Integrating customer's preferences in the QFD planning process using a combined benchmarking and imprecise goal programming model

Quality function deployment (QFD) is a customer-oriented design tool for developing new or improved products to achieve higher customer satisfaction by integrating various functions of an organization. The engineering characteristics (ECs) affecting the product performances are designed to match the customer attributes (CAs). However, from the viewpoint of the QFD team, product design processes are performed in imprecise environments, and more than one factor must be taken into account in determining the target levels of ECs, especially the limited resources and increased market competition. This paper presents an imprecise goal programming (GP) approach to determine the optimum target levels of ECs in QFD for maximizing customer satisfaction under resource limitation and considerations of market competition. Based on benchmarking data of CAs, the concept of satisfaction functions is utilized to formulate explicitly the customer's preferences and to integrate the competitive analysis of target market into the modelling and solution process. In addition, the relationships linking CAs and ECs and the ECs to each other are integrated by functional relationships. The proposed approach will be illustrated through a car door design example.     

iOS application for quadrotor remote control

With the progress of electronics technology, the development of civilian UAV (unmanned aerial vehicle) applications becomes possible. In addition, smartphones have rapidly gained popularity and become very important due to the simple operability and mobility. Hence, there is a need to have an easy and flexible way to control a UAV using such technology. In this study, a remote controller using an iOS device is developed for a quadrotor to enable remote control with easy operations. Four basic programs for obtaining compass information, controlling a gimbal, autopilot function for return, and video preview function are developed and implemented for an iOS device. The basic functionalities of the programs are evaluated and confirmed through experiments using a quadrotor and an iOS device.     

Functional segmentation of dynamic nuclear images by cross-psi B-energy operator

We describe a new segmentation method of dynamic nuclear medicine images based on the cross-Psi(B)-energy operator. Psi(B) is a nonlinear measure which quantifies the interaction between two time-signals including their first and second derivatives. Similarity measure, noted SimilB, between the time activity curve (TAC) of each pixel and the mean value of the TACs of a reference region of the scintigraphic image series is calculated. The resulting SimilB map is a functional image representing regions with different temporal dynamics. Some new properties of Psi(B) are presented. Particularly, we show that Psi(B) as a similarity measure is robust to both scale and time shift. The proposed method is applied to nuclear cardiac sequences for visualization and analysis of the ventricular emptying pattern, which may be useful in studying motion or conduction abnormalities. Results of a normal subject and four patients with abnormal ventricular contraction patterns are presented to highlight the suitability of this operator for studying non-stationary TAC series.     

An optimal energy‐efficient clustering method in wireless sensor networks using multi‐objective genetic algorithm

In this study, an optimal method of clustering homogeneous wireless sensor networks using a multi‐objective two‐nested genetic algorithm is presented. The top level algorithm is a multi‐objective genetic algorithm (GA) whose goal is to obtain clustering schemes in which the network lifetime is optimized for different delay values. The low level GA is used in each cluster in order to get the most efficient topology for data transmission from sensor nodes to the cluster head. The presented clustering method is not restrictive, whereas existing intelligent clustering methods impose certain conditions such as performing two‐tiered clustering. A random deployed model is used to demonstrate the efficiency of the proposed algorithm. In addition, a comparison is made between the presented algorithm other GA‐based clustering methods and the Low Energy Adaptive Clustering Hierarchy protocol. The results obtained indicate that using the proposed method, the network's lifetime would be extended much more than it would be when using the other methods. Copyright © 2011 John Wiley & Sons, Ltd.     

