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28,451 Article Results

Optimization of Arithmetical Operators for the Enhanced Wallace Stage

10.11591/ijeecs.v9.i3.pp591-594
K. Gugan , S. V. Saravanan
In the field of Digital signal processing (DSP), the reduction of some logical elements counts is one of the main considerations. To minimize the area, computational delay, and power, the digital form FIR filter is to be implemented. The optimization of the ATP (Area, Time and Power) is achieved by using the efficient multiplication and accumulation unit (MAC). In this work, the direct form FIR filter with the efficient MAC unit is presented. At the initial stage, the half adders and full adders are to be modified by the reduction of the logical gates. The modified half and full adder are implemented in the Wallace tree multiplier for performing the efficient multiplication process. Carry save adder is divided into the two stages to reduce the computational delay of arithmetical operators. The proposed MAC design is implemented in the direct form FIR filter by using the HDL language.
Volume: 9
Issue: 3
Page: 591-594
Publish at: 2018-03-01

Performance Analysis of ANN Model for Estimation of Trophic Status Index of Lakes

10.11591/ijai.v7.i1.pp1-10
Tushar Anthwal , Akanksha Chandola , M P Thapliyal
The health of water bodies across the globe is of high concern as the pollution is accelerating rigorously. With the interventions of simple technology, some significant changes could be bought up. Lakes are dying because of high Trophic Index Status which shows the eutrophication level of water bodies. Taking this into account, feed forward back propagation neural network model is used to estimate the Trophic Status Index (TSI) of lakes which could compute the value of TSI with the given parameters; pH, temperature, dissolved oxygen, Secchi disk transparency, chlorophyll and total phosphate. Two learning algorithms; Levenberg Marquardt (LM) and Broyden–Fletcher–Goldfarb–Shanno (BFGS) Quasi Newton were used to train the network, which belongs to different classes. The results were analyzed using mean square error function and further checked for the deviation from actual data. Among both the training algorithm; LM demonstrated better performance with 0.0007 average mean square error for best validation performance and BFGS Quasi Newton shows the average mean square error of 1.07.
Volume: 7
Issue: 1
Page: 1-10
Publish at: 2018-03-01

Power of Ambient Tempurature on the Performance of the Semiconductor Laser

10.11591/ijeecs.v9.i3.pp606-608
J. S. Ashwin , N. Manoharan
In this paper, the impact of surrounding temperature on the execution of the semiconductor laser is systematically examined in principle. We constructed the recreation display and the simulation results about showed that ambient temperature changes would influence the laser chip temperature, bringing about the laser key parameters in reproduction comes about.
Volume: 9
Issue: 3
Page: 606-608
Publish at: 2018-03-01

Parameter Estimation of DC Motor using Adaptive Transfer Function Based on Nelder-Mead Optimisation

10.11591/ijeecs.v9.i3.pp696-702
Byamakesh Nayak , Sangeeta Sahu , Tanmoy Roy Choudhury
This paper explains an adaptive method for estimation of unknown parameters of transfer function model of any system for finding the parameters. The transfer function of the model with unknown model parameters is considered as the adaptive model whose values are adapted with the experimental data. The minimization of error between the experimental data and the output of the adaptive model have been realised by choosing objective function based on different error criterions. Nelder-Mead optimisation Method is used for adaption algorithm. To prove the method robustness and for students learning, the simple system of separately excited dc motor is considered in this paper. The experimental data of speed response and corresponding current response are taken and transfer function parameters of  dc motors are adapted based on Nelder-Mead optimisation to match with the experimental data. The effectiveness of estimated parameters with different objective functions are compared and validated with machine specification parameters.
Volume: 9
Issue: 3
Page: 696-702
Publish at: 2018-03-01

Artificial Neural Network for Healthy Chicken Meat Identification

10.11591/ijai.v7.i1.pp63-70
Fajar Yumono , Imam Much Ibnu Subroto , Sri Arttini Dwi Prasetyowati
Indonesia is the country with the largest number of Muslims in the world. Every Muslim is taught to consume thoyyiban halal meat or healthy chicken because it is slaughtered in the right way and stored in a good way too. But the reality in the market of many chicken meat on the market can not meet that criteria. Identification of healthy chicken meat can be done with laboratory experiments, but that is not simple and takes time. This experiment offers a cheaper, faster approach, with very high accuracy. The experimental approach is based on color and texture analysis on 5 types of meat quality based on healthy value. Color analysis was performed using artificail neural network (ANN) while texture analysis used Canny edge detection. Experimental results show that the color histogram approach with ANN is better than the texture approach, ie 94% versus 66%. It can be concluded that the freshness of a chicken does not have much effect on the texture of the meat but it has an effect on the color change in the meat.
Volume: 7
Issue: 1
Page: 63-70
Publish at: 2018-03-01

