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:
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
Over recent years, the evolution of mobile wireless communication in the world has become more important after arrival 5G technology. This evolution journey consists of several generations start with 1G followed by 2G, 3G, 4G, and under research future generations 5G is still going on. The advancement of remote access innovations is going to achieve 5G mobile systems will focus on the improvement of the client stations anywhere the stations. The fifth era ought to be an increasingly astute innovation that interconnects the whole society by the massive number of objects over the Internet its internet of thing IOT technologies. In this paper present a review of advancement mobile generations by contrasting the type, data transmission rate, challenges, techniques, features and applications used to give by comparing and clarifying the enhancements have been produced till the upcoming 5G revulsion. Also, highlights on innovation 5G its idea, necessities, service, features advantages and applications
Detection of objects that are not common is an important issue in the field of classification of vehicles to come. In object detection, many objects have been classified, such as cars, motorbikes, bicycles, and others. But there are still many objects that are not common, especially in Indonesia. There are still many objects that only exist in Indonesia but not in other countries. Like illegal parking, carts street vendors, and many more. Therefore the writer takes the object detection theme. This proposal proposes detecting unusual objects. The object that the author will detect is illegal parking. With the tools the authors will make, there will be a new classification of illegal parking. In this way a new classification of object detection will be born, namely illegal parking objects. So foreign people will not be confused by the situation they will encounter in Indonesia. The output of this research is the label of illegal parking classification and the probability value of the results of the illegal parking classification. The object detection system uses a faster R-CNN algorithm that can work well when detecting object distances and get accurate results for distances of 6 meters by 70%, 12 meters at 90%, 18 meters at 70%
Slope Detection with road lane detection using Image Processing is one of the methods used to detect boundaries of the road using a different range of color from the road environment to distinguish road lane and non-road lane. This research using the road lane detection method that is inspired and based on previous research that we modified and develop to detect the slope of the road using OpenCV libraries and Linear Regression Method. Detection is done by making an intersection line from upper and down line that detected from Image Processing. This Research using a truck prototype with a 1:11 dimension to simulate the system and using prototype road to with the same dimension of the truck. The result shows that system can detect the slope of the road with accuracy reaching 90%
Generally, the green technology has been taken for granted in terms of providing clean and cheap energy without realising the costs. However, there are many trade-offs concurrent with enabling such technology. Accordingly, this paper evaluates and compares the green energy based networks with traditional counterparts. It presents a mathematical model which helps understand-ing the different variables that are necessary to advocate the green/renewable method over tra-ditional, or vice versa. This research shows that the cost efficiency (CE) of green networks can be relatively high, about twice the traditional, that is represented by cloud radio access network (C-RAN). Based on experimental data, this research shows that green technology requires more operational caring than traditional to produce same amount of power. With variant sites, cities, countries, geographical areas and equipment’s manufacturing characteristics, the model can pre-dict the total green systems’ trade-offs in the future. By doing so, the service providers, investors or network vendors are able to re-consider and decide the shifting between both types of networks
