A gas sensor array was developed in a 10 × 10 mm(2) space using Screen Printing and Pulse Laser Ablation Deposition (PLAD) techniques. Heater, electrode, and an insulator interlayer were printed using the screen printing method on an alumina substrate, while tin oxide and platinum films, as sensing and catalyst layers, were deposited on the electrode at room temperature using the PLAD method, respectively. To ablate SnO(2) and Pt targets, depositions were achieved by using a 1,064 nm Nd-YAG laser, with a power of 0.7 J/s, at different deposition times of 2, 5 and 10 min, in an atmosphere containing 0.04 mbar (4 kPa) of O(2). A range of spectroscopic diffraction and real space imaging techniques, SEM, EDX, XRD, and AFM were used in order to characterize the surface morphology, structure, and composition of the films. Measurement on the array shows sensitivity to some solvent and wood smoke can be achieved with short response and recovery times.
Fabrication of a test strip for detection of benzoic acid was successfully implemented by immobilizing tyrosinase, phenol and 3-methyl-2-benzothiazolinone hydrazone (MBTH) onto filter paper using polystyrene as polymeric support. The sensing scheme was based on the decreasing intensity of the maroon colour of the test strip when introduced into benzoic acid solution. The test strip was characterized using optical fiber reflectance and has maximum reflectance at 375 nm. It has shown a highly reproducible measurement of benzoic acid with a calculated RSD of 0.47% (n = 10). The detection was optimized at pH 7. A linear response of the biosensor was obtained in 100 to 700 ppm of benzoic acid with a detection limit (LOD) of 73.6 ppm. At 1:1 ratio of benzoic acid to interfering substances, the main interfering substance is boric acid. The kinetic analyses show that, the inhibition of benzoic is competitive inhibitor and the inhibition constant (K(i)) is 52.9 ppm. The activity of immobilized tyrosinase, phenol, and MBTH in the test strip was fairly sustained during 20 days when stored at 3 °C. The developed test strip was used for detection of benzoic acid in food samples and was observed to have comparable results to the HPLC method, hence the developed test strip can be used as an alternative to HPLC in detecting benzoic acid in food products.
A Schottky diode has been designed and fabricated on an n-AlGaAs/GaAs high-electron-mobility-transistor (HEMT) structure. Current-voltage (I-V) measurements show good device rectification, with a Schottky barrier height of 0.4349 eV for Ni/Au metallization. The differences between the Schottky barrier height and the theoretical value (1.443 eV) are due to the fabrication process and smaller contact area. The RF signals up to 1 GHz are rectified well by the fabricated Schottky diode and a stable DC output voltage is obtained. The increment ratio of output voltage vs input power is 0.2 V/dBm for all tested frequencies, which is considered good enough for RF power detection. Power conversion efficiency up to 50% is obtained at frequency of 1 GHz and input power of 20 dBm with series connection between diode and load, which also shows the device's good potential as a rectenna device with further improvement. The fabricated n-AlGaAs/GaAs Schottky diode thus provides a conduit for breakthrough designs for RF power detectors, as well as ultra-low power on-chip rectenna device technology to be integrated in nanosystems.
The major compounds in honey are carbohydrates such as monosaccharides and disaccharides. The same compounds are found in cane-sugar concentrates. Unfortunately when sugar concentrate is added to honey, laboratory assessments are found to be ineffective in detecting this adulteration. Unlike tracing heavy metals in honey, sugar adulterated honey is much trickier and harder to detect, and traditionally it has been very challenging to come up with a suitable method to prove the presence of adulterants in honey products. This paper proposes a combination of array sensing and multi-modality sensor fusion that can effectively discriminate the samples not only based on the compounds present in the sample but also mimic the way humans perceive flavours and aromas. Conversely, analytical instruments are based on chemical separations which may alter the properties of the volatiles or flavours of a particular honey. The present work is focused on classifying 18 samples of different honeys, sugar syrups and adulterated samples using data fusion of electronic nose (e-nose) and electronic tongue (e-tongue) measurements. Each group of samples was evaluated separately by the e-nose and e-tongue. Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) were able to separately discriminate monofloral honey from sugar syrup, and polyfloral honey from sugar and adulterated samples using the e-nose and e-tongue. The e-nose was observed to give better separation compared to e-tongue assessment, particularly when LDA was applied. However, when all samples were combined in one classification analysis, neither PCA nor LDA were able to discriminate between honeys of different floral origins, sugar syrup and adulterated samples. By applying a sensor fusion technique, the classification for the 18 different samples was improved. Significant improvement was observed using PCA, while LDA not only improved the discrimination but also gave better classification. An improvement in performance was also observed using a Probabilistic Neural Network classifier when the e-nose and e-tongue data were fused.