Computational Morphological Analysis of Yorùbá Language Words

10.11591/ijai.v7.i1.pp11-18
Safiriyu Ijiyemi Eludiora , O R Ayemonisan
Nigeria official languages are English, Yorùbá, Igbo and Hausa. The focus of the study reported in this paper is to develop learning tool that can assist learners to learn the Yorùbá language using its alphabets. The study is critical to Yorùbá language, because of its endangerment. There is need to introduce different learning tools that can mitigate its extinction. A Yorùbá word perfect system was developed to assist people in learning the Yorùbá language. English and Yorùbá words formation are experimented using computational morphological approach (word formation). The theoretical framework considered Finite state automata (FSA) to realise different ways of combining the consonants and vowels to form word. Two to five letter words were considered. The system was designed and implemented using UML tools and python programming language.The system will teach the users on how the words are formed, and the number of syllables in each word. The user  need not to know how to tone mark word before he/she can use the system. Any word typed will be analysed according to its number of syllables. This approach produces representatives of all parts of speech (POS) of the two languages. It produces corpora for the two languages
Volume: 7
Issue: 1
Page: 11-18
Publish at: 2018-03-01

Design of Low Power Low Noise Amplifier using Gm-boosted Technique

10.11591/ijeecs.v9.i3.pp685-689
Maizan Muhamad , Norhayati Soin , Harikrishnan Ramiah
This paper presents the development of low noise amplifier integrated circuit using 130nm RFCMOS technology. The low noise amplifier function is to amplify extremely low noise amplifier without adding noise and preserving required signal to a noise ratio. A detailed methodology and analysis that leads to a low power LNA are being discussed throughout this paper. Inductively degenerated and Gm-boosted topology are used to design the circuit. Design specifications are focused for 802.11b/g/n IEEE Wireless LAN Standards with center frequency of 2.4 GHz. The best low noise amplifier provides a power gain (S21) of 19.841 dB with noise figure (NF) of 1.497 dB using the gm-boosted topology while the best low power amplifier drawing 4.19mW power from a 1.2V voltage supply using the inductively degenerated.
Volume: 9
Issue: 3
Page: 685-689
Publish at: 2018-03-01

Mobile-robot Navigation through Fuzzy Behavioral Algorithm & Vector-polar Histogram Algorithm

10.11591/ijeecs.v9.i3.pp565-571
Alaudeen Basha , V. Vijayakumar
The route of self-governing ground vehicles through general conditions has gotten generous research consideration. Be that as it may, the writing contains not very many correlations of the course ideal models for AGVs, particularly for calculations utilising range discoverers. The fluffy behavioural approach and vector field histogram (VFH) approach are outstanding strategies that can be actualised using range discoverers. This paper will concentrate on looking at their structure, simplicity of programming and calculation tuning, and execution. Both methodologies actualised on a Pioneer 2 robot, outfitted with a SICK laser run discoverer.
Volume: 9
Issue: 3
Page: 565-571
Publish at: 2018-03-01

An Automatic Coffee Plant Diseases Identification Using Hybrid Approaches of Image Processing and Decision Tree

10.11591/ijeecs.v9.i3.pp806-811
Abrham Debasu Mengistu , Seffi Gebeyehu Mengistu , Dagnachew Melesew Alemayehu
Coffee Leaf Rust (CLR), Coffee Berry Disease (CBD) and Coffee Wilt Disease (CWD) are the three main diseases that attack coffee plants. This paper presents the identification of these types diseases using hybrid approaches of image processing and decision tree. The images are taken from Southern Ethiopia, Jimma and Zegie. In this paper backpropagation artificial neural network (BPNN) and decision tree had been used as techniques; a total of 9100 images were collected. From these, 70% are used for training and the remaining 30% are used for testing. In general, 94.5% accuracy achieved when decision tree and BPNN with tanh activation function are combined.
Volume: 9
Issue: 3
Page: 806-811
Publish at: 2018-03-01

Investigation and Visualization of Query Determine Spatial Pattern in GIS

10.11591/ijeecs.v9.i3.pp552-554
Anto Xavier. A , A. Arivazhagan
Earth elements are arranged following one or many standards called spatial patterns. Around the globe many elements share normal examples. To find those patterns and dissecting those through a few information visualization strategies can prompt a decent choice supporting framework. Information like area astute populace, schools and healing facilities is gathered from various sources. To store GIS information PostgreSQL and PostGIS is giving a good support and capable database. GIS maps are made utilizing instrument QGIS (Open source) for the visualization reason. To characterize basic example from the given dataset, bunches are framed from populace field. To bunch information OPTICS grouping strategy is utilized. At that point choice tree by data pick up strategy is utilized for the administered learning. To show the outcome open source programming Geo server is utilized. Geo server handle the client questions and show the outcome on the dynamic maps.
Volume: 9
Issue: 3
Page: 552-554
Publish at: 2018-03-01

