An efficient genetic algorithm for large-scale transmit power control of dense and robust wireless networks in harsh industrial environments

The industrial wireless local area network (IWLAN) is increasingly dense, due to not only the penetration of wireless applications to shop floors and warehouses, but also the rising need of redundancy for robust wireless coverage. Instead of simply powering on all access points (APs), there is an unavoidable need to dynamically control the transmit power of APs on a large scale, in order to minimize interference and adapt the coverage to the latest shadowing effects of dominant obstacles in an industrial indoor environment. To fulfill this need, this paper formulates a transmit power control (TPC) model that enables both powering on/off APs and transmit power calibration of each AP that is powered on. This TPC model uses an empirical one-slope path loss model considering three-dimensional obstacle shadowing effects, to enable accurate yet simple coverage prediction. An efficient genetic algorithm (GA), named GATPC, is designed to solve this TPC model even on a large scale. To this end, it leverages repair mechanism-based population initialization, crossover and mutation, parallelism as well as dedicated speedup measures. The GATPC was experimentally validated in a small-scale IWLAN that is deployed a real industrial indoor environment. It was further numerically demonstrated and benchmarked on both small- and large-scales, regarding the effectiveness and the scalability of TPC. Moreover, sensitivity analysis was performed to reveal the produced interference and the qualification rate of GATPC in function of varying target coverage percentage as well as number and placement direction of dominant obstacles. (C) 2018 Elsevier B.V. All rights reserved

Perimeter coverage scheduling in wireless sensor networks using sensors with a single continuous cover range

In target monitoring problem, it is generally assumed that the whole target object can be monitored by a single sensor if the target falls within its sensing range. Unfortunately, this assumption becomes invalid when the target object is very large that a sensor can only monitor part of it. In this paper, we study the perimeter coverage problem where the perimeter of a big object needs to be monitored, but each sensor can only cover a single continuous portion of the perimeter. We describe how to schedule the sensors so as to maximize the network lifetime in this problem. We formally prove that the perimeter coverage scheduling problem is NP-hard in general. However, polynomial time solution exists in some special cases. We further identify the sufficient conditions for a scheduling algorithm to be a 2-approximation solution to the general problem, and propose a simple distributed 2-approximation solution with a small message overhead. Copyright © 2010 K.-S. Hung and K.-S. Lui.published_or_final_versio

Engine performance characteristics and evaluation of variation in the length of intake plenum

In the engine with multipoint fuel injection system using electronically controlled fuel injectors has an intake manifold in which only the air flows and, the fuel is injected into the intake valve. Since the intake manifolds transport mainly air, the supercharging effects of the variable length intake plenum will be different from carbureted engine. Engine tests have been carried out with the aim of constituting a base study to design a new variable length intake manifold plenum. The objective in this research is to study the engine performance characteristics and to evaluate the effects of the variation in the length of intake plenum. The engine test bed used for experimental work consists of a control panel, a hydraulic dynamometer and measurement instruments to measure the parameters of engine performance characteristics. The control panel is being used to perform administrative and management operating system. Besides that, the hydraulic dynamometer was used to measure the power of an engine by using a cell filled with liquid to increase its load. Thus, measurement instrument is provided in this test to measure the as brake torque, brake power, thermal efficiency and specific fuel consumption. The results showed that the variation in the plenum length causes an improvement on the engine performance characteristics especially on the fuel consumption at high load and low engine speeds which are put forward the system using for urban roads. From this experiment, it will show the behavior of engine performance

Methodological Issues in Multistage Genome-Wide Association Studies

Because of the high cost of commercial genotyping chip technologies, many investigations have used a two-stage design for genome-wide association studies, using part of the sample for an initial discovery of ``promising'' SNPs at a less stringent significance level and the remainder in a joint analysis of just these SNPs using custom genotyping. Typical cost savings of about 50% are possible with this design to obtain comparable levels of overall type I error and power by using about half the sample for stage I and carrying about 0.1% of SNPs forward to the second stage, the optimal design depending primarily upon the ratio of costs per genotype for stages I and II. However, with the rapidly declining costs of the commercial panels, the generally low observed ORs of current studies, and many studies aiming to test multiple hypotheses and multiple endpoints, many investigators are abandoning the two-stage design in favor of simply genotyping all available subjects using a standard high-density panel. Concern is sometimes raised about the absence of a ``replication'' panel in this approach, as required by some high-profile journals, but it must be appreciated that the two-stage design is not a discovery/replication design but simply a more efficient design for discovery using a joint analysis of the data from both stages. Once a subset of highly-significant associations has been discovered, a truly independent ``exact replication'' study is needed in a similar population of the same promising SNPs using similar methods.Comment: Published in at http://dx.doi.org/10.1214/09-STS288 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Information and Communications Technology in Chronic Disease Care: Why is Adoption So Slow and Is Slower Better?

Unlike the widespread adoption of information and communications technology (ICT) in much of the economy, adoption of ICT in clinical care is limited. We examine how a number of not previously emphasized features of the health care and ICT markets interact and exacerbate each other to create barriers for adoption. We also examine how standards can address these barriers and the key issues to consider before investing in ICT. We conclude that the ICT market exhibits a number of unique features that may delay or completely prevent adoption, including low product differentiation, high switching costs, and lack of technical compatibility. These barriers are compounded by the many interlinked markets in health care, which substantially blunt the use of market forces to influence adoption. Patient heterogeneity also exacerbates the barriers by wide variation in needs and ability for using ICT, by high demands for interoperability, and by higher replacement costs. Technical standards are critical for ensuring optimal use of the technology. Careful consideration of the socially optimal time to invest is needed. The value of waiting in health care is likely to be so much greater than in other sectors because the costs of adopting the wrong type of ICT are so much higher.