Abstract: The growth of the aquaculture industry has been
associated with negative environmental impacts through the
discharge of raw effluents into the adjacent receiving water bodies.
Macrophytes from natural saline lakes, which have adaptability to the
high salinity, can be suitable for saline effluent treatment. Eight
emergent species from natural saline area were planted in an
experimental gravel bed hydroponic mesocosm (GBH) which was
treated with effluent water from an intensive fish farm using
geothermal water. In order to examine the applicability of the
halophytes in treatment processes, we tested the relative efficacy of
total nitrogen (TN), total phosphorus (TP), potassium (K), sodium
(Na), magnesium (Mg) and calcium (Ca) removal for the saline
wastewater treatment. Four of the eight species, which were
Phragmites australis, Typha angustifolia, Glyceria maxima, Scirpus
lacustris spp. tabernaemontani could survive and contribute the
experimental treatment.
Abstract: Traditional higher-education classrooms allow lecturers to observe students- behaviours and responses to a particular pedagogy during learning in a way that can influence changes to the pedagogical approach. Within current e-learning systems it is difficult to perform continuous analysis of the cohort-s behavioural tendency, making real-time pedagogical decisions difficult. This paper presents a Virtual Learning Process Environment (VLPE) based on the Business Process Management (BPM) conceptual framework. Within the VLPE, course designers can model various education pedagogies in the form of learning process workflows using an intuitive flow diagram interface. These diagrams are used to visually track the learning progresses of a cohort of students. This helps assess the effectiveness of the chosen pedagogy, providing the information required to improve course design. A case scenario of a cohort of students is presented and quantitative statistical analysis of their learning process performance is gathered and displayed in realtime using dashboards.
Abstract: Rice seed expression (cDNA) library in the Lambda
Zap 11® phage constructed from the developing grain 10-20 days
after flowering was transformed into yeast for functional
complementation assays in three salt sensitive yeast mutants S.
cerevisiae strain CY162, G19 and Axt3K. Transformed cells of G19
and Axt3K with pYES vector with cDNA inserts showed enhance
tolerance than those with empty pYes vector. Sequencing of the
cDNA inserts revealed that they encode for the putative proteins with
the sequence homologous to rice putative protein PROLM24
(Os06g31070), a prolamin precursor. Expression of this cDNA did
not affect yeast growth in absence of salt. Axt3k and G19 strains
expressing the PROLM24 were able to grow upto 400 mM and 600
mM of NaCl respectively. Similarly, Axt3k mutant with PROLM24
expression showed comparatively higher growth rate in the medium
with excess LiCl (50 mM). The observation that expression of
PROLM24 rescued the salt sensitive phenotypes of G19 and Axt3k
indicates the existence of a regulatory system that ameliorates the
effect of salt stress in the transformed yeast mutants. However, the
exact function of the cDNA sequence, which shows partial sequence
homology to yeast UTR1 is not clear. Although UTR1 involved in
ferrous uptake and iron homeostasis in yeast cells, there is no
evidence to prove its role in Na+ homeostasis in yeast cells. Absence
of transmembrane regions in Os06g31070 protein indicates that salt
tolerance is achieved not through the direct functional
complementation of the mutant genes but through an alternative
mechanism.
Abstract: Innovations in technology have created new ethical
challenges. Essential use of electronic communication in the
workplace has escalated at an astronomical rate over the past decade.
As such, legal and ethical dilemmas confronted by both the employer
and the employee concerning managerial control and ownership of einformation
have increased dramatically in the USA. From the
employer-s perspective, ownership and control of all information
created for the workplace is an undeniable source of economic
advantage and must be monitored zealously. From the perspective of
the employee, individual rights, such as privacy, freedom of speech,
and freedom from unreasonable search and seizure, continue to be
stalwart legal guarantees that employers are not legally or ethically
entitled to abridge in the workplace. These issues have been the
source of great debate and the catalyst for legal reform. The fine line
between ethical and legal has been complicated by emerging
technologies. This manuscript will identify and discuss a number of
specific legal and ethical issues raised by the dynamic electronic
workplace and conclude with suggestions that employers should
follow to respect the delicate balance between employees- legal
rights to privacy and the employer's right to protect its knowledge
systems and infrastructure.
Abstract: Artificial Immune System is adopted as a Heuristic
Algorithm to solve the combinatorial problems for decades.
Nevertheless, many of these applications took advantage of the benefit
for applications but seldom proposed approaches for enhancing the
efficiency. In this paper, we continue the previous research to develop
a Self-evolving Artificial Immune System II via coordinating the T
and B cell in Immune System and built a block-based artificial
chromosome for speeding up the computation time and better
performance for different complexities of problems. Through the
design of Plasma cell and clonal selection which are relative the
function of the Immune Response. The Immune Response will help
the AIS have the global and local searching ability and preventing
trapped in local optima. From the experimental result, the significant
performance validates the SEAIS II is effective when solving the
permutation flows-hop problems.
