Abstract: Ever since industrial revolution began, our ecosystem
has changed. And indeed, the negatives outweigh the positives.
Industrial waste usually released into all kinds of body of water, such
as river or sea. Tempeh waste is one example of waste that carries
many hazardous and unwanted substances that will affect the
surrounding environment. Tempeh is a popular fermented food in
Asia which is rich in nutrients and active substances. Tempeh liquid
waste- in particular- can cause an air pollution, and if penetrates
through the soil, it will contaminates ground-water, making it
unavailable for the water to be consumed. Moreover, bacteria will
thrive within the polluted water, which often responsible for causing
many kinds of diseases. The treatment used for this chemical waste is
biological treatment such as constructed wetland and activated
sludge. These kinds of treatment are able to reduce both physical and
chemical parameters altogether such as temperature, TSS, pH, BOD,
COD, NH3-N, NO3-N, and PO4-P. These treatments are implemented
before the waste is released into the water. The result is a
comparation between constructed wetland and activated sludge,
along with determining which method is better suited to reduce the
physical and chemical subtances of the waste.
Abstract: Program slicing is the task of finding all statements in
a program that directly or indirectly influence the value of a variable
occurrence. The set of statements that can affect the value of a
variable at some point in a program is called a program backward
slice. In several software engineering applications, such as program
debugging and measuring program cohesion and parallelism, several
slices are computed at different program points. The existing
algorithms for computing program slices are introduced to compute a
slice at a program point. In these algorithms, the program, or the
model that represents the program, is traversed completely or
partially once. To compute more than one slice, the same algorithm
is applied for every point of interest in the program. Thus, the same
program, or program representation, is traversed several times.
In this paper, an algorithm is introduced to compute all forward
static slices of a computer program by traversing the program
representation graph once. Therefore, the introduced algorithm is
useful for software engineering applications that require computing
program slices at different points of a program. The program
representation graph used in this paper is called Program Dependence
Graph (PDG).
Abstract: In this study, an inland metropolitan area, Gwangju, in Korea was selected to assess the amplification potential of earthquake motion and provide the information for regional seismic countermeasure. A geographic information system-based expert system was implemented for reliably predicting the spatial geotechnical layers in the entire region of interesting by building a geo-knowledge database. Particularly, the database consists of the existing boring data gathered from the prior geotechnical projects and the surface geo-knowledge data acquired from the site visit. For practical application of the geo-knowledge database to estimate the earthquake hazard potential related to site amplification effects at the study area, seismic zoning maps on geotechnical parameters, such as the bedrock depth and the site period, were created within GIS framework. In addition, seismic zonation of site classification was also performed to determine the site amplification coefficients for seismic design at any site in the study area. KeywordsEarthquake hazard, geo-knowledge, geographic information system, seismic zonation, site period.
Abstract: Problem-based learning (PBL) is one of the student
centered approaches and has been considered by a number of higher
educational institutions in many parts of the world as a method of
delivery. This paper presents a creative thinking approach for
implementing Problem-based Learning in Mechanics of Structure
within a Malaysian Polytechnics environment. In the learning
process, students learn how to analyze the problem given among the
students and sharing classroom knowledge into practice. Further,
through this course-s emphasis on problem-based learning, students
acquire creative thinking skills and professional skills as they tackle
complex, interdisciplinary and real-situation problems. Once the
creative ideas are generated, there are useful additional techniques
for tender ideas that will grow into a productive concept or solution.
The combination of creative skills and technical abilities will enable
the students to be ready to “hit-the-ground-running" and produce in
industry when they graduate.
Abstract: This paper deals with modeling and parameter
identification of nonlinear systems described by Hammerstein model
having Piecewise nonlinear characteristics such as Dead-zone
nonlinearity characteristic. The simultaneous use of both an easy
decomposition technique and the triangular basis functions leads to a
particular form of Hammerstein model. The approximation by using
Triangular basis functions for the description of the static nonlinear
block conducts to a linear regressor model, so that least squares
techniques can be used for the parameter estimation. Singular Values
Decomposition (SVD) technique has been applied to separate the
coupled parameters. The proposed approach has been efficiently
tested on academic examples of simulation.