Architecting Virality: Information Sharing from Government FB Page to Netizens

10.11591/ijeecs.v9.i3.pp660-666
Afdallyna Fathiyah Harun , Siti Nuradzarul Aqmaar Adzman , Fauzi Mohd Saman , Saiful Izwan Suliman
In accordance with e-government initiatives, many ministries in Malaysia have engaged content to public using social media for better two-way communications. However, creating an online presence is not necessarily easy as digital content consumers are often bombarded with information and those that fail to capture information will be rendered uninteresting and irrelevant. This is imperative as for most part, users are in control of where they allocate attention and what they share. Using virality as a context, it is opined that information content that are well-designed will trigger specific information and propel the sharing of that information over the Internet. A study employing FB post categorization and sharing motivations survey was carried out in the context of Ministry of Health Malaysia Facebook page. The findings show that users are inclined towards Infographics with various sharing motivations. The results can be used by Malaysian ministries on how best to design and disseminate information for the benefit of the netizens on social media sites.
Volume: 9
Issue: 3
Page: 660-666
Publish at: 2018-03-01

Effect of Integrated Feedback on Classroom Climate of Secondary School Teachers

10.11591/ijere.v7i1.11146
Nilesh Kumar Patel
This study aimed at finding out the effect of Integrated feedback on Classroom climate of secondary school teachers. This research is experimental in nature. Non-equivalent control group design suggested by Stanley and Campbell (1963) was used for the experiment. Integrated feedback was treatment and independent variable, Classroom climate was dependent variable and pre- Classroom climate, and Intelligence were considered as covariates. The sample of the study comprised of 77 secondary school teachers and 220 students studying in secondary classes from purposively selected four schools of Indore city. The data for Classroom climate, Job satisfaction and Intelligence were collected through standardized tools. One-way ANCOVA and 2X2 factorial design ANCOVA were used for data analysis. Hypotheses were tasted at level of significance with α = 0.05. It was found that the treatment has significant effect over Classroom climate when pre- Classroom climate was taken as covariate. The results also shown that Classroom climate was independent of the treatment when Intelligence and pre- Classroom climate were separately considered as covariates. In addition, classroom climate was also found independent of interaction between feedback and intelligence when pre – Classroom climate was taken as covariate.
Volume: 7
Issue: 1
Page: 65-71
Publish at: 2018-03-01

Search Engine-inspired Ranking Algorithm for Trading Networks

10.11591/ijeecs.v9.i3.pp812-818
Andri Mirzal
Ranking algorithms based on link structure of the network are well-known methods in web search engines to improve the quality of the searches. The most famous ones are PageRank and HITS. PageRank uses probability of random surfers to visit a page as the score of that page, and HITS instead of produces one score, proposes using two scores, authority and hub scores, where the authority scores describe the degree of popularity of pages and hub scores describe the quality of hyperlinks on pages. In this paper, we show the differences between WWW network and trading network, and use these differences to create a ranking algorithm for trading networks. We test our proposed method with international trading data from United Nations. The similarity measures between vectors of proposed algorithm and vector of standard measure give promising results.
Volume: 9
Issue: 3
Page: 812-818
Publish at: 2018-03-01

Internet of Things Based Weather Forecast Monitoring System

10.11591/ijeecs.v9.i3.pp555-557
Atul Kulkarni , Debajyoti Mukhopadhyay
Weather forecasting is a significant function in meteorology and has been one of the most systematically challenging troubles around the world.This scheme deals with the structure of a weather display method using small cost components so that any electronics hobbyist can construct it. As a replacement for using sensors to collect the weather data, the development gets the information from weather stations placed around the world through a global weather data supplier. Severe weather phenomena challengedifficult weather forecast approach with the partial explanation. Weather events have numerous parameters that are not possible to detail and compute. Growing on communication methods enables weather predictsspecialist systems to combine and share possessions and thus hybrid systems have emerged. Still, though these improvements on climate predict, these expert systems can’t be entirely reliable while weather forecast is central problem.
Volume: 9
Issue: 3
Page: 555-557
Publish at: 2018-03-01

Improving Resilience and Self-Esteem among University Students with Entrepreneurship Simulation Board Game

10.11591/ijere.v7i1.11406
Kususanto Prihadi , Damien Z.Y. Cheow , Jonathan H.E Yong , Megaaneesh Sundrasagran
This study aims to evaluate the effect of the frequency of playing a board game that simulates entrepreneurial experience called “Traders” on the university students’ resilience and self-esteem. Traders Board Game (TBG) was developed in 2015 with an aim to improve several entrepreneurship skills among young adults, and resilience being one of them. Pre and posttests of resilience have been done to 12 participants before they were divided into three groups: the control group, who did not play the game, the experimental group A, who played the game once a week for three weeks, and the experimental group B, who played the game twice a week for three weeks. Resilience was measured by adapting Connor-Davidson Resilience Scale, whereas self-esteem was measured by utilizing Mruk two-dimensional Self-esteem scale. There was a statistically significant difference among the the three groups in resilience improvement, where the experimental group A scored the highest, and no significant difference was discovered in terms of self-eteem improvement. The results suggested that playing TBG in certain frequency significantly improves resilience among the participants.
Volume: 7
Issue: 1
Page: 48-56
Publish at: 2018-03-01
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