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Ternate, Indonesia

Wahab L.H.A.,Gadjah Mada University | Wahab L.H.A.,Khairun University | Susanto A.,Gadjah Mada University | Insap Santosa P.,Gadjah Mada University | Tjokronegoro M.,Gadjah Mada University
International Journal of Imaging and Robotics | Year: 2016

Analysis and interpretation of malaria parasite images were performed in which one of them was to obtain the parasite image patterns, thus it could be conducted classification process towards image based on its pattern. The parasite image pattern is different between one and another, this depends on parasite type. Differentiating between one image and another needs a feature for each pattern. This study, therefore, aimed to analyze and evaluate algorithms of learning vector quantization neural network for malaria parasite pattern recognition test in real time. The result of this study showed that the LVQ network classification method could recognize 92% object,. Algorithm time complexity for LVQ is O(n). © 2016 by IJIR (CESER PUBLICATIONS).

Najamuddin,Khairun University | Prartono T.,Bogor Agricultural University | Sanusi H.S.,Bogor Agricultural University | Nurjaya I.W.,Bogor Agricultural University
Marine Pollution Bulletin | Year: 2016

Lead (Pb) and zinc (Zn) concentrations from surface sediments were determined at 17 stations in riverine, estuarine, and marine environments during the wet and dry seasons. The geochemical fractionations were obtained by a sequential extraction procedure in five geochemical forms: exchangeable, bound to carbonate, iron-manganese oxide, organic, and residual fractions. The concentrations of Pb and Zn in the water were higher during the wet season than the dry season and higher in the riverine and marine samples than the estuarine samples. Following geochemical fractionation, the metals were found mainly in the residual fraction. The results indicated that the concentrations were influenced by season, with the sources of Pb and Zn derived mainly from rivers and natural sources. The contamination status in the estuary of the Jeneberang River was classified as weak to moderate pollution and the risk level to aquatic biota attributed was no risk to low risk. © 2016.

Islam M.S.,Mawlana Bhashani Science and Technology University | Al Mamun S.,Lincoln University at Christchurch | Muliadi,Khairun University | Rana S.,Mawlana Bhashani Science and Technology University | And 2 more authors.
Agrivita | Year: 2015

Brick kiln is a big environmental issue for the agriculture of Bangladesh as it was observed that the agricultural production in the soil close to the brick kiln was lesser than the same soil far from brick kiln. The study was conducted to assess the impact of brick kiln operation to the degradation of topsoil quality at Singair of Kalihati upazila in Tangail, Bangladesh, during the period of July to December 2013. The Soil was collected from areas close to the brick fields and far from the brick fields at a depth of 0-15 cm. The Electrical Con-ductance (EC) was found almost double in the soil samples close to the brick field than the soil samples far from brick field. The organic mattter content in the soil sample close to the brickfield was significantly lower than that of the far soil sample. The mean values of total N, available P and S were also significantly lower in the soil samples close to the brick kiln, 0.05%, 12.4, and 8.36 ppm respectively in the close soils, while 0.06%, 24.6, and 11.7 ppm respectively in the far soil. There were no significant changes observed in the other elements. © 2015, Agriculture Faculty Brawijaya University. All rights reserved.

Hamsir Ayub Wahab I.I.S.,Gadjah Mada University | Hamsir Ayub Wahab I.I.S.,Khairun University | Susanto A.,Gadjah Mada University | Insap Santosa P.,Gadjah Mada University | Tjokronegoro M.,Gadjah Mada University
Journal of Theoretical and Applied Information Technology | Year: 2014

The main challenge in detecting malaria parasites is how to identify the subset of relevant features. The objective of this study was to identify a subset of features that are most predictive of malaria parasites using second-order statistical features and principal component analysis methods. Relevant features will provide the successful implementation of the overall detection modeling, which will reduce the computational and analytical efforts. The results showed that the combination of the principal components of the feature value the correlation to the ASM, and the contrast to the correlation can separate classes of malaria parasites. © 2005 - 2014 JATIT & LLS. All rights reserved.

Khairun University | Entity website

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