Abstract: In any trust model, the two information sources that a peer relies on to predict trustworthiness of another peer are direct experience as well as reputation. These two vital components evolve over time. Trust evolution is an important issue, where the objective is to observe a sequence of past values of a trust parameter and determine the future estimates. Unfortunately, trust evolution algorithms received little attention and the proposed algorithms in the literature do not comply with the conditions and the nature of trust. This paper contributes to this important problem in the following ways: (a) presents an algorithm that manages and models trust evolution in a P2P environment, (b) devises new mechanisms for effectively maintaining trust values based on the conditions that influence trust evolution , and (c) introduces a new methodology for incorporating trust-nurture incentives into the trust evolution algorithm. Simulation experiments are carried out to evaluate our trust evolution algorithm.
Abstract: This paper presents the comparative study of coded
data methods for finding the benefit of concealing the natural data
which is the mercantile secret. Influential parameters of the number
of replicates (rep), treatment effects (τ) and standard deviation (σ)
against the efficiency of each transformation method are investigated.
The experimental data are generated via computer simulations under
the specified condition of the process with the completely
randomized design (CRD). Three ways of data transformation consist
of Box-Cox, arcsine and logit methods. The difference values of F
statistic between coded data and natural data (Fc-Fn) and hypothesis
testing results were determined. The experimental results indicate
that the Box-Cox results are significantly different from natural data
in cases of smaller levels of replicates and seem to be improper when
the parameter of minus lambda has been assigned. On the other hand,
arcsine and logit transformations are more robust and obviously,
provide more precise numerical results. In addition, the alternate
ways to select the lambda in the power transformation are also
offered to achieve much more appropriate outcomes.
Abstract: In the highly competitive and rapidly changing global
marketplace, independent organizations and enterprises often come
together and form a temporary alignment of virtual enterprise in a
supply chain to better provide products or service. As firms adopt the
systems approach implicit in supply chain management, they must
manage the quality from both internal process control and external
control of supplier quality and customer requirements. How to
incorporate quality management of upstream and downstream supply
chain partners into their own quality management system has recently
received a great deal of attention from both academic and practice.
This paper investigate the collaborative feature and the entities-
relationship in a supply chain, and presents an ontology of
collaborative supply chain from an approach of aligning
service-oriented framework with service-dominant logic. This
perspective facilitates the segregation of material flow management
from manufacturing capability management, which provides a
foundation for the coordination and integration of the business process
to measure, analyze, and continually improve the quality of products,
services, and process. Further, this approach characterizes the different
interests of supply chain partners, providing an innovative approach to
analyze the collaborative features of supply chain. Furthermore, this
ontology is the foundation to develop quality management system
which internalizes the quality management in upstream and
downstream supply chain partners and manages the quality in supply
chain systematically.
Abstract: In this paper we will develop a sequential life test approach applied to a modified low alloy-high strength steel part used in highway overpasses in Brazil.We will consider two possible underlying sampling distributions: the Normal and theInverse Weibull models. The minimum life will be considered equal to zero. We will use the two underlying models to analyze a fatigue life test situation, comparing the results obtained from both.Since a major chemical component of this low alloy-high strength steel part has been changed, there is little information available about the possible values that the parameters of the corresponding Normal and Inverse Weibull underlying sampling distributions could have. To estimate the shape and the scale parameters of these two sampling models we will use a maximum likelihood approach for censored failure data. We will also develop a truncation mechanism for the Inverse Weibull and Normal models. We will provide rules to truncate a sequential life testing situation making one of the two possible decisions at the moment of truncation; that is, accept or reject the null hypothesis H0. An example will develop the proposed truncated sequential life testing approach for the Inverse Weibull and Normal models.
Abstract: Sonogram images of normal and lymphocyte thyroid tissues have considerable overlap which makes it difficult to interpret and distinguish. Classification from sonogram images of thyroid gland is tackled in semiautomatic way. While making manual diagnosis from images, some relevant information need not to be recognized by human visual system. Quantitative image analysis could be helpful to manual diagnostic process so far done by physician. Two classes are considered: normal tissue and chronic lymphocyte thyroid (Hashimoto's Thyroid). Data structure is analyzed using K-nearest-neighbors classification. This paper is mentioned that unlike the wavelet sub bands' energy, histograms and Haralick features are not appropriate to distinguish between normal tissue and Hashimoto's thyroid.
