Precise time and frequency intercomparison between NPL, India and PTB, Federal Republic of Germany via satellite symphonie-1

A time and frequency intercomparison experiment conducted using Earth stations in New Delhi, India and Raisting, FRG is described. The NPL clock was placed at New Delhi Earth Station and the Raisting Clock was calibrated with PTB/Primary standard via LORAN-C and travelling clocks. The random uncertainity of time comparisons, represented by two sample Allan Variance sigma (30 seconds), was less than 10 nanoseconds. The relative frequency difference between the NPL and Raisting Clocks, SNPL, RAIS, as measured over the 44 days period was found to be -15.7 x 10 to the -13th power. The relative frequency difference between PTB Primary Standard and Raisting Clock, SPTB, RAIS, during this period, was measured to be -22.8 x 10 to the -13th power. The relative frequency difference between NPL clock and PTB Primary Standard, SNPL, PTB, thus, is +7.1 x 10 to the -13th power. The clock rate (UTC, India) of +7.1 + or - 0.5 x 10 to the -13th power, agrees well with that obtained via VLF phase measurements over one year period and with USNO travelling clock time comparisons made in September, 1980

Measurements of plasma temperature and electron density in laser-induced copper plasma by time-resolved spectroscopy of neutral atom and ion emissions

Plasma produced by a 355 nm pulsed Nd:YAG laser with a pulse duration of 6 ns focussed onto a copper solid sample in air at atmospheric pressure is studied spectroscopically. The temperature and electron density characterizing the plasma are measured by time-resolved spectroscopy of neutral atom and ion line emissions in the time window of 300-2000 ns. An echelle spectrograph coupled with a gated intensified charge coupled detector is used to record the plasma emissions. The temperature is obtained using the Boltzmann plot method and the electron density is determined using the Saha-Boltzmann equation method. Both parameters are studied as a function of delay time with respect to the onset of the laser pulse. The results are discussed. The time window where the plasma is optically thin and is also in local thermodynamic equilibrium (LTE), necessary for the laser-induced breakdown spectroscopy (LIBS) analysis of samples, is deduced from the temporal evolution of the intensity ratio of two Cu I lines. It is found to be 700-1000 ns

Produksi Program Acara Berita Feature “Harmoni Islam” di Cakra Semarang TV sebagai Program Director.

Menjelang Bulan Ramadhan, banyak stasiun televisi baik nasional maupun lokal yang berlomba-lomba membuat berbagai program untuk ikut memeriahkan datangnya bulan suci Ramadhan. Namun, kebanyakan stasiun televisi menampilkan program-program yang tidak sesuai dengan suasana Ramadhan yang religius seperti program acara lawak yang penuh kekerasan dan hanya menghibur saja, tanpa adanya edukasi.Oleh karena itu program kami membuat satu produk jurnalistik berupa tayangan televisi dengan format berita feature yang membahas tentang informasi-informasi seputar agama Islam untuk mengisi momentum Ramadhan yang dikemas secara santai, mudah dimengerti, dan tampilan visual yang menarik. Pengambilan target audience berdasarkan pada usia produktif dimana usia produktif merupakan usia-usia aktif, kritis dan selalu ingin tahu dan dapat menganalisis, memahami ajaran Islam sehingga dapat menerjemahkan maksud simbolik dari program acara yang disajikan.Pengerjaan tayangan Harmoni Islam melalui tahap pra produksi, produksi, dan pasca produksi, program Harmoni Islam tayang setiap hari pada bulan Ramadhan pada pukul 17.00 - 18.00 WIB, di Cakra Semarang TV, yang tergabung dalam Pelangi Ramdhan.Diharapkan masyarakat mendapatkan tayangan yang edukasi dan menambah informasi mengenai Islam

Spectroscopy of laser-produced plasmas: setting up of high-performance laser-induced breakdown spectroscopy system

