaining 12 individuals in the dataset are classified as non-MDD.
The dataset encompasses diverse sensor data, including temperature measurements, SpO2 readings, pulse rates, and accelerometer data. It is important to note that all data points were collected within a controlled environment, ensuring reliability and consistency throughout the dataset.
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These datasets are gathered from an array of four gas sensors to be used for the odor detection and recognition system. The smell inspector Kit IX-16 used to create the dataset. each of 4 sensor has 16 channels of readings. Odors of different 12 samples are taken from these six sensors
1- Natural Air
2- Fresh Onion
3- Fresh Garlic
4- Black Lemon
5- Tomato
6- Petrol
7- Gasoline
8- Coffee
9- Orange
10- Colonia Perfume
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These datasets are gathered from an array of six gas sensors to be used for the odor recognition system. The sensors those used to create the data set are; Df-NH3, MQ-136, MQ-135, MQ-8, MQ-4, and MQ-2.
odors of different 10 samples are taken from these six sensors
1- Natural Air
2- Fresh Onion
3- Fresh Garlic
4- Fresh Lemon
5- Tomato
6- Petrol
7- Gasoline
8- Coffee 1,2
9- Orange
10- Colonia Perfume
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Database of the times the device remained in each state (idle, low power mode, transmitting and listening, respectively), number of hops, hop distance (d), transmission rate (_R) and size of the packet sent (_Nb), measured on the Tmote Sky device using an Aloha Puro protocol with RDC implemented in the Contiki operating system.
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Researchers have widely used commercial and alternative measurement systems in impedance-based structural health monitoring (SHM), where a piezoelectric transducer attached to the monitored structure is excited while its electrical impedance is measured. However, the literature lacks sufficient attention to the required number of cycles of the excitation signal, an issue frequently overlooked by researchers.
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