Abstract: This paper aims to present a framework for the
organizational knowledge management, which seeks to deploy a
standardized structure for the integrated management of knowledge is
a common language based on domains, processes and global
indicators inspired by the COBIT framework 5 (ISACA, 2012),
which supports the integration of three technologies, enterprise
information architecture (EIA), the business process modeling (BPM)
and service-oriented architecture (SOA). The Gomak Framework is a
management platform that seeks to integrate the information
technology infrastructure, the structure of applications, information
infrastructure, and business logic and business model to support a
sound strategy of organizational knowledge management, low
process-based approach and concurrent engineering. Concurrent
engineering (CE) is a systematic approach to integrated product
development that respond to customer expectations, involving all
perspectives in parallel, from the beginning of the product life cycle.
(European Space Agency, 2000).
Abstract: This paper presents a new technique of compensation
of the effect of variation parameters in the direct field oriented
control of induction motor. The proposed method uses an adaptive
tuning of the value of synchronous speed to obtain the robustness for
the field oriented control. We show that this adaptive tuning allows
having robustness for direct field oriented control to changes in rotor
resistance, load torque and rotational speed. The effectiveness of the
proposed control scheme is verified by numerical simulations. The
numerical validation results of the proposed scheme have presented
good performances compared to the usual direct-field oriented
control.
Abstract: This paper presents a new Hybrid Fuzzy (HF) PID type controller based on Genetic Algorithms (GA-s) for solution of the Automatic generation Control (AGC) problem in a deregulated electricity environment. In order for a fuzzy rule based control system to perform well, the fuzzy sets must be carefully designed. A major problem plaguing the effective use of this method is the difficulty of accurately constructing the membership functions, because it is a computationally expensive combinatorial optimization problem. On the other hand, GAs is a technique that emulates biological evolutionary theories to solve complex optimization problems by using directed random searches to derive a set of optimal solutions. For this reason, the membership functions are tuned automatically using a modified GA-s based on the hill climbing method. The motivation for using the modified GA-s is to reduce fuzzy system effort and take large parametric uncertainties into account. The global optimum value is guaranteed using the proposed method and the speed of the algorithm-s convergence is extremely improved, too. This newly developed control strategy combines the advantage of GA-s and fuzzy system control techniques and leads to a flexible controller with simple stricture that is easy to implement. The proposed GA based HF (GAHF) controller is tested on a threearea deregulated power system under different operating conditions and contract variations. The results of the proposed GAHF controller are compared with those of Multi Stage Fuzzy (MSF) controller, robust mixed H2/H∞ and classical PID controllers through some performance indices to illustrate its robust performance for a wide range of system parameters and load changes.
Abstract: The drastic increase in the usage of SMS technology
has led service providers to seek for a solution that enable users of
mobile devices to access services through SMSs. This has resulted in
the proposal of solutions towards SMS-based service invocation in
service oriented environments. However, the dynamic nature of
service-oriented environments coupled with sudden load peaks
generated by service request, poses performance challenges to
infrastructures for supporting SMS-based service invocation. To
address this problem we adopt load balancing techniques. A load
balancing model with adaptive load balancing and load monitoring
mechanisms as its key constructs is proposed. The load balancing
model then led to realization of Least Loaded Load Balancing
Framework (LLLBF). Evaluation of LLLBF benchmarked with round
robin (RR) scheme on the queuing approach showed LLLBF
outperformed RR in terms of response time and throughput.
However, LLLBF achieved better result in the cost of high
processing power.
Abstract: In this work we present a solution for DAGC (Digital
Automatic Gain Control) in WLAN receivers compatible to IEEE 802.11a/g standard. Those standards define communication in 5/2.4
GHz band using Orthogonal Frequency Division Multiplexing OFDM modulation scheme. WLAN Transceiver that we have used
enables gain control over Low Noise Amplifier (LNA) and a
Variable Gain Amplifier (VGA). The control over those signals is
performed in our digital baseband processor using dedicated hardware block DAGC. DAGC in this process is used to automatically control the VGA and LNA in order to achieve better
signal-to-noise ratio, decrease FER (Frame Error Rate) and hold the
average power of the baseband signal close to the desired set point.
