Frequency Insertion Strategy for Channel Assignment Problem

This paper presents a new heuristic method for quickly finding a good feasible solution to the channel assignment problem (CAP). Like many other greedy-type heuristics for CAP, the proposed method also assigns a frequency to a call, one at a time. Hence, the method requires computational time that increases only linear to the number of calls. However, what distinguishes the method from others is that it starts with a narrow enough frequency band so as to provoke violations of constraints that we need to comply with in order to avoid radio interference. Each violation is then resolved by inserting frequencies at the most appropriate positions so that the band of frequencies expands minimally. An extensive computational experiment using a set of randomly generated problems as well as the Philadelphia benchmark instances shows that the proposed method perform statistically better than existing methods of its kind and even yields optimum solutions to most of Philadelphia benchmark instances among which two cases are reported for the first time ever, in this paper. Won-Young Shin was born in Busan, Korea in 1978. He received B.S. in industrial engineering from Pohang University of Science and Technology (POSTECH) in 2001 and M.S in operation research and applied statistics from POSTECH in 2003. Since 2003 he has been a researcher of Agency for Defense Development (ADD) in Korea. He is interested in optimization of communication system and applied statistics. Soo Y. Chang is an associate professor in the Department of Industrial Engineering at Pohang University of Science and Technology (POSTECH), Pohang, Korea. He teaches linear programming, discrete optimization, network flows and operations research courses. His research interests include mathematical programming and scheduling. He has published in several journals including Discrete Applied Mathematics, Computers and Mathematics with Application, IIE Transactions, International Journal of Production Research, and so on. He is a member of Korean IIE, and ORMSS. Jaewook Lee is an assistant professor in the Department of Industrial Engineering at Pohang University of Science and Technology (POSTECH), Pohang, Korea. He received the B.S. degree in mathematics with honors from Seoul National University, and the Ph.D. degree from Cornell University in applied mathematics in 1993 and 1999, respectively. He is currently an assistant professor in the department of industrial engineering at the Pohang University of Science and Technology (POSTECH). His research interests include nonlinear systems, neural networks, nonlinear optimization, and their applications to data mining and financial engineering. Chi-Hyuck Jun was born in Seoul, Korea in 1954. He received B.S. in mineral and petroleum engineering from Seoul National University in 1977, M.S. in industrial engineering from Korea Advanced Institute of Science and Technology in 1979 and Ph.D. in operations research from University of California, Berkeley, in 1986. Since 1987 he has been with the department of industrial engineering, Pohang University of Science and Technology (POSTECH) and he is now a professor and the department head. He is interested in performance analysis of communication and production systems. He has published in several journals including IIE Transactions, IEEE Transactions, Queueing Systems and Chemometrics and Intelligent Laboratory Systems. He is a member of IEEE, INFORMS and ASQ.     

Assessing stem cell research productivity

Honour Index (HoI), a method to evaluate research performance within different research fields, was derived from the impact factor (IF). It can be used to rate and compare different categories of journals. HoI was used in this study to determine the scientific productivity of stem cell research in the Asian Four Dragons (Hong Kong, Singapore, South Korea and Taiwan) from 1981 to 2001. The methodology applied in this study represents a synthesis of universal indicator studies and bibliometric analyses of subfields at the micro-level. We discuss several comparisons, and conclude the developmental trend in stem cell research for two decades. This revised version was published online in August 2006 with corrections to the Cover Date.     

Mining predecessor–successor rules from DAG data

Data mining extracts implicit, previously unknown, and potentially useful information from databases. Many approaches have been proposed to extract information, and one of the most important ones is finding association rules. Although a large amount of research has been devoted to this subject, none of it finds association rules from directed acyclic graph (DAG) data. Without such a mining method, the hidden knowledge, if any, cannot be discovered from the databases storing DAG data such as family genealogy profiles, product structures, XML documents, task precedence relations, and course structures. In this article, we define a new kind of association rule in DAG databases called the predecessor–successor rule, where a node x is a predecessor of another node y if we can find a path in DAG where x appears before y. The predecessor–successor rules enable us to observe how the characteristics of the predecessors influence the successors. An approach containing four stages is proposed to discover the predecessor–successor rules. © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 621–637, 2006.     