This paper reports the design of an electronic nose (E-nose) prototype for reliable measurement and correct classification of beverages. The prototype was developed and fabricated in the laboratory using commercially available metal oxide gas sensors and a temperature sensor. The repeatability, reproducibility and discriminative ability of the developed E-nose prototype were tested on odors emanating from different beverages such as blackcurrant juice, mango juice and orange juice, respectively. Repeated measurements of three beverages showed very high correlation (r > 0.97) between the same beverages to verify the repeatability. The prototype also produced highly correlated patterns (r > 0.97) in the measurement of beverages using different sensor batches to verify its reproducibility. The E-nose prototype also possessed good discriminative ability whereby it was able to produce different patterns for different beverages, different milk heat treatments (ultra high temperature, pasteurization) and fresh and spoiled milks. The discriminative ability of the E-nose was evaluated using Principal Component Analysis and a Multi Layer Perception Neural Network, with both methods showing good classification results.
This paper reports the design, characterization and implementation of a fiber Bragg grating (FBG)-based temperature sensor for an insulted-gate Bipolar transistor (IGBT) in a solar panel inverter. The FBG is bonded to the higher coefficient of thermal expansion (CTE) side of a bimetallic strip to increase its sensitivity. Characterization results show a linear relationship between increasing temperature and the wavelength shift. It is found that the sensitivity of the sensor can be categorized into three characterization temperature regions between 26 °C and 90 °C. The region from 41 °C to 90 °C shows the highest sensitivity, with a value of 14 pm/°C. A new empirical model that considers both temperature and strain effects has been developed for the sensor. Finally, the FBG-bimetal temperature sensor is placed in a solar panel inverter and results confirm that it can be used for real-time monitoring of the IGBT temperature.
New acrylic microspheres were synthesised by photopolymerisation where the succinimide functional group was incorporated during the microsphere preparation. An optical biosensor for urea based on reflectance transduction with a large linear response range to urea was successfully developed using this material. The biosensor utilized succinimide-modified acrylic microspheres immobilized with a Nile blue chromoionophore (ETH 5294) for optical detection and urease enzyme was immobilized on the surface of the microspheres via the succinimide groups. No leaching of the enzyme or chromoionophore was observed. Hydrolysis of the urea by urease changes the pH and leads to a color change of the immobilized chromoionophore. When the color change was monitored by reflectance spectrophotometry, the linear response range of the biosensor to urea was from 0.01 to 1,000 mM (R2 = 0.97) with a limit of detection of 9.97 μM. The biosensor response showed good reproducibility (relative standard deviation = 1.43%, n = 5) with no interference by major cations such as Na+, K+, NH4+ and Mg2+. The use of reflectance as a transduction method led to a large linear response range that is better than that of many urea biosensors based on other optical transduction methods.