DAGC function in baseband processor is done in few steps: measuring power levels of baseband samples of an RF signal,accumulating the differences between the measured power level and
actual gain setting, adjusting a gain factor of the accumulation, and
applying the adjusted gain factor the baseband values. Based on the measurement results of RSSI signal dependence to input power we have concluded that this digital AGC can be implemented applying
the simple linearization of the RSSI. This solution is very simple but also effective and reduces complexity and power consumption of the
DAGC. This DAGC is implemented and tested both in FPGA and in ASIC as a part of our WLAN baseband processor. Finally, we have integrated this circuit in a compact WLAN PCMCIA board based on MAC and baseband ASIC chips designed from us.
Abstract: The development of the power electronics has allowed
increasing the precision and reliability of the electrical trainings,
thanks to the adjustable inverters, as the Pulse Wide Modulation
(PWM) five level inverters, which is the object of study in this
article.The authors treat the relation between the law order adopted for
a given system and the oscillations of the electrical and mechanical
parameters of which the tolerance depends on the process with which
they are integrated (paper factory, lifting of the heavy loads,
etc.).Thus the best choice of the regulation indexes allows us to
achieve stability and safety training without investment (management
of existing equipment).
Abstract: As is needless to say; a majority of accidents, which occur, are due to drunk driving. As such, there is no effective mechanism to prevent this. Here we have designed an integrated system for the same purpose. Alcohol content in the driver-s body is detected by means of an infrared breath analyzer placed at the steering wheel. An infrared cell directs infrared energy through the sample and any unabsorbed energy at the other side is detected. The higher the concentration of ethanol, the more infrared absorption occurs (in much the same way that a sunglass lens absorbs visible light, alcohol absorbs infrared light). Thus the alcohol level of the driver is continuously monitored and calibrated on a scale. When it exceeds a particular limit the fuel supply is cutoff. If the device is removed also, the fuel supply will be automatically cut off or an alarm is sounded depending upon the requirement. This does not happen abruptly and special indicators are fixed at the back to avoid inconvenience to other drivers using the highway signals. Frame work for integration of sensors and control module in a scalable multi-agent system is provided .A SMS which contains the current GPS location of the vehicle is sent via a GSM module to the police control room to alert the police. The system is foolproof and the driver cannot tamper with it easily. Thus it provides an effective and cost effective solution for the problem of drunk driving in vehicles.
Abstract: In this paper, a class of impulsive BAM fuzzy cellular neural networks with time delays in the leakage terms is formulated and investigated. By establishing a delay differential inequality and M-matrix theory, some sufficient conditions ensuring the existence, uniqueness and global exponential stability of equilibrium point for impulsive BAM fuzzy cellular neural networks with time delays in the leakage terms are obtained. In particular, a precise estimate of the exponential convergence rate is also provided, which depends on system parameters and impulsive perturbation intention. It is believed that these results are significant and useful for the design and applications of BAM fuzzy cellular neural networks. An example is given to show the effectiveness of the results obtained here.
Abstract: Charge Simulation Method (CSM) is one of the very widely used numerical field computation technique in High Voltage (HV) engineering. The high voltage fields of varying non uniformities are encountered in practice. CSM programs being case specific, the simulation accuracies heavily depend on the user (programmers) experience. Here is an effort to understand CSM errors and evolve some guidelines to setup accurate CSM models, relating non uniformities with assignment factors. The results are for the six-point-charge model of sphere-plane gap geometry. Using genetic algorithm (GA) as tool, optimum assignment factors at different non uniformity factors for this model have been evaluated and analyzed. It is shown that the symmetrically placed six-point-charge models can be good enough to set up CSM programs with potential errors less than 0.1% when the field non uniformity factor is greater than 2.64 (field utilization factor less than 52.76%).
Abstract: Super-resolution is nowadays used for a high-resolution
image produced from several low-resolution noisy frames. In
this work, we consider the problem of high-quality interpolation of a
single noise-free image. Such images may come from different sources,
i.e., they may be frames of videos, individual pictures, etc. On
the other hand, in the encoder we apply a downsampling via
bidimen-sional interpolation of each frame, and in the decoder we
apply a upsampling by which we restore the original size of the
image. If the compression ratio is very high, then we use a
convolutive mask that restores the edges, eliminating the blur.
Finally, both, the encoder and the complete decoder are implemented
on General-Purpose computation on Graphics Processing Units
(GPGPU) cards. In fact, the mentioned mask is coded inside texture
memory of a GPGPU.