A standard on human response to vibration — one of a new breed?

Human response to vibration is used as an example for consideration of the requirements of standards in the human factors field. It is suggested that standards relating to people may be concerned primarily with the design of equipment for optimum satisfaction of users, and that this demands a different approach to standards if they are to be effective. It is argued that a clear distinction should be made between standards intended to protect people from harmful conditions, standards intended to minimise the risk of people being harmed, and standards intended to give advice and information. In the case of human response to vibration it is suggested that standards should relate to agreed methods of measurement and assessment, limitations to preserve health, limitations to be applied in specific situations in order to prevent the risk of accidents, together with a data base for designers to work from.     

A pseudo-immersive virtual environment—a framework for modelling sheet deformation

This paper presents a real-time, computationally inexpensive environment for accurate simulations of sheet materials on a personal computer. The approach described differs from other techniques through its novel use of multilayer sheet structures. The ultimate aim is to incorporate into the environment the capacity of simulating a range of temperatures. A pseudo-immersive Window on World (WoW) environment is used to handle the implementation of the real-time, aesthetically accurate deformation algorithm (MaSSE-Mass-Spring Simulation Engine). The motion of the sheet is controlled by simulated gravity and through its interaction with objects that have been inserted into a virtual room. In addition, the WoW interface is used to adjust environmental parameters dynamically and adjust the scene viewing perspective. An obvious use of the environment is centred on mechanical engineering-based real-time simulations of heat-sensitive sheet materials. This would allow for a wide range of applications in virtual manufacturing including the clothing industry and hostile environments.     

Structural shape optimization—A survey

This paper is a survey of structural shape optimization with an emphasis on techniques dealing with shape optimization of the boundaries of two- and three-dimensional bodies. Attention is focused on the special problems of structural shape optimization which are due to a finite element model which must change during the optimization process. These problems include the requirement for sophisticated automated mesh generation techniques and careful choice of design variables. They also include special problems in obtaining sufficiently accurate sensitivity derivatives.     

How to divide a territory? A new simple differential formalism for optimization of set functions

In many practical problems, we must optimize a set function, i.e., find a set A for which f(A)→max, where f is a function defined on the class of sets. Such problems appear in design, in image processing, in game theory, etc. Most optimization problems can be solved (or at least simplified) by using the fact that small deviations from an optimal solution can only decrease the value of the objective function; as a result, some derivative must be equal to 0. This approach has been successfully used, e.g., for set functions in which the desired set A is a shape, i.e., a smooth (or piece-wise smooth) surface. In some real-life problems, in particular, in the territorial division problem, the existing methods are not directly applicable. For such problems, we design a new simple differential formalism for optimizing set functions. ©1999 John Wiley & Sons, Inc.     

Computer aided chemistry—III. Spectral envelope deconvolution based on a simplex optimization procedure

A Simplex optimization technique has been applied to the problem of fitting complicated absorption and magnetic circular dichroism (MCD) spectra that comprise many overlapping, Gaussian bands. Both a weighted centroid Simplex routine and a non-linear least-squares routine have been incorporated into a FORTRAN 77 program to carry out the fitting of electronic spectra. The performance of these two procedures was compared by fitting synthetic spectra to which varying degrees of noise had been added, and were judged according to the ability of each routine to reproduce the original band shape parameters that were used to construct the synthetic spectral envelopes. Only the Simplex procedure was successful at fitting the MCD data. Both the non-linear least-squares and Simplex routines performed adequately in tests using the synthetic absorption spectral data. However, the least-squares optimization routine was considerably faster than the Simplex routine at finding a solution when significant noise was present in the test absorption spectra. The presence of significant levels of electronic noise in a spectrum can reduce the precision and accuracy of the deconvolution results and many cause the deconvolution procedure to degenerate to a false minimum. Degeneracy of the fitting procedures at local minima, which corresponded to sets of band shape parameters that provided a good fit to either the absorption or MCD spectrum of a chemical species, but not both spectra, was overcome by fitting each absorption and MCD spectrum of a pair of spectra from the same chemical species, successively, until a set of band shape parameters was found that provided reasonable fits of both spectra. This deconvolution procedure, which successively optimizes a pair of absorption and MCD spectra, has been very valuable in fitting complex spectra of zinc phthalocyanine π-cation radical complexes.     