This paper presents an acoustic noise cancelling technique using an inverse kepstrum system as an innovations-based whitening application for an adaptive finite impulse response (FIR) filter in beamforming structure. The inverse kepstrum method uses an innovations-whitened form from one acoustic path transfer function between a reference microphone sensor and a noise source so that the rear-end reference signal will then be a whitened sequence to a cascaded adaptive FIR filter in the beamforming structure. By using an inverse kepstrum filter as a whitening filter with the use of a delay filter, the cascaded adaptive FIR filter estimates only the numerator of the polynomial part from the ratio of overall combined transfer functions. The test results have shown that the adaptive FIR filter is more effective in beamforming structure than an adaptive noise cancelling (ANC) structure in terms of signal distortion in the desired signal and noise reduction in noise with nonminimum phase components. In addition, the inverse kepstrum method shows almost the same convergence level in estimate of noise statistics with the use of a smaller amount of adaptive FIR filter weights than the kepstrum method, hence it could provide better computational simplicity in processing. Furthermore, the rear-end inverse kepstrum method in beamforming structure has shown less signal distortion in the desired signal than the front-end kepstrum method and the front-end inverse kepstrum method in beamforming structure.
A new patterning method using Deoxyribose Nucleic Acid (DNA) strands capable of producing nanogaps of less than 100 nm is proposed and investigated in this work. DNA strands from Bosenbergia rotunda were used as the fundamental element in patterning DNA on thin films of aluminium (Al) metal without the need for any lithographic techniques. The DNA strands were applied in buffer solutions onto thin films of Al on silicon (Si) and the chemical interactions between the DNA strands and Al creates nanometer scale arbitrary patterning by direct transfer of the DNA strands onto the substrate. This simple and cost-effective method can be utilized in the fabrication of various components in electronic chips for microelectronics and Nano Electronic Mechanical System (NEMS) applications in general.
In this paper, a personal verification method using finger vein is presented. Finger vein can be considered more secured compared to other hands based biometric traits such as fingerprint and palm print because the features are inside the human body. In the proposed method, a new texture descriptor called local line binary pattern (LLBP) is utilized as feature extraction technique. The neighbourhood shape in LLBP is a straight line, unlike in local binary pattern (LBP) which is a square shape. Experimental results show that the proposed method using LLBP has better performance than the previous methods using LBP and local derivative pattern (LDP).
Nanocrystalline SnO(x) (x = 1-2) thin films were prepared on glass substrates by a simple chemical bath deposition method. Triethanolamine was used as complexing agent to decrease time and temperature of deposition and shift the pH of the solution to the noncorrosive region. The films were characterized for composition, surface morphology, structure and optical properties. X-ray diffraction analysis confirms that SnO(x) thin films consist of a polycrystalline structure with an average grain size of 36 nm. Atomic force microscopy studies show a uniform grain distribution without pinholes. The elemental composition was evaluated by energy dispersive X-ray spectroscopy. The average O/Sn atomic percentage ratio is 1.72. Band gap energy and optical transition were determined from optical absorbance data. The film was found to exhibit direct and indirect transitions in the visible spectrum with band gap values of about 3.9 and 3.7 eV, respectively. The optical transmittance in the visible region is 82%. The SnO(x) nanocrystals exhibit an ultraviolet emission band centered at 392 nm in the vicinity of the band edge, which is attributed to the well-known exciton transition in SnO(x). Photosensitivity was detected in the positive region under illumination with white light.
Behavioural assessment of experimental pain is an essential method for analysing and measuring pain levels. Rodent models, which are widely used in behavioural tests, are often subject to external forces and stressful manipulations that cause variability of the parameters measured during the experiment. Therefore, these parameters may be inappropriate as indicators of pain. In this article, a stepping-force analgesimeter was designed to investigate the variations in the stepping force of rats in response to pain induction. The proposed apparatus incorporates new features, namely an infrared charge-coupled device (CCD) camera and a data acquisition system. The camera was able to capture the locomotion of the rats and synchronise the stepping force concurrently so that each step could be identified. Inter-day and intra-day precision and accuracy of each channel (there were a total of eight channels in the analgesimeter and each channel was connected to one load cell and one amplifier) were studied using different standard load weights. The validation studies for each channel also showed convincing results whereby intra-day and inter-day precision were less than 1% and accuracy was 99.36-100.36%. Consequently, an in vivo test was carried out using 16 rats (eight females and eight males). The rats were allowed to randomly walk across the sensor tunnel (the area that contained eight channels) and the stepping force and locomotion were recorded. A non-expert, but from a related research domain, was asked to differentiate the peaks of the front and hind paw, respectively. The results showed that of the total movement generated by the rats, 50.27 ± 3.90% in the case of the male rats and 62.20 ± 6.12% in that of the female rats had more than two peaks, a finding which does not substantiate the assumptions made in previous studies. This study also showed that there was a need to use the video display frame to distinguish between the front and hind paws in the case of 48.80 ± 4.01% of the male rats and 66.76 ± 5.35% of the female rats. Evidently the assumption held by current researchers regarding stepping force measurement is not realistic in terms of application, and as this study has shown, the use of a video display frame is essential for the identification of the front and hind paws through the peak signals.