Intelligent process analytics for CRM

Many organisations use decision models in their processes such as tables or trees to provide decision support to their operational divisions. For example, in fault management, customer contact centre operators usually use a decision model in the form of prescribed interviews. Based on the answers given by customers, the operator navigates through the decision model to reach an assessment of the problem. In order to achieve customer satisfaction and operational excellence, it is very important to constantly monitor the performance of a decision model not only on an overall level, but also on the level of individual decisions. In this paper we present a configurable business process analytics tool, known as the intelligent Universal Service Management System, that constantly monitors decision data and is capable of optimising the decisions based on high-level business objectives. We explain the various features of the software and show how it can be used to optimise decision processes. We also show how we can easily provide a customised version to monitor the performance of provision processes.     

Low-temperature poly-SiGe alloy growth of high gain/speed pin infrared photosensor with gold-induced lateral crystallization (Au-ILC)

The hydrogenated poly-silicon germanium (poly-SiGe:H) epitaxial film has been investigated using gold-induced lateral crystallization (Au-ILC) technology on a-SiGe:H layers at 10-h 350/spl deg/C annealing temperature and 60-sccm hydrogen (H/sub 2/) content. Using this optimal condition, the growth rate of the induced Au was as large as 15.9 /spl mu/m/h. With a low annealing temperature (/spl les/400/spl deg/C) and large growth rate, this novel technology will be noticeably useful for poly-SiGe:H pin IR-sensing fabrication on a conventional precoated indium tin oxide (ITO)-glass substrate. Under a 1-/spl mu/W IR-LED incident light (with peak wave length at 710 nm) and at a 5-V biased voltage, the poly-SiGe:H pin IR sensor developed by the Au-ILC technology, i.e., an Al (anode)/n poly-SiGe:H/i poly-SiGe:H/p poly-SiGe:H/ITO (cathode)/glass-substrate structure allowed for maximum optical gain and response speed. The optical gains and the response speeds were almost 600 and 130%, respectively, better than that of a traditional pin type. Meanwhile, the FWHM of a poly-SiGe:H pin sensor with Au-ILC technology was reduced from 280 to 150 nm. This reveals excellent IR-sensing selectivity. These IR-sensing trials demonstrated again that the proposed Au-ILC technology has very useful application in the field of low cost integrated circuits on optoelectronic applications.     

Solutions to a combined problem of excessive hydrogen sulfide in biogas and struvite scaling.

The Woodman Point Wastewater Treatment Plant (WWTP) in Western Australia has experienced two separate problems causing avoidable maintenance costs: the build-up of massive struvite (MgNH4PO4. 6H2O) scaling downstream of the anaerobic digester and the formation of hydrogen sulfide (H2S) levels in the digester gas to levels that compromised gas engine operation and caused high operating costs on the gas scrubber. As both problems hang together with a chemical imbalance in the anaerobic digester, we decided to investigate whether both problems could be (feasibly and economically) addressed by a common solution (such as dosing of iron solutions to precipitate both sulfide and phosphate), or by using separate approaches. Laboratory results showed that, the hydrogen sulfide emission in digesters could be effectively and economically controlled by the addition of iron dosing. Slightly higher than the theoretical value of 1.5 mol of FeCl3 was required to precipitate 1 mol of dissolved sulfide inside the digester. Due to the high concentration of PO4(3-) in the digested sludge liquor, significantly higher iron is required for struvite precipitation. Iron dosing did not appear an economic solution for struvite control via iron phosphate formation. By taking advantage of the natural tendency of struvite formation in the digester liquid, it is possible to reduce the risk of struvite precipitation in and around the sludge-dewatering centrifuge by increasing the pH to precipitate struvite out before passing through the centrifuge. However, as the Mg2+/PO4(3-) molar ratio in digested sludge was low, by increasing the pH alone (using NaOH) the precipitation of PO4(3-) was limited by the amount of cations (Ca2+ and Mg2+) available in the sludge. Although this would reduce struvite precipitation in the centrifuge, it could not significantly reduce PO4(3-) recycling back to the plant. For long-term operation, maximum PO4(3-) reduction should be the ultimate aim to minimise PO4(3-) accumulation in the plant. Magnesium hydroxide liquid (MHL) was found to be the most cost-effective chemical to achieve this goal. It enhanced struvite precipitation from both, digested sludge and centrate to the point where more than 95% PO4(3-) reduction in the digested sludge was achieved.