Abstract: This paper reviews the objectives, methods and results of previous studies on biodrying of solid waste in several countries. Biodrying of solid waste is a novel technology in developing countries such as in Malaysia where high moisture content in organic waste makes the segregation process for recycling purposes complicated and diminishes the calorific value for the use of fuel source. In addition, the high moisture content also encourages the breeding of vectors and disease-bearing animals. From the laboratory results, the average moisture content of organic waste, paper, plastics and metals are 58.17%, 37.93%, 29.79% and 1.03% respectively for UKM campus. Biodrying of solid waste is a simple method of waste treatment as well as a cost-efficient technology to dry the solid waste. The process depends on temperature monitoring and air flow control along with the natural biodegradable process of organic waste. This review shows that the biodrying of solid waste method has high potential in treatment and recycling of solid waste, be useful for biodrying study and implementation in Malaysia.
Abstract: In the past years, the world has witnessed significant work in the field of Manufacturing. Special efforts have been made in the implementation of new technologies, management and control systems, among many others which have all evolved the field. Closely following all this, due to the scope of new projects and the need of turning the existing flexible ideas into more autonomous and intelligent ones, i.e.: moving toward a more intelligent manufacturing, the present paper emerges with the main aim of contributing to the analysis and a few customization issues of a new iCIM 3000 system at the IPSAM. In this process, special emphasis in made on the material flow problem. For this, besides offering a description and analysis of the system and its main parts, also some tips on how to define other possible alternative material flow scenarios and a partial analysis of the combinatorial nature of the problem are offered as well. All this is done with the intentions of relating it with the use of simulation tools, for which these have been briefly addressed with a special focus on the Witness simulation package. For a better comprehension, the previous elements are supported by a few figures and expressions which would help obtaining necessary data. Such data and others will be used in the future, when simulating the scenarios in the search of the best material flow configurations.
Abstract: Design and modeling of nonlinear systems require the
knowledge of all inside acting parameters and effects. An empirical
alternative is to identify the system-s transfer function from input and
output data as a black box model. This paper presents a procedure
using least squares algorithm for the identification of a feed drive
system coefficients in time domain using a reduced model based on
windowed input and output data. The command and response of the
axis are first measured in the first 4 ms, and then least squares are
applied to predict the transfer function coefficients for this
displacement segment. From the identified coefficients, the next
command response segments are estimated. The obtained results
reveal a considerable potential of least squares method to identify the
system-s time-based coefficients and predict accurately the command
response as compared to measurements.
Abstract: Lately, significant work in the area of Intelligent
Manufacturing has become public and mainly applied within the
frame of industrial purposes. Special efforts have been made in the
implementation of new technologies, management and control
systems, among many others which have all evolved the field. Aware
of all this and due to the scope of new projects and the need of
turning the existing flexible ideas into more autonomous and
intelligent ones, i.e.: Intelligent Manufacturing, the present paper
emerges with the main aim of contributing to the design and analysis
of the material flow in either systems, cells or work stations under
this new “intelligent" denomination. For this, besides offering a
conceptual basis in some of the key points to be taken into account
and some general principles to consider in the design and analysis of
the material flow, also some tips on how to define other possible
alternative material flow scenarios and a classification of the states a
system, cell or workstation are offered as well. All this is done with
the intentions of relating it with the use of simulation tools, for which
these have been briefly addressed with a special focus on the Witness
simulation package. For a better comprehension, the previous
elements are supported by a detailed layout, other figures and a few
expressions which could help obtaining necessary data. Such data and
others will be used in the future, when simulating the scenarios in the
search of the best material flow configurations.
Abstract: Candida albicans ATCC 10231 had low endogenous activity of the alternative oxidase compared with that of C. albicans ATCC 10261. In C. albicans ATCC 10231 the endogenous activity declined as the cultures aged. Alternative oxidase activity could be induced in C. albicans ATCC 10231 by treatment with cyanide, but the induction of this activity required the presence of oxygen which could be replaced, at least in part, with high concentrations of potassium ferricyanide. We infer from this that the expression of the gene encoding the alternative oxidase is under the control of a redoxsensitive transcription factor.
