-*- mode: org -*-
Seemingly unrelated noise from the query or database (duplicate entries)
* 104(<-336): Resource-Aware Compiler Prefetching for Fine-Grained Many-Cores

Super-scalar, out-of-order processors that can have tens of read and
write requests in the execution window place significant demands on
Memory Level Parallelism (MLP). Multi- and many-cores with shared
parallel caches further increase MLP demand. Current cache hierarchies
however have been unable to keep up with this trend, with modern
designs allowing only 4-16 concurrent cache misses. This disconnect is
exacerbated by recent highly parallel architectures (e.g. GPUs) where
power and area per-core budget favor numerous lighter cores with less
resources, further reducing support for MLP on a per-core
basis. Support for hardware and software prefetch increases MLP
pressure since these techniques overlap multiple memory requests with
existing computation. In this paper, we propose and evaluate a novel
Resource-Aware Prefetching (RAP) compiler algorithm that is aware of
the number of simultaneous prefetches supported, and optimized for the
same. We implemented our algorithm in a GCC-derived compiler and
evaluated its performance using an emerging fine-grained many-core
architecture. Our results show that the RAP algorithm outperforms a
well-known loop prefetching algorithm by up to 40.15% in run-time on
average across benchmarks and the state-of-the art GCC implementation
by up to 34.79%, depending upon hardware configuration. Moreover, we
compare the RAP algorithm with a simple hardware prefetching
mechanism, and show run-time improvements of up to 24.61%. To
demonstrate the robustness of our approach, we conduct a design-space
exploration (DSE) for the considered target architecture by varying
(i) the amount of chip resources designated for per-core prefetch
storage and (ii) off-chip bandwidth. We show that the RAP algorithm is
robust in that it improves performance across all design points
considered. We also identify the Pareto-optimal hardware-software
configuration which delivers 53.66% run-time improvement on average
while using only 5.47% more chip area than the bare-bones design.

2011



* 109(<-471): Functional organization of the major late transcriptional unit of canine adenovirus type 2

Vectors derived from canine adenovirus type 2 (CAV-2) are attractive
candidates for gene therapy and live recombinant vaccines. CAV-2
vectors described thus far have been generated by modifying the virus
genome, most notably early regions 1 and 3 or the fiber
gene. Modification of these genes was underpinned by previous
descriptions of their mRNA and protein-coding sequences. Similarly,
the construction of new CAV-2 vectors bearing changes in other genomic
regions, in particular many of those expressed late in the viral
cycle, will require prior characterization of the corresponding
transcriptional units. In this study, we provide a detailed
description of the late transcriptional organization of the CAV-2
genome. We examined the major late transcription unit (MLTU) and
determined its six families of mRNAs controlled by the putative major
late promoter (MLP). All mRNAs expressed from the MLTU had a common
non-coding tripartite leader (224 nt) at their 5' end. In transient
transfection assays, the predicted MLP sequence was able to direct
luciferase gene expression and the TPL sequence yielded a higher
amount of transgene product. Identification of viral transcriptional
products following in vitro infection confirmed most of the predicted
protein-coding regions that were deduced from computer analysis of the
CAV-2 genome. These findings contribute to a better understanding of
gene expression in CAV-2 and lay the foundation required for genetic
modifications aimed at vector optimization.

2009


* 112(<-  9): A new methodology for investigating the cost-optimality of energy retrofitting a building category

According to the Energy Performance of Buildings Directive (EPBD)
Recast, building energy retrofitting should aim "to achieving
cost-optimal levels". However, the detection of cost-optimal levels
for an entire building stock is a complex task. This paper tackles
such issue by introducing a novel methodology, aimed at supporting
robust cost-optimal energy retrofit solutions for building
categories. Since the members of one building category provide highly
different energy performance, they cannot be correctly represented by
only one reference design as stipulated by the EPBD Recast. Therefore,
a representative building sample (RBS) is here used to consider
potential variations in all parameters affecting energy
performance. Simulation-based uncertainty analysis is employed to
identify the optimal RBS size, followed by simulation-based
sensitivity analysis to identify proper retrofit actions. Then
post-processing is performed to investigate the cost-effectiveness of
all possible retrofit packages including energy-efficient HVAC
systems, renewables, and energy saving measures. The methodology is
denoted as SLABE, 'Simulation-based Large-scale
uncertainty/sensitivity Analysis of Building Energy performance'. It
employs EnergyPlus and MATLAB (R). For demonstration, SLABE is applied
to office buildings built in South Italy during 1920-1970. The results
show that the cost-optimal retrofit package includes the installation
of condensing gas boiler, water-cooled chiller and full-roof
photovoltaic system. (C) 2015 Elsevier B.V. All rights reserved.

