Building’s Air Conditioning systems require moving liquids for dweller comfort. Clogged pipes, system degradation can cause pressure buildups, leaks and other faults which leads to damage to the building. Most of the leaks in the commercial building occur due to poor maintenance and/or material degradation. Visual inspection is most predominantly used to solve this problem in the industry. This paper introduces the Internet of Things technology to detect leakage in building’s hydronic pipes with the support of sensors, fault detection method and mechanical control. The system consists of: Microcontroller, Windows application and website application. Internet of Things technology was used to monitor and control the hydronics using microcontroller’s capability of connecting to main server which is used to transmit the data to the cloud. The prototype was successfully built and tested. Promising results show that leaks above 2ml/s could be detected after 4 seconds specifically for the built small-scale system while control and monitor feature could be implemented with Internet of Things technology.

Detection of non-ionizing electromagnetic radiation is central to managing health and environmental hazards resulting from its exposure. This research focused on the design and development of a non-ionizing electromagnetic radiation detector that is sensitive to the medium frequency of 50Hz to 30MHz and their corresponding power density. The device consists of the sensing, amplifying, filtering and microcontroller sections. The sensing section is made up of a coil wound on a ferrite rod, it detects radiations from the surroundings and converts it to a voltage signal. The voltage produced is then fed to the operational amplifiers in the amplifying section. Afterwards, the output signal is fed to the filtering section where unwanted signals are eliminated. The analogue signal output from the active filter is then fed to the microcontroller section where it is converted to a digital signal through the analogue to digital converter (ADC). The ADC then presents the converted signal in a readable form to be displayed on the liquid crystal display (LCD). The developed equipment was calibrated (in µW/cm2) using an existing detector EMF DT 1130. With an average calibration coefficient value of 2.32, the detector was found to perform excellently well at both medium and low-frequency ranges.

One unsolved problem in the development of an effective welding training simulator is how to construct an accurate 3D welding torch model based on the moving position of this torch in the training process. This paper presents an effective approach to deal with the problem. The whole scene is constructed in the base coordinate system and the torch is modeled as a 3D object in the sub-coordinate system. The sub-coordinate system firstly overlaps the base coordinate system, and it’s continuously changing as the trainer operates the torch. A nine axis sensor is installed in the torch at a selected point, which is the origin of the sub-coordinate system. The sensor can measure the rotation posture of the torch. Another marked point that can be captured by the Binocular Vision System (BVS) is installed with an infrared emitter. The BVS can measure the coordinate values of this point in the base coordinate system. As long as the coordinate values of a certain point on the model and its rotation posture based on this point can be determined, the VR development tool, such as Unity-3d,can track the model in real-time. That is the algorithm of this system, which is verified by Pro/E, a 3D modeling software. The approach presented above is applied to a welding training simulator product, which has been put into use and proved to be effective.

The cancer is a menacing disease. More care is required while diagnosing cancer disease. Mostly CT modality is used for Cancer therapy. Image processing techniques [1] can help doctors to diagnose easily and more accurately. Image pre-processing [2], segmentation methods [3] are used in extraction of cancerous nodules from CT images. Many researches have been done on segmentation of CT images with different algorithms, but they failed to reach 100% accuracy. This research work, proposes a model for analysis of CT image segmentation with filtered and without filtered images. And brings out the importance of pre-processing of CT images.

The vast need for refractories in Nigeria makes it imperative to domesticate its production in the country in order to reduce over-reliance on their importation. In this research, refractory porcelain crucibles were produced from indigenous ceramic raw materials from Ikere Ekiti and Awo (locations in South Western, Nigeria). Chemical analysis was carried out on the raw materials using X-ray Fluorescence Spectrometer (XRF) to determine their chemical compositions. Five body compositions, labeled as samples A-E were formulated and the crucibles were produced using slip casting. They were dried and fired in a gas kiln up to 13000C for 6 hours. The result of the standard tests carried out on the locally produced porcelain crucibles showed total shrinkage of 10%-15%, water absorption of 0.36%-0.72%, compressive strength of 1.43N/mm2-1.65 N/mm2 and refractoriness of 1680.20C-1717.50C. The result showed that ceramic raw materials sourced from the selected deposits in South Western Nigeria are suitable for the production of porcelain crucibles with good refractory properties.