Abstract: Rooted in the study of social functioning of space in architecture, Space Syntax (SS) and the more recent Network Pattern (NP) researches demonstrate the 'spatial structures' of city, i.e. the hierarchical patterns of streets, junctions and alley ends. Applying SS and NP models, planners can conceptualize the real city-s patterns. Although, both models yield the optimal path of the city their underpinning displays of the city-s spatial configuration differ. The Axial Map analyzes the topological non-distance-based connectivity structure, whereas, the Central-Node Map and the Shortcut-Path Map, in contrast, analyze the metrical distance-based structures. This research contrasts and combines them to understand various forms of city-s structures. It concludes that, while they reveal different spatial structures, Space Syntax and Network Pattern urban models support each the other. Combining together they simulate the global access and the locally compact structures namely the central nodes and the shortcuts for the city.
Abstract: The introduction of haptic elements in a graphic user interfaces are becoming more widespread. Since haptics are being introduced rapidly into computational tools, investigating how these models affect Human-Computer Interaction would help define how to integrate and model new modes of interaction. The interest of this paper is to discuss and investigate the issues surrounding Haptic and Graphic User Interface designs (GUI) as separate systems, as well as understand how these work in tandem. The development of these systems is explored from a psychological perspective, based on how usability is addressed through learning and affordances, defined by J.J. Gibson. Haptic design can be a powerful tool, aiding in intuitive learning. The problems discussed within the text is how can haptic interfaces be integrated within a GUI without the sense of frivolity. Juxtaposing haptics and Graphic user interfaces has issues of motivation; GUI tends to have a performatory process, while Haptic Interfaces use affordances to learn tool use. In a deeper view, it is noted that two modes of perception, foveal and ambient, dictate perception. These two modes were once thought to work in tandem, however it has been discovered that these processes work independently from each other. Foveal modes interpret orientation is space which provide for posture, locomotion, and motor skills with variations of the sensory information, which instructs perceptions of object-task performance. It is contended, here, that object-task performance is a key element in the use of Haptic Interfaces because exploratory learning uses affordances in order to use an object, without meditating an experience cognitively. It is a direct experience that, through iteration, can lead to skill-sets. It is also indicated that object-task performance will not work as efficiently without the use of exploratory or kinesthetic learning practices. Therefore, object-task performance is not as congruently explored in GUI than it is practiced in Haptic interfaces.
Abstract: We present a label-free biosensor based on
electrochemical impedance spectroscopy for the detection of proinflammatory
cytokine Tumor Necrosis Factor (TNF-α). Secretion of
TNF-α has been correlated to the onset of various diseases including
rheumatoid arthritis, Crohn-s disease etc. Gold electrodes were
patterned on a silicon substrate and self assembled monolayer of
dithiobis-succinimidyl propionate was used to develop the biosensor
which achieved a detection limit of ~57fM. A linear relationship was
also observed between increasing TNF-α concentrations and chargetransfer
resistance within a dynamic range of 1pg/ml – 1ng/ml.
Abstract: Application of pesticides in the paddy fields has
deleterious effects on non-target organisms including cyanobacteria
which are photosynthesizing and nitrogen fixing micro-organisms
contributing significantly towards soil fertility and crop yield.
Pesticide contamination in the paddy fields has manifested into a
serious global environmental concern. To study the effect of one such
pesticide, three cyanobacterial strains; Anabaena fertilissima,
Aulosira fertilissima and Westiellopsis prolifica were selected for
their stress responses to an Organochlorine insecticide - 6, 7, 8, 9, 10,
10-hexachloro-1, 5, 5a, 6, 9, 9a-hexahydro-6, 9-methano-2, 4, 3-
benzodioxathiepine-3-oxide, with reference to their photosynthesic
pigments-chlorophyll-a and carotenoids as well as accessory
pigments-phycobiliproteins (phycocyanin, allophycocyanin and
phycoerythrin), stress induced biochemical metabolites like
carbohydrates, proteins, amino acids, phenols and enzymes-nitrate
reductase, glutamine synthetase and succinate dehydrogenase. All
the three cyanobacterial strains were adversely affected by the
insecticide doses and inhibition was dose dependent. Reduction in
photosynthetic and accessory pigments, metabolites, nitrogen fixing
and respiratory enzymes of the test organisms were accompanied
with an initial increase in their total protein at lower Organochlorine
doses. On the other hand, increased amount of phenols in all the
insecticide treated concentrations was indicative of stressed activities
of the organisms.
