Abstract: Computational techniques derived from digital image processing are playing a significant role in the security and digital copyrights of multimedia and visual arts. This technology has the effect within the domain of computers. This research presents discrete M-band wavelet transform (MWT) and cosine transform (DCT) based watermarking algorithm by incorporating the principal component analysis (PCA). The proposed algorithm is expected to achieve higher perceptual transparency. Specifically, the developed watermarking scheme can successfully resist common signal processing, such as geometric distortions, and Gaussian noise. In addition, the proposed algorithm can be parameterized, thus resulting in more security. To meet these requirements, the image is transformed by a combination of MWT & DCT. In order to improve the security further, we randomize the watermark image to create three code books. During the watermark embedding, PCA is applied to the coefficients in approximation sub-band. Finally, first few component bands represent an excellent domain for inserting the watermark.
Abstract: Hybrid photovoltaic thermal (PV/T) solar system comprises a solar collector which is disposed on photovoltaic solar cells. The disadvantage of a conventional photovoltaic cell is that its performance decreases as the temperature increases. Indeed, part of the solar radiation is converted into electricity and is dissipated as heat, increasing the temperature of the photovoltaic cell with respect to the ambient temperature. The objective of this work is to study experimentally and implement a hybrid prototype to evaluate electrical and thermal performance. In this paper, an experimental study of two new configurations of hybrid collectors is exposed. The results are given and interpreted. The two configurations of absorber studied are a new combination with tubes and galvanized tank, the other is a tubes and sheet.
Abstract: This study presents energy saving in general-purpose
pumps widely used in industrial applications. Such pumps are
normally driven by a constant-speed electrical motor which in most
applications must support varying load conditions. This is equivalent
to saying the loading conditions mismatch the designed optimal
energy consumption requirements of the intended application thus
resulting in substantial energy losses. In the held experiments it was
indicated that combination of mechanical and electrical speed drives
can contribute to lower energy consumption in the pump without
negatively distorting the required performance indices of a typical
centrifugal pump at substantially lower energy consumption. The
registered energy savings were recorded to be within the 15-40%
margin. It was also indicated that although VSDs are installed at a
cost, the financial burden is balanced against the earnings resulting
from the associated energy savings.
Abstract: At present, dictionary attack has been the basic tool for
recovering key passwords. In order to avoid dictionary attack, users
purposely choose another character strings as passwords. According to
statistics, about 14% of users choose keys on a keyboard (Kkey, for
short) as passwords. This paper develops a framework system to attack
the password chosen from Kkeys and analyzes its efficiency. Within
this system, we build up keyboard rules using the adjacent and parallel
relationship among Kkeys and then use these Kkey rules to generate
password databases by depth-first search method. According to the
experiment results, we find the key space of databases derived from
these Kkey rules that could be far smaller than the password databases
generated within brute-force attack, thus effectively narrowing down
the scope of attack research. Taking one general Kkey rule, the
combinations in all printable characters (94 types) with Kkey adjacent
and parallel relationship, as an example, the derived key space is about
240 smaller than those in brute-force attack. In addition, we
demonstrate the method's practicality and value by successfully
cracking the access password to UNIX and PC using the password
databases created
Abstract: this paper presents an auto-regressive network called the Auto-Regressive Multi-Context Recurrent Neural Network (ARMCRN), which forecasts the daily peak load for two large power plant systems. The auto-regressive network is a combination of both recurrent and non-recurrent networks. Weather component variables are the key elements in forecasting because any change in these variables affects the demand of energy load. So the AR-MCRN is used to learn the relationship between past, previous, and future exogenous and endogenous variables. Experimental results show that using the change in weather components and the change that occurred in past load as inputs to the AR-MCRN, rather than the basic weather parameters and past load itself as inputs to the same network, produce higher accuracy of predicted load. Experimental results also show that using exogenous and endogenous variables as inputs is better than using only the exogenous variables as inputs to the network.
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: The concepts of knowledge creation and innovation
have a strong relationship but this relationship has not been examined
systematically. This study examines the utilization of knowledge
creation processes of the Theory of Knowledge Creation in Higher
Education Institutions. These processes consist of socialization,
externalization, combination and internalization. This study suggests
that the utilization of these processes will give impacts on innovation
in academic performance. A cross-sectional study was conducted
using survey questionnaires to collect data of the utilization of
knowledge creation processes and classroom-s innovation. The
samples are Business Management students of a Malaysian Higher
Education Institution. The results of this study could help Higher
Education Institutions to enrich the learning process of students
through knowledge creation and innovation.
Abstract: The aim of the study was to investigate the possible
use of commercial Computational Fluid Dynamics (CFD) software in
the design process of a domestic gas boiler. Because of the limited
computational resources some simplifications had to be made in
order to contribute to the design in a reasonable timescale.
The porous media model was used in order to simulate the
influence of the pressure drop characteristic of particular elements of
a heat transfer system on the water-flow distribution in the system.
