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This paper describes the proposal for an airframe noise prediction method that can be used in Indonesian aircraft design research and industry. Since the industry is strategic, whether economically or securely, the country should build their own technology in all phases. Noise assessment is one of the sophisticated procedures in designing and manufacturing aircraft. Indonesia has not developed and manufactured engines, therefore airframe noise prediction is a relevant object to study. This method is proposed to be a utility to improve Indonesian aircraft design specifications. Based on the analogy theory of aeroacoustics, the use of Ffowcs Williams and Hawkings (FWH) equation was chosen to represent noise. The noise prediction method was developed by simulating and modeling in OpenFOAM, an open-source software based on the finite volume method. Its reliability has been proven in research and industrial computational fluid dynamics. The proposed method is developed from CFD and is compatible with using a personal computer device. The algorithm based on boundary conditions and hardware specifications has been built. Each step has been designed to support FWH Equation solver uniquely for this study. Computational domains represent the airflow area overrun a solid object. For the reason of far-field radiation, the domain token is 20 times the dimension of the object, and wall functions are applied. The atmosphere condition of low flight level and low to medium subsonic speed is taken to represent various aircraft designs and configurations. The condition represents the existing Indonesian industry of civil and military flying vehicles, and its possibility to develop.

One way to diagnose a disease is to examine pictures of tissue thought to be affected by the disease. Near-infrared properties are subdivided into nonionizing, noninvasive, and nonradiative properties. Near-infrared also has selectivity properties for the objects it passes through. With this selectivity, the resulting attenuation coefficient value will differ depending on the type of material or wavelength. By measuring the output and input intensity values, as well as the attenuation coefficient, the thickness of a material can be measured. The thickness value can then be used to display a reconstructed image. In this study, the object studied was a phantom consisting of silicon rubber, margarine, and gelatin. The results showed that margarine materials could be decomposed from other ingredients with a wavelength of 980 nm.

This report is focused on the linear region of I-V characteristics of nanoscale highly-doped p-i-n diodes fabricated within ultrathin silicon-on-insulator (SOI) structures with an intrinsic layer length of 200 nm and 700 nm under a forward bias at a temperature range from 50 K to 250 K. The doping concentrations of Boron and Phosphorus in SOI p-i-n diodes are high, 1×1020 cm-3 and 2×1020 cm-3, respectively. The linearity of I-V characteristics of the p-i-n diodes under a certain forward bias voltage range and temperature range from 50 K to 250 K indicate these devices are suitable for low temperature sensing purposes. We conclude that highly-doped p-i-n diodes produce a higher current as the temperature decreases under a certain bias voltage range. Nanoscale diodes with longer and wider intrinsic layers generate higher currents under a certain range of bias voltage and low temperature measurements.