2015



* 113(<- 84): Recent development and application of several high-efficiency surface heat exchangers for energy conversion and utilization

In the present study, the recent research of three kinds of surface
heat exchangers, i.e., shell-and-tube heat exchangers with helical
baffles, air-cooled heat exchangers used in large air-cooled systems,
and primary surface heat exchangers are reviewed. They are used in the
energy conversion and utilization for liquid to liquid, gas to gas and
liquid to gas heat exchange, respectively. It can be concluded that
the helical baffled shell-and-tube heat exchangers (STHXs) should be
used to replace the conventional segmental baffled STHXs in
industries, despite there are a lot of research work have to be done,
especially on the novel combined helical baffles. The primary surface
gas to gas heat exchangers are developing towards to the snore complex
3D CC primary surfaces, such as the double-wave CC primary surface,
offset-bubble primary surface and 3D anti-phase secondary
corrugation. The whole performance for the air-cooled heat exchangers
in the air cooling system and the multi-objectives optimization for
air-cooled heat exchangers should be paid more attention, considering
the heat transfer, pumper power, space usage and other economic
influence factors. (C) 2014 Elsevier Ltd. All rights reserved.

2014



* 114(<-432): Multi-criteria Axiomatic Design Approach to Evaluate Sites for Grid-connected Photovoltaic Power Plants: A Case Study in Turkey

Global warming and climate change are the most serious problems for
developing countries as well as the world. Therefore, the usage of
renewable energy sources is gaining importance for sustainable energy
development and environmental protection. Turkey is one of the
developing countries whose demand of electricity is sharply
increasing. In order to meet this demand by means of renewable
sources, solar power is a suitable source due to the high solar energy
potential of Turkey among the renewable sources. In this article, the
multi-criteria axiomatic design (AD) approach is proposed for the
evaluation of sites for a grid-connected photovoltaic power plant
(GCPP) in Turkey. For this aim, four evaluation criteria, which have
great influence on determination of a GCPP site are taken into
account.

2010





* 115(<- 45): Cyclone optimization by COMPLEX method and CFD simulation

The most important performance parameters in cyclone design are the
pressure drop and collection efficiency. In general, the best designs
provide relatively high efficiency with a low pressure drop. In this
study, the multiobjective optimization of cyclones operating with a
low particle loading (15 g/m(3)) and small particle diameter (5 mu m
to 15 mu m) is performed using the COMPLEX algorithm, a constrained
derivative-free optimization method. The objective function is
formulated to maximize the collection efficiency with a maximum
pressure drop restriction. All objective function evaluations are
carried out by CFD simulation with the code CYCLO-EE5 based on the
Eulerian multi-fluid concept. An optimized design cyclone is obtained
applying the proposed methodology in a feasible time 15 days of
computational effort). Also, in comparison with the Stairmand and
Lapple cyclones the collection efficiency was 3.5% and 9.2% higher and
the pressure drop was 63% and 11.4% lower, respectively. The increase
in the collection efficiency with lower pressure drop was due to the
displacement of the tangential velocity peak toward the wall and an
increase in the tangential velocity near the wall. (C) 2015 Elsevier
B.V. All rights reserved.

2015





* 116(<- 59): Design of a novel gas cyclone vortex finder using the adjoint method

Gas cyclones have many industrial applications in solid-gas
separation. The vortex finder is an essential part in gas cyclones
where the shape and diameter highly affect the cyclone
performance. Many optimization studies have been conducted to optimize
the cylindrical vortex finder diameter. This study introduces a new
vortex finder shape optimized for minimum pressure drop using the
discrete adjoint method. The new optimum cyclone will save 66% from
the driving power needed for the Stairmand cyclone. To efficiently
perform the grid independence study for the new cyclone, a new
framework using the adjoint solver and the grid convergence index is
proposed and tested. The proposed framework relies on local mesh
adaptation instead of the global mesh refinement approach. A
comparison of numerical simulation of the new cyclone and the
Stairmand cyclone confirms the superior performance of the new vortex
finder shape for the pressure drop and the cut-off diameter. The
results of this study open a new era gas cyclones geometry
optimization by using the adjoint method instead of the traditional
surrogate based optimization technique. Moreover, the computational
costs for the grid independence studies will be reduced via the
application of the adjoint methods. (C) 2015 Elsevier B.V. All rights
reserved.