Abstract: The study of a real function of two real variables can be supported by visualization using a Computer Algebra System (CAS). One type of constraints of the system is due to the algorithms implemented, yielding continuous approximations of the given function by interpolation. This often masks discontinuities of the function and can provide strange plots, not compatible with the mathematics. In recent years, point based geometry has gained increasing attention as an alternative surface representation, both for efficient rendering and for flexible geometry processing of complex surfaces. In this paper we present different artifacts created by mesh surfaces near discontinuities and propose a point based method that controls and reduces these artifacts. A least squares penalty method for an automatic generation of the mesh that controls the behavior of the chosen function is presented. The special feature of this method is the ability to improve the accuracy of the surface visualization near a set of interior points where the function may be discontinuous. The present method is formulated as a minimax problem and the non uniform mesh is generated using an iterative algorithm. Results show that for large poorly conditioned matrices, the new algorithm gives more accurate results than the classical preconditioned conjugate algorithm.
Abstract: Selection of the best possible set of suppliers has a
significant impact on the overall profitability and success of any
business. For this reason, it is usually necessary to optimize all
business processes and to make use of cost-effective alternatives for
additional savings. This paper proposes a new efficient context-aware
supplier selection model that takes into account possible changes of
the environment while significantly reducing selection costs. The
proposed model is based on data clustering techniques while
inspiring certain principles of online algorithms for an optimally
selection of suppliers. Unlike common selection models which re-run
the selection algorithm from the scratch-line for any decision-making
sub-period on the whole environment, our model considers the
changes only and superimposes it to the previously defined best set
of suppliers to obtain a new best set of suppliers. Therefore, any recomputation
of unchanged elements of the environment is avoided
and selection costs are consequently reduced significantly. A
numerical evaluation confirms applicability of this model and proves
that it is a more optimal solution compared with common static
selection models in this field.
Abstract: Predicting short term wind speed is essential in order
to prevent systems in-action from the effects of strong winds. It also
helps in using wind energy as an alternative source of energy, mainly
for Electrical power generation. Wind speed prediction has
applications in Military and civilian fields for air traffic control,
rocket launch, ship navigation etc. The wind speed in near future
depends on the values of other meteorological variables, such as
atmospheric pressure, moisture content, humidity, rainfall etc. The
values of these parameters are obtained from a nearest weather
station and are used to train various forms of neural networks. The
trained model of neural networks is validated using a similar set of
data. The model is then used to predict the wind speed, using the
same meteorological information. This paper reports an Artificial
Neural Network model for short term wind speed prediction, which
uses back propagation algorithm.
Abstract: Planning the transition period for the adoption of
alternative fuel-technology powertrains is a challenging task that
requires sophisticated analysis tools. In this study, a system dynamic
approach was applied to analyze the bi-directional interaction
between the development of the refueling station network and vehicle
sales. Besides, the developed model was used to estimate the
transition cost to reach a predefined target (share of alternative fuel
vehicles) in different scenarios. Several scenarios have been analyzed
to investigate the effectiveness and cost of incentives on the initial
price of vehicles, and on the evolution of fuel and refueling stations.
Obtained results show that a combined set of incentives will be more
effective than just a single specific type of incentives.
Abstract: In India, the quarrel between the budding human
populace and the planet-s unchanging supply of freshwater and
falling water tables has strained attention the reuse of gray water as
an alternative water resource in rural development. This paper
present the finest design of laboratory scale gray water treatment
plant, which is a combination of natural and physical operations such
as primary settling with cascaded water flow, aeration, agitation and
filtration, hence called as hybrid treatment process. The economical
performance of the plant for treatment of bathrooms, basins and
laundries gray water showed in terms of deduction competency of
water pollutants such as COD (83%), TDS (70%), TSS (83%), total
hardness (50%), oil and grease (97%), anions (46%) and cations
(49%). Hence, this technology could be a good alternative to treat
gray water in residential rural area.