A new numerical method on American option pricing

Mathematically, the Black-Scholes model of American option pricing is a free boundary problem of partial differential equation. It is well known that this model is a nonlinear problem, and it has no closed form solution. We can only obtain an approximate solution by numerical method, but the precision and stability are hard to control, because the singularity at the exercise boundary near expiration date has a great effect on precision and stability for numerical method. We propose a new numerical method, FDA method, to solve the American option pricing problem, which combines advantages the Semi-Analytical Method and the Front-Fixed Difference Method. Using the FDA method overcomes the difficulty resulting from the singularity at the terminal of optimal exercise boundary. A large amount of calculation shows that the FDA method is more accurate and stable than other numerical methods.     

A new multi-criteria optimization strategy for shared control in?wheelchair assisted navigation

In todays aging society, many people require mobility assistance, that can be provided by robotized assistive wheelchairs with a certain degree of autonomy when manual control is unfeasible due to disability. Robot wheelchairs, though, are not supposed to be completely in control because lack of human intervention may lead to loss of residual capabilities and frustration. Most of these systems rely on shared control, which typically consists of swapping control from human to robot when needed. However, this means that persons never deal with situations they find difficult. We propose a new shared control approach to allow constant cooperation between humans and robots, so that assistance may be adapted to the user??s skills. Our proposal is based on the reactive navigation paradigm, where robot and human commands become different goals in a Potential Field. Our main novelty is that human and robot attractors are weighted by their respective local efficiencies at each time instant. This produces an emergent behavior that combines both inputs in an efficient, safe and smooth way and is dynamically adapted to the user??s needs. The proposed control scheme has been successfully tested at hospital Fondazione Santa Lucia (FSL) in Rome with several volunteers presenting different disabilities.     

A new nonmonotone filter Barzilai–Borwein method for solving unconstrained optimization problems

In this paper, a finite filter is used in the structure of the Barzilai–Browein (BB) gradient method in order to propose a new modified BB algorithm for solving large-scale unconstrained optimization problems. Our algorithm is equipped with a relaxed nonmonotone line search technique which allows the algorithm to enjoy the nonmonotonicity properties from scratch. Under some suitable conditions, the global convergence property of the new proposed algorithm is established. Numerical results on some test problems in CUTEr library show the efficiency and effectiveness of the new algorithm in practice too.     

An integrated new product development framework – an application on green and low-carbon products

Companies need to be innovative to survive in today's competitive market; thus, new product development (NPD) has become very important. This research constructs an integrated NPD framework for developing new products. In stage one, customer attributes (CAs) and engineering characteristics (ECs) for developing products are collected, and fuzzy interpretive structural modelling (FISM) is applied to understand the relationships among these critical factors. Based on quality function deployment (QFD), a house of quality is then built, and fuzzy analytic network process (FANP) is adopted to calculate the relative importance of ECs. In stage two, fuzzy failure mode and effects analysis (FFMEA) is applied to understand the potential failures of the ECs and to determine the importance of ECs with respect to risk control. In stage three, a goal programming (GP) model is constructed to consider the outcome from the FANP-QFD, FFMEA and other objectives, in order to select the most important ECs. Due to pollution and global warming, environmental protection has become an important topic. With both governments and consumers developing environmental consciousness, successful green and low-carbon NPD provides an important competitive advantage, enabling the survival or renewal of firms. The proposed framework is implemented in a panel manufacturing firm for designing a green and low-carbon product.     

