Good Response Time Research Articles

Pengujian Aplikasi Sistem Informasi Absensi Karyawan PT Prakarsa Mitra Andalan Menggunakan Metode Black Box

Technological developments that gave birth to many quality software products. Quality software is software that has gone through testing. In software testing there are several things that must be tested, namely the software must be in accordance with what the user wants or needs, the software must work well when used so that there are no errors, the software must have a good response time when run. Software must be a cost and time efficiency solution. In software testing, one of the methods used is by using the blackbox method. The blackbox method has its own technique, one of which is the equivalence partitioning technique. The equivalence partitioning technique is a technique of dividing several parts or partitions to check each part or partition by testing the software.

High-performance CuO nanowire printed devices for visible light sensing and switching characteristics

CuO nanowires (NWs) were synthesized by thermal oxidation of Cu wire in a muffle furnace. The furnace was set to 600 ˚C for 24 h to obtain a high aspect ratio NWs (400–700), with good crystallinity and negligible impurities. Further, CuO NWs were transferred to the silicon substrate to form a two-terminal, single nanowire device using contact printing. The fabricated devices exhibit good photocurrent, response, and recovery time (<50 ms). Also, the printed devices were analyzed at various bias voltages to explore the switching characteristics.

High Humidity Response of Sol–Gel-Synthesized BiFeO3 Ferroelectric Film

In this work, a BiFeO3 film is prepared via a facile sol–gel method, and the effects of the relative humidity (RH) on the BiFeO3 film in terms of capacitance, impedance and current–voltage (I–V) are explored. The capacitance of the BiFeO3 film increased from 25 to 1410 pF with the increase of RH from 30% to 90%. In particular, the impedance varied by more than two orders of magnitude as RH varied between 30% and 90% at 10 Hz, indicating a good hysteresis and response time. The mechanism underlying humidity sensitivity was analyzed by complex impedance spectroscopy. The adsorption of water molecules played key roles at low and high humidity, extending the potential application of ferroelectric BiFeO3 films in humidity-sensitive devices.

Green potentiometric determination of some of the third-generation antihistamines: Fexofenadine, Desloratadine, and Levocetirizine by using new carbon paste electrodes

BackgroundThe Current study describes the construction of three carbon paste electrodes for the quantitative measurement of the third-generation antihistamines fexofenadine (FEX), Desloratadine (DES), and Levocetirizine (LEV). The different assembly steps of the sensor are described. The proposed potentiometric method Presents a green, fast, simple, and sensitive procedure for the determination of these drugs in their pure and pharmaceutical forms. ResultsThe quantitative determination of the antihistamines drugs was achieved using the constructed carbon paste electrodes. The presented analytical method obeyed linearity in the concentration range (5 × 10−6–1 × 10−2) M for FEX and DES, (1 × 10−5 – 1 × 10−2) M for LEV. The values of the Nernstian slopes (-57.40, -29.01, -56.01) mV/ decade indicate the closeness of these values from the ideal Nernstian slope value. The limits of quantification (LOQ) were (2.17 × 10−8- 6.31 × 10−8- 3.3 × 10−8) M, respectively. In addition, the electrodes exhibited good selectivity, repeatability (RSD<2%), stability, and fast response time. The method was validated and employed for the determination of the studied drugs in pharmaceutical dosage forms, the average recovery values were (99.13–99.53–99.90)% for FEX, DES, and LEV, respectively. ConclusionOur study included the construction of the first carbon paste electrodes for potentiometric determination of some of the third-generation antihistamines. The findings have shown that carbon paste electrodes excel over the traditional ion -selective electrodes and present an accurate, precise, green, robust, and cost-effective analytical method.

Sensitive Electrochemical Non-Enzymatic Detection of Glucose Based on Wireless Data Transmission.