Further, a combination of CFD analyses and spread sheet
calculations was used in order to solve the flow distribution problem.
Abstract: Speech enhancement is the process of eliminating
noise and increasing the quality of a speech signal, which is
contaminated with other kinds of distortions. This paper is on
developing an optimum cascaded system for speech enhancement.
This aim is attained without diminishing any relevant speech
information and without much computational and time complexity.
LMS algorithm, Spectral Subtraction and Kalman filter have been
deployed as the main de-noising algorithms in this work. Since these
algorithms suffer from respective shortcomings, this work has been
undertaken to design cascaded systems in different combinations and
the evaluation of such cascades by qualitative (listening) and
quantitative (SNR) tests.
Abstract: The study of cytokine expression in mice under the
influence of inactivated poliovirus and Imovaks polio vaccine in
combination with derivatives of chitosan shows various kinds of
processes. There is a significant increase in IL-12 in the serum of
immunized animals, which should stimulate the production of IFN-γ
NK-cells and T-cells and polarize the immune response to Th1 type.
Thus, the derivatives of chitosan can promote cell component of the
immune response, providing a full antiviral immunity.
Abstract: For future Broad band ISDN, Asynchronous Transfer
Mode (ATM) is designed not only to support a wide range of traffic
classes with diverse flow characteristics, but also to guarantee the
different quality of service QOS requirements. The QOS may be
measured in terms of cell loss probability and maximum cell delay.
In this paper, ATM networks in which the virtual path (VP)
concept is implemented are considered. By applying the Markov
Deterministic process method, an efficient algorithm to compute the
minimum capacity required to satisfy the QOS requirements when
multiple classes of on-off are multiplexed on to a single VP. Using
the result, we then proposed a simple algorithm to determine different
combinations of VP to achieve the optimum of the total capacity
required for satisfying the individual QOS requirements (loss- delay).
Abstract: Microaneurysm is a key indicator of diabetic retinopathy that can potentially cause damage to retina. Early detection and automatic quantification are the keys to prevent further damage. In this paper, which focuses on automatic microaneurysm detection in images acquired through non-dilated pupils, we present a series of experiments on feature selection and automatic microaneurysm pixel classification. We found that the best feature set is a combination of 10 features: the pixel-s intensity of shade corrected image, the pixel hue, the standard deviation of shade corrected image, DoG4, the area of the candidate MA, the perimeter of the candidate MA, the eccentricity of the candidate MA, the circularity of the candidate MA, the mean intensity of the candidate MA on shade corrected image and the ratio of the major axis length and minor length of the candidate MA. The overall sensitivity, specificity, precision, and accuracy are 84.82%, 99.99%, 89.01%, and 99.99%, respectively.
Abstract: Treatment of tar-containing wastewater is necessary
for the successful operation of biomass gasification plants (BGPs). In
the present study, tar-containing wastewater was treated using lime
and alum for the removal of in-organics, followed by adsorption on
powdered activated carbon (PAC) for the removal of organics. Limealum
experiments were performed in a jar apparatus and activated
carbon studies were performed in an orbital shaker. At optimum
concentrations, both lime and alum individually proved to be capable
of removing color, total suspended solids (TSS) and total dissolved
solids (TDS), but in both cases, pH adjustment had to be carried out
after treatment. The combination of lime and alum at the dose ratio
of 0.8:0.8 g/L was found to be optimum for the removal of inorganics.
The removal efficiency achieved at optimum
concentrations were 78.6, 62.0, 62.5 and 52.8% for color, alkalinity,
TSS and TDS, respectively. The major advantages of the lime-alum
combination were observed to be as follows: no requirement of pH
adjustment before and after treatment and good settleability of
sludge. Coagulation-precipitation followed by adsorption on PAC
resulted in 92.3% chemical oxygen demand (COD) removal and
100% phenol removal at equilibrium. Ammonia removal efficiency
was found to be 11.7% during coagulation-flocculation and 36.2%
during adsorption on PAC. Adsorption of organics on PAC in terms
of COD and phenol followed Freundlich isotherm with Kf = 0.55 &
18.47 mg/g and n = 1.01 & 1.45, respectively. This technology may
prove to be one of the fastest and most techno-economically feasible
methods for the treatment of tar-containing wastewater generated
from BGPs.
Abstract: One of the factors to maintain system survivability is
the adequate reactive power support to the system. Lack of reactive
power support may cause undesirable voltage decay leading to total
system instability. Thus, appropriate reactive power support scheme
should be arranged in order to maintain system stability. The strength
of a system capacity is normally denoted as system loadability. This
paper presents the enhancement of system loadability through
optimal reactive power planning technique using a newly developed
optimization technique, termed as Multiagent Immune Evolutionary
Programming (MAIEP). The concept of MAIEP is developed based
on the combination of Multiagent System (MAS), Artificial Immune
System (AIS) and Evolutionary Programming (EP). In realizing the
effectiveness of the proposed technique, validation is conducted on
the IEEE-26-Bus Reliability Test System. The results obtained from
pre-optimization and post-optimization process were compared
which eventually revealed the merit of MAIEP.
