Diurnal microclimate profile in tropical coastal built environment (case: Universitas Islam Sultan Agung campus area, Semarang)

Microclimate is caused by the interaction between atmosphere and earth surfaces in local areas. Built environment has pay attention in microclimate since it considerably affects the thermal earth surfaces. This research is located in tropical coastal area, specifically at Universitas Islam Sultan Agung Semarang campus area as a part of built environment where close to the Java sea. The aim of this paper is to investigate the diurnal pattern of microclimate in research location before modelled to the wider area. A numerical modelling method is applied in this research to simulate the diurnal thermal pattern. The research shows that microclimate is influenced by the earth surface objects and following the sun movement respectively.

Software-defined cooking using a microwave oven

Despite widespread popularity, today's microwave ovens are limited in their cooking capabilities, given that they heat food blindly, resulting in a nonuniform and unpredictable heating distribution. We present software-defined cooking (SDC), a low-cost closed-loop microwave oven system that aims to heat food in a software-defined thermal trajectory. SDC achieves this through a novel high-resolution heat sensing and actuation system that uses microwave-safe components to augment existing microwaves. SDC first senses the thermal gradient by using arrays of neon lamps that are charged by the electromagnetic (EM) field a microwave produces. SDC then modifies the EM-field strength to desired levels by accurately moving food on a programmable turntable toward sensed hot and cold spots. To create a more skewed arbitrary thermal pattern, SDC further introduces two types of programmable accessories: A microwave shield and a susceptor. We design and implement one experimental test bed by modifying a commercial off-the-shelf microwave oven. Our evaluation shows that SDC can programmatically create temperature deltas at a resolution of 21°C with a spatial resolution of 3 cm without the programmable accessories, and 183°C with them. We further demonstrate how an SDC-enabled microwave can be enlisted to perform unexpected cooking tasks: Cooking meat and fat in bacon discriminatively and heating milk uniformly.

Thermosemiotics of hands. Neuropathic disorders in thermotopography of hands

Central and peripheral neurological pathology, which affects the thermal pattern and thermoreactions of the hands, is diverse both in etiology and pathogenesis, and in the nature and severity of thermal imaging signs, depending on the localization, severity and duration of the disease, individual adaptive and compensatory features, and a number of other reasons. The variants of the temperature distribution on the surface of the hands and its changes under the influence of specialized functional tests in injuries and diseases of the peripheral nerves of the upper limb, as well as in disorders of segmental and suprasegmental genesis, studied with the help of thermal imaging, are the subject of this article.

Thermal Simulations of Cancerous Breast Tumors and Cysts on a Realistic Female Torso

Thermography as a clinical imaging technique has been around for several decades, however it has not become a common diagnostic technique mainly due to its low specificity. The development of computational models of heat transfer in biological tissue can provide a deeper knowledge of healthy and non-healthy thermal patterns could increase the usefulness of thermography in clinical diagnosis. In this work the thermal pattern of cancerous and benign breast tumors are calculated through finite element computer simulations using a realistic female human torso. The simulation results show a thermal pattern which is consistent with infrared images of female subjects and it is not present in simulations performed using other approximate geometries of the breast. A parametric study using cancerous tumors and cysts as a function of size and depth show that the temperature over the skin closest to the tumor decreases for benign tumors while it increases for malignant tumors, also the temperature patterns show a 20% deviation from thermal simulations using a hemispherical breast model. This result indicates that there is a strong geometric component in the human temperature pattern. These results are a first step to understand benign and malignant thermal processes in the breast which might help increase the usefulness of infrared imaging in breast clinical diagnosis.

Inverse thermal modeling and experimental validation for breast tumor detection by using highly personalized surface thermal patterns and geometry of the breast

Infrared (IR) Thermography is currently a supplementary technique for breast cancer diagnosis. There have been studies using IR thermography and numerical modeling in an attempt to detect tumor inside the breast. Most of these studies focused on either the “forward modeling” problem or only used idealized or population-averaged patients’ data, whereas identification of the tumor inside the breast based on the thermal pattern is an “inverse modeling” problem dependent on personalized information of the patient. Inverse modeling is based on the idea that the surface thermal pattern of the breast can be used to determine the tumor features based on physical and physiological principles. The current study aims to develop a well-validated inverse thermal modeling framework that could be used to determine the depth and size of tumor inside a breast based on personalized patients’ breast data, such as thermogram and 3D geometry using efficient design optimization techniques and Finite Element Modeling (FEM) to support the process. The numerical modeling was validated by the experiments, conducted using artificial breasts. Results show that although DIRECT Optimization method can be employed to find the depth and size of the tumor with good accuracy, the technique can be very time consuming. On the other hand, Response Surface Optimization method is also able to find the depth and size of the tumor with less accuracy but faster when compared with DIRECT Optimization. The last method tested, Nelder-Mead method, failed to detect the tumor. The study concludes that Response Surface Optimization method should be used first, and after the range of parameters are found, the DIRECT optimization method can be applied for more accurate results. However the GA method was found to be the only viable and efficient design optimization method for reverse modeling when blood perfusion was adopted in the breast model and many parameters were searched for with patient specific data input for breast tumor diagnosis.

Fuzzy Controller Applied to a Remote Energy Harvesting Emulation Platform

In the last decades, a lot of effort has been made in order to improve the use of environmentally friendly and renewable energy sources. In a context of small energy usage, energy harvesting takes place and thermal energy sources are one of its main energy sources because there are several unused heat sources available in the environment that may be used as renewable energy sources. To rapidly evaluate the energy potential of such thermal sources is a hard task, therefore, a way to perform this is welcome. In this work, a thermal pattern emulation system to evaluate potential thermal source in a easy way is proposed. The main characteristics of the proposed system is that it is online and remote, that is, while the thermal-source-under-test is being measured, the system is emulating it and evaluating the generated energy remotely. The main contribution of this work was to replace the conventional Proportional Integral Derivative (PID) controller to a Fuzzy-Proportional Integral (PI) controller. In order to compare both controllers, three tests were carried out, namely: (a) step response, (b) perturbation test, (c) thermal emulation of the thermal pattern obtained from a potential thermal source: tree trucks. Experimental results show that the Fuzzy-PI controller was faster than the PID, achieving a setting time 41.26% faster, and also was more efficient with a maximum error 53% smaller than the PID.