@artikel{Sarwar20191824,
tajuk = {Sokongan sosial, optimisme, efikasi kendiri ibu bapa dan kesejahteraan ibu kanak-kanak dengan gangguan spektrum autisme},
pengarang = {F Sarwar dan S A Panatik dan A Rajab dan N Nordin},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074977478&doi = 10.5958% 2f0976-5506.2019.02719.0&rakan kongsi = 40&md5=6760a63e9eca52a1bb463dc10bd5abe6},
doi = {10.5958/0976-5506.2019.02719.0},
terbitan = {09760245},
tahun = {2019},
tarikh = {2019-01-01},
jurnal = {Jurnal India Penyelidikan dan Pembangunan Kesihatan Awam},
isi padu = {10},
nombor = {9},
halaman = {1824-1829},
penerbit = {Jurnal India Penyelidikan dan Pembangunan Kesihatan Awam},
abstrak = {Ia telah dihipotesiskan bahawa optimisme, efikasi kendiri dan sokongan sosial adalah peramal positif kepuasan hidup dan kesan positif dan peramal negatif tekanan yang dirasakan dan kesan negatif. Data dikumpul dengan kaedah tinjauan daripada 47 ibu kepada kanak-kanak autisme di Lahore dan Faisalabad. Hipotesis telah diuji pada empat model empat pembolehubah bersandar menggunakan analisis regresi hierarki. Keputusan menggambarkan bahawa efikasi kendiri ibu bapa adalah peramal yang signifikan bagi keempat-empat pembolehubah bersandar, sokongan sosial adalah peramal penting kepuasan hidup dan tekanan yang dirasakan, manakala keyakinan hanya meramalkan varians secara signifikan dalam kepuasan hidup. Kajian itu adalah yang pertama dari jenisnya yang akan dilakukan dengan sampel dalam konteks Pakistan dan mempunyai implikasi penting untuk ahli psikologi klinikal. Mereka boleh merancang intervensi untuk meningkatkan kesejahteraan subjektif dan mengurangkan tekanan secara langsung atau tidak langsung dengan memberi tumpuan kepada anteseden yang diuji dalam kajian.. © 2019, Jurnal India Penyelidikan dan Pembangunan Kesihatan Awam. Hak cipta terpelihara.},
nota = {dipetik oleh 0},
kata kunci = {Dewasa, Artikel, Assessment of Humans, Autisme, Anak-anak, Correlation Analysis, Kajian Lintas Bahagian, Perempuan, Manusia, Life Orientation Test, Kepuasan Hidup, Skala Likert, Lelaki, Maternal Behavior, Multidimensional Scale of Percieved Social Support, Optimism, Parenting Sense of Competence, Skala Tekanan yang Diperhatikan, Positive and Negative Affect Schedule, Soal selidik, Satisfaction with Life Scale, Konsep Kendiri, Sokongan Sosial, Kesejahteraan},
pubstate = {diterbitkan},
tppubtype = {artikel}
}

@artikel{Bhat2014851,
tajuk = {Automated diagnosis of autism: In search of a mathematical marker},
pengarang = {S Bhat and U R Acharya and H Adeli and G M Bairy and A Adeli},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84925286949&doi=10.1515%2frevneuro-2014-0036&rakan kongsi = 40&md5=04858a5c9860e9027e3113835ca2e11f},
doi = {10.1515/revneuro-2014-0036},
terbitan = {03341763},
tahun = {2014},
tarikh = {2014-01-01},
jurnal = {Reviews in the Neurosciences},
isi padu = {25},
nombor = {6},
halaman = {851-861},
penerbit = {Walter de Gruyter GmbH},
abstrak = {Autism is a type of neurodevelopmental disorder affecting the memory, behavior, emotion, learning ability, and communication of an individual. An early detection of the abnormality, due to irregular processing in the brain, can be achieved using electroencephalograms (LIHAT). The variations in the EEG signals cannot be deciphered by mere visual inspection. Computer-aided diagnostic tools can be used to recognize the subtle and invisible information present in the irregular EEG pattern and diagnose autism. This paper presents a state-of-theart review of automated EEG-based diagnosis of autism. Various time domain, frequency domain, time-frequency domain, and nonlinear dynamics for the analysis of autistic EEG signals are described briefly. A focus of the review is the use of nonlinear dynamics and chaos theory to discover the mathematical biomarkers for the diagnosis of the autism analogous to biological markers. A combination of the time-frequency and nonlinear dynamic analysis is the most effective approach to characterize the nonstationary and chaotic physiological signals for the automated EEGbased diagnosis of autism spectrum disorder (ASD). The features extracted using these nonlinear methods can be used as mathematical markers to detect the early stage of autism and aid the clinicians in their diagnosis. This will expedite the administration of appropriate therapies to treat the disorder. © 2014 Walter de Gruyter GmbH.},
nota = {dipetik oleh 34},
kata kunci = {Algoritma, Artikel, Autisme, Gangguan Spektrum Autisme, Automasi, Biological Model, Otak, Chaos Theory, Correlation Analysis, Detrended Fluctuation Analysis, Disease Marker, Electrode, Elektroencephalogram, Elektroensefalografi, Entropy, Fourier Transformation, Fractal Analysis, Frequency Domain Analysis, Manusia, Mathematical Analysis, Mathematical Marker, Mathematical Parameters, Models, Neurologic Disease, Neurological, Nonlinear Dynamics, Nonlinear System, Patofisiologi, Jurnal Keutamaan, Prosedur, Pemprosesan isyarat, Model Statistik, Masa, Time Frequency Analysis, Wavelet Analysis},
pubstate = {diterbitkan},
tppubtype = {artikel}
}