Abstract: Metallic micro parts are playing an important role in micro-fabrication industry. Recently, we have demonstrated a new deformation mechanism for micro-formability of polycrystalline materials. Different depressed micro-features smaller than the grain size have been successfully fabricated on 6061 aluminum alloy (AA6061) substrates with good fidelity. To further verify this proposed deformation mechanism that grain size is not a limiting factor, we demonstrate here that in addition of depressed features, protruded micro-features on a polycrystalline substrate can similarly be fabricated.
Abstract: Nowadays, under developed countries for progress in
science and technology and decreasing the technologic gap with
developed countries, increasing the capacities and technology
transfer from developed countries. To remain competitive, industry is
continually searching for new methods to evolve their products.
Business model is one of the latest buzzwords in the Internet and
electronic business world. To be successful, organizations must look
into the needs and wants of their customers. This research attempts to
identify a specific feature of the company with a strong competitive
advantage by analyzing the cause of Customer satisfaction. Due to
the rapid development of knowledge and information technology,
business environments have become much more complicated.
Information technology can help a firm aiming to gain a competitive
advantage. This study explores the role and effect of Information
Communication Technology in Business Models and Customer
satisfaction on firms and also relationships between ICTs and
Outsourcing strategic.
Abstract: Experiments were conducted to characterize fire
properties of wood exposed to the certain external heat flux and
under variety of wood moisture content. Six kinds of Indonesian
wood: keruing, sono, cemara, kamper, pinus, and mahoni were
exposed to radiant heat from a conical heater, result in appearance of
a stable flame on the wood surface caused by spontaneous ignition. A
thermocouple K-type was used to measure the wood surface
temperature. Temperature histories were recorded throughout each
experiment at 1 s intervals using a TC-08. Data of first ignition time
and temperature, end ignition time and temperature, and charring rate
have been successfully collected. It was found that the ignition
temperature and charring rate depend on moisture content of wood.
Abstract: The greenhouse effect and limitations on carbon
dioxide emissions concern engine maker and the future of the
internal combustion engines should go toward substantially and
improved thermal efficiency engine. Homogeneous charge
compression ignition (HCCI) is an alternative high-efficiency
technology for combustion engines to reduce exhaust emissions and
fuel consumption. However, there are still tough challenges in the
successful operation of HCCI engines, such as controlling the
combustion phasing, extending the operating range, and high
unburned hydrocarbon and CO emissions. HCCI and the exploitation
of ethanol as an alternative fuel is one way to explore new frontiers
of internal combustion engines with an eye towards maintaining its
sustainability. This study was done to extend database knowledge
about HCCI with ethanol a fuel.
Abstract: This work presents a multiple objective linear programming (MOLP) model based on the desirability function approach for solving the aggregate production planning (APP) decision problem upon Masud and Hwang-s model. The proposed model minimises total production costs, carrying or backordering costs and rates of change in labor levels. An industrial case demonstrates the feasibility of applying the proposed model to the APP problems with three scenarios of inventory levels. The proposed model yields an efficient compromise solution and the overall levels of DM satisfaction with the multiple combined response levels. There has been a trend to solve complex planning problems using various metaheuristics. Therefore, in this paper, the multi-objective APP problem is solved by hybrid metaheuristics of the hunting search (HuSIHSA) and firefly (FAIHSA) mechanisms on the improved harmony search algorithm. Results obtained from the solution of are then compared. It is observed that the FAIHSA can be used as a successful alternative solution mechanism for solving APP problems over three scenarios. Furthermore, the FAIHSA provides a systematic framework for facilitating the decision-making process, enabling a decision maker interactively to modify the desirability function approach and related model parameters until a good optimal solution is obtained with proper selection of control parameters when compared.
Abstract: The design problem of Infinite Impulse Response (IIR)
digital filters is usually expressed as the minimization problem of
the complex magnitude error that includes both the magnitude and
phase information. However, the group delay of the filter obtained
by solving such design problem may be far from the desired group
delay. In this paper, we propose a design method of stable IIR digital
filters with prespecified maximum group delay errors. In the proposed
method, the approximation problems of the magnitude-phase and
group delay are separately defined, and these two approximation
problems are alternately solved using successive projections. As a
result, the proposed method can design the IIR filters that satisfy the
prespecified allowable errors for not only the complex magnitude but
also the group delay by alternately executing the coefficient update
for the magnitude-phase and the group delay approximation. The
usefulness of the proposed method is verified through some examples.
Abstract: Since the 1980s, banks and financial service institutions have been running in an endless race of innovation to cope with the advancing technology, the fierce competition, and the more sophisticated and demanding customers. In order to guide their innovation efforts, several researches were conducted to identify the success and failure factors of new financial services. These mainly included organizational factors, marketplace factors and new service development process factors. They almost all emphasized the importance of customer and market orientation as a response to the highly perceptual and intangible characteristics of financial services. However, they deemphasized the critical characteristics of high involvement of risk and close correlation with the economic conditions, a factor that heavily contributed to the Global financial Crisis of 2008. This paper reviews the success and failure factors of new financial services. It then adds new perspectives emerging from the analysis of the role of innovation in the global financial crisis.