Abstract: Most real world systems express themselves formally
as a set of nonlinear algebraic equations. As applications grow, the
size and complexity of these equations also increase. In this work, we
highlight the key concepts in using the homotopy analysis method
as a methodology used to construct efficient iteration formulas for
nonlinear equations solving. The proposed method is experimentally
characterized according to a set of determined parameters which
affect the systems. The experimental results show the potential and
limitations of the new method and imply directions for future work.
Abstract: In this paper we introduce new data oriented modeling
of uniform random variable well-matched with computing systems. Due to this conformity with current computers structure, this modeling will be efficiently used in statistical inference.
Abstract: The effectiveness of consuming a nutrient fortified oat drink on iron, zinc, vitamin A and vitamin C status was assessed among a cohort of school-aged Filipino children. Ultimate study implementation permitted only a within-subject comparison of change in nutritional status after four months of consuming a nutrient fortified oat drink. Thirty-eight anemic children (5-8 years) consumed an oat drink fortified with iron as NaFeEDTA, zinc, vitamin A and vitamin C for 120 days. Height, weight, serum nutrient levels, anemia status and dietary intake were assessed pre and post intervention. Thirty-four anemic children completed the intervention. After 4 months of intervention, prevalence of anemia decreased by 68% and significant improvements in iron and vitamin A status were observed. Results demonstrate the effectiveness of the fortified oat drink in alleviating anemia in young children and highlight the value of fortification programs
Abstract: Generation system reliability assessment is an
important task which can be performed using deterministic or
probabilistic techniques. The probabilistic approaches have
significant advantages over the deterministic methods. However,
more complicated modeling is required by the probabilistic
approaches. Power generation model is a basic requirement for this
assessment. One form of the generation models is the well known
capacity outage probability table (COPT). Different analytical
techniques have been used to construct the COPT. These approaches
require considerable mathematical modeling of the generating units.
The unit-s models are combined to build the COPT which will add
more burdens on the process of creating the COPT. Decimal to
Binary Conversion (DBC) technique is widely and commonly applied
in electronic systems and computing This paper proposes a novel
utilization of the DBC to create the COPT without engaging in
analytical modeling or time consuming simulations. The simple
binary representation , “0 " and “1 " is used to model the states o f
generating units. The proposed technique is proven to be an effective
approach to build the generation model.
Abstract: In this paper, genetic algorithm (GA) opmization technique is applied to design Flexible AC Transmission System (FACTS)-based damping controllers. Two types of controller structures, namely a proportional-integral (PI) and a lead-lag (LL) are considered. The design problem of the proposed controllers is formulated as an optimization problem and GA is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. The proposed controllers are tested on a weakly connected power system subjected to different disturbances. The non-linear simulation results are presented to show the effectiveness of the proposed controller and their ability to provide efficient damping of low frequency oscillations. It is also observed that the proposed SSSC-based controllers improve greatly the voltage profile of the system under severe disturbances. Further, the dynamic performances of both the PI and LL structured FACTS-controller are analyzed at different loading conditions and under various disturbance condition as well as under unbalanced fault conditions..