Abstract: The future of business intelligence (BI) is to integrate
intelligence into operational systems that works in real-time
analyzing small chunks of data based on requirements on continuous
basis. This is moving away from traditional approach of doing
analysis on ad-hoc basis or sporadically in passive and off-line mode
analyzing huge amount data. Various AI techniques such as expert
systems, case-based reasoning, neural-networks play important role
in building business intelligent systems. Since BI involves various
tasks and models various types of problems, hybrid intelligent
techniques can be better choice. Intelligent systems accessible
through web services make it easier to integrate them into existing
operational systems to add intelligence in every business processes.
These can be built to be invoked in modular and distributed way to
work in real time. Functionality of such systems can be extended to
get external inputs compatible with formats like RSS. In this paper,
we describe a framework that use effective combinations of these
techniques, accessible through web services and work in real-time.
We have successfully developed various prototype systems and done
few commercial deployments in the area of personalization and
recommendation on mobile and websites.
Abstract: The need for Information Security in organizations, regardless of their type and size, is being addressed by emerging standards and recommended best practices. The various standards and practices which evolved in recent years and are still being developed and constantly revised, address the issue of Information Security from different angles. This paper attempts to provide an overview of Information Security Standards and Practices by briefly discussing some of the most popular ones. Through a comparative study of their similarities and differences, some insight can be obtained on how their combination may lead to an increased level of Information Security.
Abstract: This work proposes an approach to address automatic
text summarization. This approach is a trainable summarizer, which
takes into account several features, including sentence position,
positive keyword, negative keyword, sentence centrality, sentence
resemblance to the title, sentence inclusion of name entity, sentence
inclusion of numerical data, sentence relative length, Bushy path of
the sentence and aggregated similarity for each sentence to generate
summaries. First we investigate the effect of each sentence feature on
the summarization task. Then we use all features score function to
train genetic algorithm (GA) and mathematical regression (MR)
models to obtain a suitable combination of feature weights. The
proposed approach performance is measured at several compression
rates on a data corpus composed of 100 English religious articles.
The results of the proposed approach are promising.
Abstract: This paper presents the development of a wavelet
based algorithm, for distinguishing between magnetizing inrush
currents and power system fault currents, which is quite adequate,
reliable, fast and computationally efficient tool. The proposed
technique consists of a preprocessing unit based on discrete wavelet
transform (DWT) in combination with an artificial neural network
(ANN) for detecting and classifying fault currents. The DWT acts as
an extractor of distinctive features in the input signals at the relay
location. This information is then fed into an ANN for classifying
fault and magnetizing inrush conditions. A 220/55/55 V, 50Hz
laboratory transformer connected to a 380 V power system were
simulated using ATP-EMTP. The DWT was implemented by using
Matlab and Coiflet mother wavelet was used to analyze primary
currents and generate training data. The simulated results presented
clearly show that the proposed technique can accurately discriminate
between magnetizing inrush and fault currents in transformer
protection.
Abstract: Cytogenetic analysis still remains the gold standard method for prenatal diagnosis of trisomy 21 (Down syndrome, DS). Nevertheless, the conventional cytogenetic analysis needs live cultured cells and is too time-consuming for clinical application. In contrast, molecular methods such as FISH, QF-PCR, MLPA and quantitative Real-time PCR are rapid assays with results available in 24h. In the present study, we have successfully used a novel MGB TaqMan probe-based real time PCR assay for rapid diagnosis of trisomy 21 status in Down syndrome samples. We have also compared the results of this molecular method with corresponding results obtained by the cytogenetic analysis. Blood samples obtained from DS patients (n=25) and normal controls (n=20) were tested by quantitative Real-time PCR in parallel to standard G-banding analysis. Genomic DNA was extracted from peripheral blood lymphocytes. A high precision TaqMan probe quantitative Real-time PCR assay was developed to determine the gene dosage of DSCAM (target gene on 21q22.2) relative to PMP22 (reference gene on 17p11.2). The DSCAM/PMP22 ratio was calculated according to the formula; ratio=2 -ΔΔCT. The quantitative Real-time PCR was able to distinguish between trisomy 21 samples and normal controls with the gene ratios of 1.49±0.13 and 1.03±0.04 respectively (p value
Abstract: Creativity is often based on an unorthodox
recombination of knowledge; in fact: 80% of all innovations use
given knowledge and put it into a new combination. Cross-industry
innovations follow this way of thinking and bring together problems
and solution ideas from different industries. Therefore analogies and
search strategies have to be developed. Taking this path, the
questions where to search, what to search and how to search have to
be answered. Afterwards, the gathered information can be used
within a planned search process. Identified solution ideas have to be
assessed and analyzed in detail for the success promising adaption
planning.