Feras Al-Hawari

Partitioned Latency Insertion Method With a Generalized Stability Criteria

This paper presents a modular approach to the high-frequency simulation of large networks. By utilizing the latency insertion method (LIM) and by studying the stability criteria of partitions of different latencies in the circuit, a robust method is formulated that is able to perform transient simulations significantly faster than the conventional LIM method. The LIM method is also extended to handle dependent sources, and a general stability criterion for selecting the time step, independent of the topology of the circuit, is proposed. The new method is verified with existing commercial tools for circuit simulations, and the improvement in run time is also depicted.

Comparative Study of Convolution and Order Reduction Techniques for Blackbox Macromodeling Using Scattering Parameters

In this paper, a fast convolution method using scattering parameters is presented for the macromodeling of blackbox multiport networks. The method is compared to model-order reduction passive macromodeling techniques in terms of robustness and computational efficiency. When scattering parameters are used as the transfer functions, convolution calculations can be accelerated to achieve superior performance and the resulting procedure leads to a robust, accurate, and efficient macromodel generation scheme. This paper examines the formulation of the convolution method. Model-order reduction techniques are reviewed and benchmark comparisons are performed.

Partitioned latency insertion method (PLIM) with stability considerations

In this paper, we present a modular approach to the high frequency simulation of large networks by utilizing the latency insertion method (LIM) and considering the stability criteria of partitions of different latencies in the circuit. This results in a robust algorithm that is able to preserve the stability condition while improving the runtime of the overall transient simulation. An extension to the LIM to handle dependent sources is also presented, along with a generalized stability criteria for selecting a maximum stable time step.

Blackbox Macromodel with S-Parameters and Fast Convolution

In this paper, the scattering parameters of blackbox multi-port networks are pre-processed in the frequency domain to satisfy causality. Next, they are approximated to yield weighted delta functions in the time domain thus allowing the fast simulation. The resulting procedure leads to a robust, accurate and efficient macromodel generation scheme.

Application of the latency insertion method to circuits with blackbox macromodel representation

In this work the latency insertion method (LIM) is applied to the treatment of blackbox networks described by their frequency-domain scattering parameters. The method allows the simulation of passive macromodels in the LIM environment. This generalization allows LIM to simulate subnetworks with frequency-dependent parameters describing phenomena such as skin effect and substrate loss. The derivation of the algorithms is presented as well as simulation results to validate the method.

The software engineering of a three-tier web-based student information system MyGJU

This paper discusses how the software development team at the German Jordanian University (GJU) adopted the project management and software development processes in the ISO/IEC 29110 series to implement a complex Student Information System (SIS). Specifically, it identifies the key points to be taken into consideration in the analysis, design, implementation, testing, and deployment phases during the iterative and incremental SIS development process. The SIS is a distributed three‐tier web‐based application that enables registrars to perform various tasks such as system setup, admission, registration, grades processing, graduation, and reporting. It was launched in the first 2015/2016 semester and enabled administration to maintain a comfortable learning environment, assess instructor performance, enhance teaching practices, and improve course content. The results of the system measurements and user survey assert that the SIS is feature rich, easy to use, fast, reliable, stable, highly available, and scalable.

An Effective Classification Approach for Big Data Security Based on GMPLS/MPLS Networks

The need for effective approaches to handle big data that is characterized by its large volume, different types, and high velocity is vital and hence has recently attracted the attention of several research groups. This is especially the case when traditional data processing techniques and capabilities proved to be insufficient in that regard. Another aspect that is equally important while processing big data is its security, as emphasized in this paper. Accordingly, we propose to process big data in two different tiers. The first tier classifies the data based on its structure and on whether security is required or not. In contrast, the second tier analyzes and processes the data based on volume, variety, and velocity factors. Simulation results demonstrated that using classification feedback from a MPLS/GMPLS core network proved to be key in reducing the data evaluation and processing time.

Innovative methodology for elevating big data analysis and security

big amount of data and information transfer among, within, and through organizations all over the globe. This big data information may include sensitive, confidential and restricted data, like financial, legal or private information. Any loss, threat, or leakage of information may trigger high-security risk on such data. Securing big data during analysis phase is still a challenge, especially in cloud systems. This paper proposes a methodology to protect big data during analysis, by classifying data before any action such as moving, copying or processing can take place. Based on big data classification, the security procedures will be activated according to data level criticality.