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Clients today want more for less and the IBM test mantra of Test Less Test Right helps address this ask by placing Combinatorial Test Design (CTD) at the heart of the solution. This document presents two case studies of CTD implementation in client engagements and focuses on the approach, process and challenges addressed to scale up the implementation and make CTD a mainstream activity. The IBM Focus...
In this paper, we present an optimization of IPOG's vertical growth phase in the presence of constraints. The vertical growth problem is modeled as a classical NP-hard graph problem called "Minimum Vertex Coloring". In the graph model, vertices are either missing tuples that are waiting to be colored or existing tests that are already colored in different colors at the initial state, edges/hyperedges...
Fingerprinting has become the most popular approach for infrastructure-free indoor positioning systems. But fingerprinting relies on frequent and exhaustive building surveys to build and maintain a radio map of the indoor environment. A concept being developed recently is the crowdsourced indoor positioning system, where users of an indoor area will collectively contribute sensor data collected by...
Online Social Networks (OSNs) are the core of most communications nowadays, leading to possibly sensitive information exchange. Privacy is an important building block of free societies, and thus, for OSNs. OSNs function as group communication systems and can be build in centralised and distributed styles. Privacy can be achieved in distributed systems as all participants contribute to privacy. Peer-to-peer-based...
This paper proposes a novel power optimization technique in which DRX cycle is activated based on the scheduling decision. DRX MAC Control Element (CE) command is issued to the UEs for which scheduling is not possible in DRX ON duration time. Simulation results show that, significant gain can be achieved in power saving using the proposed method under specific scheduler design parameter conditions...
Sensor network virtualization enables the possibility of sharing common physical resources to multiple stakeholder applications. This paper focuses on addressing the dynamic adaptation of already assigned virtual sensor network resources to respond to time varying application demands. We propose an optimization framework that dynamically allocate applications into sensor nodes while accounting for...
We present an arbitrary-shaped patch antenna design procedure. The design technique is based on a variant of Biogeography Based Optimization (BBO) algorithm. In this paper, we apply Opposition-Based Learning (OBL) concepts for antenna design. More specifically, we use a new Modified Biogeography Based Optimization (BBO) algorithm enhanced with OBL techniques. The preliminary results of the proposed...
In this paper, we study exact multi-level logic benchmarks. We refer to an exact logic benchmark, or exact benchmark in short, as the optimal implementation of a given Boolean function, in terms of minimum number of logic levels and/or nodes. Exact benchmarks are of paramount importance to design automation because they allow engineers to test the efficiency of heuristic techniques used in practice...
Robust semidefinite programs are NP-hard in general. In contrast, robust linear programs admit equivalent reformulations as finite-dimensional convex programs provided that the problem data are parameterized affinely in the uncertain parameters; and that the underlying uncertainty set is described by an affine slice of a proper cone. In this paper, we propose a hierarchy of inner and outer polyhedral...
Spider Monkey Optimization is a well known meta-heuristic in the arena of nature inspired algorithms. It is basically known for its stagnation removal power in its original design. To balance the meta-heuristics mechanisms while preserving premature convergence, a new variant is developed which is named as Modified spider monkey optimization. In this paper, metropolis principle is used from simulated...
Gravitational search algorithm is a nature inspired optimization algorithm, inspired by newton's law of gravity and law of motion. In this paper, a new variant of Gravitational search algorithm is presented. The exploration and exploitation capability of GSA is balanced by splitting the whole swarm into two groups. The search process is modified so that one group better exploits and one group becomes...
These days, handling complicated tasks has become an undeniable usage of real-time embedded systems. Also How to allocate resource effectively becomes an important issue. Utilizing real time device can be really useful in order to execute complex jobs those are needed to be scheduled. However, the authors tried to tackle overload situation in real-time systems by using HPIO (Hybrid PSO and IWO). The...
The purpose of this article is to explain how a fuzzy linear programming model can be transformed into a fuzzy multi-objective linear programming model and then solved. An algorithm is developed to present our approach and fuzzy optimal solution is obtained. To demonstrate the efficiency and feasibility of the proposed approach, one numerical example has been solved.
This paper presents an assessment of different computational intelligences, i.e evolutionary algorithm (EP), firefly algorithm (FA) and cuckoo search algorithm (CSA) for solving single-objective optimization problem. Recently, these algorithms have been widely used and applied to solve different types of optimization problems. However, the performance of these optimization algorithms have not been...
In optimizing PID controller's parameters using any optimization algorithm, fitness function is one of the important area to be explored. Among frequently used fitness function is a weighted transient response index (WTRI) where the weight is given to each of the transient response component including rise time, settling time, overshoot and steady state error based on their priority set in specification...
The implementation of PSO algorithm in optimizing PID controller's parameters has been in active research area recently. One of the popular plant to be controlled using this control strategy is a DC motor and various types of DC motors with variations in parameters value have been used in this research area. Moment of inertia is one of the important parameters of a DC motor which can affect the output...
Graph algorithms with large, sparse inputs oftentimes perform poorly on cache-based platforms. For parallel spanning forest and minimum spanning forest computations, we propose three locality optimizations, Update, Stages, and PSM, that improve the cache performance. Update exploits the "graft-and-shortcut" pattern of the base algorithms. PSM transforms irregular accesses into regular ones...
The growing complexity and diversity of vehicle systems makes it increasingly hard to identify and resolve the root cause of an unplanned maintenance session at hand in a dealer workshop. This especially holds for workshop staff with limited qualifications and experience. By today, the workshop staff is supported by expert-based systems, where knowledge was manually generated, i. e., by formalizing...
A number of important applied problems in engineering, finance and medicine can be formulated as a problem of anomaly detection. A classical approach to the problem is to describe a normal state using a one-class support vector machine. Then to detect anomalies we quantify a distance from a new observation to the constructed description of the normal class. In this paper we present a new approach...
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