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All Journal Jurnal Manajemen dan Agribisnis TELKOMNIKA (Telecommunication Computing Electronics and Control)
Uswah Khairuddin
Universiti Teknologi Malaysia
Agriculture, Biological Sciences & Forestry Computer Science & IT Economics, Econometrics & Finance

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Energy extraction method for EEG channel selection Hilman Fauzi; M. Abdullah Azzam; Mohd. Ibrahim Shapiai; Masaki Kyoso; Uswah Khairuddin; Tadayasu Komura
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 5: October 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i5.12805

Abstract

Channel selection is an improvement technique to optimize EEG-based BCI performance. In previous studies, many channel selection methods—mostly based on spatial information of signals—have been introduced. One of these channel selection techniques is the energy calculation method. In this paper, we introduce an energy optimization calculation method, called the energy extraction method. Energy extraction is an extension of the energy calculation method, and is divided into two steps. The first step is energy calculation and the second is energy selection. In the energy calculation step, l2-norm is used to calculate channel energy, while in the energy selection method we propose three techniques: “high value” (HV), “close to mean” (CM), and “automatic”. All proposed framework schemes for energy extraction are applied in two types of datasets. Two classes of datasets i.e. motor movement (hand and foot movement) and motor imagery (imagination of left and right hand movement) were used. The system used a Common Spatial Pattern (CSP) method to extract EEG signal features and k-NN as a classification method to classify the signal features with k = 3. Based on the test results, all schemes for the proposed energy extraction method yielded improved BCI performance of up to 58%. In summary, the energy extraction approach using the CM energy selection method was found to be the best channel selection technique.
The Growth Performance and Costs of Rearing Friesian Crossbreed Dairy Young Stock in Malaysian Commercial Farm Ang Xin Tong; Norhariani Mohd Nor; Shanmugavelu Sithambaram; Mark Wen Han Hiew; Uswah Khairuddin; Mohd Ibrahim Shapiai; Nurul Aisyah Mohd Suhaimi; Peter Lee Ah Kong; Muhammad Ali Hanapiah
Jurnal Manajemen & Agribisnis Vol. 18 No. 3 (2021): JMA Vol. 18 No. 3, November 2021
Publisher : School of Business, Bogor Agricultural University (SB-IPB)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17358/jma.18.3.362

Abstract

The important elements in rearing dairy young stock are good farm management, proper growth and optimal costs of rearing. A survey on these important elements was conducted at two commercial farms in Johor and Sabah in 2019. The farm herd size is 214 heads and 2,221 heads with 163,682 litres and 4.2 mil. litres of milk production, in Johor and Sabah respectively. In addition, the body weight data of 188 dairy young stock was collected and analysed to determine the growth performance using polynomial growth function. The results showed the two farms have youngstock with different Friesian blood levels (60% and 70% in Johor, and 87.5% in Sabah) with different growth performance. The average weight of dairy young stock with 60%, 70% and 87.5% Friesian blood levels at birth were 21.31±3.70kg, 22.33±2.23kg and 26.55±2.68kg, respectively, while average weight at 3 months of age were 45.00±7.07kg, 55.57±8.36kg and 75.84±12.54kg, respectively. Heifers with 87.5% Friesian blood levels was bred at 15 months of age (444kg) while heifers with lower Friesian blood levels was bred 6 months later (250kg). The average rearing (feed) cost was RM4,932 (USD1,194)/heifer. The findings of this study can give awareness and insights in the performance and costs of rearing crossbreed dairy young stock in tropics. Keywords: tropical, dairy, young stock, management, rearing cost
Co-Authors Ang Xin Tong Hilman Fauzi, Hilman M. Abdullah Azzam Mark Wen Han Hiew Masaki Kyoso Mohd Ibrahim Shapiai Mohd. Ibrahim Shapiai Muhammad Ali Hanapiah Norhariani Mohd Nor Nurul Aisyah Mohd Suhaimi Peter Lee Ah Kong Shanmugavelu Sithambaram Tadayasu Komura