Hybrid Coding Technique for Pulse Detection in an Optical Time Domain Reflectometer

The paper introduces a novel hybrid coding technique for improved pulse detection in an optical time domain reflectometer. The hybrid schemes combines Simplex codes with signal averaging to articulate a very sophisticated coding technique that considerably reduces the processing time to extract specified coding gains in comparison to the existing techniques. The paper quantifies the coding gain of the hybrid scheme mathematically and provide simulative results in direct agreement with the theoretical performance. Furthermore, the hybrid scheme has been tested on our self-developed OTDR

Task Runtime Prediction in Scientific Workflows Using an Online Incremental Learning Approach

Many algorithms in workflow scheduling and resource provisioning rely on the performance estimation of tasks to produce a scheduling plan. A profiler that is capable of modeling the execution of tasks and predicting their runtime accurately, therefore, becomes an essential part of any Workflow Management System (WMS). With the emergence of multi-tenant Workflow as a Service (WaaS) platforms that use clouds for deploying scientific workflows, task runtime prediction becomes more challenging because it requires the processing of a significant amount of data in a near real-time scenario while dealing with the performance variability of cloud resources. Hence, relying on methods such as profiling tasks' execution data using basic statistical description (e.g., mean, standard deviation) or batch offline regression techniques to estimate the runtime may not be suitable for such environments. In this paper, we propose an online incremental learning approach to predict the runtime of tasks in scientific workflows in clouds. To improve the performance of the predictions, we harness fine-grained resources monitoring data in the form of time-series records of CPU utilization, memory usage, and I/O activities that are reflecting the unique characteristics of a task's execution. We compare our solution to a state-of-the-art approach that exploits the resources monitoring data based on regression machine learning technique. From our experiments, the proposed strategy improves the performance, in terms of the error, up to 29.89%, compared to the state-of-the-art solutions.Comment: Accepted for presentation at main conference track of 11th IEEE/ACM International Conference on Utility and Cloud Computin

Drop size in a liquid pulsed sieve-plate extraction column

Peer reviewedPublisher PD

Effect of Air-Drying on Physical Properties of Shea Kernel

In order to design postharvest processing equipment for shea kernel, it is necessary to evaluate its physical and engineering properties. In this study, the physical properties of shea kernel were investigated at five moisture levels for two size categories of large size kernel (LSK) and small size kernel (SSK) as the kernels were air-dried from an initial high moisture content. As the SSK dry from moisture content of 73.38 to 6.58% (db), major, intermediate and minor diameters decreased from 30.80 to 23.32mm, 21.63 to 15.76 mm and 19.42 to 13.36 mm, respectively. The geometric mean diameter also decreased from 19.96 to 19.54 mm while sphericity and surface area also decreased from 0.76 to 0.73 and 17.31 to 9.08cm2 , respectively. The mass and volume as well decreased from 6.82 to 3.14 g, 6.8 to 2.59 cm3 while kernel density increased from 1.04 to 1.26 g/cm2 as the moisture content decreased. The static coefficient of friction on galvanized iron, wood and steel decreased from 0.68 to 0.39, 0.76 to 0.45 and 0.57 to 0.42 respectively. The angle of repose however increased from 23.4 to 30.5 degrees. Corresponding values were also observed for LSK categories. Regression equations were utilized to model the relationship between moisture content and the physical attributes for the shea kernel

Coupled-channels analyses for large-angle quasi-elastic scattering in massive systems

We discuss in detail the coupled-channels approach for the large-angle quasi-elastic scattering in massive systems, where many degrees of freedom may be involved in the reaction. We especially investigate the effects of single, double and triple phonon excitations on the quasi-elastic scattering for $^{48}$Ti,$^{54}$Cr,$^{56}$Fe,$^{64}$Ni and $^{70}$Zn$+^{208}$Pb systems, for which the experimental cross sections have been measured recently. We show that the present coupled-channels calculations well account for the overall width of the experimental barrier distribution for these systems. In particular, it is shown that the calculations taking into account single quadrupole phonon excitations in $^{48}$Ti and triple octupole phonon excitations in $^{208}$Pb reasonably well reproduce the experimental quasi-elastic cross section and barrier distribution for the $^{48}$Ti$+^{208}$Pb reaction. On the other hand, $^{54}$Cr,$^{56}$Fe,$^{64}$Ni and $^{70}$Zn$+^{208}$Pb systems seem to require the double quadrupole phonon excitations in the projectiles in order to reproduce the experimental data.Comment: 11 pages, 6 figure

A Tablet Screen Cast Receiver for Classroom with Low End Android Devices

Salah satu aktivitas menggunakan tablet adalah presentasi. Saat ini, kebanyakan aktivitas presentasi dilakukan menggunakan adapter VGA untuk bisa tersambung dengan LCD Proyektor. Konfigurasi ini memungkin presentasi berbasis kabel. Dan ini adalah hal yang menyulitkan penggunaannya untuk perangkat tablet yang memiliki sifat mobilitas tinggi. Beruntung, sudah ada banyak vendor yang menyediakan sistem presentasi yang bersahabat dengan membuatnya menjadi nirkabel. Tapi sistem tersebut hanya mendukung perangkat tablet high end. Pada makalah ini, kami mengajukan sebuah penerima tablet screen cast untuk perangkat tablet android low end. Yang memiliki potensi untuk diimplementasikan di kelas. Dari eksperimen, kami memperoleh hasil 9 FPS dengan delay sebesar 2 detik