Abstract: This study aimed to develop and initially validate an instrument that measures social competency among tertiary level faculty members. A review of extant literature on social competence was done. The review of extant literature led to the writing of the items in the initial instrument which was evaluated by 11 Subject Matter Experts (SMEs). The SMEs were either educators or psychologists. The results of the evaluations done by the SMEs served as bases for the creation of the pre-try-out instrument used in the first trial-run. Insights from the first trial-run participants led to the development of the main try-out instrument used in the final test administration. One Hundred Forty-one participants from five private Higher Education Institutions (HEIs) in the National Capital Region (NCR) and five private HEIs in Central Luzon in the Philippines participated in the final test administration. The reliability of the instrument was evaluated using Cronbach-s Coefficient Alpha formula and had a Cronbach-s Alpha of 0.92. On the other hand, Factor Analysis was used to evaluate the validity of the instrument and six factors were identified. The development of the final instrument was based on the results of the evaluation of the instrument-s reliability and validity. For purposes of recognition, the instrument was named “Social Competency Inventory for Tertiary Level Faculty Members (SCI-TLFM)."
Abstract: A Finite Volume method based on Characteristic Fluxes for compressible fluids is developed. An explicit cell-centered resolution is adopted, where second and third order accuracy is provided by using two different MUSCL schemes with Minmod, Sweby or Superbee limiters for the hyperbolic part. Few different times integrator is used and be describe in this paper. Resolution is performed on a generic unstructured Cartesian grid, where solid boundaries are handled by a Cut-Cell method. Interfaces are explicitely advected in a non-diffusive way, ensuring local mass conservation. An improved cell cutting has been developed to handle boundaries of arbitrary geometrical complexity. Instead of using a polygon clipping algorithm, we use the Voxel traversal algorithm coupled with a local floodfill scanline to intersect 2D or 3D boundary surface meshes with the fixed Cartesian grid. Small cells stability problem near the boundaries is solved using a fully conservative merging method. Inflow and outflow conditions are also implemented in the model. The solver is validated on 2D academic test cases, such as the flow past a cylinder. The latter test cases are performed both in the frame of the body and in a fixed frame where the body is moving across the mesh. Adaptive Cartesian grid is provided by Paramesh without complex geometries for the moment.
Abstract: This study attempts to investigate the relationship
between internal CSR practices and organizational commitment
based on the social exchange theory (SET). Specifically, we examine
the impact of five dimensions of internal CSR practices on
organizational commitment: health and safety, human rights, training
and education, work life balance and workplace diversity. The
proposed model was tested on a sample of 336 frontline employees
within the banking sector in Jordan. Results showed that all internal
CSR dimensions are significantly and positively related to affective
and normative commitment. In addition, the findings of this study
indicate that all internal CSR dimensions did not have a significant
relationship with continuance commitment. Limitations of the study,
directions for future research, and implications of the findings are
discussed.
Abstract: This study discusses the effect of uncertainty on
production levels of a petrochemical complex. Uncertainly or
variations in some model parameters, such as prices, supply and
demand of materials, can affect the optimality or the efficiency of any
chemical process. For any petrochemical complex with many plants,
there are many sources of uncertainty and frequent variations which
require more attention. Many optimization approaches are proposed
in the literature to incorporate uncertainty within the model in order
to obtain a robust solution. In this work, a stability analysis approach
is applied to a deterministic LP model of a petrochemical complex
consists of ten plants to investigate the effect of such variations on
the obtained optimal production levels. The proposed approach can
determinate the allowable variation ranges of some parameters,
mainly objective or RHS coefficients, before the system lose its
optimality. Parameters with relatively narrow range of variations, i.e.
stability limits, are classified as sensitive parameters or constraints
that need accurate estimate or intensive monitoring. These stability
limits offer easy-to-use information to the decision maker and help in
understanding the interaction between some model parameters and
deciding when the system need to be re-optimize. The study shows
that maximum production of ethylene and the prices of intermediate
products are the most sensitive factors that affect the stability of the
optimum solution
Abstract: The effects of global warming on India vary from the
submergence of low-lying islands and coastal lands to the melting of
glaciers in the Indian Himalayas, threatening the volumetric flow rate
of many of the most important rivers of India and South Asia. In
India, such effects are projected to impact millions of lives. As a
result of ongoing climate change, the climate of India has become
increasingly volatile over the past several decades; this trend is
expected to continue.
