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This letter presents a study on the imaging capabilities of a mixed-mode fibre cantilever-based endoscopic scanner using cladding mode and multimode core detection methods. Characterization of the mixed-mode fibre cantilever was performed to determine the properties of the fibre cantilever and assess the capability of detection via the multimode core detection. Furthermore, we demonstrated the capabilities of these detection modes by imaging cellular samples. The findings reveal that cladding mode detection provides a bright image of the cellular structures with the $16.8~\mu $ m nucleus. Meanwhile, the images obtained from the multimode core detection reveal the irregularities on the surface, producing a pseudo-three-dimensional image of the sample. The application of multiple detection methods in the endoscopic scanner opens up new potential for more comprehensive optical imaging applications.

This work highlights the development of zeolitic-imidazolate frameworks 8 (ZIFs-8) to enhance surface plasmon resonance (SPR) sensor for methylene blue compound detection. ZIF-8 was synthesized via the solvothermal method. XRD results show the appearance of diffraction peaks at $2\theta = 7.4^{\circ }$ , 10.4°, 12.7°, and 18.0°, which are assigned to 011, 002, 112, 022, 013, and 222 lattice planes, respectively, confirming the high crystalline ZIF-8 produced. The X-ray photoelectron spectroscopy (XPS) analysis exhibits the presence of C, O, Zn, and N elements on the surface of the ZIF-8 structure. Methylene blue was detected through the donor-acceptor interaction of a lone pair of Zn atoms in ZIF-8 with methylene blue. These two materials can also interact through $\pi $ – $\pi $ interactions because both ZIF-8 and methylene blue possess aromatic rings in their structure. The FESEM characterization shows a uniform particle size produced on a surface of Au thin film in the 100–130-nm range. A good sensitivity of 1.3821° ppm $^{-{1}}$ with a detection and quantification limit of 0.92 and 2.79 ppm, respectively, was obtained for the SPR sensor using ZIF-8 as a sensing material at a low methylene blue concentration range in comparison to bare Au. Nonetheless, the steepness of the graph started to decline after 1 ppm methylene blue concentration due to the fully occupied active sites on the surface of ZIF-8. In the selectivity study, a prominent SPR shift was observed when ZIF-8 interacted with methylene blue, compared to other interferences, proving that ZIF-8 has a good selectivity toward methylene blue.

This study introduces a new approach to enhance the measurement speed in the suggested system-on-chip (SoC) by incorporating quadratic least mean square (LMS) filtering with moving average (MA) and moving median (MM) filters at a low-averaging stage. The use of MA and MM filters in the frequency and time domains yields a significant enhancement in the reliability and accuracy of the Brillouin frequency shift (BFS). Our method, as demonstrated in this study, exhibits a significantly reduced latency, which ranges from 14 to 1563 times faster than Brillouin optical time-domain analysis (BOTDA) systems that rely on an oscilloscope and a computer for data processing, and the BOTDA system utilizing SoC with LMS filtering alone. Compared with LMS curve fitting alone, the implementation of this technique greatly enhances accuracy with low averages by 84%. These filters enable the identification of minor disruptions along the cable. The proposed method successfully detects small variations in Brillouin frequency while maintaining the spatial resolution of sensors. The deployed filters result in a spatial resolution ranging from 1.6 to 1.5 m, which demonstrates greater constancy than the normal range of 2–1.6 m. This study successfully employs filtering techniques in the frequency and time domains by incorporating low averaging and a broad dynamic range. The use of SoC technology in BOTDA improves measurement speed, accuracy, and the preservation of spatial resolution constancy. However, the measurable fiber length is limited due to ac coupling on the analog-to-digital converter board. The algorithm and dataset are publicly available at GitHub.

Diabetic foot ulceration (DFU) could potentially be avoided by continuously monitoring plantar (foot sole) temperature at home to alert the onset of tissue breakdown. Systems, which can measure plantar temperature in real-time, have limited availability and are relatively expensive. We report on the synthesis, design, characterization, and implementation of a laser-induced graphene (LIG) based smart insole capable of measuring plantar temperature and pressure continuously and generating and storing the plantar temperature maps. Our proposed solution is lightweight, cheaper, and comparable in sensitivity, Limit of Detection, Range of Detection, Response Time, and Recovery time to other available solutions. This is the first study to utilize LIG in insoles to generate temperature maps that effectively identify patients with severe DSPN and those at high risk of DFU.