Abstract: Herein, we report the different types of surface morphology due to the interaction between the pure protein Insulin (INS) and catanionic surfactant mixture of Sodium Dodecyl Sulfate (SDS) and Cetyl Trimethyl Ammonium Bromide (CTAB) at air/water interface obtained by the Langmuir-Blodgett (LB) technique. We characterized the aggregations by Scanning Electron Microscopy (SEM), Atomic Force Microscopy (AFM) and Fourier transform infrared spectroscopy (FTIR) in LB films. We found that the INS adsorption increased in presence of catanionic surfactant at air/water interface. The presence of small amount of surfactant induces two-stage growth kinetics due to the pure protein absorption and protein-catanionic surface micelle interaction. The protein remains in native state in presence of small amount of surfactant mixture. Smaller amount of surfactant mixture with INS is producing surface micelle type structure. This may be considered for drug delivery system. On the other hand, INS becomes unfolded and fibrillated in presence of higher amount of surfactant mixture. In both the cases, the protein was successfully immobilized on a glass substrate by the LB technique. These results may find applications in the fundamental science of the physical chemistry of surfactant systems, as well as in the preparation of drug-delivery system.
Abstract: Efficient preprocessing is very essential for automatic
recognition of handwritten documents. In this paper, techniques on
segmenting words in handwritten Arabic text are presented. Firstly,
connected components (ccs) are extracted, and distances among
different components are analyzed. The statistical distribution of this
distance is then obtained to determine an optimal threshold for words
segmentation. Meanwhile, an improved projection based method is
also employed for baseline detection. The proposed method has been
successfully tested on IFN/ENIT database consisting of 26459
Arabic words handwritten by 411 different writers, and the results
were promising and very encouraging in more accurate detection of
the baseline and segmentation of words for further recognition.
Abstract: This paper presents a method to support dynamic
packing in cases when no collision-free path can be found. The
method, which is primarily based on path planning and shrinking of
geometries, suggests a minimal geometry design change that results
in a collision-free assembly path. A supplementing approach to
optimize geometry design change with respect to redesign cost is
described. Supporting this dynamic packing method, a new method
to shrink geometry based on vertex translation, interweaved with
retriangulation, is suggested. The shrinking method requires neither
tetrahedralization nor calculation of medial axis and it preserves the
topology of the geometry, i.e. holes are neither lost nor introduced.
The proposed methods are successfully applied on industrial
geometries.
Abstract: An implant elicits a biological response in the
surrounding tissue which determines the acceptance and long-term
function of the implant. Dental implants have become one of the
main therapy methods in clinic after teeth lose. A successful implant
is in contact with bone and soft tissue represent by fibroblasts. In our
study we focused on the interaction between six different chemically
and physically modified titanium implants (Tis-MALP, Tis-O, Tis-
OA, Tis-OPAAE, Tis-OZ, Tis-OPAE) with alveolar fibroblasts as
well as with five type of microorganisms (S. epidermis, S.mutans, S.
gordonii, S. intermedius, C.albicans). The analysis of microorganism
adhesion was determined by CFU (colony forming unite) and biofilm
formation. The presence of α3β1 and vinculin expression on alveolar
fibroblasts was demonstrated using phospho specific cell based
ELISA (PACE). Alveolar fibroblasts have the highest expression of
these proteins on Tis-OPAAE and Tis-OPAE. It corresponds with
results from bacterial adhesion and biofilm formation and it was
related to the lowest production of collagen I by alveolar fibroblasts
on Tis-OPAAE titanium disc.
Abstract: The paper investigates the potential of support vector
machines and Gaussian process based regression approaches to
model the oxygen–transfer capacity from experimental data of
multiple plunging jets oxygenation systems. The results suggest the
utility of both the modeling techniques in the prediction of the
overall volumetric oxygen transfer coefficient (KLa) from operational
parameters of multiple plunging jets oxygenation system. The
correlation coefficient root mean square error and coefficient of
determination values of 0.971, 0.002 and 0.945 respectively were
achieved by support vector machine in comparison to values of
0.960, 0.002 and 0.920 respectively achieved by Gaussian process
regression. Further, the performances of both these regression
approaches in predicting the overall volumetric oxygen transfer
coefficient was compared with the empirical relationship for multiple
plunging jets. A comparison of results suggests that support vector
machines approach works well in comparison to both empirical
relationship and Gaussian process approaches, and could successfully
be employed in modeling oxygen-transfer.
Abstract: A framework to estimate the state of dynamically
varying environment where data are generated from heterogeneous
sources possessing partial knowledge about the environment is presented.
This is entirely derived within Dempster-Shafer and Evidence
Filtering frameworks. The belief about the current state is expressed
as belief and plausibility functions. An addition to Single Input
Single Output Evidence Filter, Multiple Input Single Output Evidence
Filtering approach is introduced. Variety of applications such as
situational estimation of an emergency environment can be developed
within the framework successfully. Fire propagation scenario is used
to justify the proposed framework, simulation results are presented.