This paper presents the development of a PC-based microwave five-port reflectometer for the determination of moisture content in oil palm fruits. The reflectometer was designed to measure both the magnitude and phase of the reflection coefficient of any passive microwave device. The stand-alone reflectometer consists of a PC, a microwave source, diode detectors and an analog to digital converter. All the measurement and data acquisition were done using Agilent VEE graphical programming software. The relectometer can be used with any reflection based microwave sensor. In this work, the application of the reflectometer as a useful instrument to determine the moisture content in oil palm fruits using monopole and coaxial sensors was demonstrated. Calibration equations between reflection coefficients and moisture content have been established for both sensors. The equation based on phase measurement of monopole sensor was found to be accurate within 5% in predicting moisture content in the fruits when compared to the conventional oven drying method.
Radio frequency identification (RFID) systems are emerging as the primary object identification mechanism, especially in supply chain management. However, RFID naturally generates a large amount of duplicate readings. Removing these duplicates from the RFID data stream is paramount as it does not contribute new information to the system and wastes system resources. Existing approaches to deal with this problem cannot fulfill the real time demands to process the massive RFID data stream. We propose a data filtering approach that efficiently detects and removes duplicate readings from RFID data streams. Experimental results show that the proposed approach offers a significant improvement as compared to the existing approaches.
The use of the enzyme alanine dehydrogenase (AlaDH) for the determination of ammonium ion (NH(4)(+)) usually requires the addition of pyruvate substrate and reduced nicotinamide adenine dinucleotide (NADH) simultaneously to effect the reaction. This addition of reagents is inconvenient when an enzyme biosensor based on AlaDH is used. To resolve the problem, a novel reagentless amperometric biosensor using a stacked methacrylic membrane system coated onto a screen-printed carbon paste electrode (SPE) for NH(4)(+) ion determination is described. A mixture of pyruvate and NADH was immobilized in low molecular weight poly(2-hydroxyethyl methacrylate) (pHEMA) membrane, which was then deposited over a photocured pHEMA membrane (photoHEMA) containing alanine dehydrogenase (AlaDH) enzyme. Due to the enzymatic reaction of AlaDH and the pyruvate substrate, NH(4)(+) was consumed in the process and thus the signal from the electrocatalytic oxidation of NADH at an applied potential of +0.55 V was proportional to the NH(4)(+) ion concentration under optimal conditions. The stacked methacrylate membranes responded rapidly and linearly to changes in NH(4)(+) ion concentrations between 10-100 mM, with a detection limit of 0.18 mM NH(4)(+) ion. The reproducibility of the amperometrical NH(4)(+) biosensor yielded low relative standard deviations between 1.4-4.9%. The stacked membrane biosensor has been successfully applied to the determination of NH(4)(+) ion in spiked river water samples without pretreatment. A good correlation was found between the analytical results for NH(4)(+) obtained from the biosensor and the Nessler spectrophotometric method.
Sensing and communication coverage are among the most important trade-offs in Wireless Sensor Network (WSN) design. A minimum bound of sensing coverage is vital in scheduling, target tracking and redeployment phases, as well as providing communication coverage. Some methods measure the coverage as a percentage value, but detailed information has been missing. Two scenarios with equal coverage percentage may not have the same Quality of Coverage (QoC). In this paper, we propose a new coverage measurement method using Delaunay Triangulation (DT). This can provide the value for all coverage measurement tools. Moreover, it categorizes sensors as 'fat', 'healthy' or 'thin' to show the dense, optimal and scattered areas. It can also yield the largest empty area of sensors in the field. Simulation results show that the proposed DT method can achieve accurate coverage information, and provides many tools to compare QoC between different scenarios.