Miniaturization and wireless continuous glucose monitoring are key factors for the successful management of diabetes. Electrochemical sensors are very versatile and can be easily miniaturized for wireless glucose monitoring. The authors report a microneedle-based enzyme-free electrochemical wireless sensor for painless and continuous glucose monitoring. The microneedles (MNs) fabricated consist of a 3 × 5 sharp and stainless-steel electrode array configuration. Each MN in the 3 × 5 array has 575 µm × 150 µm in height and width, respectively. A glucose-catalyzing layer, porous platinum black, was electrochemically deposited on the tips of the MNs by applying a fixed cathodic current of 2.5 mA cm−2 for a period of 200 s. For the non-interference glucose sensing, the platinum (Pt)-black-coated MN was carefully packaged into a biocompatible ionomer, nafion. The surface morphologies of the bare and modified MNs were studied using field-emission scanning electron microscopy (FESEM) and energy-dispersive X-ray analysis (EDX). The wireless glucose sensor displayed a broad linear range of glucose (1→30 mM), a good sensitivity and higher detection limit of 145.33 μA mM−1 cm−2 and 480 μM, respectively, with bare AuMN as a counter electrode. However, the wireless device showed an improved sensitivity and enhanced detection limit of 445.75, 165.83 μA mM−1 cm−2 and 268 μM, respectively, with the Pt-black-modified MN as a counter electrode. The sensor also exhibited a very good response time (2 s) and a limited interference effect on the detection of glucose in the presence of other electroactive oxidizing species, indicating a very fast and interference-free chronoamperometric response.

Self-biased high sensitivity near-infrared photodetector based on nanocrystalline indium nitride film

Most photodetectors based on nanoparticles have been designed to be powered by an external power source, which is used to simulate the photo-created carriers in order to generate a photocurrent. This clearly increases the weight and size of the device. As a consequence, their applications in areas like in-situ wireless environmental sensing and medical therapy monitoring are strictly limited. Constructing self-powered (0 V bias voltage) systems that can operate autonomously, wirelessly, and sustainably is an important research direction for next-generation nanodevices. In this study, a novel near-infrared self-powered photodetector based on indium nitride nanocrystals (InN-NCs) film that operates without an external power source is fabricated. A cost-effective and simple radio frequency technique was used to growth the film onto silicon substrate. The photodetector has good self-powered photo-response properties under NIR (850 nm) light, including high sensitivity (1300) and good response time (rise time 160 ms and decay time 210 ms).

Flexible and Wireless Normal‐Tangential Force Sensor Based on Resonant Mechanism for Robotic Gripping Applications

AbstractThe ability to detect both normal and tangential forces is essential for robotic tactile systems, while most available sensors implement this function at the cost of complex electrode structure and wiring. Here a fully flexible sensor for wireless detection of normal and tangential force based on resonant mechanism is reported. The components of the sensor are designed and optimized to meet the requirement, and the sensor shows good sensitivity, hysteresis characteristics, response time, and stability in the wired test. Wireless operation is carried out through inductive coupling, and the collected spectrum of reflection coefficient can reflect both normal force and tangential force information. In the case of individual input, the sensitivity is −0.19 MHz kPa−1 to normal force in the range of 0–200 kPa, and −0.031 dB kPa−1 to tangential force in the range of 0–50 kPa. As proofs of concept, maximum static friction coefficient tests and robotic gripping experiments are demonstrated for preliminary determination of surface roughness and material identification respectively. In particular, a total recognition accuracy of 92.5% is achieved by random forest‐based machine learning for balls with different materials in the gripping experiment.

The Response Time of Trauma and non Trauma Patients Handling in Emergency Room Surabaya

Background: Emergency room is one of the unit services in hospitals that provide first services in patients with threat of disability or even death. Emergency room is a service unit in hospital with 24 service hours for 7 days in a week. The high risk and working hours in the emergency room requires the medical personnel that have a good response times in triage room. Objective: To compare response time of medical personnel when handling trauma and non trauma patients in the emergency room. Method: A non-experimental, quantitative research methods using analytic observational. The population of this study was patient in emergency room Soetomo hospital Surabaya. The amount of the sample was 244 which divided into 41 trauma case and 203 non trauma case. Result: Response time of patients with trauma injuries that include quick category (&lt; 5 minutes) amounted to 35 patients and 6 patients in slow category (&gt; 5 minutes) with average response times of trauma patients is 6.244 minutes. Response time of patients with non trauma injuries that include quick category (&lt; 5 minutes) amounted to 161 patients and 42 patients in slow category (&gt;5 minutes) with average response times of non trauma patients is 3.722 minutes. The p value response times of medical personnel in dealing with trauma and non-trauma patients is 0.374 (&gt; 0.05) which means there is no difference in response times from medical personnel in handling trauma and non-trauma patients. Conclusion: There was no difference in the response time of medical personnel in trauma and non-traumatic patients handling (p&gt;0,05). Overall, it was found that the average emergency room’s response time at Soetomo hospital was 4.15 minutes, still meeting the applicable standards.