Climate change is one of the most important global environmental
challenges, with implications for food production, water supply,
health, energy, etc. Addressing climate change requires a good
scientific understanding as well as coordinated action at national and
global level. The climate change issue is part of the larger challenge
of sustainable development. As a result, climate policies can be more
effective when consistently embedded within broader strategies
designed to make national and regional development paths more
sustainable. The impact of climate variability and change, climate
policy responses, and associated socio-economic development will
affect the ability of countries to achieve sustainable development
goals.
A very well calibrated Soil and Water Assessment Tool (R2 =
0.9968, NSE = 0.91) was exercised over the Khatra sub basin of the
Kangsabati River watershed in Bankura district of West Bengal,
India, in order to evaluate projected parameters for agricultural
activities. Evapotranspiration, Transmission Losses, Potential
Evapotranspiration and Lateral Flow to reach are evaluated from the
years 2041-2050 in order to generate a picture for sustainable
development of the river basin and its inhabitants.
India has a significant stake in scientific advancement as well as
an international understanding to promote mitigation and adaptation.
This requires improved scientific understanding, capacity building,
networking and broad consultation processes. This paper is a
commitment towards the planning, management and development of
the water resources of the Kangsabati River by presenting detailed
future scenarios of the Kangsabati river basin, Khatra sub basin, over
the mentioned time period.
India-s economy and societal infrastructures are finely tuned to the
remarkable stability of the Indian monsoon, with the consequence
that vulnerability to small changes in monsoon rainfall is very high.
In 2002 the monsoon rains failed during July, causing profound loss
of agricultural production with a drop of over 3% in India-s GDP.
Neither the prolonged break in the monsoon nor the seasonal rainfall
deficit was predicted. While the general features of monsoon
variability and change are fairly well-documented, the causal
mechanisms and the role of regional ecosystems in modulating the
changes are still not clear. Current climate models are very poor at
modelling the Asian monsoon: this is a challenging and critical
region where the ocean, atmosphere, land surface and mountains all
interact. The impact of climate change on regional ecosystems is
likewise unknown. The potential for the monsoon to become more
volatile has major implications for India itself and for economies
worldwide. Knowledge of future variability of the monsoon system,
particularly in the context of global climate change, is of great
concern for regional water and food security.
The major findings of this paper were that of all the chosen
projected parameters, transmission losses, soil water content,
potential evapotranspiration, evapotranspiration and lateral flow to
reach, display an increasing trend over the time period of years 2041-
2050.
Abstract: Most neural network (NN) models of human category learning use a gradient-based learning method, which assumes that locally-optimal changes are made to model parameters on each learning trial. This method tends to under predict variability in individual-level cognitive processes. In addition many recent models of human category learning have been criticized for not being able to replicate rapid changes in categorization accuracy and attention processes observed in empirical studies. In this paper we introduce stochastic learning algorithms for NN models of human category learning and show that use of the algorithms can result in (a) rapid changes in accuracy and attention allocation, and (b) different learning trajectories and more realistic variability at the individual-level.
Abstract: Chitosan is a biopolymer composed of glucosamine
and N-acetyl glucosamine. Solubility and viscosity pose problems in
some applications. These problems can be overcome with unique
modifications. In this study, firstly, chitosan was modified by caffeic
acid and thioglycolic acid, separately. Then, growing effects of these
modified polymers was observed in U937 cell line. Caffeic acid is a
phenolic compound and its modifications act carcinogenic inhibitors
in drugs. Thiolated chitosans are commonly being used for drugdelivery
systems in various routes, because of enhancing
mucoadhesiveness property. U937 cell line was used model cell for
leukaemia. Modifications were achieved by 1 – 15 % binding range.
