The Improvement of first Iteration Log Periodic Fractal Koch Antenna with Slot Implementation

In this paper, a slotted is introduced at each of the radiating elements on the 1st iteration log periodic fractal Koch antenna (LPFKA). The antenna is designed to testify the appropriate performance at UHF Digital television which operates from 4.0 GHz to 1.0 GHz. The dimension of the conventional 0th iteration LPKFA is successfully reduced by 17% with the implementation of slotted. The results show a good agreement with a stable radiation pattern across the operating bandwidth, stable gain more than 5 dBi and reflection coefficient of below -10 dB over the desired frequency range

Frequency tuning varactor-loaded reconfigurable antenna for m-WiMAX and WLAN applications

A design approach for a microstrip patch antenna to achieve the reconfigurable dual-band operation with a tunable device is presented in this work. The approach uses a BB833 varactor diode in the middle of a slotted patch antenna which which is able to produce dual-band resonant frequencies. The reconfigurable antenna is designed and simulated in CST Microwave Studio® software and is later, fabricated on a FR-4 substrate with a dielectric constant, εr of 4.5, loss tangent, tan δ of 0.019 and thickness, h of 1.6 mm. By changing the DC voltages of the varactor diode, different capacitance values of the varactor diode are obtained which dictate the specific resonant frequencies. From the simulation results, the capacitance value of 0.5 pF with a bias voltage of 2.0 V is chosen as it produces the required dual-band resonant frequencies at 3.38 GHz and 5.37 GHz for desired applications in the m-WiMAX and WLAN bands

Agarwood oil quality classifier using machine learning

Agarwood oil is known as one of the most expensive and precious oils being traded. It is widely used in traditional ceremonies and religious prayers. Its quality plays an important role on the market price that it can be traded. This paper proposes on a proper classification method of the agarwood oil quality using machine learning model k-nearest neighbour (k-NN). The chemical compounds of the agarwood oil from high and low quality are used to train and build the k-NN classifier model. Correlation reduce the dimension of the data before it is being fed into the model. The results show a very high accuracy (100%) model trained and can be used to classify the agarwood oil quality accurately. Keywords: agarwood oil; k-nearest neighbours; quality; machine learning

Frequency reconfiguration mechanism of a PIN diode on a reconfigurable antenna for LTE and WLAN Applications

Microstrip patch antennas are increasingly gaining popularity for usage in portable wireless system applications due to their light weight, low profile structure, low cost of production and robust nature. The patch is generally made of a conducting material such as copper or gold and can take any possible shapes, but rectangular shapes are generally used to simplify analysis and performance prediction. Microstrip patch antenna radiates due to the fringing fields between the patch edge and ground plane. In this work, a frequency reconfigurable antenna with a BAR63-02V Positive-Intrinsic-Negative (PIN) diode is designed, simulated and fabricated. The antenna operates at 2.686GHz for Long-Term Evolution (LTE2500) and 5.164GHz for Wireless Local Area Network (WLAN) applications. In the OFF state, the antenna operates at 5.302GHz, which is also suitable for WLAN application. The proposed antenna is fabricated on a FR-4 substrate with a relative dielectric constant, εr of 4.5, thickness, h of 1.6mm and loss tangent, tan δ of 0.019. The fabrication process is carried out at the Advanced Printed Circuit Board (PCB) Design Laboratory in UTHM

Facile, environmentally friendly, cost effective and scalable production of few-layered graphene

© 2017 Elsevier B.V. Commercialization of graphene is still one the biggest challenges in the carbon field despite the development of several methods for its production. The lack of simple, cost-effective and scalable methods for mass-production of graphene hampers its promotion to the market. Here, we propose a new method for large-scale p roduction of mono- and few-layered graphene via liquid phase exfoliation with the use of wet ball milling in the presence of organic solvents at extremely low temperatures. The wet ball milling combined with the temperature modulated high surface energy solvents affords exfoliation of bulk graphite into graphenes in a fast, scalable, cost effective and environmentally friendly process. The thorough statistical analysis of as-prepared graphene flakes demonstrates that more than 61% of the flakes comprise less than 5 layers, while ∼14% of the flakes were monolayer graphene. Combined with the ∼30% yield of few-layer graphene out of the graphite precursor, this method demonstrates incredible efficiency in just 45 min. In the presence of methanol, our method results in formation of predominantly bi-layer graphene, which is more difficult to obtain in scalable fashion, than mono-layer graphene. The high quality of as-obtained graphenes is fully confirmed by Raman spectroscopy, TEM, SAED, AFM and X-ray photoelectron spectroscopy

Post transition metal substituted Keggin-type POMs as thin film chemiresistive sensors for H2O and CO2 detection

Chemiresitive sensing allows the affordable and facile detection of small molecules such as H2O and CO2. Herein, we report a novel class of Earth-abundant post transition metal substituted Keggin polyoxometalates (POMs) for chemiresistive sensing applications, with conductivities up to 0.01 S cm−1 under 100% CO2 and 65% Relative Humidity (RH)

Design process and simulation testing of a shape memory alloy actuated robotic microgripper

Microgrippers are commonly used for micromanipulation of micro-objects with dimensions from 1 to 100 µm and attain features of reliable accuracy, low cost, wide jaw aperture and variable applied force. This paper studies the design process, simulation, and testing of a microgripper which can manipulate and assemble a platinum resistance temperature probe, made from a 25 µm diameter platinum wire, a 20 mm diameter tinned copper wire, and a printed circuit board type connector. Various microgripper structures and actuator types were researched and reviewed to determine the most suitable design for the required micromanipulation task. Operation tests using SolidWorks and ANSYS software were conducted to test a parallelogram structure with flexible single-notch hinges. The best suited material was found to be Aluminium alloy 7075-T6 as it was capable of producing a large jaw tip displacement of 0.7 mm without exceeding its tensile yield strength limit. A shape memory alloy was chosen as a choice of actuator to close the microgripper jaws. To ensure a repeatably accurate datum point, the final microgripper consisted of a fixed arm and a flexible arm. An optimisation process using ANSYS studied the hinge thickness and radius dimensions of the microgripper which improved its deflection whilst reducing the experienced stress