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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
Arjuna Subject : -
Articles 65 Documents
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Search results for , issue "Vol 18, No 1: April 2020" : 65 Documents clear
Identification of language in a cross linguistic environment Merin Thomas; Dr Latha c A; Antony Puthussery
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp544-548

Abstract

World has become very small due to software internationationalism. Applications of machine translations are increasing day by day. Using multiple languages in the social media text is an developing trend. .Availability of   fonts in the native language enhanced the usage of native text in internet communications. Usage of   transliterations of language   has become quite common. In Indian scenario current generations are   familiar to talk in native language but not to read and write in the native language, hence they started using English representation of native language in textual messages. This paper describes the   identification of the transliterated text in cross lingual environment .In this paper a Neural network model   identifies the prominent language in the text and hence the same can be used to identify the meaning of the text in the concerned language. The model is based upon Recurrent Neural Networks that found to be the most efficient in machine translations. Language identification can serve as a base for many applications in multi linguistic environment. Currently the South Indian Languages Malayalam, Tamil are identified from given text. An algorithmic approach of Stop words based model is depicted in this paper. Model can be also enhanced to address all the Indian Languages that are in use.
Battery health and performance monitoring system: a closer look at state of health (SoH) assessment methods of a Lead-Acid battery D Selvabharathi; N Muruganantham
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp261-267

Abstract

Batteries are one of the most compact and reliable sources of sustainable energy. Lead-Acid batteries are the battery-powered sort of batteries concocted during the 1980s. The significant utilization of lead-acid battery is in beginning, lighting and start frameworks of vehicles.To guarantee the health and to dodge potential disappointments of a battery it is important to examine its Territory of health precisely. This examination expects to give efficiently evaluating the accessible writing on the condition of health estimation techniques. This study focuses on many factors and provides a suggestion for the defended battery manufacturing process. This study provides increasing efforts toward the advancement of battery interms of specific power, energy density, durability, invulnerability, economics, and performance in various applications.
Solving wireless sensor network coverage problem using LAEDA Shirin Khezri; Mahdi Nazaari A
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp452-458

Abstract

Coverage improvement is one of the main problems in wireless sensor networks. Given a finite number of sensors, improvement of the sensor deployment will provide sufficient sensor coverage and save cost of sensors for locating in grid points. For achieving good coverage, the sensors should be placed in adequate places. In this article, estimation of distribution algorithm based on learning automata is presented for solving the sensor placement (LAEDA-SP) in distributed sensor networks by considering two factors: 1) the complete coverage and 2) the minimum costs. The proposed algorithm is a model based on search optimization method that uses a set of learning automata as a probabilistic model of high-quality solutions seen in the search process. It is applied in a various area with different size. The results not only confirmed the successes of using the new method in sensor replacement but also they showed that the proposed method performs more efficiently compared to the state-of-the-art methods such as simulated annealing (SA) and population-based incremental learning algorithms (PBIL).
CMOS based thermal detector for processor Lee Che Yang; Warsuzarina Mat Jubadi
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp276-283

Abstract

This project proposed a design of low power CMOS-based thermal detector which can detect the temperature of processor such as in Central Processing Unit. By re-designing temperature detector circuit using CMOS technology, the reduction in power consumption and area size of the thermal detector can be obtained.  In this paper, the design of thermal detector consists of temperature sensing core, amplifier, and Analog to Digital Converter (ADC), respectively. The sensor was designed using 0.13 µm CMOS technology and operates by sensing the temperature of processor and produced a digital output value. The temperature detection range was setup between 0 °C to 80 °C with 10 °C resolution. The temperature detector was capable to show temperature readings in binary value. It consumed an average power of 558.2 µW and a space occupancy of 0.0118 mm².
Developed third iterative dichotomizer based on feature decisive values for educational data mining Saja Taha Ahmed; Rafah Al-Hamdani; Muayad Sadik Croock
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp209-217

Abstract

Recently, the decision trees have been adopted among the preeminent utilized classification models. They acquire their fame from their efficiency in predictive analytics, easy to interpret and implicitly perform feature selection. This latter perspective is one of essential significance in Educational Data Mining (EDM), in which selecting the most relevant features has a major impact on classification accuracy enhancement. The main contribution is to build a new multi-objective decision tree, which can be used for feature selection and classification. The proposed Decisive Decision Tree (DDT) is introduced and constructed based on a decisive feature value as a feature weight related to the target class label. The traditional Iterative Dichotomizer 3 (ID3) algorithm and the proposed DDT are compared using three datasets in terms of some ID3 issues, including logarithmic calculation complexity and multi-values featuresselection. The results indicated that the proposed DDT outperforms the ID3 in the developing time. The accuracy of the classification is improved on the basis of 10-fold cross-validation for all datasets with the highest accuracy achieved by the proposed method is 92% for the student.por dataset and holdout validation for two datasets, i.e. Iraqi and Student-Math. The experiment also shows that the proposed DDT tends to select attributes that are important rather than multi-value. 

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