Increasing binding ratios showed higher radical-scavenging activity
and reducing cell growth, in compared to native chitosan. Caffeic
acid modifications showed higher radical-scavenging activity than
thiolated chitosans at the same concentrations. Caffeic acid and
thioglycolic acid modifications inhibited growth of U937, effectively.
Abstract: The current speech interfaces in many military
applications may be adequate for native speakers. However,
the recognition rate drops quite a lot for non-native speakers
(people with foreign accents). This is mainly because the nonnative
speakers have large temporal and intra-phoneme
variations when they pronounce the same words. This
problem is also complicated by the presence of large
environmental noise such as tank noise, helicopter noise, etc.
In this paper, we proposed a novel continuous acoustic feature
adaptation algorithm for on-line accent and environmental
adaptation. Implemented by incremental singular value
decomposition (SVD), the algorithm captures local acoustic
variation and runs in real-time. This feature-based adaptation
method is then integrated with conventional model-based
maximum likelihood linear regression (MLLR) algorithm.
Extensive experiments have been performed on the NATO
non-native speech corpus with baseline acoustic model trained
on native American English. The proposed feature-based
adaptation algorithm improved the average recognition
accuracy by 15%, while the MLLR model based adaptation
achieved 11% improvement. The corresponding word error
rate (WER) reduction was 25.8% and 2.73%, as compared to
that without adaptation. The combined adaptation achieved
overall recognition accuracy improvement of 29.5%, and
WER reduction of 31.8%, as compared to that without
adaptation.
Abstract: The density estimates considered in this paper comprise
a base density and an adjustment component consisting of a linear
combination of orthogonal polynomials. It is shown that, in the
context of density approximation, the coefficients of the linear combination
can be determined either from a moment-matching technique
or a weighted least-squares approach. A kernel representation of
the corresponding density estimates is obtained. Additionally, two
refinements of the Kronmal-Tarter stopping criterion are proposed
for determining the degree of the polynomial adjustment. By way of
illustration, the density estimation methodology advocated herein is
applied to two data sets.
Abstract: Gas condensate Reservoirs show complicated thermodynamic behavior when their pressure reduces to under dew point pressure. Condensate blockage around the producing well cause significant reduction of production rate as well bottom-hole pressure drops below saturation pressure. The main objective of this work was to examine the well test analysis of naturally fractured lean gas condensate reservoir and investigate the effect of condensate formed around the well-bore on behavior of single phase pseudo pressure and its derivative curves. In this work a naturally fractured lean gas condensate reservoir is simulated with compositional simulator. Different sensitivity analysis done on Corry parameters and result of simulator is feed to analytical well testing software. For consideration of these phenomena eighteen compositional models with Capillary number effect are constructed. Matrix relative permeability obeys Corry relative permeability and relative permeability in fracture is linear. Well testing behavior of these models are studied and interpreted. Results show different sensitivity analysis on relative permeability of matrix does not have strong effect on well testing behavior even most part of the matrix around the well is occupied with condensate.
Abstract: In pressure vessels contain hydrogen, the role of
hydrogen will be important because of hydrogen cracking problem. It
is difficult to predict what is happened in metallurgical field spite of a
lot of studies have been searched. The main role in controlling the
mass diffusion as driving force is related to stress. In this study, finite
element analysis is implemented to estimate material-s behavior
associated with hydrogen embrittlement. For this purpose, one model
of a pressure vessel is introduced that it has definite boundary and
initial conditions. In fact, finite element is employed to solve the
sequentially coupled mass diffusion with stress near a crack front in a
pressure vessel. Modeling simulation intergrarnular fracture of AISI
4135 steel due to hydrogen is investigated. So, distribution of
hydrogen and stress are obtained and they indicate that their
maximum amounts occur near the crack front. This phenomenon is
happened exactly the region between elastic and plastic field.
Therefore, hydrogen is highly mobile and can diffuse through crystal
lattice so that this zone is potential to trap high volume of hydrogen.
Consequently, crack growth and fast fracture will be happened.