Diabetic sensorimotor polyneuropathy (DSPN) leads to pain, diabetic foot ulceration (DFU), amputation, and death. The diagnosis of advanced DSPN to identify those at risk is key to preventing DFU and amputation. Alterations in foot pressure and temperature may help to detect DSPN and the risk of DFU. We have applied a robust machine-learning approach to identify patients with severe DSPN using standing foot temperature maps generated using temperature sensor data. A robust shallow operational neural network model DSPNet is proposed. The study utilized a labeled dataset from the University Hospital Magdeburg, Magdeburg, Germany, consisting of temperature sensor data from eight different points on the foot in seating and standing positions in patients with severe DSPN ( $n =25$ ) and healthy controls ( $n =18$ ). The proposed network achieved an F1 score of 90.3% for identifying patients with DSPN and outperformed current state-of-the-art deep-learning network methods. This is the first of its kind of research where the results confirm that temperature maps are not only effective in the detection of those at high risk of DFU but also in identifying patients with severe DSPN. Such sensors could easily be incorporated into smart insoles.

The staggering innovations and emergence of numerous deep learning (DL) applications have forced researchers to reconsider hardware architecture to accommodate fast and efficient application-specific computations. Applications, such as object detection, image recognition, speech translation, as well as music synthesis and image generation, can be performed with high accuracy at the expense of substantial computational resources using DL. Furthermore, the desire to adopt Industry 4.0 and smart technologies within the Internet of Things infrastructure has initiated several studies to enable on-chip DL capabilities for resource-constrained devices. Specialized DL processors reduce dependence on cloud servers, improve privacy, lessen latency, and mitigate bandwidth congestion. As we reach the limits of shrinking transistors, researchers are exploring various application-specific hardware architectures to meet the performance and efficiency requirements for DL tasks. Over the past few years, several software optimizations and hardware innovations have been proposed to efficiently perform these computations. In this article, we review several DL accelerators, as well as technologies with emerging devices, to highlight their architectural features in application-specific integrated circuit (IC) and field-programmable gate array (FPGA) platforms. Finally, the design considerations for DL hardware in portable applications have been discussed, along with some deductions about the future trends and potential research directions to innovate DL accelerator architectures further. By compiling this review, we expect to help aspiring researchers widen their knowledge in custom hardware architectures for DL.

The synthesis of novel material 1,4‐bis[2‐(5‐thiophen‐2‐yl)‐1‐benzothiophene]‐2,5‐dioctyloxybenzene pentamer (BOBzBT2) was carried out via Williamson etherification, bromination, and Suzuki coupling. Functionalization was carried out via the incorporation of dioctyloxy‐substituents on phenylene moiety to improve its solubility. The elongation of the π‐conjugation backbone was carried out through the addition of benzo[b]thiophene rings of BOBzBT2to accelerate cation radicals′ formation. In FTIR, the disappearance of the stretching peak of υ(CBr) at 657 cm−1confirms the coupling of benzo[b]thiophene rings end‐capped the BOBzBT2UV‐visible shows the appearance of two broad bands at 343 nm and 422 nm, that related to π‐π* transition between thiophene and bithiophene groups with 2,5‐bis(dioctyloxy)benzene moiety in the π‐conjugated backbone, respectively. DSC shows that the BOBzBT2is a high purity compound. A gradual relaxation occurred between BOBzBT2with creatinine as observed in UV‐visible analysis. It is expected that the BOBzBT2sensed creatinine via NH−S and NH−O hydrogen bonding interactions. A novel material of 1,4‐bis[2‐(5‐thiophen‐2‐yl)‐1‐benzothiophene]‐2,5‐dioctyloxybenzene pentamer (BOBzBT2)was synthesized. In FTIR, the disappearance of the stretching peak of υ(CBr) at 657 cm−1confirms the coupling of benzo[b]thiophene rings end‐capped the BOBzBT2. The appearance of two broad bands at 343 nm and 422 nm in UV‐visible is related to π–* transition between thiophene and bithiophene groups with 2,5‐bis(dioctyloxy)benzene moiety in the π‐conjugated backbone, respectively. It is expected that the BOBzBT2sensed creatinine via NH−S and NH−O hydrogen bonding interactions.

