In order to implement an integrated optical quantum circuit, designing waveguides based on the quantum box is of prime importance. To do this we have investigated optical waveguide both with and without optical pumping. The rate of absorption and emission using an array of AlGaAs/GaAs quantum box core/shell structure in the optical waveguide with various pumping intensities has computed. By con...

In order to implement an integrated optical quantum circuit, designing waveguides based on the quantum box is of prime importance. To do this we have investigated optical waveguide both with and without optical pumping. The rate of absorption and emission using an array of AlGaAs/GaAs quantum box core/shell structure in the optical waveguide with various pumping intensities has computed. By con...

The purpose of this research is predicting the stock prices using the Particle Swarm Optimization Algorithm and Box-Jenkins method. In this way, the information of 165 corporations is collected from 2001 to 2016. Then, this research considers price to earnings per share and earnings per share as main variables. The relevant regression equation was created using two variables of earnings per sha...

Embedding a System on a Programmable Chip with in the constraint of available resources brings out ingenuity of a SoPC designer. The paper covers an efficient Soft processor based USB communication device driver implementation on FPGA using a 10% foot print so as to set aside the rest 90% of the logic resources of the programmable chip for other compute and control intensive tasks. Using a Soft...

The Mining Software Repositories (MSR) field analyzes software repository data to uncover knowledge and assist development of ever growing, complex systems. However, existing approaches and platforms for MSR analysis face many challenges when performing large-scale MSR studies. Such approaches and platforms rarely scale easily out of the box. Instead, they often require custom scaling tricks an...

This paper presents a contextual model for software-intensive systems development to guide the adoption and adaptation of agile software development practices. This model was found especially useful when the project context departs significantly from the “agile sweet spot”, i.e., the ideal conditions in which agile software development practices originated from, and where they are most likely t...

Complex problems may require sophisticated, non-linear learning methods such as kernel machines or deep neural networks to achieve state of the art prediction accuracies. However, high prediction accuracies are not the only objective to consider when solving problems using machine learning. Instead, particular scientific applications require some explanation of the learned prediction function. ...

We seek to address the lack of labeled data (and high cost of annotation) for textual entailment in some domains. To that end, we first create (for experimental purposes) an entailment dataset for the clinical domain, and a highly competitive supervised entailment system, ENT, that is effective (out of the box) on two domains. We then explore self-training and active learning strategies to addr...

State-of-the-art solvers for mixed integer programming (MIP) problems are highly parameterized, and finding parameter settings that achieve high performance for specific types of MIP instances is challenging. We study the application of an automated algorithm configuration procedure to different MIP solvers, instance types and optimization objectives. We show that this fully-automated process y...