A new fuzzy decision-making procedure applied to emergency electric power distribution scheduling

In this paper a new fuzzy decision-making procedure is developed. Two levels of weightings, called upper and lower weights, are proposed to calculate the fuzzy weightings of different criteria. The preference table is introduced to calculate the upper and lower weights. Also a new method is developed to determine the expected preference values of different alternatives. These values are used for generating the priority list of alternatives. The procedure is applied for providing an emergency electric power distribution, scheduling time table. The IEEE 14-bus standard system and a 14-bus system with four power plants are considered as case studies. Using fuzzy decision-making procedure, the regions with more priorities are more connected to the distribution net, while the maximum consumption criterion is also reasonably respected.     

Constructing malware normalizers using term rewriting

A malware mutation engine is able to transform a malicious program to create a different version of the program. Such mutation engines are used at distribution sites or in self-propagating malware in order to create variation in the distributed programs. Program normalization is a way to remove variety introduced by mutation engines, and can thus simplify the problem of detecting variant strains. This paper introduces the “normalizer construction problem” (NCP), and formalizes a restricted form of the problem called “NCP=”, which assumes a model of the engine is already known in the form of a term rewriting system. It is shown that even this restricted version of the problem is undecidable. A procedure is provided that can, in certain cases, automatically solve NCP= from the model of the engine. This procedure is analyzed in conjunction with term rewriting theory to create a list of distinct classes of normalizer construction problems. These classes yield a list of possible attack vectors. Three strategies are defined for approximate solutions of NCP=, and an analysis is provided of the risks they entail. A case study using the virus suggests the approximations may be effective in practice for countering mutated malware. R. Mathur is presently at McAfee AVERT Labs.     

Influence of dietary iron deficiency on acute metal intoxication

The frequent difficulties encountered in the diagnosis of pediatric sarcomas, caused by the lack of observable differentiation at the light microscopic level, has led to the routine use of immunohistochemistry in pediatric surgical pathology. To a large degree the advent of this staining technique has led to the correct assessment of many perplexing lesions that previously would have been given inconclusive diagnoses. However, with increased usage and testing, it has become apparent that there are few, if any, "magic bullets" in immunohistochemistry for pediatric pathologists. Thus, it behooves diagnosticians to be careful in the usage of this technique, to be aware of possible discrepancies in its results, and to remember the ancillary nature of its application. The following article will review selected markers commonly used in pediatric surgical pathology, from both previous reports and the author's perspective, and will briefly consider several new phenotypic markers which have potential utility with childhood sarcomas.     

Massively Parallel Computation Using Graphics Processors with Application to Optimal Experimentation in Dynamic Control

The rapid growth in the performance of graphics hardware, coupled with recent improvements in its programmability has lead to its adoption in many non-graphics applications, including a wide variety of scientific computing fields. At the same time, a number of important dynamic optimal policy problems in economics are athirst of computing power to help overcome dual curses of complexity and dimensionality. We investigate if computational economics may benefit from new tools on a case study of imperfect information dynamic programming problem with learning and experimentation trade-off, that is, a choice between controlling the policy target and learning system parameters. Specifically, we use a model of active learning and control of a linear autoregression with the unknown slope that appeared in a variety of macroeconomic policy and other contexts. The endogeneity of posterior beliefs makes the problem difficult in that the value function need not be convex and the policy function need not be continuous. This complication makes the problem a suitable target for massively-parallel computation using graphics processors (GPUs). Our findings are cautiously optimistic in that the new tools let us easily achieve a factor of 15 performance gain relative to an implementation targeting single-core processors. Further gains up to a factor of 26 are also achievable but lie behind a learning and experimentation barrier of their own. Drawing upon experience with CUDA programming architecture and GPUs provides general lessons on how to best exploit future trends in parallel computation in economics.     

Java-MaC: A Run-Time Assurance Approach for Java Programs

We describe Java-MaC, a prototype implementation of the Monitoring and Checking (MaC) architecture for Java programs. The MaC architecture provides assurance that the target program is running correctly with respect to a formal requirements specification by monitoring and checking the execution of the target program at run-time. MaC bridges the gap between formal verification, which ensures the correctness of a design rather than an implementation, and testing, which does not provide formal guarantees about the correctness of the system.Use of formal requirement specifications in run-time monitoring and checking is the salient aspect of the MaC architecture. MaC is a lightweight formal method solution which works as a viable complement to the current heavyweight formal methods. In addition, analysis processes of the architecture including instrumentation of the target program, monitoring, and checking are performed fully automatically without human direction, which increases the accuracy of the analysis. Another important feature of the architecture is the clear separation between monitoring implementation-dependent low-level behaviors and checking high-level behaviors, which allows the reuse of a high-level requirement specification even when the target program implementation changes. Furthermore, this separation makes the architecture modular and allows the flexibility of incorporating third party tools into the architecture. The paper presents an overview of the MaC architecture and a prototype implementation Java-MaC.     