Abstract: The present paper was concerned primarily with the
analysis, simulation of the air flow and thermal patterns in a lecture
room. The paper is devoted to numerically investigate the influence
of location and number of ventilation and air conditioning supply and
extracts openings on air flow properties in a lecture room. The work
focuses on air flow patterns, thermal behaviour in lecture room where
large number of students. The effectiveness of an air flow system is
commonly assessed by the successful removal of sensible and latent
loads from occupants with additional of attaining air pollutant at a
prescribed level to attain the human thermal comfort conditions and
to improve the indoor air quality; this is the main target during the
present paper. The study is carried out using computational fluid
dynamics (CFD) simulation techniques as embedded in the
commercially available CFD code (FLUENT 6.2). The CFD
modelling techniques solved the continuity, momentum and energy
conservation equations in addition to standard k – ε model equations
for turbulence closure.
Throughout the investigations, numerical validation is carried out by
way of comparisons of numerical and experimental results. Good
agreement is found among both predictions.
Abstract: Sparse representation which can represent high dimensional
data effectively has been successfully used in computer vision
and pattern recognition problems. However, it doesn-t consider the
label information of data samples. To overcome this limitation,
we develop a novel dimensionality reduction algorithm namely
dscriminatively regularized sparse subspace learning(DR-SSL) in this
paper. The proposed DR-SSL algorithm can not only make use of
the sparse representation to model the data, but also can effective
employ the label information to guide the procedure of dimensionality
reduction. In addition,the presented algorithm can effectively deal
with the out-of-sample problem.The experiments on gene-expression
data sets show that the proposed algorithm is an effective tool for
dimensionality reduction and gene-expression data classification.
Abstract: Intellectual capital measurement is a central aspect of knowledge management. The measurement and the evaluation of intangible assets play a key role in allowing an effective management of these assets as sources of competitiveness. For these reasons, managers and practitioners need conceptual and analytical tools taking into account the unique characteristics and economic significance of Intellectual Capital. Following this lead, we propose an efficiency and productivity analysis of Intellectual Capital, as a determinant factor of the company competitive advantage. The analysis is carried out by means of Data Envelopment Analysis (DEA) and Malmquist Productivity Index (MPI). These techniques identify Bests Practice companies that have accomplished competitive advantage implementing successful strategies of Intellectual Capital management, and offer to inefficient companies development paths by means of benchmarking. The proposed methodology is employed on the Biotechnology industry in the period 2007-2010.
Abstract: The success of an e-learning system is highly
dependent on the quality of its educational content and how effective,
complete, and simple the design tool can be for teachers. Educational
modeling languages (EMLs) are proposed as design languages
intended to teachers for modeling diverse teaching-learning
experiences, independently of the pedagogical approach and in
different contexts. However, most existing EMLs are criticized for
being too abstract and too complex to be understood and manipulated
by teachers. In this paper, we present a visual EML that simplifies the
process of designing learning scenarios for teachers with no
programming background. Based on the conceptual framework of the
activity theory, our resulting visual EML focuses on using Domainspecific
modeling techniques to provide a pedagogical level of
abstraction in the design process.
Abstract: The present work encounters the solution of the defect identification problem with the use of an evolutionary algorithm combined with a simplex method. In more details, a Matlab implementation of Genetic Algorithms is combined with a Simplex method in order to lead to the successful identification of the defect. The influence of the location and the orientation of the depressed ellipsoidal flaw was investigated as well as the use of different amount of static data in the cost function. The results were evaluated according to the ability of the simplex method to locate the global optimum in each test case. In this way, a clear impression regarding the performance of the novel combination of the optimization algorithms, and the influence of the geometrical parameters of the flaw in defect identification problems was obtained.
Abstract: In rapidly changing market environment, firms are investing a lot of time and resources into new product development (NPD) projects to make profit and to obtain competitive advantage. However, failure rate of NPD projects is becoming high due to various internal and external risks which hinder successful NPD projects. To reduce the failure rate, it is critical that risks have to be managed effectively and efficiently through good strategy, and treated by optimal responses to minimize risk cost. Four strategies are adopted to handle the risks in this study. The optimal responses are characterized by high reduction of risk costs with high efficiency. This study suggests a framework to decide the optimal responses considering the core risks, risk costs, response efficiency and response costs for successful NPD projects. Both binary particles warm optimization (BPSO) and multi-objective particle swarm optimization (MOPSO) methods are mainly used in the framework. Although several limitations exist in use for real industries, the frame work shows good strength for handling the risks with highly scientific ways through an example.
Abstract: Automatic face detection is a complex problem in
image processing. Many methods exist to solve this problem such as
template matching, Fisher Linear Discriminate, Neural Networks,
SVM, and MRC. Success has been achieved with each method to
varying degrees and complexities. In proposed algorithm we used
upright, frontal faces for single gray scale images with decent
resolution and under good lighting condition. In the field of face
recognition technique the single face is matched with single face
from the training dataset. The author proposed a neural network
based face detection algorithm from the photographs as well as if any
test data appears it check from the online scanned training dataset.
Experimental result shows that the algorithm detected up to 95%
accuracy for any image.