Abstract: This study has investigated the antidiabetic and
antioxidant potential of Pseudovaria macrophylla bark extract on
streptozotocin–nicotinamide induced type 2 diabetic rats. LCMSQTOF
and NMR experiments were done to determine the chemical
composition in the methanolic bark extract. For in vivo experiments,
the STZ (60 mg/kg/b.w, 15 min after 120 mg/kg/1 nicotinamide, i.p.)
induced diabetic rats were treated with methanolic extract of
Pseuduvaria macrophylla (200 and 400 mg/kg·bw) and
glibenclamide (2.5 mg/kg) as positive control respectively.
Biochemical parameters were assayed in the blood samples of all
groups of rats. The pro-inflammatory cytokines, antioxidant status
and plasma transforming growth factor βeta-1 (TGF-β1) were
evaluated. The histological study of the pancreas was examined and
its expression level of insulin was observed by
immunohistochemistry. In addition, the expression of glucose
transporters (GLUT 1, 2 and 4) were assessed in pancreas tissue by
western blot analysis. The outcomes of the study displayed that the
bark methanol extract of Pseuduvaria macrophylla has potentially
normalized the elevated blood glucose levels and improved serum
insulin and C-peptide levels with significant increase in the
antioxidant enzyme, reduced glutathione (GSH) and decrease in the
level of lipid peroxidation (LPO). Additionally, the extract has
markedly decreased the levels of serum pro-inflammatory cytokines
and transforming growth factor beta-1 (TGF-β1). Histopathology
analysis demonstrated that Pseuduvaria macrophylla has the
potential to protect the pancreas of diabetic rats against peroxidation
damage by downregulating oxidative stress and elevated
hyperglycaemia. Furthermore, the expression of insulin protein,
GLUT-1, GLUT-2 and GLUT-4 in pancreatic cells was enhanced.
The findings of this study support the anti-diabetic claims of
Pseudovaria macrophylla bark.
Abstract: In this paper, we introduce an e-collaborative learning circles methodology which utilizes the information and communication technologies (ICTs) in e-educational processes. In e-collaborative learning circles methodology, the teachers and students announce their research projects on various mailing lists and discussion boards using available ICTs. The teachers & moderators and students who are already members of the e-forums, discuss the project proposals in their classrooms sent out by the potential global partner schools and return the requested feed back to the proposing school(s) about their level of the participation and contribution in the research. In general, an e-collaborative learning circle project is implemented with a small and diverse group (usually 8-10 participants) from around the world. The students meet regularly over a period of weeks/months through the ICTs during the ecollaborative learning process. When the project is completed, a project product (e-book / DVD) is prepared and sent to the circle members. In this research, when taking into account the interests and motivation of the participating students with the facilitating role of the teacher(s), the students in each circle do research to obtain new data and information, thus enabling them to have the opportunity to meet both different cultures and international understandings across the globe. However, while the participants communicate along with the members in the circle they also practice and develop their communication language skills. Finally, teachers and students find the possibility to develop their skills in using the ICTs as well.
Abstract: In this paper, a semi empirical formula is presented based on the experimental results to predict the first pick (maximum force) value in the instantaneous folding force- axial distance diagram of a square column. To achieve this purpose, the maximum value of the folding force was assumed to be a function of the average folding force. Using the experimental results, the maximum value of the force necessary to initiate the first fold in a square column was obtained with respect to the geometrical quantities and material properties. Finally, the results obtained from the semi empirical relation in this paper, were compared to the experimental results which showed a good correlation.
Abstract: In this paper we suggest a method for setting
electronic credits for the customers. In this method banks and
market-sites help each other to make doing large shopping through
internet so easy. By developing this system, the people who have less
money to buy most of the things they want, become able to buy all of
them just through a credit. This credit is given by market-sites
through a banking control on it. The method suggested can stop
being imprisoned because of banking debts.
Abstract: Since communications between tag and reader in RFID
system are by radio, anyone can access the tag and obtain its any
information. And a tag always replies with the same ID so that it is
hard to distinguish between a real and a fake tag. Thus, there are many
security problems in today-s RFID System. Firstly, unauthorized
reader can easily read the ID information of any Tag. Secondly,
Adversary can easily cheat the legitimate reader using the collected
Tag ID information, such as the any legitimate Tag. These security
problems can be typically solved by encryption of messages
transmitted between Tag and Reader and by authentication for Tag.
