Abstract: As the trend of manufacturing is being dominated depending on services, products and processes are more and more related with sophisticated services. Thus, this research starts with the discussion about integration of the product, process, and service in the innovation process. In particular, this paper sets out some foundations for a theory of service innovation in the field of manufacturing, and proposes the dynamic model of service innovation related to product and process. Two dynamic models of service innovation are suggested to investigate major tendencies and dynamic variations during the innovation cycle: co-innovation and sequential innovation. To structure dynamic models of product, process, and service innovation, the innovation stages in which two models are mainly achieved are identified. The research would encourage manufacturers to formulate strategy and planning for service development with product and process.
Abstract: Bone remodeling occurs by the balanced action of
bone resorbing osteoclasts (OC) and bone-building osteoblasts.
Increased bone resorption by excessive OC activity contributes
to malignant and non-malignant diseases including osteoporosis.
To study OC differentiation and function, OC formed in
in vitro cultures are currently counted manually, a tedious
procedure which is prone to inter-observer differences. Aiming
for an automated OC-quantification system, classification of
OC and precursor cells was done on fluorescence microscope
images based on the distinct appearance of fluorescent nuclei.
Following ellipse fitting to nuclei, a combination of eight
features enabled clustering of OC and precursor cell nuclei.
After evaluating different machine-learning techniques, LOGREG
achieved 74% correctly classified OC and precursor cell
nuclei, outperforming human experts (best expert: 55%). In
combination with the automated detection of total cell areas,
this system allows to measure various cell parameters and most
importantly to quantify proteins involved in osteoclastogenesis.
Abstract: In this paper, we propose a novel improvement for the generalized Lloyd Algorithm (GLA). Our algorithm makes use of an M-tree index built on the codebook which makes it possible to reduce the number of distance computations when the nearest code words are searched. Our method does not impose the use of any specific distance function, but works with any metric distance, making it more general than many other fast GLA variants. Finally, we present the positive results of our performance experiments.
Abstract: A new digital transceiver circuit for asynchronous frame detection is proposed where both the transmitter and receiver contain all digital components, thereby avoiding possible use of conventional devices like monostable multivibrators with unstable external components such as resistances and capacitances. The proposed receiver circuit, in particular, uses a combinational logic block yielding an output which changes its state as soon as the start bit of a new frame is detected. This, in turn, helps in generating an efficient receiver sampling clock. A data latching circuit is also used in the receiver to latch the recovered data bits in any new frame. The proposed receiver structure is also extended from 4- bit information to any general n data bits within a frame with a common expression for the output of the combinational logic block. Performance of the proposed hardware design is evaluated in terms of time delay, reliability and robustness in comparison with the standard schemes using monostable multivibrators. It is observed from hardware implementation that the proposed circuit achieves almost 33 percent speed up over any conventional circuit.
Abstract: Subdivision is a method to create a smooth surface from a coarse mesh by subdividing the entire mesh. The conventional ways to compute and render surfaces are inconvenient both in terms of memory and computational time as the number of meshes will increase exponentially. An adaptive subdivision is the way to reduce the computational time and memory by subdividing only certain selected areas. In this paper, a new adaptive subdivision method for triangle meshes is introduced. This method defines a new adaptive subdivision rules by considering the properties of each triangle's neighbors and is embedded in a traditional Loop's subdivision. It prevents some undesirable side effects that appear in the conventional adaptive ways. Models that were subdivided by our method are compared with other adaptive subdivision methods
Abstract: This paper presents a unified approach based graph
theory and system theory postulates for the modeling and analysis
of Simple open cycle Gas turbine system. In the present paper, the
simple open cycle gas turbine system has been modeled up to its subsystem
level and system variables have been identified to develop the
process subgraphs. The theorems and algorithms of the graph theory
have been used to represent behavioural properties of the system like
rate of heat and work transfers rates, pressure drops and temperature
drops in the involved processes of the system. The processes have
been represented as edges of the process subgraphs and their limits
as the vertices of the process subgraphs. The system across variables
and through variables has been used to develop terminal equations of
the process subgraphs of the system. The set of equations developed
for vertices and edges of network graph are used to solve the system
for its process variables.
Abstract: In this paper, a new technique for fast painting with
different colors is presented. The idea of painting relies on applying
masks with different colors to the background. Fast painting is
achieved by applying these masks in the frequency domain instead of
spatial (time) domain. New colors can be generated automatically as a
result from the cross correlation operation. This idea was applied
successfully for faster specific data (face, object, pattern, and code)
detection using neural algorithms. Here, instead of performing cross
correlation between the input input data (e.g., image, or a stream of
sequential data) and the weights of neural networks, the cross
correlation is performed between the colored masks and the
background. Furthermore, this approach is developed to reduce the
computation steps required by the painting operation. The principle of
divide and conquer strategy is applied through background
decomposition. Each background is divided into small in size subbackgrounds
and then each sub-background is processed separately by
using a single faster painting algorithm. Moreover, the fastest painting
is achieved by using parallel processing techniques to paint the
resulting sub-backgrounds using the same number of faster painting
algorithms. In contrast to using only faster painting algorithm, the
speed up ratio is increased with the size of the background when using
faster painting algorithm and background decomposition. Simulation
results show that painting in the frequency domain is faster than that in
the spatial domain.