Two-dimensional-material-based photodetectors are gaining prominence in optoelectronic applications, but there are certain factors to consider with bulk material usage. The demand for a highly responsive and highly efficient device with an inexpensive fabrication method is always of paramount importance. Carbon nanotubes (CNT) are well known, owing to their upheld vigorous structural and optoelectronic characteristics, but to fabricate them at a large scale involves multifarious processes. A visible range photodetector device structure developed using a simple and inexpensive drop-casting technique is reported here. The optoelectronic characteristics of the device are studied with IV measurements under the light and dark conditions by incorporating a thin CNT layer on top of tungsten-disulfide-based heterojunction photodetector to enhance the overall characteristics such as detectivity, responsivity, photocurrent, rise time, and fall time in the visible range of the light spectrum with a violet light source at 441 nm. In the DC bias voltage range of −20 to 20 V, IV measurements are carried out under dark and illumination conditions with different incident power densities. The threshold voltage is recognized at 2.0 V. Photocurrent is found to be highly dependent on the state of the incident light. For 0.3074mW/cm^2 illuminated power, the highest responsivity and detectivity are determined to be 0.57 A/W and 2.89×10^11 Jones. These findings encourage an alternative fabrication method at a large scale to grow CNTs for the enhancement of optoelectronic properties of present two-dimensional-material-based optoelectronic and photonics applications.

In the realm of optoelectronics to produce thin film, SWCNT (Single-Walled Carbon Nanotube) is a promising alternative to Indium Tin Oxide (ITO). However, it is still challenging to manufacture SWCNT thin film that is low-cost, homogenous and has minimal sheet resistance. In this work, SWCNT thin films were deposited by using the automated spray coating method. To enhance the film quality and optoelectronic characteristics, post-deposition treatment through nitric acid vapor was carried out. The optimized SWCNT thin films exhibited optical transparency in the range of 60.4% at 800 nm and sheet resistance of 6.6 Ω/square. The sheet resistance of our fabricated SWCNT thin films was lower than the value of ITO films (10 Ω/square), putting forth evidence which suggests the potential of SWCNTs as an alternative to ITO.

AbstractSemiconductor optical amplifier (SOA) is one of the commonly used amplifiers in optical networks. This paper reviews the SOA implementation in coarse wavelength division multiplexing (CWDM) systems, which includes the explanation of the fundamental concepts such as the configuration, principle of operation as amplifiers, and the performance in different CWDM topologies. Simulation using OptiSystem software was carried out to determine the gain saturation at high input power and longer wavelengths. It shows that SOA implementation in CWDM networks is capable of providing flat gain for 40 nm wavelength span.

Choosing methods to assess student program outcomes is a matter of balancing best practices against the constraints imposed by the respective education authorities mainly the Engineering Accreditation Council (EAC) for engineering degrees offered by institutions of higher education in Malaysia. Methods that directly measure student learning and yield the most rigorous results are usually the most time consuming and may require the expertise of educational researchers or outside consultants. Currently, the Department of Electrical, Electronics and Systems Engineering at UKM use their classroom and existing grading practices to collect data that will contribute to assess student learning directly, but this requires extra time and effort. In addition, mechanisms to adequately report the findings need to be properly implemented. Another mechanism that could be used to assess student program outcomes is through a thoroughly designed student exit strategy. The exit strategy implemented this academic year involves two parts; exit survey and exit test. This is a Continuous Quality Improvement (CQI) effort done since the past two academic years that enables the department to assess student program outcomes directly and indirectly in one approach. The exit strategy has proven successful as a valid measurement of student program outcomes. The exit strategy which combines both direct and indirect assessment forms a comprehensive and robust tool to effectively measure student program outcomes.