HUBUNGAN DUKUNGAN KELUARGA DENGAN KONSEP DIRI PASIEN TUBERKULOSIS PARU DI BALAI KESEHATAN PARU MASYARAKAT BANDA ACEH TAHUN 2012

KEMENTRIAN PENDIDIKAN DAN KEBUDAYAANUNIVERSITAS SYIAH KUALAFAKULTAS KEDOKTERANPROGRAM STUDI ILMU KEPERAWATANSKRIPSI7 Oktober 2012Xiv + VI Bab + 73 halaman + 13 tabel + 1 skema + 14 lampiranAAN SOFYANA0807101060003HUBUNGAN DUKUNGAN KELUARGA DENGAN KONSEP DIRI PASIENTUBERKULOSIS PARU DI BALAI KESEHATAN PARU MASYARAKATBANDA ACEH TAHUN 2012ABSTRAKPenderita TB Paru masih mengalami stigma sosial dan ketidakadilan di masyarakat,diantaranya yaitu gangguan komponen konsep diri. Keluarga dapat menjadikelompok pendukung utama dalam hal pencegahan terjadinya gangguan komponenkonsep diri pada pasien TB Paru. Tujuan penelitian ini untuk mengetahui hubungandukungan keluarga dengan konsep diri pasien Tuberkulosis Paru di Balai KesehatanParu Masyarakat Banda Aceh 2012. Jenis penelitian adalah deskriptif korelatif.Desain penelitian cross sectional study melalui tekhnik purposive sampling denganjumlah sampel sebanyak 63 pasien TB Paru. Pengumpulan data penelitian dilakukanmulai tanggal 3 - 6 september 2012 dengan membagikan kuisioner yang terdiri dari35 item pernyataan dalam skala likert dan dichotomous choice. Metode analisis datadengan menggunakan uji statistik chi-square, hasil penelitian adalah ada hubunganantara dukungan sosial keluarga (P-value 0,005), dukungan penilaian (P-value0,010), dukungan tambahan (P-value 0,010) dan dukungan emosional (P-value0,022) dengan konsep diri pasien TB Paru. Maka dapat disimpulkan bahwa adahubungan antara dukungan keluarga (P-value 0,005) dengan konsep diri pasienTuberkulosis paru di Balai Kesehatan Paru Masyarakat Banda Aceh tahun 2012.Saran bagi Poliklinik Paru BKPM adalah agar dapat meningkatkan pengetahuanpasien TB Paru bahwa penyakit TB Paru dapat disembuhkan dengan berobat secarateratur dan bagi keluarga untuk dapat memberikan dukungan sehingga dapatmeningkatkan konsep diri pasien kearah yang positif.Kata kunci : Tuberkulosis paru, konsep diri, dukungan keluargaDaftar bacaan : 24 buku + 8 jurnal + 4 internet (1999-2012)Banda Ace

Triminimal Parametrization of Quark Mixing Matrix

Starting from a new zeroth order basis for quark mixing (CKM) matrix based on the quark-lepton complementarity and the tri-bimaximal pattern of lepton mixing, we derive a triminimal parametrization of CKM matrix with three small angles and a CP-violating phase as its parameters. This new triminimal parametrization has the merits of fast convergence and simplicity in application. With the quark-lepton complementary relations, we derive relations between the two unified triminimal parametrizations for quark mixing obtained in this work and for lepton mixing obtained by Pakvasa-Rodejohann-Weiler. Parametrization deviating from quark-lepton complementarity is also discussed.Comment: 9 pages, no figur

Multi-Label Classification with Label Graph Superimposing

Images or videos always contain multiple objects or actions. Multi-label recognition has been witnessed to achieve pretty performance attribute to the rapid development of deep learning technologies. Recently, graph convolution network (GCN) is leveraged to boost the performance of multi-label recognition. However, what is the best way for label correlation modeling and how feature learning can be improved with label system awareness are still unclear. In this paper, we propose a label graph superimposing framework to improve the conventional GCN+CNN framework developed for multi-label recognition in the following two aspects. Firstly, we model the label correlations by superimposing label graph built from statistical co-occurrence information into the graph constructed from knowledge priors of labels, and then multi-layer graph convolutions are applied on the final superimposed graph for label embedding abstraction. Secondly, we propose to leverage embedding of the whole label system for better representation learning. In detail, lateral connections between GCN and CNN are added at shallow, middle and deep layers to inject information of label system into backbone CNN for label-awareness in the feature learning process. Extensive experiments are carried out on MS-COCO and Charades datasets, showing that our proposed solution can greatly improve the recognition performance and achieves new state-of-the-art recognition performance.Comment: AAAI 202

Unified triminimal parametrizations of quark and lepton mixing matrices

We present a detailed study on triminimal parametrizations of quark and lepton mixing matrices with different basis matrices. We start with a general discussion on the triminimal expansion of the mixing matrix and on possible unified quark and lepton parametrization using quark-lepton complementarity (QLC). We then consider several interesting basis matrices and compare the triminimal parametrizations with the Wolfenstein-like parametrizations. The usual Wolfenstein parametrization for quark mixing is a triminimal expansion around the unit matrix as the basis. The corresponding QLC lepton mixing matrix is a triminimal expansion around the bimaximal basis. Current neutrino oscillation data show that the lepton mixing matrix is very well represented by the tri-bimaximal mixing. It is natural to take it as an expanding basis. The corresponding zeroth order basis for quark mixing in this case makes the triminimal expansion converge much faster than the usual Wolfenstein parametrization. The triminimal expansion based on tri-bimaximal mixing can be converted to the Wolfenstein-like parametrizations discussed in the literature. We thus have a unified description between different kinds of parametrizations for quark and lepton sectors: the standard parametrizations, the Wolfenstein-like parametrizations, and the triminimal parametrizations.Comment: 14 latex pages, no figure, to appear in PR