Abstract: The aim of this work was to investigate the potential of soil microorganisms and the burhead plant, as well as the combination of soil microorganisms and plants to remediate monoethylene glycol (MEG), diethylene glycol (DEG), and triethylene glycol (TEG) in synthetic wastewater. The result showed that a system containing both burhead plant and soil microorganisms had the highest efficiency in EGs removal. Around 100% of MEG and DEG and 85% of TEG were removed within 15 days of the experiments. However, the burhead plant had higher removal efficiency than soil microorganisms for MEG and DEG but the same for TEG in the study systems. The removal rate of EGs in the study system related to the molecular weight of the compounds and MEG, the smallest glycol, was removed faster than DEG and TEG by both the burhead plant and soil microorganisms in the study system.
Abstract: A satellite is being integrated and tested by BISEE (Beijing Institute of Spacecraft Environment Engineering). This paper describes the infrared lamp array simulation technology used for satellite thermal balance and thermal vacuum test. These tests were performed in KM6 space environmental simulator in Beijing, China. New software and hardware developed by BISEE, along with enhanced heat flux uniformity, provided for well accomplished thermal balance and thermal vacuum tests. The flux uniformity of lamp array was satisfied with test requirement. Monitored background radiometer offered reliable heat flux measurements with remarkable repeatability. Simulation software supplied accurate thermal flux distribution predictions.
Abstract: Distributed Generation (DG) in the form of renewable
power generation systems is currently preferred for clean power
generation. It has a significant impact on the distribution systems.
This impact may be either positively or negatively depending on the
distribution system, distributed generator and load characteristics. In
this works, an overview of DG is briefly introduced. The technology
of DG is also listed while the technical impacts and economic
impacts are explained.
Abstract: The resident registration number was adopted for the purposes of enhanced services for resident convenience and effective performance of governmental administrative affairs. However, it has been used for identification purposes customarily and irrationally in line with the development and spread of the Internet. In response to the growing concern about the leakage of collected RRNs and possible abuses of stolen RRNs, e.g. identity theft, for crimes, the Korean Communications Commission began to take legal/regulatory actions in 2011 to minimize the online collection and use of resident registration numbers. As the use of the RRN was limited after the revision of the Act on Promotion of Information and Communications Network Utilization and Information Protection, etc., online business providers were required to have alternatives to the RRN for the purpose of identifying the user's identity and age, in compliance with the law, and settling disputes with customers. This paper presents means of verifying the personal identity by taking advantage of the commonly used infrastructure and simply replacing personal information entered and stored, without requiring users to enter their RRNs.
Abstract: Modern organizations operate under the pressure of
dynamic and often unpredictable changes, both in external and
internal environment. Market success, in this context, requires a
particular competence in the form of flexibility, interpreted here both
on the level of individuals and on the level of organization. This
paper addresses the changes taking place in the sphere of
employment, as observed in economic entities operating on Polish
market. Based on own empirical studies, the authors focus on the
progressing trend of ‘flexibilization’ of employment, particularly in
the context of transformations in organizational structure, designed to
facilitate the transition into management by projects and
differentiation of labor forms.
Abstract: Artificial Neural Network (ANN) has been
extensively used for classification of heart sounds for its
discriminative training ability and easy implementation. However, it
suffers from overparameterization if the number of nodes is not
chosen properly. In such cases, when the dataset has redundancy
within it, ANN is trained along with this redundant information that
results in poor validation. Also a larger network means more
computational expense resulting more hardware and time related
cost. Therefore, an optimum design of neural network is needed
towards real-time detection of pathological patterns, if any from heart
sound signal. The aims of this work are to (i) select a set of input
features that are effective for identification of heart sound signals and
(ii) make certain optimum selection of nodes in the hidden layer for a
more effective ANN structure. Here, we present an optimization
technique that involves Singular Value Decomposition (SVD) and
QR factorization with column pivoting (QRcp) methodology to
optimize empirically chosen over-parameterized ANN structure.
Input nodes present in ANN structure is optimized by SVD followed
by QRcp while only SVD is required to prune undesirable hidden
nodes. The result is presented for classifying 12 common
pathological cases and normal heart sound.
