Fungsi Filsafat Pendidikan Terhadap Ilmu Pendidikan

Tulisan ini membahas tentang filsafat pendidikan terhadap ilmu pendidikan.Filsafat merupakan acuan untuk meningkatkan mutu pendidikan., disadari atautidak, nampaknya dapat mempengaruhi situasi dan kondisi yangmemprihatinkan seperti saat ini, kita menumpukan seluruh harapan kepadapendidikan, karena sadar bahwa hanya melalui pendidikan kita dapatmemperbaiki hidup. Manusia tidak terlepas dari jangkauan pikirannya yangmencirikan hakekat manusia dan berpikirlan dia menjadi manusia, danselanjutnya Ilmu pengetahuan berkembang dari rasa ingin tahu, yangmerupakan ciri khas manusia. Ilmu pengetahuan merupakan upaya khususmanusia untuk menyingkapkan realitas, supaya memungkinkan manusiaberkomunikasi satu sama lain, membangun dialog dengan mengakui yang lain,dan meningkatkan harkat kemanusiaannya

Participatory impact assessment of ticks on cattle milk production in pastoral and agro-pastoral production systems of Borana Zone, Oromia Regional State, Southern Ethiopia

Participatory impact assessment of ticks on Borana cattle milk production was conducted from January 2010 to July 2010. The objectives of this study were to assess the status of tick infestation in relation to climate change, teats blinding and milk production and to estimate the economic losses caused as a result of the effect of ticks on dairy cattle and its implications on food security in Yabello, Moyale and Meo districts of Borana zone. Multi-stage sampling technique was employed and the data was analyzed using descriptive statistics and matrix triangulation. Thus, about six villages “Ollas” were systematically identified and a total of 86 households were interviewed employing questionnaires comprising 6-12 pastoralists and agropastoralists per ten PAs which in sum contained 60-120 individuals who provided information pertaining to the objectives set; in which increase of ticks population at an alarming rate was perceived having several factors affecting and its real impact of blinding on teats which signal loss of milk production which in fact revealed economic loss and implicated food insecurity on vulnerable social groups, specifically children and elders >80 years old within the settings. Tick resistance to currently available acaricides was complained by communities. It was observed that acaricides were sold in open market and there was no strong control on illegal veterinary drug vendors. Communities also purchase these acaricides and misuse them which, contributed to the increase of acaricide resistance. This is a good indication for policy makers and local authorities to take strict action on illegal drug vendors

Deep Discrete Hashing with Self-supervised Pairwise Labels

Hashing methods have been widely used for applications of large-scale image retrieval and classification. Non-deep hashing methods using handcrafted features have been significantly outperformed by deep hashing methods due to their better feature representation and end-to-end learning framework. However, the most striking successes in deep hashing have mostly involved discriminative models, which require labels. In this paper, we propose a novel unsupervised deep hashing method, named Deep Discrete Hashing (DDH), for large-scale image retrieval and classification. In the proposed framework, we address two main problems: 1) how to directly learn discrete binary codes? 2) how to equip the binary representation with the ability of accurate image retrieval and classification in an unsupervised way? We resolve these problems by introducing an intermediate variable and a loss function steering the learning process, which is based on the neighborhood structure in the original space. Experimental results on standard datasets (CIFAR-10, NUS-WIDE, and Oxford-17) demonstrate that our DDH significantly outperforms existing hashing methods by large margin in terms of~mAP for image retrieval and object recognition. Code is available at \url{https://github.com/htconquer/ddh}

Large-scale data for multiple-view stereopsis

The seminal multiple-view stereo benchmark evaluations from Middlebury and by Strecha et al. have played a major role in propelling the development of multi-view stereopsis (MVS) methodology. The somewhat small size and variability of these data sets, however, limit their scope and the conclusions that can be derived from them. To facilitate further development within MVS, we here present a new and varied data set consisting of 80 scenes, seen from 49 or 64 accurate camera positions. This is accompanied by accurate structured light scans for reference and evaluation. In addition all images are taken under seven different lighting conditions. As a benchmark and to validate the use of our data set for obtaining reasonable and statistically significant findings about MVS, we have applied the three state-of-the-art MVS algorithms by Campbell et al., Furukawa et al., and Tola et al. to the data set. To do this we have extended the evaluation protocol from the Middlebury evaluation, necessitated by the more complex geometry of some of our scenes. The data set and accompanying evaluation framework are made freely available online. Based on this evaluation, we are able to observe several characteristics of state-of-the-art MVS, e.g. that there is a tradeoff between the quality of the reconstructed 3D points (accuracy) and how much of an object’s surface is captured (completeness). Also, several issues that we hypothesized would challenge MVS, such as specularities and changing lighting conditions did not pose serious problems. Our study finds that the two most pressing issues for MVS are lack of texture and meshing (forming 3D points into closed triangulated surfaces)