Abstract: Rice husk is one of the alternative fuels for Thailand because of its high potential and environmental benefits. Nonetheless, the environmental profile of the electricity production from rice husk must be assessed to ensure reduced environmental damage. A 10 MW pilot plant using rice husk as feedstock is the study site. The environmental impacts from rice husk power plant are evaluated by using the Life Cycle Assessment (LCA) methodology. Energy, material and carbon balances have been determined for tracing the system flow. Carbon closure has been used for describing of the net amount of CO2 released from the system in relation to the amount being recycled between the power plant and the CO2 adsorbed by rice husk. The transportation of rice husk to the power plant has significant on global warming, but not on acidification and photo-oxidant formation. The results showed that the impact potentials from rice husk power plant are lesser than the conventional plants for most of the categories considered; except the photo-oxidant formation potential from CO. The high CO from rice husk power plant may be due to low boiler efficiency and high moisture content in rice husk. The performance of the study site can be enhanced by improving the combustion efficiency.
Abstract: Evolutionary Algorithms are population-based,
stochastic search techniques, widely used as efficient global
optimizers. However, many real life optimization problems often
require finding optimal solution to complex high dimensional,
multimodal problems involving computationally very expensive
fitness function evaluations. Use of evolutionary algorithms in such
problem domains is thus practically prohibitive. An attractive
alternative is to build meta models or use an approximation of the
actual fitness functions to be evaluated. These meta models are order
of magnitude cheaper to evaluate compared to the actual function
evaluation. Many regression and interpolation tools are available to
build such meta models. This paper briefly discusses the
architectures and use of such meta-modeling tools in an evolutionary
optimization context. We further present two evolutionary algorithm
frameworks which involve use of meta models for fitness function
evaluation. The first framework, namely the Dynamic Approximate
Fitness based Hybrid EA (DAFHEA) model [14] reduces
computation time by controlled use of meta-models (in this case
approximate model generated by Support Vector Machine
regression) to partially replace the actual function evaluation by
approximate function evaluation. However, the underlying
assumption in DAFHEA is that the training samples for the metamodel
are generated from a single uniform model. This does not take
into account uncertain scenarios involving noisy fitness functions.
The second model, DAFHEA-II, an enhanced version of the original
DAFHEA framework, incorporates a multiple-model based learning
approach for the support vector machine approximator to handle
noisy functions [15]. Empirical results obtained by evaluating the
frameworks using several benchmark functions demonstrate their
efficiency
Abstract: Heat powered solid sorption is a feasible alternative to
electrical vapor compression refrigeration systems. In this paper,
activated carbon (powder type Maxsorb and fiber type ACF-A10)-
CO2 based adsorption cooling cycles are studied using the pressuretemperature-
concentration (P-T-W) diagram. The specific cooling
effect (SCE) and the coefficient of performance (COP) of these two
cooling systems are simulated for the driving heat source
temperatures ranging from 30 ºC to 90 ºC in terms of different
cooling load temperatures with a cooling source temperature of 25
ºC. It is found from the present analysis that Maxsorb-CO2 couple
shows higher cooling capacity and COP. The maximum COPs of
Maxsorb-CO2 and ACF(A10)-CO2 based cooling systems are found
to be 0.15 and 0.083, respectively. The main innovative feature of
this cooling cycle is the ability to utilize low temperature waste heat
or solar energy using CO2 as the refrigerant, which is one of the best
alternative for applications where flammability and toxicity are not
allowed.