Smart CloudBench—A framework for evaluating cloud infrastructure performance

Cloud migration allows organizations to benefit from reduced operational costs, improved flexibility, and greater scalability, and enables them to focus on core business goals. However, it also has the flip side of reduced visibility. Enterprises considering migration of their IT systems to the cloud only have a black box view of the offered infrastructure. While information about server pricing and specification is publicly available, there is limited information about cloud infrastructure performance. Comparison of alternative cloud infrastructure offerings based only on price and server specification is difficult because cloud vendors use heterogeneous hardware resources, offer different server configurations, apply different pricing models and use different virtualization techniques to provision them. Benchmarking the performance of software systems deployed on the top of the black box cloud infrastructure offers one way to evaluate the performance of available cloud server alternatives. However, this process can be complex, time-consuming and expensive, and cloud consumers can greatly benefit from tools that can automate it. Smart CloudBench is a generic framework and system that offers automated, on-demand, real-time and customized benchmarking of software systems deployed on cloud infrastructure. It provides greater visibility and insight into the run-time behavior of cloud infrastructure, helping consumers to compare and contrast available offerings during the initial cloud selection phase, and monitor performance for service quality assurance during the subsequent cloud consumption phase. In this paper, we first discuss the rationale behind our approach for benchmarking the black box cloud infrastructure. Then, we propose a generic architecture for benchmarking representative applications on the heterogeneous cloud infrastructure and describe the Smart CloudBench benchmarking workflow. We also present simple use case scenarios that highlight the need for tools such as Smart CloudBench.     

The file allocation problem—A queueing network optimization approach

A set of customers use a connected network of computer installations, each accessing the network from a particular node. These customers share information contained in a set of data files. A typical customer's need is characterized by a request requiring a subset of these files being accessed in a Markovian sequence. The cycle time for this customer is the total time taken on the average to complete his request sequence. The objective is to locate a single copy of each of the files in such a way that a weighted sum of these response times is minimized. The problem is modelled as a Closed Queueing Network optimization problem. Models are developed for both single and multiple chain cases. An incremental analysis approach is used to solve the single chain case. For the multiple chain case, it is shown how this model approximates to a set partitioning problem under certain conditions. Efficient heuristics are developed to solve this partitioning problem. With certain simplifying assumptions, the associated communication problem is then included in the model.     

Recent advances on distributed online optimization

Online optimization has received numerous attention in recent two decades, mostly inspired by its potential applications to auctions, smart grids, portfolio management, dictionary learning, neural networks, and so on. Generally, online optimization is a sequence of decision making processes, where a sequence of time-varying loss functions are gradually revealed in a dynamic environment which may be adversarial. At each time instant, the loss function information at current time is revealed to the decision maker only after her/his decision is made. The objective of online optimization is to choose the best decision at each time step as far as possible, but unfortunately, this goal is generally diffcult or impossible to achieve. As such, to measure the performance for an algorithm, two metrics are usually exploited, i.e., regret and competitive ratio, for which the former one is leveraged more frequently in the literature. Moreover, two kinds of regrets, i.e., static and dynamic regrets, are usually considered by researchers, where the static regret is to compare the performance with a cumulative loss with respect to the same best decision through all the time horizons, while the dynamic regret is with respect to the best decision at each time instant. More recently, another regret, called adaptive regret , has been proposed and investigated as a suitable metric for changing environments, as dynamic regret does. Historically, centralized online optimization is first addressed, that is, there is a centralized decision maker who can access all the information on the revealed loss function at each time. Along this line, a wide range of results have thus far been reported in the literature. For example, online optimization was studied subject to feasible set constraints, where it has been shown that the optimal bound is O( √ T) for static regret....     

Land administration and cadastral trends — a framework for re-engineering

This paper reviews the need for a new land administration vision that takes a more integrated approach rather than the historic fragmented approach and examines change management of land administration and cadastral systems in the context of global drivers of change. This results in the development of a framework for re-engineering land administration systems. After discussing a land administration vision the paper reviews trends and issues in the context of this framework. While the paper discusses global issues and trends, the paper concentrates on the experiences and ongoing land administration research of the authors' and their colleagues with a focus on Australia.     

A Krylov–Arnoldi reduced order modelling framework for efficient,fully coupled,structural–acoustic optimization

In this work, a reduced order multidisciplinary optimization procedure is developed to enable efficient, low frequency, undamped and damped, fully coupled, structural–acoustic optimization of interior cavities backed by flexible structural systems. This new method does not require the solution of traditional eigen value based problems to reduce computational time during optimization, but are instead based on computation of Arnoldi vectors belonging to the induced Krylov Subspaces. The key idea of constructing such a reduced order model is to remove the uncontrollable, unobservable and weakly controllable, observable parts without affecting the noise transfer function of the coupled system. In a unified approach, the validity of the optimization framework is demonstrated on a constrained composite plate/prism cavity coupled system. For the fully coupled, vibro–acoustic, unconstrained optimization problem, the design variables take the form of stacking sequences of a composite structure enclosing the acoustic cavity. The goal of the optimization is to reduce sound pressure levels at the driver’s ear location. It is shown that by incorporating the reduced order modelling procedure within the optimization framework, a significant reduction in computational time can be obtained, without any loss of accuracy—when compared to the direct method. The method could prove as a valuable tool to analyze and optimize complex coupled structural–acoustic systems, where, in addition to fast analysis, a fine frequency resolution is often required.     

