Om musik og mode (tøjfirmaet Ben Sherman) i England i 1960'erne og 1970'erne
Om musik og mode (tøjfirmaet Ben Sherman) i England i 1960'erne og 1970'erne
Untuk itu, perencanaan karir aparatur juga perlu diatur dengan sistem yang jelas,
pengaturan penggajian yang layak, penerapan sistem penghargaan atas
prestasi perlu dilakukan, dan berbagai upaya lainnya yang berakibat pada ...
Kualitas hasil belajar program keterampilan di Madrasah Aliyah tergantung dari keberhasilan kegiatan pembelajaran yang didukung oleh berbagai komponen-komponen pendidikan. Komponen-komponen yang terdiri dari: Kurikulum, tenaga pendidikan, Sarana Prasarana, Sistem Pengelolaan, Kondisi Siswa dan Lingkungan Sosial Ekonomi sebagaimana disebutkan harus diberdayakan se-optimal mungkin dalam kegiatan pembelajaran. Dari komponen-komponen tersebut, faktor Tenaga Kependidikan, Sarana Prasarana dan sistem pengelolaan manajemen, merupakan faktor yang tidak pembelajaran. Tenaga kependidikan adalah Guru Keterampilan, Sarana Prasarana yaitu faktor pendukung pada kegiatan keterampilan berupa gedung dan peralatannya, sedangkan sistem pengelolaan manajemen adalah berupa perencanaan, persiapan mengajar, juga sistem yang mendukung program pengajaran keterampilan yaitu kurikulum, pendanaan dan dukungan baik dukungan internal maupun dukungan eksternal pada Madrasah Aliyah di Jakarta. Alasan dari ketiga faktor yang menjadi perhatian penulis untuk ditinjau dan ditelaah dengan mengembangkan variable-variabel permasalahannya adalah ketiga komponen pendidikan tersebut dapat diandalkan fungsi dan pemberdayaan terhadap komponen lainnya dalam keberhasilan pencapaian tujuan pendidikan.
A. Hasil Penelitian 1. Program Studi Keterampilan Pada Madrasah Aliyah yang
ada di Madrasah Aliyah Jakarta. Sesuai dengan permohonan ijin penelitian yang
peneliti ajukan kepada Ketua Program Magister Administrasi Pendidikan untuk ...
Services, rehabilitation, and institutional care for the blind in Indonesia; research report.
Diantara ketiga kepemimpinan yang dikemuka- kan yang terbaik menurut
pimpinan Panti adalah kombinasi antara pe tugas dengan anak asuh secara
bergantian. Oleh karena dengan membe rikan kesempatan kepada anak asuh
berarti kita ...
The research and development in modeling and simulation of human cognizance functions requires a high performance computing platform for large-scale mathematical models. Traditional computing architecture cannot fulfill the needs in arithmetic computation and communication bandwidth. This work presents a hybrid computing architecture that consists of a general purpose microprocessor and a hardware accelerator for accelerating the BSB model operations, recall and training. The BSB model, an associative neural network was first described by Anderson et al. (1977) is used primarily to model the effects of human cognizance functions. This work proposes an architecture and FPGA (Field Programmable Gate Array) design for 128-neuron BSB model, for both recall and training operations. This work also proposes a design for implementing multiple 128-neuron BSB models on a single FPGA and the design was tested by performing a demo on a host PC. The pattern recognition application was extensively tested on the 128-neuron BSB model. Experimental results show that, hardware implementation of 128-neuron BSB model is 7.4x faster than the software only implementation.
This work presents a hybrid computing architecture that consists of a general purpose microprocessor and a hardware accelerator for accelerating the BSB model operations, recall and training.
Detailed spatial and temporal mapping of anatomical changes in human brain is crucial in understanding the basis of age-related cognitive advancement and various neurological disorders. Magnetic resonance imaging (MRI) is a non-invasive medical imaging technique that provides high resolution structural images of human brain. Tensor-based morphometry (TBM) is an image analysis technique that characterizes local shape differences from the gradients of the deformation field. TBM can be applied to cross-sectional MRI data for local shape comparisons between two or more groups of subjects, based on nonlinearly registering individual brain scans to a common anatomical template. Moreover, when TBM is applied to longitudinal MRI study, the derived Jacobian maps represent the percentage of tissue change over time. In my dissertation work, I explored the application of TBM in mapping anatomical changes of human brain during normal development, anomalous development in autism, age related memory condition known as mild cognitive impairment (MCI), and neurodegeneration in Alzheimer's disease (AD). In the normal development study, Jacobian maps tracking dynamic tissue growth were created for each of the 13 healthy developing children. Statistical analyses revealed significant tissue growth in cerebral white matter, contrasted with gray matter loss in parietal, temporal, and occipital lobe. A linear regression with age and gender suggested a slowing down of the growth rate in regions with the greatest white matter growth. Next, by comparing the regional tissue change rate from the longitudinal brain scans of 13 autistic and 7 normal developing boys, I revealed aberrant development in brain regions that have been implicated in autism's social impairment, communication deficits and repetitive behaviors. Finally, in one of the largest brain MRI studies to date, I compared the anatomical distribution of atrophy in 165 AD patients, 330 MCI subjects, and 181 controls and revealed 3D correlations between neuroimaging markers, genes, and future clinical changes. Baseline temporal lobe atrophy mapped by TBM correlated with current cognitive performance, future cognitive decline, and conversion from MCI to AD over the following year. Overall, I demonstrated that tensor-based Jacobian is a sensitive and reliable method to detect regional tissue changes during normal and pathological conditions.
Detailed spatial and temporal mapping of anatomical changes in human brain is crucial in understanding the basis of age-related cognitive advancement and various neurological disorders.