Abstract: In this research, an aerobic composting method is
studied to reuse organic waste from rubber factory waste as soil fertilizer and to study the effect of cellulolytic microbial activator
(CMA) as the activator in the rubber factory waste composting. The
performance of the composting process was monitored as a function
of carbon and organic matter decomposition rate, temperature and
moisture content. The results indicate that the rubber factory waste is best composted with water hyacinth and sludge than composted
alone. In addition, the CMA is more affective when mixed with the rubber factory waste, water hyacinth and sludge since a good fertilizer is achieved. When adding CMA into the rubber factory
waste composted alone, the finished product does not achieve a
standard of fertilizer, especially the C/N ratio.
Finally, the finished products of composting rubber factory waste and water hyacinth and sludge (both CMA and without CMA), can be an environmental friendly alternative to solve the disposal problems of rubber factory waste. Since the C/N ratio, pH, moisture
content, temperature, and nutrients of the finished products are acceptable for agriculture use.
Abstract: E-Appointment Scheduling (EAS) has been developed
to handle appointment for UMP students, lecturers in Faculty of
Computer Systems & Software Engineering (FCSSE) and Student
Medical Center. The schedules are based on the timetable and
university activities. Constraints Logic Programming (CLP) has been
implemented to solve the scheduling problems by giving
recommendation to the users in part of determining any available
slots from the lecturers and doctors- timetable. By using this system,
we can avoid wasting time and cost because this application will set
an appointment by auto-generated. In addition, this system can be an
alternative to the lecturers and doctors to make decisions whether to
approve or reject the appointments.
Abstract: This paper proposes a technique to block adult images displayed in websites. The filter is designed so as to perform even in exceptional cases such as, where face detection is not possible or improper face visibility. This is achieved by using an alternative phase to extract the MFC (Most Frequent Color) from the Human Body regions estimated using a biometric of anthropometric distances between fixed rigidly connected body locations. The logical results generated can be protected from overriding by a firewall or intrusion, by encrypting the result in a SSH data packet.
Abstract: This paper presents a new heuristic algorithm useful
for long-term planning of survivable WDM networks. A multi-period
model is formulated that combines network topology design and
capacity expansion. The ability to determine network expansion
schedules of this type becomes increasingly important to the
telecommunications industry and to its customers. The solution
technique consists of a Genetic Algorithm that allows generating
several network alternatives for each time period simultaneously and
shortest-path techniques to deduce from these alternatives a least-cost
network expansion plan over all time periods. The multi-period
planning approach is illustrated on a realistic network example.
Extensive simulations on a wide range of problem instances are
carried out to assess the cost savings that can be expected by
choosing a multi-period planning approach instead of an iterative
network expansion design method.
Abstract: The paper presents a compressor anti-surge control
system, that results in maximizing compressor throughput with
pressure standard deviation reduction, increased safety margin
between design point and surge limit line and avoiding possible
machine surge. Alternative control strategies are presented.
Abstract: Neural networks offer an alternative approach both
for identification and control of nonlinear processes in process
engineering. The lack of software tools for the design of controllers
based on neural network models is particularly pronounced in this
field. SIMULINK is properly a widely used graphical code
development environment which allows system-level developers to
perform rapid prototyping and testing. Such graphical based
programming environment involves block-based code development
and offers a more intuitive approach to modeling and control task in
a great variety of engineering disciplines. In this paper a
SIMULINK based Neural Tool has been developed for analysis and
design of multivariable neural based control systems. This tool has
been applied to the control of a high purity distillation column
including non linear hydrodynamic effects. The proposed control
scheme offers an optimal response for both theoretical and practical
challenges posed in process control task, in particular when both,
the quality improvement of distillation products and the operation
efficiency in economical terms are considered.
Abstract: Four design alternatives for lateral force-resisting
systems of tall buildings in Dubai, UAE are presented. Quantitative
comparisons between the different designs are also made. This paper
is intended to provide different feasible lateral systems to be used in
Dubai in light of the available seismic hazard studies of the UAE.
The different lateral systems are chosen in conformance with the
International Building Code (IBC). Moreover, the expected behavior
of each system is highlighted and light is shed on some of the cost
implications associated with lateral system selection.