It is a well-known fact that laser-induced breakdown spectroscopy (LIBS) has emerged as one of the best analytical techniques for multi-elemental compositional analysis of samples. We report assembling and optimization of LIBS set up using high resolution and broad-range echelle spectrograph coupled to an intensified charge coupled device (ICCD) to detect and quantify trace elements in environmental and clinical samples. Effects of variations of experimental parameters on spectroscopy signals of copper and brass are reported. Preliminary results of some plasma diagnostic calculations using recorded time-resolved optical emission signals are also reported for brass samples

Load-based generic polca: performance assessement using simulation

POLCA (i.e. Paired-cell Overlapping Loops of Cards with Authorization) is a card-based decision support system for production control, developed to support the adoption of Quick Response Manufacturing. Two variants of POLCA have been proposed in the literature to improve POLCA performance: Load Based POLCA and Generic POLCA. In this paper, we combine these two variants into a single production control system and analyse its performance for different backlog-sequencing rules. The results of a simulation study carried out for a make-to-order flow shop, support the strategy of combining these two POLCA variants and show that capacity-slack backlog sequencing based on corrected aggregate load have the potential for improving performance.info:eu-repo/semantics/publishedVersio

A review on a deep learning perspective in brain cancer classification

AWorld Health Organization (WHO) Feb 2018 report has recently shown that mortality rate due to brain or central nervous system (CNS) cancer is the highest in the Asian continent. It is of critical importance that cancer be detected earlier so that many of these lives can be saved. Cancer grading is an important aspect for targeted therapy. As cancer diagnosis is highly invasive, time consuming and expensive, there is an immediate requirement to develop a non-invasive, cost-effective and efficient tools for brain cancer characterization and grade estimation. Brain scans using magnetic resonance imaging (MRI), computed tomography (CT), as well as other imaging modalities, are fast and safer methods for tumor detection. In this paper, we tried to summarize the pathophysiology of brain cancer, imaging modalities of brain cancer and automatic computer assisted methods for brain cancer characterization in a machine and deep learning paradigm. Another objective of this paper is to find the current issues in existing engineering methods and also project a future paradigm. Further, we have highlighted the relationship between brain cancer and other brain disorders like stroke, Alzheimer’s, Parkinson’s, andWilson’s disease, leukoriaosis, and other neurological disorders in the context of machine learning and the deep learning paradigm

Measure-valued differentiation for stationary Markov chains

http://staff.feweb.vu.nl/bheidergot

Serological survey of catteries for cats infected with feline coronavirus

A serological survey on antibodies against feline coronavirus (FCo V) was conducted in four catteries in Klang Valley, Selangor, Malaysia. A total number of 24 cats of various breeds, ages and gender were randomly sampled from each cattery. The level of antibody titers were tested using a dot blot ELISA test kit ImmunofCombʳ, All cats showed a previous exposure to FeCo V. All the cats (100%) sampled from the catteries are infected with the virus. Approximately 42% and 58% of the sampled cats exhibited medium and high positive antibodies titers against FeCoY, respectively. This is the first study conducted in Malaysia to gauge the status of FeCo V antibody titer in cats

Role of Artificial Intelligence in Radiogenomics for Cancers in the Era of Precision Medicine

Radiogenomics, a combination of “Radiomics” and “Genomics,” using Artificial Intelligence (AI) has recently emerged as the state-of-the-art science in precision medicine, especially in oncology care. Radiogenomics syndicates large-scale quantifiable data extracted from radiological medical images enveloped with personalized genomic phenotypes. It fabricates a prediction model through various AI methods to stratify the risk of patients, monitor therapeutic approaches, and assess clinical outcomes. It has recently shown tremendous achievements in prognosis, treatment planning, survival prediction, heterogeneity analysis, reoccurrence, and progression-free survival for human cancer study. Although AI has shown immense performance in oncology care in various clinical aspects, it has several challenges and limitations. The proposed review provides an overview of radiogenomics with the viewpoints on the role of AI in terms of its promises for computa-tional as well as oncological aspects and offers achievements and opportunities in the era of precision medicine. The review also presents various recommendations to diminish these obstacles