Using Verilog Hardware Description Language to teach Computer Architecture Courses

This paper investigates both the computation accuracy (based on the power balance error) and the cost in terms of the number of FDTD-grid cells due to the artifact rotation for a cellular handset close to the user’s head. Two study cases are simulated to assess the EM coupling of a cellular handset and a MRI-based human head model at 900 MHz; firstly, both handset and head CAD models are aligned to the FDTD-grid, secondly, handset close to a rotated head in compliance with IEEE-1528 standard. A FDTD-based platform, SEMCAD-X, is used; where conventional and interactive gridder approaches are implemented to achieve the simulations. The results show that owing to the artifact rotation, the computation error may increase up to 30%, whereas, the required number of grid cells may increase up to 25%

As software systems grow, their complexity augments dramatically. In consequence their understandability and evolvability are becoming a difficult task, therefore a way to describe the architecture of software systems is becoming a must. The architecture of a software system can be described using either an architecture description language (ADL) or an object-oriented modeling language. In this article, we show how we can build a hybrid model, based on the two approaches, to describe the architecture of software systems. This approach profits from the advantages of the two approaches, i.e. the explicit presentation of functional aspects in object-oriented modeling and the explicit separation of competition (components) from interactions (connectors) in architectural description.

Significant challenges has been introduced for IP networks with the advent of new emerging applications, such as VOIP and E-Commerce, that require delivering quality guarantees. However, IP networks were originally designed to support best effort delivery only. Two Quality of Service (QoS) standard models, IntServ, DiffServ have been standardized by the Internet Engineering Task Force (IETF). Although these methods guarantee delivery, they have drawbacks such as complexity, restrictions of predefined classes and higher end-to-end delay. In this paper, a new QoS mathematical model has been proposed. This model is based on the principles of Network Calculus in which an incoming traffic flow is regulated by an arrival curve that upper bounds its rate. Then, this traffic flow is lower bounded and delayed by a service latency time at each node on its way to the destination node. The worst case end-to-end delay is derived and illustrated by a numerical example. The proposed model has achieved acceptable end-to-end delay compared with the other models.

This paper presents a novel cellular handset design with a bottom-mounted short loaded-whip antenna. This new handset design is modeled and simulated using a finite difference time-domain (FDTD)-based platform SEMCAD. The proposed handset is based on a current commercially available bar-phone type with a curvature shape, keypad positioned above the screen, and top-mounted antenna. The specific absorption rates (SARs) are determined computationally in the specific anthropomorphic mannequin (SAM) and anatomically correct model of a human head when exposed to the EM-field radiation of the proposed cellular handset and the handset with top-mounted antenna. The two cellular handsets are simulated to operate at both GSM standards, 900 MHz as well as 1800 MHz, having different antenna dimensions and intput power of 0.6 W and 0.125 W, respectively. The proposed human hand holding the two handset models is a semirealistic hand model consists of three tissues: skin, muscle, and bone. The simulations are conducted with handset positions based on the IEEE standard 1528-2003. The results show that the proposed handset has a significant improvement of antenna efficiency when it is hand-held close to head, as compared with the handset of top-mounted antenna. Also, the results show that a significant reduction of the induced SAR in the human head-tissues can be achieved with the proposed handset

This paper is intended to investigate intensely the impact of multipossible hand-hold positions on the electromagnetic (EM) interaction of handset antennas and a human by using a finite-difference time-domain (FDTD) method. Candy-bar handsets with different external and internal antenna positions operating in the GSM900, GSM1800/DCS, and UMTS/IMT-2000 bands are hereby simulated with configuration of the most parts in order to achieve the commercially available handset model design. Homogeneous and heterogeneous phantoms both are used to simulate the human head, whereas, a semirealistic model with three different tissues is designed to simulate a human hand holding a set. Both of the antenna performance including the total isotropic sensitivity (TIS) and the specific absorption rate (SAR) in tissues are examined for the different suggested applicable cases, where various positions of antenna, handset and hand are considered in simulations. This simulation study determines that both of the antenna performance and the SAR in tissues significantly alter owing to the positioning of the handset against user’s head at different hand levels; where a maximum alteration is observed due to the exposure of handset with internal antenna, as compared with the handset having external antenna.

This paper presents a through investigation into the effect of the external antenna and printed circuit board (PCB) positions in cellular hand-sets on the coupling between the handset and human-head at GSM-900 frequency standard. The antenna performance and the specific absorption rate (SAR) induced in a human head were computed using a Finite Difference Time-Domain based platform (SEMCAD). A numerical correct model of a European female head was adopted and a semi-realistic hand model was designed during the simulation. The results showed that the optimum position for the antenna and PCB in hand-set close to head is the far right-corner for the right-hand users and the far left-corner for the left-hand users, where a minimum SAR in head is achieved.

This paper investigates the impact of the hand-hold positions on both antenna performance and the specific absorption rate (SAR) induced in the user’s head. A cellular handset with external antenna operating at GSM-900 frequency is modeled and simulated using a finite difference time-domain (FDTD)-based platform SEMCAD-X. A specific anthropomorphic mannequin (SAM) is adopted to simulate the user’s head, whereas a semirealistic CAD-model of three-tissues is designed to simulate the user’s hand. The results show that in case of the handset in hand close to head at different positions; the antenna total efficiency gets reduced to (14.5% - 5.9%) at cheek-position and to (27.5% to 11.8%) at tilt-position. The peak averaged SAR1g values in head close to handset without hand, are 4.67 W/Kg and 2.66 W/Kg at cheek and tilt-position, respectively. Due to the presence of hand, the SAR1g in head gets reduced to (3.67-3.31 W/Kg) at cheek-position and to (1.84-1.64 W/Kg) at tilt-position, depending on the hand-hold position.

This paper presents empirical methods for enhancing the accuracy of inductive learning systems. It

addresses the problems of: learning propositional production rules in multi-class classification tasks in

noisy domains, maintaining continuous learning when confronted with new situations after the learning

phase is completed, and classifying an object when no rule is satisfied for it.

It is shown that interleaving the learning and performance-evaluation processes, allows accurate

classifications to be made on real-world data sets. The paper presents the system ARIS which

implements this approach, and it is shown that the resulting classifications are often more accurate than

those made by the non-refined knowledge bases.

The core design decision that lies behind ARIS is that it employs an ordering of the rules according to

their weight. A rule’s weight is learned by using Bayes’ theorem to calculate weights for the rule’s

conditions and to combine them. This model focuses the analysis of the knowledge base and assists the

refinement process significantly.

The system is non-interactive, it relies on heuristics to focus the refinement on those experiments that

appear to be most consistent with the refinement data set. The design framework of ARIS consists of a

tabular model for expressing rule weights, and the relationship between refinement cases and the rules

satisfied for each case to focus the refinement process. The system has been used to refine knowledge

bases created by ARIS itself, as well as to refine knowledge bases created by the RIPPER and C4.5

systems [6,25] in ten selected domains. Two main advantages have been observed. First, the ability to

gradually improve the knowledge base as the refinement proceeds. Second, is the ability to learn strong

rules utilising condition’s weight using minimum covering algorithm. Thus, by taking account of this

information we improve the applicability and quality of refinement