2015





* 119(<-212): Investigation of PWR core optimization using harmony search algorithms

This work addresses applications of the classical harmony search (HS),
improved harmony search (IHS) and the harmony search with differential
mutation based pith adjustment (HSDM) to PWR core reloading pattern
optimization problems. Proper loading pattern of fuel assemblies (FAs)
depends on both neutronic and thermal-hydraulic aspects; obtaining
optimal arrangement of fuel assemblies, FA, in a core to meet special
objective functions is a complex problem. In this paper, in the first
step HS, IHS and HSDM methods are implemented and compared with other
meta-heuristic algorithms on Shekel's Foxholes problem. In the second
step to evaluate proposed techniques in PWR cores, maximization of
multiplication factor, k(eff), decreasing of power picking factor
(PPF) as much as possible and power density flattening are chosen as
neutronic objective functions for two PWR test cases although other
variables can be taken into account. In the third step, obtaining
maximum core average critical heat flux (CHF) along no void generation
throughout the cores are two thermal-hydraulic objective functions
which are included to the desired neutronic objective functions. For
neutronic and thermal-hydraulic computation, PARCS (Purdue Advanced
Reactor Core Simulator) and COBRA-EN codes are used
respectively. Coupling the harmony search with the PARCS code and the
COBRA-EN code, we developed a core reloading pattern optimization
code. The results, convergence rate and reliability of the techniques
are quiet promising and show that the harmony algorithms perform very
well. Furthermore, it is found that harmony searches have potential
for other optimization applications in other nuclear engineering
field. (C) 2013 Elsevier Ltd. All rights reserved.

2013




* 122(<-591): Optimization of a reverse osmosis system using genetic algorithm

Reverse Osmosis (RO) has found extensive application in industry as a
highly efficient separation process. In most cases, it is required to
select the optimum set of operating variables such that the
performance of the system is maximized. In this work, an attempt has
been made to optimize the performance of RO system with a cellulose
acetate membrane to separate NaCl-Water system using Genetic Algorithm
(GA). The GAs are faster and more efficient than conventional gradient
based optimization techniques. The optimization problem was to
maximize the observed rejection of the solute by varying the feed
flowrate and overall permeate flux across the membrane for a constant
feed concentration. To model the system, a well-established transport
model for RO system, the Spiegler-Kedem model was used. It was found
that the GA converged rapidly to the optimal solution at the 8th
generation. The effect of varying GA parameters like size of
population, crossover probability, and mutation probability on the
result was also studied. The algorithm converged to the optimum
solution set at the 8th generation. It was also seen that varying the
computational parameters significantly affected the results.

2006



* 123(<-530): Multi-objective optimization in combinatorial chemistry applied to the selective catalytic reduction of NO with C3H6

A high-throughput approach, aided by multi-objective experimental
design of experiments based on a genetic algorithm, was used to
optimize the combinations and concentrations of a noble metal-free
solid catalyst system active in the selective catalytic reduction of
NO with C3H6. The optimization framework is based on PISA [S. Bleuler,
M. Laumanns, L. Thiele, E. Zitzler, Proc. of EMO'03 (2003) 4941, and
two state-of-the-art evolutionary multi-objective algorithms-SPEA2
[E. Zitzler, M. Laumanns, L. Thiele, in: K.C. Giannakoglou, et
al. (Eds.), Evolutionary Methods for Design, Optimisation and Control
with Application to Industrial Problems (EUROGEN 2001), International
Center for Numerical Methods in Engineering (CIMNE), 2002, p. 95] and
IBEA [E. Zitzler, S. Kunzli, Conference on Parallel Problem Solving
from Nature (PPSN VIII), 2004, p. 832]-were used for
optimization. Constraints were satisfied by using so-called "repair
algorithms." The results show that evolutionary algorithms are
valuable tools for screening and optimization of huge search spaces
and can be easily adapted to direct the search towards multiple
objectives. The best noble metal free catalysts found by this method
are combinations of Cu, Ni, and Al. Other catalysts active at low
temperature include Co and Fe. (C) 2007 Elsevier Inc. All rights
reserved.