Abstract: A finite element analysis (FEA) computer software HyperWorks is utilized in re-designing an automotive component to reduce its mass. Reduction of components mass contributes towards environmental sustainability by saving world-s valuable metal resources and by reducing carbon emission through improved overall vehicle fuel efficiency. A shape optimization analysis was performed on a rear spindle component. Pre-processing and solving procedures were performed using HyperMesh and RADIOSS respectively. Shape variables were defined using HyperMorph. Then optimization solver OptiStruct was utilized with fatigue life set as a design constraint. Since Stress-Number of Cycle (S-N) theory deals with uni-axial stress, the Signed von Misses stress on the component was used for looking up damage on S-N curve, and Gerber criterion for mean stress corrections. The optimization analysis resulted in mass reduction of 24% of the original mass. The study proved that the adopted approach has high potential use for environmental sustainability.
Abstract: A wireless Ad-hoc network consists of wireless nodes
communicating without the need for a centralized administration, in
which all nodes potentially contribute to the routing process.In this
paper, we report the simulation results of four different scenarios for
wireless ad hoc networks having thirty nodes. The performances of
proposed networks are evaluated in terms of number of hops per
route, delay and throughput with the help of OPNET simulator.
Channel speed 1 Mbps and simulation time 600 sim-seconds were
taken for all scenarios. For the above analysis DSR routing protocols
has been used. The throughput obtained from the above analysis
(four scenario) are compared as shown in Figure 3. The average
media access delay at node_20 for two routes and at node_20 for four
different scenario are compared as shown in Figures 4 and 5. It is
observed that the throughput will degrade when it will follow
different hops for same source to destination (i.e. it has dropped from
1.55 Mbps to 1.43 Mbps which is around 9.7%, and then dropped to
0.48Mbps which is around 35%).
Abstract: In this study, a software has been developed to predict
the optimum conditions for drying of cotton based yarn bobbins in a
hot air dryer. For this purpose, firstly, a suitable drying model has
been specified using experimental drying behavior for different
values of drying parameters. Drying parameters in the experiments
were drying temperature, drying pressure, and volumetric flow rate of
drying air. After obtaining a suitable drying model, additional curve
fittings have been performed to obtain equations for drying time and
energy consumption taking into account the effects of drying
parameters. Then, a software has been developed using Visual Basic
programming language to predict the optimum drying conditions for
drying time and energy consumption.
Abstract: In gas lifted oil fields, the lift gas should be distributed optimally among the wells which share gas from a common source to maximize total oil production. One of the objectives of the paper is to show that a linear MPC consisting of a control objective and an economic objective can be used both as an optimizer and a controller for gas lifted systems. The MPC is based on linearized model of the oil field developed from first principles modeling. Simulation results show that the total oil production is increased by 3.4%. Difficulties in accurately measuring the bottom hole pressure using sensors in harsh operating conditions can be resolved by using an Unscented Kalman Filter (UKF) for estimation. In oil fields where input disturbance (total supply of gas) is not measured, UKF can also be used for disturbance estimation. Increased total oil production due to optimization leads to increased profit.
Abstract: Integration of system process information obtained
through an image processing system with an evolving knowledge
database to improve the accuracy and predictability of wear particle
analysis is the main focus of the paper. The objective is to automate
intelligently the analysis process of wear particle using classification
via self organizing maps. This is achieved using relationship
measurements among corresponding attributes of various
measurements for wear particle. Finally, visualization technique is
proposed that helps the viewer in understanding and utilizing these
relationships that enable accurate diagnostics.
Abstract: Integration of system process information obtained
through an image processing system with an evolving knowledge
database to improve the accuracy and predictability of wear debris
analysis is the main focus of the paper. The objective is to automate
intelligently the analysis process of wear particle using classification
via self-organizing maps. This is achieved using relationship
measurements among corresponding attributes of various
measurements for wear debris. Finally, visualization technique is
proposed that helps the viewer in understanding and utilizing these
relationships that enable accurate diagnostics.
Abstract: Glaucoma diagnosis involves extracting three features
of the fundus image; optic cup, optic disc and vernacular. Present
manual diagnosis is expensive, tedious and time consuming. A
number of researches have been conducted to automate this process.
However, the variability between the diagnostic capability of an
automated system and ophthalmologist has yet to be established. This
paper discusses the efficiency and variability between
ophthalmologist opinion and digital technique; threshold. The
efficiency and variability measures are based on image quality
grading; poor, satisfactory or good. The images are separated into
four channels; gray, red, green and blue. A scientific investigation
was conducted on three ophthalmologists who graded the images
based on the image quality. The images are threshold using multithresholding
and graded as done by the ophthalmologist. A
comparison of grade from the ophthalmologist and threshold is made.
The results show there is a small variability between result of
ophthalmologists and digital threshold.