Disaster-survivable cloud-network mapping

Cloud-computing services are provided to consumers through a network of servers and network equipment. Cloud-network (CN) providers virtualize resources [e.g., virtual machine (VM) and virtual network (VN)] for efficient and secure resource allocation. Disasters are one of the worst threats for CNs as they can cause massive disruptions and CN disconnection. A disaster may also induce post-disaster correlated, cascading failures which can disconnect more CNs. Survivable virtual-network embedding (SVNE) approaches have been studied to protect VNs against single physical-link/-node and dual physical-link failures in communication infrastructure, but massive disruptions due to a disaster and their consequences can make SVNE approaches insufficient to guarantee cloud-computing survivability. In this work, we study the problem of survivable CN mapping from disaster. We consider risk assessment, VM backup location, and post-disaster survivability to reduce the risk of failure and probability of CN disconnection and the penalty paid by operators due to loss of capacity. We formulate the proposed approach as an integer linear program and study two scenarios: a natural disaster, e.g., earthquake and a human-made disaster, e.g., weapons-of-mass-destruction attack. Our illustrative examples show that our approach reduces the risk of CN disconnection and penalty up to 90 % compared with a baseline CN mapping approach and increases the CN survivability up to 100 % in both scenarios.     

Effect of Fe-doping on the structural and optical properties of ZnO thin films prepared by spray pyrolysis

Fe-doped ZnO thin films have been prepared by spray pyrolysis on glass substrates and the influence of Fe-doping concentration on the structural and optical properties of the films has been studied.The X-ray diffraction (XRD) analysis shows that Fe doping has a significant effect on crystalline quality,grain size and strain in the thin films.The best crystalline structure is obtained for 3 at%Fe doping as observed from scanning electron microscopy (SEM) and XRD.However,lower or higher Fe-doping degrades the crystalline quality in turn.Moreover,UV spectroscopy demonstrates the influence of Fe-incorporation on visible range transmittance of ZnO where the best transmittance is obtained for 3 at%doping.The results have been illustrated simultaneously focusing previous results obtained from literature.     

Disaster-aware service provisioning with manycasting in cloud networks

Cloud services delivered by high-capacity optical datacenter networks are subject to disasters which may cause large-area failures, leading to huge data loss. Survivable service provisioning is crucial to minimize the effects of network/datacenter failures and maintain critical services in case of a disaster. We propose a novel disaster-aware service-provisioning scheme that multiplexes service over multiple paths destined to multiple servers/datacenters with manycasting. Our scheme maintains some bandwidth (i.e., degraded service) after a disaster failure vs. no service at all. We formulate this problem into a mathematical model which turns out to be an Integer Linear Program (ILP), and we provide heuristic optimization approaches as ILP is intractable for large problem instances. Numerical examples show that exploiting manycasting by intelligently selecting destinations in a risk-aware manner for service provisioning offers high level of survivability against link and node failures that may be caused by disasters and post-disaster failures at no extra cost compared to the other survivable schemes.     

Connection Management Protocols for Dynamic Lightpath Provisioning in Future WDM Networks

This paper investigates and compares the performance of two GMPLS-based distributed control and management protocols for dynamic lightpath provisioning in future IP networks. The first protocol is a global information-based link state approach that consists of both an integrated RWA algorithm and a signaling algorithm. Two triggering mechanisms for the LSAs update procedures are considered; one is periodic-based and the other is threshold-based. The second protocol is a local-information based fixed alternate link routing approach where the signaling protocol is closely integrated with the RWA protocols.     

Ant-based routing and QoS-effective data collection for mobile wireless sensor network

Mobility management in mobile wireless sensor networks (MWSNs) is a complex problem that must be taken into account. In MWSN, nodes move in and out of the network randomly. Hence, a path formed between two distant nodes is highly susceptible to changes due to unpredictable node movement. Also, due to the limited resources in WSN, the paths used for data transmission must be tested for the link quality and time consumed for data forwarding. In order to solve these issues, in this paper, an ant-based routing protocol with QoS-effective data collection mechanism is proposed. In this protocol, the link quality and link delay are estimated for each pair of nodes. Link quality is estimated in terms of packet reception rate, received signal strength indicator, and link quality index. A reliable path is chosen from the source to the destination based on the paths traversed by forward ants and backward ants. Then, if the link is found to be defective during data transmission, a link reinforcement technique is used to deliver the data packet at the destination successfully. The mobile robots collect the information with high data utility. In addition, each mobile robot is equipped with multiple antennas, and space division multiple access technique is then applied for effective data collection from multiple mobile robots. Simulation results show that the proposed routing protocol provides reliability by reducing the packet drop and end-to-end delay when compared to the existing protocols.