Technology Reports of Kansai University (ISSN: 04532198) is a monthly peer-reviewed and open-access international Journal. It was first built in 1959 and officially in 1975 till now by kansai university, japan. The journal covers all sort of engineering topic, mathematics and physics. Technology Reports of Kansai University (TRKU) was closed access journal until 2017. After that TRKU became open access journal. TRKU is a scopus indexed journal and directly run by faculty of engineering, kansai university.
Technology Reports of Kansai University (ISSN: 04532198) is a peer-reviewed journal. The journal covers all sort of engineering topic as well as mathematics and physics. the journal's scopes are
in the following fields but not limited to:
Evaporative cooling is a good alternative of refrigeration cooling systems. This system is environmentally friendly and consumes low electrical energy. However, this system has some disadvantages which is greatly affect on the performance of the system. One of these problems is the affected by external conditions (humidity) makes space uncomfortable and reduces the effectiveness of evaporative cooling. This paper will focus on overcome this problem and improving the performance of the system. An evaporative cooling system was combined with heat recovery and desiccant in order to improve the performance of the system in a humid condition. The unit was constructed and installed at University of Technology in Baghdad. The system includes ducting, desiccant bed, plate heat exchanger (heat recovery), centrifugal fans and heaters. This is accomplished through reducing the moisture imposed on the cooling unit, as a result of handling the latent load of air (by desiccant material). Three air flow rate of supply in desiccant were studied (0.48, 0.61, and 0.73 m³/s). Four regeneration air flow rate in desiccant were studied (0.15, 0.28, 0.49 and 0.59 m³/s). The results show adding the desiccant material and heat recovery system could improve the performance of the system by 106 % (in a humid condition W=20.86 g/kg)
Alzheimer's disease is a neurological disorder that is a major cause of dementia in the world. Early detection of Alzheimer's is very important to delay the degradation of brain function which can happen in a short time. Also, it is important to determine the right treatment for patients. Medical imaging such as MRI and CT-Scan can use for analysis of this deterioration. However, it requires a high cost for setting this protocol. As an alternative tool that can be used for analysis is an electroencephalogram (EEG). Therefore, in this study, we propose an early detection method for Alzheimer's based on EEG signals. To achieve this purpose, we used an open dataset consisting of 11 MCI patients and 16 normal subjects. Theta wave energy was analyzed and becomes a vector feature on each EEG electrode. Support vector machines (SVM) with 5-fold cross-validation are employed to evaluate the proposed method. Test results show the highest accuracy is 81.5%. This study shows that EEG analysis has the potential to be developed as supporting tools in the diagnosis of cognitive impairment