IJITEE (International Journal of Information Technology and Electrical Engineering)
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95 research outputs found
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One-Input Three-Output Current-Mode Universal Filter Using Translinear Current Conveyors
Full text linkThis paper presents a new current-mode universal filter with one-input three-output employing three translinear current conveyors and two grounded capacitors. The proposed filter provides low-pass, band-pass, high-pass current response with high output impedance output which can be directly connected for current-mode circuit. The band-pass and all-pass filters can also be obtained. The parameters wo and Q can be controlled separately and electronically by the bias currents of current conveyors. For realizing all filtering functions, no passive and active matching conditions are required. The active and passive sensitivities are low. The characteristic of the proposed circuit can be confirmed by SPICE simulations
Current-Controlled Current-Mode Quadrature Oscillator Using Translinear Current Conveyors
Full text linkIn this paper, a current-mode quadrature oscillator using second-generation current conveyors (CCIIs) is presented. The proposed oscillator consists of two CCIIs, two grounded capacitors and two grounded resistors. The circuit is suitable for integrated circuit implementation by using grounded capacitors. In addition, a new current-controlled current-mode quadrature oscillator using two current controlled second generation current conveyors (CCCIIs) and two grounded capacitors can be obtained by replacing CCIIs and resistors series at X terminals with CCCIIs. The condition of oscillation and frequency of oscillation can be orthogonally controlled. The frequency of oscillation can be controlled by grounded resistors and external bias currents. The proposed circuits have been simulated by SPICE simulations. The simulation results are confirmed the proposed theory
Digitalization of Human Head Anthropometry Measurement Using Pixels Measurement Method
Full text linkHead Anthropometry is a part of anthropometry that needed to be measured carefully. It is because human head becomes an important part that necessary to be protected. The protection aims to look after the safety of the human head. Safety factors can be achieved by designing head products. Therefore, head anthropometry data is required to make a product design Currently, data retrieval of head anthropometry is still using several measuring devices such as anthropometers, sliding callipers, spreading callipers, and tape gauges. This measurement method makes the standard deviation become higher and also take a lot of time to capture huge amounts of anthropometry data. However, the problem has been resolved by other study research with building a head dimension measurement system using digital camera. But the system still need the integration with digital camera. This study uses the IP Camera that has been integrated with the system to capture human head from the front and side. The captured image is segmented into several areas based on head dimension. Then, the image is processed using pixel measurement method by performing feature extraction on each head dimension to get the result of head dimension measurement. The result shows that calliper measurement and system measurement against ten of fourteen human head anthropometry dimensions is identical with the best distance between IP Camera and the head as far as 200 cm. This head anthropometry data is expected to make a contribution to Indonesian Ergonomics Society
Deep Learning Methods for EEG Signals Classification of Motor Imagery in BCI
Full text linkEEG signals are obtained from an EEG device after recording the user's brain signals. EEG signals can be generated by the user after performing motor movements or imagery tasks. Motor Imagery (MI) is the task of imagining motor movements that resemble the original motor movements. Brain Computer Interface (BCI) bridges interactions between users and applications in performing tasks. Brain Computer Interface (BCI) Competition IV 2a was used in this study. A fully automated correction method of EOG artifacts in EEG recordings was applied in order to remove artifacts and Common Spatial Pattern (CSP) to get features that can distinguish motor imagery tasks. In this study, a comparative studies between two deep learning methods was explored, namely Deep Belief Network (DBN) and Long Short Term Memory (LSTM). Usability of both deep learning methods was evaluated using the BCI Competition IV-2a dataset. The experimental results of these two deep learning methods show average accuracy of 50.35% for DBN and 49.65% for LSTM
Page Load Time Speed Increase on Disease Outbreak Investigation Information System Website
Full text linkOutbreaks or extraordinary events often become an issue that occurs in Indonesia. Therefore, an outbreak investigation information system is required to collect, manage and analyze data quickly and accurately. On the other hand, challenges in data accessing processes in certain locations are still constrained by a slow internet connection. This paper conducted speed increase of a page load or site speed time from disease outbreaks investigation information system website.Page load time speed testing was carried out using Google Chrome Developer Tools and using simulation speeds of 2.5 Mbps. Testing time was carried out by dividing the time into three sections, morning hours, working hours and night hours. Implementation of page load time increase includes reducing HTTP requests, utilizing GZIP compression, performing code minification, setting browser chache, using CDN, and using other enhancement techniques.The results showed that after implementing an increase in page load time by turning off cache and using cache, there was an increase in site speed. When the browser cache was turned off, an average page load time increased of 54.79% from the previous time. Whereas when using the browser cache, page load time speed increased by 55.28% from the previous time
Designing a Smart Mirror as a Laboratory Information Media Using Raspberry Pi