A Six-sigma approach for benchmarking of RP&M processes

This paper presents a methodology of using six-sigma quality tools for benchmarking of rapid prototyping & manufacturing (RP&M) processes. It involves the fabrication of a geometric benchmark part and a methodology to control and identify the best performance of the process to reduce the variablity in the fabricated parts. The approach is demonstrated with a case study based on the direct laser sintering (DLS) process for prototyping using plastic powder. In the case study an identified set of six-sigma/ statistical process control tools is employed to determine and best tune factors affecting the desired outcomes of the built parts.     

Carrier concentration dependence of donor activation energy in n-type GaN epilayers grown on Si (1 1 1) by plasma-assisted MBE

The n-type GaN layers were grown by plasma-assisted MBE and either intentionally doped with Si or unintentionally doped. The optical characteristics of a donor level in Si-doped, GaN were studied in terms of photoluminescence (PL) spectroscopy as a function of electron concentration. Temperature dependent PL measurements allowed us to estimate the activation energy of a Si-related donor from temperature-induced decay of PL intensity. PL peak positions, full width at half maximum of PL and activation energies are found to be proportional to the cube root of carrier density. The involvement of donor levels is supported by the temperature-dependent electron concentration measurements.     

Pinch Roller Failure Analysis and Resulting Enhancement of Rebar Mechanical Properties

Reinforcing bars, popularly termed “rebars,” are used to impart tensile strength to concrete structures. Concrete has high resistance to weathering and fire and high compressive strength but almost no tensile strength, hence rebars are used to provide the latter to concrete. Property consistency along the length of rebars is an important prerequisite. When the finished product is subjected to thermomechanical treatment (TMT), proper control of rolling and water box parameters and efficient pinch rolling are needed to achieve acceptable properties. Variation of yield strength (YS) along TMT bars from the front to back end has been observed within the same heat treatment. In the presented investigation, it was observed that pinch rolling ineffectiveness is the main reason for the poor mechanical properties at the back end. The pinch roller was unable to support the back end of the TMT bars properly to maintain the speed and tension of the bars, resulting in nonuniform cooling of the back end through the water box and subsequent mechanical property failure. Due to the substandard material of the pinch roller, it was unable to hold the back end of the bar properly. Based on analysis of the roller it was concluded that it failed due to improper microstructure, resulting in inadequate hardness and toughness for the stringent operating conditions. AISI H13 is a better material to use in such high-service-temperature conditions. Moreover, proper heat treatment is needed to achieve adequate hardness and microstructure properties. After proper heat treatment of pinch rollers, their service life was increased twofold, minimizing the YS variation along the rebars.     

Building Resilience Through Disaster Waste Management——UN Environment's Experiences and Approaches

Integrating disaster waste issue is a critical component of making humanitarian action fit for the future,anticipating global risks and challenges such as increased vulnerability due to climate change and environmental degradation.This requires a fundamental shift towards a model that not only strengthens the response to crises but also learns and adapts in order to anticipate and act before such waste garnered.This article conducted analyses on the characteristics of disasters in the past two decades.Uncertainties confound disaster waste management,including the timing and magnitude of each disaster,and the amounts and types of waste that will be generated.For these reasons alone,disaster waste management must be an integral part of development planning and processes.Making 10 years since the 2008 Wenchuan earthquake,this article highlights that disaster waste management is not only debris clearance or waste management following a disaster,but also includes prevention and pre-disaster preparedness aspects in terms of enhancing resilience of local communities.Such"mainstreaming,"ensures that disaster waste management(DWM)will be treated as a priority issue,on an ongoing basis.Based on UN Environment's experiences and approaches,this paper emphasises that preparedness is the key,and that priority should be accorded to integrating disaster contingency planning in national and city level waste management strategies as well as mainstreaming waste management issues within broader disaster preparedness and response plans and actions.It is envisaged that the issues presented and the gaps identified in this paper will provide a basis for future comprehensive and cohesive research on disaster waste management.In turn,this research can lead to better preparedness and response on disaster waste management.