Engineering 3D‐Architected Gyroid MXene Scaffolds for Ultrasensitive Micromechanical Sensing

A novel piezoresistive sensor based on ultralight 3D MXene scaffold (3DMS) is developed by a facile and architecturally versatile method using additively manufactured, polymer‐based gyroidal triply periodic minimal surface (TPMS) as the initial sacrificial scaffold. A neat MXene scaffold with the gyroidal TPMS structure is prepared by dip coating MXene sheets onto 3D‐printed polymeric Gyroid lattices, followed by thermal treatment. 3DMS exhibits a high compressive strength of 27.18 kPa and a thermal conductivity of 0.3454 W m−1 K−1. The thermal conductivity of the MXene layer in the 3D structure can reach up to 23.88 Wm−1 K−1, which demonstrates that 3DMS has high versatility for all‐in‐one applications, such as thermal insulation, sensors, and energy storage. The 3DMS developed herein combines the high electrical conductivity of MXene (Ti3C2Tx), intricacy of the gyroidal structure, as well as high porosity, offering a promising platform for high‐performance sensors. In addition, the piezoresistive sensor shows extremely high sensitivity (134.48 kPa−1), good response time (477 ms) and recovery time (402 ms), and improvable durability, validating its potentials for measuring pressure distribution in various engineering devices.

Single-phase high-entropy oxide-based chemiresistor: Toward selective and sensitive detection of methane gas for real-time applications

Detecting methane (CH4) with good selectivity is one of the most important safety precautions to prevent catastrophic incidents in the current industrial environment. Detection of small molecular size, inert and nonpolar characteristic gases at trace levels using chemiresistive technique at room temperature is still challenging because of weak adsorption between gas and sensing material. Therefore, we fabricated a single-phase high entropy oxide based chemiresistor and tested it towards the various gases and several hydrocarbons at room temperature, but the sensor displayed a higher selectivity to CH4 gas than other gases. Further, the sensor characteristics revealed a significant response to CH4 gas, good response and recovery time, good long-term stability, and an experimental detection limit of 25 ppm. Besides, the as-fabricated sensor is low-cost, small in size and consumes 50 nW power, much lower than the other commercialized light-based sensors. As proof of concept, the fabricated sensor was utilized to measure CH4 gas in a real-time atmosphere. The sensor reflected response characteristics similar to the controlled environment and recovered without carrier gas. This facile approach sheds light on the rational design of high-entropy oxides, paving the way for mass production and commercialization of ultra-trace gas detection sensors with superior sensing capability.

CdS based chemiresistor with Schottky contact: Toxic gases detection with enhanced sensitivity and selectivity at room temperature

Surmounting the selectivity issue of gas sensors and detecting low ppm concentration of gases is highly significant for widespread deployments of sensors to build networks in applications including vehicular emission, fuel-based household appliances, and industrial emissions. Herein, a strategy is proposed to improve the selectivity and sensitivity of the cadmium sulfide (CdS) based sensor via changes in contact material by utilizing different metals. CdS was deposited via the SILAR method on three different glass substrates which have Au, ITO, and Ag contacts, respectively, through which Schottky barrier height (SBH) was adjusted between CdS and metal contact. CdS was thoroughly verified by structural and morphological characterization techniques. As-fabricated devices were tested, and gas sensing results suggest that Au and ITO contacts have significantly superior selectivity towards NO2 and CO gases over other gases. Further, experimental values reveal that sensors can detect up to 0.3 ppm and 1.25 ppm, respectively. Good selectivity can be attributed to the regulation of the SBH. Additionally, as-fabricated devices displayed good long-term stability and short response and recovery times. The present study may provide a rational design for fabricating a high-performance chemiresistive gas sensor for the detection of sub-ppm levels of hazardous gases present in the environment.

Artificial intelligence (AI)-driven smart glove for object recognition application

The development of soft sensors with high sensitivities and good response time is particularly useful for healthcare and robotics applications. This article presents a smart glove with an object recognition feature using the support vector machine (SVM), a supervised machine learning algorithm. A smart glove was fabricated using five resistive flex sensors, which can be attached on each of the fingers, respectively. The flex sensor was characterized. A microcontroller was used to receive and process the data from the flex sensor and transmit it to a PC for machine learning and prediction. The SVM model was trained using 160 training data set, and the trained model could be used to recognize three objects with different shapes with an accuracy of 91.88%. The proposed AI-based smart glove has shown high accuracy in object recognition. The proposed approach can possibly provide a promising low-cost solution for the healthcare and robotics industries.