Full text linkDevelopment of microprocessor technology provides new ideas for creating smart devices, one of which is in the field of smart home. Smart home is a concept of a home integrated with a smart system and supported by technology that enables all work to be more effective and efficient. Mirror is a household device that is beneficial to humans. In this paper, a research on smart mirrors is explained. A smart mirror is a mirror integrated with an intelligent system so that it can display multimedia data originating from the internet using Raspberry as a computing tool, PIR sensor as a tool to control monitors, and DC fans as a tool to control temperature system. In this paper, the mirror was able to display information about time, weather, academic calendar, lab work schedules, prayer schedules, and academic news. A PIR sensor has a good accuracy when the device is placed at 180 cm above the ground and the distance between mirror and humans when mirroring is 70 cm. A DC fan was utilized to stabilize the system temperature in a range of 40 to 50 oC
Khmer Treebank Construction via Interactive Tree Visualization
Full text linkDespite the fact that there are a number of researches working on Khmer Language in the field of Natural Language Processing along with some resources regarding words segmentation and POS Tagging, we still lack of high-level resources regarding syntax, Treebanks and grammars, for example. This paper illustrates the semi-automatic framework of constructing Khmer Treebank and the extraction of the Khmer grammar rules from a set of sentences taken from the Khmer grammar books. Initially, these sentences will be manually annotated and processed to generate a number of grammar rules with their probabilities once the Treebank is obtained. In our experiments, the annotated trees and the extracted grammar rules are analyzed in both quantitative and qualitative way. Finally, the results will be evaluated in three evaluation processes including Self-Consistency, 5-Fold Cross-Validation, Leave-One-Out Cross-Validation along with the three validation methods such as Precision, Recall, F1-Measure. According to the result of the three validations, Self-Consistency has shown the best result with more than 92%, followed by the Leave-One-Out Cross-Validation and 5-Fold Cross Validation with the average of 88% and 75% respectively. On the other hand, the crossing bracket data shows that Leave-One-Out Cross Validation holds the highest average with 96% while the other two are 85% and 89%, respectively
Bandwidth Upgrade in Printed Dipole Antennas Design for LTE Base Station
No full textAbstract—In this study the research design development has been carried out by changing the radiating element field width. Radiating element field extension was administered by simulating it and trying to measure the value one by one in antenna simulator software. The radiating element widening was administered so that the resulting bandwidth could be greater. After changing the width of the field, an element radiating field length adjustment was administered to adjust the operating frequency used in Indonesia. After the design worked at the desired frequency and produced a desired bandwidth, antenna fabrication was administered and its results was tested using Mini VNA Tiny to find out the antenna value if mass produced
Product Recommendation System Design Using Cosine Similarity and Content-based Filtering Methods
Full text linkThe wide variety of products offered by a company, combined with the consistent demands of specific products from customers, create a certain problem for the organization when they want to market a new product. Organization need information that could help them promote the most suitable product based on their customer’s characteristics. The organization also need to suggest alternative products for customer if the requested product is unavailable. In this research, we design a Recommender System that could suggest either new or alternatif products to customer based on their characteristic and transaction history. This proposed system adopts Cosine Similarity method to calculate product similarity score and Content-based Filtering to calculate customer recommendation score and used as a model for the proposed system. Subsequently, these models are used to classify customers as well as products according to their transaction behavior and consequently recommends new products more likely to be purchased by them. Based on the testing results of the proposed system, it can be concluded that the chosen methods can be utilized to recommend products and costumer of products. It is shown that Precision and Recall of product similarity scores and customer recommendation for product scores are 100% and 93.47%
Prototype of Student Attendance Application Based on Face Recognition Using Eigenface Algorithm
Full text linkPrototype of face recognition based attendance application that has been developed to overcome weaknesses in DTETI UGM student manual attendance system has several weaknesses. These weaknesses are a decrease in facial recognition accuracy when operating under conditions of varying environmental light intensity and in condition of face rotating towards z axis rotation centre. In addition, application prototype also does not yet have a database to store attendance results. In this paper, a new application prototype has been developed using Eigenface face detection and recognition algorithm and Haar-based Cascade Classifier. Meanwhile, to overcome prototype performance weaknesses of the previously developed application, a pre-processing method was proposed in another study was added. Processes in the method were geometry transformation, histogram levelling separately, image smoothing using bilateral filtering, and elliptical masking. The test results showed that in the category of various environmental light intensity conditions, face recognition accuracy from developed application prototypes was 16.71% better than previous application prototypes. Meanwhile, in category of face slope conditions at z axis rotation centre, face recognition accuracy from developed application prototype was 38.47% better. Attendance database system was also successfully implemented and running without error