The sensing responses in aqueous solution of an open-gated pH sensor fabricated on an AlGaN/GaN high-electron-mobility-transistor (HEMT) structure are investigated. Under air-exposed ambient conditions, the open-gated undoped AlGaN/GaN HEMT only shows the presence of a linear current region. This seems to show that very low Fermi level pinning by surface states exists in the undoped AlGaN/GaN sample. In aqueous solution, typical current-voltage (I-V) characteristics with reasonably good gate controllability are observed, showing that the potential of the AlGaN surface at the open-gated area is effectively controlled via aqueous solution by the Ag/AgCl gate electrode. The open-gated undoped AlGaN/GaN HEMT structure is capable of distinguishing pH level in aqueous electrolytes and exhibits linear sensitivity, where high sensitivity of 1.9 mA/pH or 3.88 mA/mm/pH at drain-source voltage, V(DS) = 5 V is obtained. Due to the large leakage current where it increases with the negative gate voltage, Nernstian like sensitivity cannot be determined as commonly reported in the literature. This large leakage current may be caused by the technical factors rather than any characteristics of the devices. Surprisingly, although there are some imperfections in the device preparation and measurement, the fabricated devices work very well in distinguishing the pH levels. Suppression of current leakage by improving the device preparation is likely needed to improve the device performance. The fabricated device is expected to be suitable for pH sensing applications.
In this study, the ability of the Capillary-attached conductive gas sensor (CGS) in real-time gas identification was investigated. The structure of the prototype fabricated CGS is presented. Portions were selected from the beginning of the CGS transient response including the first 11 samples to the first 100 samples. Different feature extraction and classification methods were applied on the selected portions. Validation of methods was evaluated to study the ability of an early portion of the CGS transient response in target gas (TG) identification. Experimental results proved that applying extracted features from an early part of the CGS transient response along with a classifier can distinguish short-chain alcohols from each other perfectly. Decreasing time of exposition in the interaction between target gas and sensing element improved the reliability of the sensor. Classification rate was also improved and time of identification was decreased. Moreover, the results indicated the optimum interval of the early transient response of the CGS for selecting portions to achieve the best classification rates.
This research investigates the use of charge coupled device (abbreviated as CCD) linear image sensors in an optical tomographic instrumentation system used for sizing particles. The measurement system, consisting of four CCD linear image sensors are configured around an octagonal shaped flow pipe for a four projections system is explained. The four linear image sensors provide 2,048 pixel imaging with a pixel size of 14 micron × 14 micron, hence constituting a high-resolution system. Image reconstruction for a four-projection optical tomography system is also discussed, where a simple optical model is used to relate attenuation due to variations in optical density, [R], within the measurement section. Expressed in matrix form this represents the forward problem in tomography [S] [R] = [M]. In practice, measurements [M] are used to estimate the optical density distribution by solving the inverse problem [R] = [S](-1)[M]. Direct inversion of the sensitivity matrix, [S], is not possible and two approximations are considered and compared-the transpose and the pseudo inverse sensitivity matrices.
An improved classification of Orthosiphon stamineus using a data fusion technique is presented. Five different commercial sources along with freshly prepared samples were discriminated using an electronic nose (e-nose) and an electronic tongue (e-tongue). Samples from the different commercial brands were evaluated by the e-tongue and then followed by the e-nose. Applying Principal Component Analysis (PCA) separately on the respective e-tongue and e-nose data, only five distinct groups were projected. However, by employing a low level data fusion technique, six distinct groupings were achieved. Hence, this technique can enhance the ability of PCA to analyze the complex samples of Orthosiphon stamineus. Linear Discriminant Analysis (LDA) was then used to further validate and classify the samples. It was found that the LDA performance was also improved when the responses from the e-nose and e-tongue were fused together.