Selective, Ultra-Sensitive, and Rapid Detection of Serotonin by Optimized ZnO Nanorod FET Biosensor.

Fluctuation in serotonin (5-HT) level is an essential manifestation of several neurological disorders. In view of such importance, it is necessary to monitor the levels of 5-HT with good sensitivity, selectivity, affordability and low response time. Zinc oxide (ZnO) based field effect transistors (FET) with attributes like minimized noise levels and large on-off ratio are regarded as emerging high performance biosensor platforms. However, their response is significantly non-linear and there has been no appreciable endeavor for improving the non-linearity. In this paper, we have introduced embedded gate electrode encompassing the channel of the FET which improves the uniformity in electric field line distribution through the electrolyte and proportionately enhances the capture of target biomolecule at ultra-low concentrations, thereby increasing the linearity. Further, we have incorporated the optimized parameters of ZnO nanorods reported previously, for rapid and selective detection of 5-HT. It has been observed that the fabricated ZnO FET biosensor lowers the detection limit down to 0.1fM which is at least one order of magnitude lower than the existing reports. The sensor also has wide linear range from 0.1fM to 1nM with a detection time of about 20 minutes. The proposed zinc oxide nanorod-based sensor can be used as an excellent tool for future diagnosis of neurological disorders.

A soft intelligent dressing with pH and temperature sensors for early detection of wound infection.

Wound infection is a common clinical problem. Traditional detection methods can not provide infection early warning information in time. With the development of flexible electronics, flexible wearable devices have been widely used in the field of intelligent monitoring. Here, we describe the development of a soft wound infection monitoring system with pH sensors and temperature sensors. The measurement range of pH was 4–10, the fitting accuracy was 99.8%, and the response time was less than 6 s. The temperature sensor array showed good accuracy and short response times in the range of 30 °C to 40 °C. A series of in vitro tests and the use of a rat model of Staphylococcus aureus infection confirmed that this flexible detection system can monitor the pH and temperature changes occurring in the early stage of infection, which provides an effective reference for clinical application.

Synthesis and characterization of ZnO/CuO nanocomposite for humidity sensor application

Metal oxide nanomaterials shows variety of applications in the field of optoelectronics, semiconductors, catalysis, coatings, solar cells, ceramics, spintronic, biological and sensors. Present paper deals with ZnO/CuO nanocomposite material synthesis, characterization and humidity sensor application. Novelty of this work is to know the high sensitivity of two conjugated n and p type semiconductor metal oxide nanocomposite at various temperatures. Nanocomposite materials are synthesized by microwave-assisted method with the help of room temperature ionic liquid (RTIL). Zinc acetate, Copper acetate, Sodium hydroxide and 1-butyl-3-methyl-imidazolium-tetrafluoroborate ([BMIM]BF4) were used as initial precursors. The obtained nanocomposite materials were annealed at different temperatures such as 500 °C, 600 °C, 700 °C and 800 °C. These annealed nanocomposite materials have been characterized by X-ray diffractometer (XRD), Particle size analyzer (PSA), Scanning electron microscope (SEM), Energy dispersive x-ray spectrometer (EDS) and Thermo gravimetric and differential thermal analyzer (TG/DTA) for analyze crystal structure, average particle size, surface morphology, elemental analysis and weight loss respectively. The humidity sensor application was predicted by controlled humidity chamber, hygrometer and digital multi meter. The resistance of the sensing element measured with respect to relative humidity from 10% to 98%. The sensitivity of the nanocomposite material increased from 1.7 % to 2.3 % along with increasing of annealing temperature 500 °C to 800 °C. ZnO/CuO nanocomposite annealed at 800 °C shows high sensitivity means it is also having good response and recovery times.

Synthesis and characterization of ZnS-based quantum dots to trace low concentration of ammonia

In the present work, a solution-based co-precipitation method has been adopted to synthesize pure and cobalt-doped ZnS quantum dots and characterized by XRD, SEM, TEM with EDX, FTIR and gas sensing properties. XRD analysis has shown a single phase of ZnS quantum dots having a zinc blend structure. TEM and XRD line broadening indicated that the average crystallite size in the sample is in the range of 2 to 5 nm. SEM micrographs show spherical-shaped quantum dots. FTIR studies show that cobalt has been successfully doped into the ZnS cubic lattice. EDX spectra have analyzed the elemental presence in the samples and it is evident that the spectra confirmed the presence of cobalt (Co), zinc (Zn), oxygen (O), and sulphur (S) elements only and no other impurities are observed. The ZnS-based quantum dot sensors reveal high sensitivity towards 50 ppm of ammonia vapors at an operating temperature of 70 °C. Hence, ZnS-based quantum dots can be a promising and quick traceable sensor towards ammonia sensing applications with good response and recovery time.