In this paper, to solve these security problems on RFID system, we
propose the Tag Authentication Scheme based on self shrinking
generator (SSG). SSG Algorithm using in our scheme is proposed by
W.Meier and O.Staffelbach in EUROCRYPT-94. This Algorithm is
organized that only one LFSR and selection logic in order to generate
random stream. Thus it is optimized to implement the hardware logic
on devices with extremely limited resource, and the output generating
from SSG at each time do role as random stream so that it is allow our
to design the light-weight authentication scheme with security against
some network attacks. Therefore, we propose the novel tag
authentication scheme which use SSG to encrypt the Tag-ID
transmitted from tag to reader and achieve authentication of tag.
Abstract: The design of technological procedures for
manufacturing certain products demands the definition and
optimization of technological process parameters. Their
determination depends on the model of the process itself and its
complexity. Certain processes do not have an adequate mathematical
model, thus they are modeled using heuristic methods. First part of
this paper presents a state of the art of using soft computing
techniques in manufacturing processes from the perspective of
applicability in modern CAx systems. Methods of artificial
intelligence which can be used for this purpose are analyzed. The
second part of this paper shows some of the developed models of
certain processes, as well as their applicability in the actual
calculation of parameters of some technological processes within the
design system from the viewpoint of productivity.
Abstract: The proposed multiplexer-based novel 1-bit full
adder cell is schematized by using DSCH2 and its layout is generated
by using microwind VLSI CAD tool. The adder cell layout
interconnect analysis is performed by using BSIM4 layout analyzer.
The adder circuit is compared with other six existing adder circuits
for parametric analysis. The proposed adder cell gives better
performance than the other existing six adder circuits in terms of
power, propagation delay and PDP. The proposed adder circuit is
further analyzed for interconnect analysis, which gives better
performance than other adder circuits in terms of layout thickness,
width and height.
Abstract: In synchronized games players make their moves simultaneously
rather than alternately. Synchronized Triomineering
and Synchronized Tridomineering are respectively the synchronized
versions of Triomineering and Tridomineering, two variants of a
classic two-player combinatorial game called Domineering. Experimental
results for small m × n boards (with m + n ≤ 12 for
Synchronized Triomineering and m + n ≤ 10 for Synchronized
Tridomineering) and some theoretical results for general k×n boards
(with k = 3, 4, 5 for Synchronized Triomineering and k = 3
for Synchronized Tridomineering) are presented. Future research is
indicated.
Abstract: Abstract–The objectives of the current study are to determine the
prevalence, etiological agents, drug susceptibility pattern and plasmid
profile of Acinetobacter baumannii isolates from Hospital-Acquired
Infections (HAI) at Community Hospital, Al Jouf Province, Saudi
Arabia. A total of 1890 patients had developed infection during
hospital admission and were included in the study. Among those who
developed nosocomial infections, 15(9.4), 10(2.7) and 118 (12.7) had
respiratory tract infection (RTI), blood stream infections (BSI) and
urinary tract (UTI) respectively. A total of 268 bacterial isolates were
isolated from nosocomial infection. S. aureus was reported in 23.5%
for of the total isolates followed by Klebsiella pneumoniae (17.5%), E.
coli (17.2%), P. aeruginosa (11.9%), coagulase negative
staphylococcus (9%), A. baumannii (7.1%), Enterobacter spp.
(3.4%), Citrobacter freundii (3%), Proteus mirabilis (2.6%), and
Proteus vulgaris and Enterococcous faecalis (0.7%). Isolated
organisms are multi-drug resistant, predominantly Gram-positive
pathogens with a high incidence of methicillin-resistant S. aureus,
extended spectrum beta lactamase and vancomycin resistant
enterococci organisms. The RFLP (Fragment Length Polymorphisms)
patterns of plasmid preparations from isolated A. baumannii isolates
had altered RFLP patterns, possibly due to the presence of plasmid(s).
Five A. baumannii isolates harbored plasmids all of which were not
less than 2.71kbp in molecular weight. Hence, it showed that the gene
coding for the isolates were located on the plasmid DNA while the
remaining isolates which have no plasmid might showed gene coding
for antibiotic resistance being located on chromosomal DNA.
Nosocomial infections represent a current problem in Community
Hospital, Al Jouf Province, Saudi Arabia. Problems associated with
SSI include infection with multidrug resistant pathogens which are
difficult to treat and are associated with increased mortality.
Abstract: We consider a network of two M/M/1 parallel queues having the same poisonnian arrival stream with rate λ. Upon his arrival to the system a customer heads to the shortest queue and stays until being served. If the two queues have the same length, an arriving customer chooses one of the two queues with the same probability. Each duration of service in the two queues is an exponential random variable with rate μ and no jockeying is permitted between the two queues. A new numerical method, based on linear programming and convex optimization, is performed for the computation of the steady state solution of the system.