Deep Semantic Matching with Foreground Detection and Cycle-Consistency

Establishing dense semantic correspondences between object instances remains a challenging problem due to background clutter, significant scale and pose differences, and large intra-class variations. In this paper, we address weakly supervised semantic matching based on a deep network where only image pairs without manual keypoint correspondence annotations are provided. To facilitate network training with this weaker form of supervision, we 1) explicitly estimate the foreground regions to suppress the effect of background clutter and 2) develop cycle-consistent losses to enforce the predicted transformations across multiple images to be geometrically plausible and consistent. We train the proposed model using the PF-PASCAL dataset and evaluate the performance on the PF-PASCAL, PF-WILLOW, and TSS datasets. Extensive experimental results show that the proposed approach performs favorably against the state-of-the-art methods.Comment: ACCV 2018. PAMI 2020 extension: arXiv:1906.0585

Micropropagación de caña de azúcar en Ecuador

Ecuador is a country where sugar cane (Saccharum spp. hybrid) exceeds 82 000 ha for sugar production. The Research Center of the National Union of sugar cane farming in Ecuador (UNCE) is plotted as objective to obtain plants of different varieties by micropropagation, to multiply quickly and efficiently, genotypes with excellent performance under the conditions of production and result in a high quality certified seed and plant genetics. It were used as initial explants shoots, of the varieties ‘Cenicaña 1985-1992’ (CC85-92), ‘Ragnar’, ‘BJ 7046’, ‘CR 74-250’, ‘SP70-1143’, ‘PCG 12 745’ ‘RD7511’ and ‘Mexico 73-0523’. The obtained seedlings were multiplied, rooted and acclimatised. Then be planted in areas where sugar cane is grown in the country. In the case of the variety ‘Ragnar’ planted an area of approximately 0.3 ha, which was determined yield (ton/ha). Micropropagation of selected varieties allowed to obtain 268 600 plants in 12 months. It was found that the varieties showed differences in their rates of multiplication. The survival of plants in the acclimatization phase was higher than 88.0%. The harvest for the experimental plot planted with the variety ‘Ragnar’ contributed 55 tons. This equates to an output of 183 ton/ha. These values are much higher than the national average. The results confirmed the non-appearance of diseased plants or Scalding RSD. These results are one of the first reports for Ecuador from the use of biotechnological methods, being the pioneers in the mass propagation of sugarcane plants.Keywords: mass propagation, Saccharum spp. hybrid, seedEcuador es un país donde la caña de azúcar (Saccharum spp. híbrido) supera las 82 000 ha dedicadas a la producción de azúcar. El Centro de Investigación de la Unión Nacional de Cañicultores del Ecuador (UNCE) se trazó como objetivo obtener plantas de diferentes variedades por micropropagación, que permitiera multiplicar de manera rápida y eficaz, genotipos con excelente comportamiento en las condiciones de producción y que resultaran en una semilla certificada de alta calidad genética y fitosanitaria. Se emplearon como explantes iniciales meristemos apicales de las variedades ‘CeniCaña 85-92’ (CC85-92),‘Ragnar’, ‘BJ 7046’, ‘CR 74-250’, ‘SP70-1143’, ‘PCG 12745’, ‘RD7511’ y ‘México 73-0523’. Las plántulas obtenidas se multiplicaron, enraizaron y aclimatizaron. Posteriormente, se sembraron en áreas donde se cultiva caña de azúcar en el país. En el caso de la variedad ‘Ragnar’ se plantó un área de aproximadamente 0.3 ha, en la cual se determinó el rendimiento (t/ha). La micropropagación de las variedades seleccionadas permitió obtener 268 600 plantas en 12 meses. Se comprobó que las variedades mostraron diferencias en sus coeficientes de multiplicación. La supervivencia de las plantas en la fase de aclimatización fue superior al 88.0%. La cosecha correspondiente a la parcela experimental sembrada con la variedad ‘Ragnar’ aportó 55 t. esto equivale a una producción de 183 t/ha. Estos valores son muy superiores a la media nacional. Los resultados confirmaron la no aparición de plantas enfermas por RSD o Escaldadura. Estos resultados constituyen uno de los primeros informes para Ecuador de la utilización de métodos biotecnológicos, siendo los pioneros en la propagación masiva de plantas de caña de azúcar.Palabras clave: propagación masiva, Saccharum spp. híbrido, semill