Highly Stable Potentiometric (Bio)Sensor for Urea and Urease Activity Determination.

There is growing interest for bioanalytical tools that might be designed for a specific user, primarily for research purposes. In this perspective, a new, highly stable potentiometric sensor based on glassy carbon/polyazulene/NH4+-selective membrane was developed and utilized for urease activity determination. Urease–urea interaction studies were carried out and the Michaelis–Menten constant was established for this enzymatic reaction. Biofunctionalization of the ammonium ion-selective sensor with urease lead to urea biosensor with remarkably good potential stability (drift coefficient ~0.9 mV/h) and short response time (t95% = 36 s). The prepared biosensor showed the Nernstian response (S = 52.4 ± 0.7 mV/dec) in the urea concentration range from 0.01 to 20 mM, stable for the experimental time of 60 days. In addition, some insights into electrical properties of the ion-to-electron transducing layer resulting from impedance spectroscopy measurements are presented. Based on the RCQ equivalent circuits comparison, it can be drawn that the polyazulene (PAz) layer shows the least capacitive behavior, which might result in good time stability of the sensor in respect to response as well as potential E0. Both the polyazulene-based solid-contact ion selective electrodes and urea biosensors were successfully used in trial studies for determination of ammonium ion and urea in human saliva samples. The accuracy of ammonium ion and urea levels determination by potentiometric method was confirmed by two reference spectrophotometric methods.

Overview of surface plasmon resonance optical sensors for Covid-19 (SARS-CoV-2) detection

The SARS-CoV-2 i.e., the novel severe acute respiratory syndrome corona virus; has caused massive loss of life. Mitigating this pandemic requires rapid inexpensive technologies for testing COVID-19. Optical sensors can be used to detect the Covid-19 virus by the surface Plasmon resonance phenomenon. Surface plasmon resonance sensors have good sensitivity, response times, fine resolution, and limits of detection. This paper, provides a brief overview on the COVID-19 effects, currently used testing technology, and potential of surface plasmon resonance optical sensors use for detecting this virus.

Characterization of Flexible Multi-Walled Carbon Nanotubes Network Sensor to Freon Gas Detection

MWCNTs-OH was used to prepare a flexible gas sensor by deposition as a network on a filter cake using the method of filtration from suspension (FFS). The morphological and structural properties of the MWCNTs network were characterized before and after exposure to Freon gas using FTIR spectra and X-ray diffractometer, which confirmed that the characteristics of the sensor did not change after exposure to the gas. The sensor was exposed to a pure Freon134a gas as well as to a mixture of Freon gas and air with different ratios at room temperature. The experiments showed that the sensor works at room temperature and the sensitivity values increased with increasing operating temperature, to be 58% until 150 ºC. The fabricated flexible sensor has good response and recovery times at low gas concentrations of 1.3, 2, and 2.7 ppm.

Classical and quantum regression analysis for the optoelectronic performance of NTCDA/p-Si UV photodiode

Due to the pivotal role of UV photodiodes in many technological applications in tandem with the high efficiency achieved by machine learning techniques in regression and classification problems, different artificial intelligence techniques are adopted to simulate and model the performance of organic/inorganic heterojunction UV photodiode. Herein, the performance of a fabricated Au/NTCDA/p-Si/Al photodiode is explained in a detailed manner and has shown an excellent responsivity and detectivity for UV light of intensities ranging from 20 to 80mW/cm2. A linear current–irradiance relationship is exhibited by the fabricated photodiode under illumination up to 65mW/cm2. It also shows good response times of trise=408ms and tfall=490ms. Furthermore, we have not only fitted the characteristic I-V curve but also evaluated three classical algorithms; K-Nearest Neighbour, Artificial Neural Network, and Genetic Programming besides using a Quantum Neural Network to predict the behavior of the device. The models have achieved outstanding results and managed to capture the trend of the target values. The Quantum Neural Network has been used for the first time to model the photodiode characteristics. The trained models are of great significance since they can be used to reduce the characterization and measurement times.