2007



* 124(<-554): Implementation of the multi-channel monolith reactor in an optimisation procedure for heterogeneous oxidation catalysts based on genetic algorithms

A multi-criteria optimisation procedure based on genetic algorithms is
carried out in search of advanced heterogeneous catalysts for total
oxidation. Simple but flexible software routines have been created to
be applied within a search space of more then 150,000 individuals. The
general catalyst design includes mono-, bi- and trimetallic
compositions assembled out of 49 different metals and depleted on an
Al2O3 support in up to nine amount levels. As an efficient tool for
high-throughput screening and perfectly matched to the requirements of
heterogeneous gas phase catalysis-especially for applications
technically run in honeycomb structures-the multi-channel monolith
reactor is implemented to evaluate the catalyst performances. Out of a
multi-component feed-gas, the conversion rates of carbon monoxide (CO)
and a model hydrocarbon (HC) are monitored in parallel. In combination
with further restrictions to preparation and pretreatment a primary
screening can be conducted, promising to provide results close to
technically applied catalysts. Presented are the resulting
performances of the optimisation process for the first catalyst
generations and the prospect of its auto-adaptation to specified
optimisation goals.

2007





* 138(<-320): A Multi-Objective Approach to Force Field Optimization: Structures and Spin State Energetics of d(6) Fe(II) Complexes

The next generation of force fields (FFs), regardless of the accuracy
of the potential energy representation, will always have parameters
that must be fitted in order to reproduce experimental and/or ab
initio data accurately. Single objective methods have been used for
many years to automate the obtaining of parameters, but this leads to
ambiguity. The solution depends on the chosen weights and is therefore
not unique. There have been few advances in solving this problem,
which thus remains a major hurdle for the development of empirical FF
methods. We propose a solution based on multi-objective evolutionary
algorithms (MOEAs). MOEAs allow the FF to be tuned against the desired
objectives and offer a powerful, efficient, and automated means to
reparameterize FFs, or even discover the parameters for a new
potential. Here, we illustrate the application of MOEAs by
reparameterizing the ligand field molecular mechanics (LFMM) FF
recently reported for modeling spin crossover in iron-(II)-amine
complexes (Deeth et al. J. Am. Chem. Soc. 2010, 132, 6876). We quickly
recover the performance of the original parameter set and then
significantly improve it to reproduce the geometries and spin state
energy differences of an extended series of complexes with RMSD errors
in Fe-N and N-N distances reduced from 0.06 angstrom to 0.03 angstrom
and spin state energy difference RMSDs reduced from 1.5 kcal mol(-1)
to 0.2 kcal mol(-1). The new parameter sets highlight, and help
resolve, shortcomings both in the non-LFMM FF parameters and in the
interpretation of experimental data for several other Fe(II)N-6 amine
complexes not used in the FF optimization.

2012





* 154(<-673): Multiobjective Linear Programming model on injection oilfield recovery system

This paper proposes a Multiobjective Linear Programming (MLP) model on
injection oilfield recovery system. A modified interior-point
algorithm to MLP problems has been constructed by using concepts of
Kamarkar's interior point algorithm and the Analytic Hierarchy Process
(AHP). This algorithm is shown to likely be more efficient than other
MLP's algorithms in the application of decision making on the
petroleum industry through the demonstration of a numerical
example. The MLP model's optimal solution allows decision makers to
optimally design the developing plan of the injection oilfield
recovery system. (C) 1998 Elsevier Science Ltd. All rights reserved.

1998


* 155(<-680): PERCEPTRONS PLAY THE REPEATED PRISONERS-DILEMMA

We examine the implications of bounded rationality in repeated games
by modeling the repeated game strategies as perceptrons
(F. Rosenblatt, ''Principles of Neurodynamics,'' Spartan Books, and
M. Minsky and S. A. Papert, ''Perceptions: An Introduction to
Computational Geometry,'' MIT Press, Cambridge, MA, 1988). In the
prisoner's dilemma game, if the cooperation outcome is Pareto
efficient, then we can establish the folk theorem by perceptrons with
single associative units (Minsky and Papert), whose computational
capability barely exceeds what we would expect from players capable of
fictitious plays (e.g., L. Shapley, Some topics in two-person games,
Adv. Game Theory 5 (1964), 1-28). (C) 1995 Academic Press, Inc.

1995



* 157(<-300): Dynamic equivalence by an optimal strategy

Due to the curse of dimensionality, dynamic equivalence remains a
computational tool that helps to analyze large amount of power
systems' information. In this paper, a robust dynamic equivalence is
proposed to reduce the computational burden and time consuming that
the transient stability studies of large power systems represent. The
technique is based on a multi-objective optimal formulation solved by
a genetic algorithm. A simplification of the Mexican interconnected
power system is tested. An index is used to assess the proximity
between simulations carried out using the full and the reduced
model. Likewise, it is assumed the use of information stemming from
power measurements units (PMUs), which gives certainty to such
information, and gives rise to better estimates. (C) 2011 Elsevier
B.V. All rights reserved.