Abstract: The design of a pattern classifier includes an attempt
to select, among a set of possible features, a minimum subset of
weakly correlated features that better discriminate the pattern classes.
This is usually a difficult task in practice, normally requiring the
application of heuristic knowledge about the specific problem
domain. The selection and quality of the features representing each
pattern have a considerable bearing on the success of subsequent
pattern classification. Feature extraction is the process of deriving
new features from the original features in order to reduce the cost of
feature measurement, increase classifier efficiency, and allow higher
classification accuracy. Many current feature extraction techniques
involve linear transformations of the original pattern vectors to new
vectors of lower dimensionality. While this is useful for data
visualization and increasing classification efficiency, it does not
necessarily reduce the number of features that must be measured
since each new feature may be a linear combination of all of the
features in the original pattern vector. In this paper a new approach is
presented to feature extraction in which feature selection, feature
extraction, and classifier training are performed simultaneously using
a genetic algorithm. In this approach each feature value is first
normalized by a linear equation, then scaled by the associated weight
prior to training, testing, and classification. A knn classifier is used to
evaluate each set of feature weights. The genetic algorithm optimizes
a vector of feature weights, which are used to scale the individual
features in the original pattern vectors in either a linear or a nonlinear
fashion. By this approach, the number of features used in classifying
can be finely reduced.
Abstract: This work aims to investigate a potential of
microalgae for utilizing industrial wastewater as a cheap nutrient for
their growth and oil accumulation. Wastewater was collected from
the effluent ponds of agro-industrial factories (cassava and ethanol
production plants). Only 2 microalgal strains were isolated and
identified as Scenedesmus quadricauda and Chlorella sp.. However,
only S. quadricauda was selected to cultivate in various wastewater
concentrations (10%, 20%, 40%, 60%, 80% and 100%). The highest
biomass obtained at 6.6×106 and 6.27×106 cells/ml when 60%
wastewater was used in flask and photo-bioreactor. The cultures gave
the highest lipid content at 18.58 % and 42.86% in cases of S.
quadricauda and S. obliquus. In addition, under salt stress (1.0 M
NaCl), S. obliquus demonstrated the highest lipid content at 50%
which was much more than the case of no NaCl adding. However, the
concentration of NaCl does not affect on lipid accumulation in case
of S. quadricauda.
Abstract: A new approach based on the consideration that electroencephalogram (EEG) signals are chaotic signals was presented for automated diagnosis of electroencephalographic changes. This consideration was tested successfully using the nonlinear dynamics tools, like the computation of Lyapunov exponents. This paper presented the usage of statistics over the set of the Lyapunov exponents in order to reduce the dimensionality of the extracted feature vectors. Since classification is more accurate when the pattern is simplified through representation by important features, feature extraction and selection play an important role in classifying systems such as neural networks. Multilayer perceptron neural network (MLPNN) architectures were formulated and used as basis for detection of electroencephalographic changes. Three types of EEG signals (EEG signals recorded from healthy volunteers with eyes open, epilepsy patients in the epileptogenic zone during a seizure-free interval, and epilepsy patients during epileptic seizures) were classified. The selected Lyapunov exponents of the EEG signals were used as inputs of the MLPNN trained with Levenberg- Marquardt algorithm. The classification results confirmed that the proposed MLPNN has potential in detecting the electroencephalographic changes.
Abstract: Wireless Sensor networks have a wide spectrum of civil and military applications that call for secure communication such as the terrorist tracking, target surveillance in hostile environments. For the secure communication in these application areas, we propose a method for generating a hierarchical key structure for the efficient group key management. In this paper, we apply A* algorithm in generating a hierarchical key structure by considering the history data of the ratio of addition and eviction of sensor nodes in a location where sensor nodes are deployed. Thus generated key tree structure provides an efficient way of managing the group key in terms of energy consumption when addition and eviction event occurs. A* algorithm tries to minimize the number of messages needed for group key management by the history data. The experimentation with the tree shows efficiency of the proposed method.
Abstract: The Corporate Social Responsibility (CSR) performance has garnered significant interest during the last two decades as numerous methodologies are proposed by Social Responsible Investment (SRI) indexes. The weight of each indicator is a crucial component of the CSR measurement procedures. Based on a previous study, the appropriate weight of each proposed indicator for the Greek telecommunication sector is specified using the rank reciprocal weighting. The Kendall-s Coefficient of Concordance and Spearman Correlation Coefficient non-parametric tests are adopted to determine the level of consensus among the experts concerning the importance rank of indicators. The results show that there is no consensus regarding the rank of indicators in most of stakeholders- domains. The equal weight for all indicators could be proposed as a solution for the lack of consensus among the experts. The study recommends three different equations concerning the adopted weight approach.