ELA—A new Approach for Learning Agents

In this paper we discuss a new incremental learning approach used to implement adaptive behavior in autonomous agents. Adaptive agents must increase their performance based on experience using some learning approach. Often, incremental learning techniques like memory-based reasoning (MBR) are used. However, traditional MBR algorithms require an adequate (generally complex) measure of similarity, need much data and spend much time for computing similarities between examples. Such problems are unacceptable for autonomous agents that live in very dynamic environments, because they have little time to make decisions. Our approach does not use similarity measures between examples, classifies examples very fast and can compact data. We represent data as a concept graph (CG), each node representing a partition of the data. We propose an algorithm that uses the partitions to classify new examples. We compare our results with other techniques and conclude that the method performs quite well. Finally, we apply the approach to an application of adaptive agents for personalizing web search.This research was funded by Région Picardie in France. We thank Emerson Paraiso and Cesar Tacla for comments and time spent with the discussions.     

Low Energy Certificate——An exploration on optimization and evaluation of energy-efficient building envelope

Energy saving is the crucial task of green architecture,energy-saving design and evaluation should be interactive.Low Energy Certificate(LEC),an interactive computer program for energy efficiency and certification of building envelope,is briefly introduced in this paper in aspects of certification standards,procedure,methods etc.Through the evaluation report of Innovation-pavilion PoI features,reference values of LEC are presented.     

Design optimization of non-uniform stiffened steel plate girders—a computer code

The paper presents a direct search design procedure that has been automated to obtain a minimum weight design of non-uniform stiffened steel plate girders. The direct search procedure does not require evaluation of design gradients and the search for minimum weight design is according to either the ASD or the LRFD design specifications of the American Institute of Steel Construction. An algorithm for the two design procedures is presented to facilitate a general utilization of the computer code. The comzputer code is tested by comparing results of minimum weight designs of a three-span stiffened steel plate girder to results obtained from a generalized reduced gradients algorithm. Results of the comparative design studies are summarized to (i) compare effectiveness of the procedure presented in this paper over a generalized gradient-based design procedure; (ii) illustrate the simplified input–output format of the computer code through a set of design examples; and (iii) compare designs obtained from the two design specifications implemented in the code.     

EFFORT: A new host–network cooperated framework for efficient and effective bot malware detection

Bots are still a serious threat to Internet security. Although a lot of approaches have been proposed to detect bots at host or network level, they still have shortcomings. Host-level approaches can detect bots with high accuracy. However they usually pose too much overhead on the host. While network-level approaches can detect bots with less overhead, they have problems in detecting bots with encrypted, evasive communication C&C channels. In this paper, we propose EFFORT, a new host–network cooperated detection framework attempting to overcome shortcomings of both approaches while still keeping both advantages, i.e., effectiveness and efficiency. Based on intrinsic characteristics of bots, we propose a multi-module approach to correlate information from different host- and network-level aspects and design a multi-layered architecture to efficiently coordinate modules to perform heavy monitoring only when necessary. We have implemented our proposed system and evaluated on real-world benign and malicious programs running on several diverse real-life office and home machines for several days. The final results show that our system can detect all 17 real-world bots (e.g., Waledac, Storm) with low false positives (0.68%) and with minimal overhead. We believe EFFORT raises a higher bar and this host–network cooperated design represents a timely effort and a right direction in the malware battle.     

The Blend station—a new ratio control structure

The paper treats the problem of ratio control. Previous solutions based on simple Ratio stations perform poorly during transients caused by setpoint changes. A new solution, the Blend station, that improves control during transients, is proposed. Both a constant-gain and an adaptive version are presented.