2012




* 160(<-558): Optimization strategies in ion chromatography

The ion chromatographer is often concerned with the separation of
complex mixtures with a variable behavior of their components, which
makes good resolution and reasonable analysis time sometimes extremely
difficult. Several optimization strategies have been proposed to solve
this problem. The most reliable and less time consuming strategies
apply resolution criteria based on theoretical or empirical retention
models to describe the retention of particular components. This review
focuses on optimization strategies in ion chromatography with a
detailed description of the ion chromatographic retention model,
objective functions, multi criteria decision making, and peak
modeling.

2007



* 166(<-628): Digital filter design using multiple pareto fronts

Evolutionary approaches have been used in a large variety of design
domains, from aircraft engineering to the designs of analog
filters. Many of these approaches use measures to improve the variety
of solutions in the population. One such measure is clustering. In
this paper, clustering and Pareto optimisation are combined into a
single evolutionary design algorithm. The population is split into a
number of clusters, and parent and offspring selection, as well as
fitness calculation, are performed on a per-cluster basis. The
objective of this is to prevent the system from converging prematurely
to a local minimum and to encourage a number of different designs that
fulfil the design criteria. Our approach is demonstrated in the domain
of digital filter design. Using a polar coordinate based pole-zero
representation, two different lowpass filter design problems are
explored. The results are compared to designs created by a human
expert. They demonstrate that the evolutionary process is able to
create designs that are competitive with those created using a
conventional design process by a human expert. They also demonstrate
that each evolutionary run can produce a number of different designs
with similar fitness values, but very different characteristics.

2004


* 179(<-397): Tolerance design optimization on cost-quality trade-off using the Shapley value method

Part tolerance design is important in the manufacturing process of
many complex products because it directly affects manufacturing cost
and product quality. It is significant to develop a reasonable
tolerance scheme considering the demands of cost and quality to reduce
the production risk and provide a guide for supplier
management. Traditionally, some kinds of cost objective functions or
variation propagation models are often applied in part tolerance
design. Moreover, designers usually solve the tolerance design problem
by constructing a single-objective model, dealing with several
single-objective problems, or establishing a comprehensive evaluating
function combining several optimization objectives with different
weights. These approaches may not adequately consider the
interdependent and the interactional relations of various demands and
balance them. This paper presents a kind of tolerance design approach
at the early design stage of automotive parts based on the Shapley
value method (SVM) of coalitional game theory considering the demands
of manufacturing cost and product quality. First the part tolerance
design problem is defined. The measuring data in regular production is
collected instead of working on specific objective functions or design
models. Then how the SVM is adopted to solve the tolerance design
problem is discussed. Lastly, a tolerance design example of a vehicle
front lamp demonstrates the application and the performance of the
proposed method. (C) 2011 The Society of Manufacturing
Engineers. Published by Elsevier Ltd. All rights reserved.

2010






* 211(<-324): Mobility Timing for Agent Communities, a Cue for Advanced Connectionist Systems

We introduce a wait-and-chase scheme that models the contact times
between moving agents within a connectionist construct. The idea that
elementary processors move within a network to get a proper position
is borne out both by biological neurons in the brain morphogenesis and
by agents within social networks. From the former, we take inspiration
to devise a medium-term project for new artificial neural network
training procedures where mobile neurons exchange data only when they
are close to one another in a proper space (are in contact). From the
latter, we accumulate mobility tracks experience. We focus on the
preliminary step of characterizing the elapsed time between neuron
contacts, which results from a spatial process fitting in the family
of random processes with memory, where chasing neurons are
stochastically driven by the goal of hitting target neurons. Thus, we
add an unprecedented mobility model to the literature in the field,
introducing a distribution law of the intercontact times that merges
features of both negative exponential and Pareto distribution laws. We
give a constructive description and implementation of our model, as
well as a short analytical form whose parameters are suitably
estimated in terms of confidence intervals from experimental
data. Numerical experiments show the model and related inference tools
to be sufficiently robust to cope with two main requisites for its
exploitation in a neural network: the nonindependence of the observed
intercontact times and the feasibility of the model inversion problem
to infer suitable mobility parameters.

2011