RUSSIAN SCHOLARS and the QUR'ÂN: Historical Perspective of the Development of Russian Orientalists in the 19th–20th Centuries

Ilmuan Rusia dan al-Qur'an: Perspektif Sejarah Perkembangan Orientalis Rusia abad ke 19 dan 20. Setelah keberhasilan Mullah Usman Ibrahim pada abad ke 18, studi al-Qur'an di Rusia sejak abad ke 19 tidak mengalami kemajuan signifikan. Kondisi ini berlanjut hingga G.S. Sablukov dan D.N Boguslavskiy pada akhirya menciptakan karya sendiri mereka tentang tafsir al-Qur'an pada masa paruh kedua abad ke 19. Perkembangan tradisi Rusia dalam pengkajian al- Qur'an semakin pesat ketika ilmuan Rusia yang lain, I. Yu. Krachkovsky, memper- kenalkan pendekatan baru dalam memahami dan menginterpretasi Kitab Suci al- Qur'an bagi masyarakat Rusia pada awal abad ke 20. Dalam makalah ini penulis mengemukakan bahwa sangat disayangkan, ilmuan Rusia memasuki era kegelapan dalam pengkajian al-Qur'an ketika regim Komunis Soviet menagmbil alih kendali pemerintahan dan memperkenalkan kebijakan dan propaganda ateistis pada paruh kedua abad ke 20. Makalah ini berupaya untuk menganalisa sejarah perkembangan studi al-Qur'an dalam kondisi sosial, kultur dan politik atmosfir akademis Rusia

Arabistika: Jendela Kecil Kajian Islam Di Rusia (Menelisik Sejarah Awal Pertumbuhan Kajian Islam Di Rusia Abad Ix-xviii M)

Study on the Islamic studies tradition (orientalism) in Russia is quite rare, whereas compared to the Europeans or the West in general, the Russians actually have far reached into contact with Islam through a variety of traditions and cultures that developed the Arab-Muslim and Arab-Jewish. This encounter in the next stage turned into the birth of a tradition encouraging the study of Russian orientalism known as arabistika. This article attempts to trace the history of the growth of Islamic studies in Russia by looking at the factors driving its development and the official policies of the country's political elite, especially of Peters the Great. The author, in this context, tries to analyze the findings of I.Yu Krachkovsky on spiritual tour performed by Russian intelligentsia to the Arab world, and the sources of Muh}ammad Na>z}im ad-Daira>wi revealing the information and documentation of ancient Russian that are immortalized by the some geographers, historians, prominent Muslim adventurers such as at}-T}abari, al-Maqdisi, al-Idri>si>, al-Mas‘u>di>, Ibn Khurdadbih, Ibn H}auqal, Ibn Fad}la>n, Ibnu Bat{u>t}a and many others. This paper also reveal many of the central role of Peter the Great in the development of arabistika tradition in Russia

Neutrino Masses, Lepton Flavor Mixing and Leptogenesis in the Minimal Seesaw Model

We present a review of neutrino phenomenology in the minimal seesaw model (MSM), an economical and intriguing extension of the Standard Model with only two heavy right-handed Majorana neutrinos. Given current neutrino oscillation data, the MSM can predict the neutrino mass spectrum and constrain the effective masses of the tritium beta decay and the neutrinoless double-beta decay. We outline five distinct schemes to parameterize the neutrino Yukawa-coupling matrix of the MSM. The lepton flavor mixing and baryogenesis via leptogenesis are investigated in some detail by taking account of possible texture zeros of the Dirac neutrino mass matrix. We derive an upper bound on the CP-violating asymmetry in the decay of the lighter right-handed Majorana neutrino. The effects of the renormalization-group evolution on the neutrino mixing parameters are analyzed, and the correlation between the CP-violating phenomena at low and high energies is highlighted. We show that the observed matter-antimatter asymmetry of the Universe can naturally be interpreted through the resonant leptogenesis mechanism at the TeV scale. The lepton-flavor-violating rare decays, such as $\mu \to e + \gamma$, are also discussed in the supersymmetric extension of the MSM.Comment: 50 pages, 22 EPS figures, macro file ws-ijmpe.cls included, accepted for publication in Int. J. Mod. Phys.

Pengaruh zikir terhadap kesihatan mental dan tekanan psikologi dalam mendepani cabaran revolusi industri 4.0

Revolusi Industri 4.0 (IR4) telah memberi implikasi negatif terhadap kesihatan mental dan psikologi dalam masyarakat seperti kemurungan, kebimbangan dan tekanan perasaan. Masalah-masalah ini mampu diatasi dengan amalan zikir sebagai terapi psikospiritual berunsur kerohanian Islam. Kajian ini berbentuk kualitatif dengan menggunakan kaedah temu bual separa-berstruktur serta analisis secara deduktif, induktif dan tematik untuk mengetahui kesan sebelum dan selepas berzikir secara berjemaah. Pendekatan Lataif Qur’aniyyah digunakan untuk memaknakan kedudukan al-zikr dan pengamalannya lebih meluas. Peserta-peserta majlis zikir bulanan dalam kajian ini terdiri daripada 83 orang dan diadakan di Kediaman Rasmi Menteri Besar Selangor. Hasil kajian menunjukkan ‘zikir bersanad’ yang diamalkan secara konsisten merupakan santapan rohani terbaik dalam mempengaruhi jiwa dan emosi individu ke arah celik akal yang menjadi matlamat kemuncak dalam kaunseling. Hal ini berkesan dalam membantu perubahan minda dan tingkah laku manusia dalam pembentukan keluarga dan masyarakat yang bersahsiah dan harmoni. Justeru, zikir yang bersanad, yakni dalam bimbingan bersama guru rohani (Mursyid), dengan fokus niat untuk mencapai ‘keterhubungan kerohanian’ dengan Nabi Muhammad (s.a.w.) dan ‘jiwa fakir’ kepada Allah (s.w.t.), serta memenuhi adab-adab dan syarat-syarat takwa adalah terapi psikospiritual yang mujarab dalam merawat pelbagai masalah mental

Human physical activity recognition algorithm based on smartphone sensor data and convolutional neural network

Human activity recognition (HAR) is a prominent application of advanced Machine Learning (ML) and Artificial Intelligence (AI) techniques that utilizes computer vision to understand the semantic meanings of heterogeneous human actions. This paper describes a supervised learning method that can distinguish human actions based on data collected from practical human movements. This study proposes a HAR classification model based on a Convolutional Neural Network (CNN) and uses the collected human action signals. The model was tested on the WISDM dataset, which resulted in a 92 % classification accuracy. This approach will help to conduct further researches on the recognition of human activities based on their biomedical signals