Abstract: Sclareolide is made from sclareol by oxidiative synthesis and subsequent crystallization, while the crystallization mother liquor still contains 15%~30%wt of sclareolide to be reclaimed. With the reaction material of sclareol is provided as plant extract, many sorts of complex impurities exist in the mother liquor. Due to the difficulty in recycling sclareolide after solvent recovery, it is common practice for the factories to discard the mother liquor, which not only results in loss of sclareolide, but also contributes extra environmental burden. In this paper, a process based on adsorption and elution has been presented for recycling of sclareolide from mother liquor. After pretreatment of the crystallization mother liquor by HZ-845 resin to remove parts of impurities, sclareolide is adsorbed by HZ-816 resin. The HZ-816 resin loaded with sclareolide is then eluted by elution solvent. Finally, the eluent containing sclareolide is concentrated and fed into the crystallization step in the process. By adoption of the recycle from mother liquor, total yield of sclareolide increases from 86% to 90% with a stable purity of the final sclareolide products maintained.
Abstract: To increase the quality of learning, teacher and learner need mutual effort for realization of educational value. For this purpose, we need to manage the co-creational education among teacher and learners. In this research, we try to find a feature of co-creational education. To be more precise, we analyzed learners’ reports by natural language processing, and extract some features that describe the state of the co-creational education.
Abstract: This article considers the problems of economic growth
and Russian energy strategy. Also in this paper, the issues related to
the economic growth prospects of Russian were discussed. Russian
energy strategy without standing Russia`s stature in global energy
markets, at the current production and extraction rates, will not be able
to sustain its own production as well as fulfil its energy strategy.
Indeed, Russia’s energy sector suffers from a chronic lack of
investments which are necessary to modernize its energy supply
system. In recent years, especially since the international financial
crisis, Russia-EU energy cooperation has made substantive progress.
Recently the break-through progress has been made, resulting mainly
from long-term contributing factors between the countries and recent
international economic and political situation changes. Analytical
material presented in the article is intended for a more detailed or
substantive analysis related to foreign economic relations of the
countries and Russia as well.
Abstract: Community living adjacent to forests and Protected
Areas, especially in South Asian countries, have a common practice
in extracting resources for their living and livelihoods. This
extraction of resources, because the way it is done, destroys the biophysical
features of the area. Deforestation, wildlife poaching, illegal
logging, unauthorized hill cutting etc. are some of the serious issues
of concern for the sustainability of the natural resources that has a
direct impact on environment and climate as a whole. To ensure
community involvement in conservation initiatives of the state,
community based forest management, commonly known as Comanagement,
has been in practice in 6 South Asian countries. These
are -India, Nepal, Sri Lanka, Pakistan, Bhutan and Bangladesh.
Involving community in forestry management was initiated first in
Bangladesh in 1979 and reached as an effective co-management
approach through a several paradigm shifts. This idea of Comanagement
has been institutionalized through a Government Order
(GO) by the Ministry of Environment and Forests, Government of
Bangladesh on November 23, 2009. This GO clearly defines the
structure and functions of Co-management and its different bodies.
Bangladesh Forest Department has been working in association with
community to conserve and manage the Forests and Protected areas
of Bangladesh following this legal document. Demographically
young people constitute the largest segment of population in
Bangladesh. This group, if properly sensitized, can produce valuable
impacts on the conservation initiatives, both by community and
government. This study traced the major factors that motivate
community youths to work effectively with different tiers of comanagement
organizations in conservation of forests and Protected
Areas of Bangladesh. For the purpose of this study, 3 FGDs were
conducted with 30 youths from the community living around the
Protected Areas of Cox’s bazar, South East corner of Bangladesh,
who are actively involved in Co-management organizations. KII were
conducted with 5 key officials of Forest Department stationed at
Cox’s Bazar. 2 FGDs were conducted with the representatives of 7
Co-management organizations working in Cox’s Bazar region and
approaches of different community outreach activities conducted for
forest conservation by 3 private organizations and Projects have been
reviewed. Also secondary literatures were reviewed for the history
and evolution of Co-management in Bangladesh and six South Asian
countries. This study found that innovative community outreach
activities that are financed by public and private sectors involving
youths and community as a whole have played a pivotal role in
conservation of forests and Protected Areas of the region. This
approach can be replicated in other regions of Bangladesh as well as
other countries of South Asia where Co-Management exists in
practice.
Abstract: Sisal leaves were subjected to enzymatic retting
method to extract the sisal fibre. A portion of the fibre was pretreated
with alkali (NaOH), and further treated with benzoyl chloride
and silane treatment reagents. Both the treated and untreated Sisal
fibre composites were used to fabricate the composite by hand lay-up
technique using unsaturated polyester resin. Tensile, flexural, water
absorption, density, thickness swelling and chemical resistant tests
were conducted and evaluated on the composites. Results obtained
for all the parameters showed an increase in the treated fibre
compared to untreated fibre. FT-IR spectra results ascertained the
inclusion of benzoyl and silane groups on the fibre surface. Scanning
electron microscopy (SEM) result obtained showed variation in the
morphology of the treated and untreated fibre. Chemical modification
was found to improve adhesion of the fibre to the matrix, as well as
physico-mechanical properties of the composites.
Abstract: Green chemistry for plant extraction of active principles is the main interest of many researchers concerned with climate change. While classical organic solvents are detrimental to our environment, greener alternatives to ionic liquids are very promising for sustainable organic chemistry. This study focused on the determination of functional groups observed in the main constituents from the ionic liquid extracts of Coleus aromaticus Benth leaves using FT-IR Spectroscopy. Moreover, this research aimed to determine the best ionic liquid that can separate functionalized plant constituents from the leaves Coleus aromaticus Benth using Fourier Transform Infrared Spectroscopy. Coleus aromaticus Benth leaf extract in different ionic liquids, elucidated pharmacologically important functional groups present in major constituents of the plant, namely, rosmarinic acid, caffeic acid and chlorogenic acid. In connection to distinctive appearance of functional groups in the spectrum and highest % transmittance, potassium chloride-glycerol is the best ionic liquid for green extraction.
Abstract: The UK has had its fair share of the shale gas
revolutionary waves blowing across the global oil and gas industry at
present. Although, its exploitation is widely agreed to have been
delayed, shale gas was looked upon favorably by the UK Parliament
when they recognized it as genuine energy source and granted
licenses to industry to search and extract the resource. This, although
a significant progress by industry, there yet remains another test the
UK fracking resource must pass in order to render shale gas
extraction feasible – it must be economically extractible and
sustainably so. Developing unconventional resources is much more
expensive and risky, and for shale gas wells, producing in
commercial volumes is conditional upon drilling horizontal wells and
hydraulic fracturing, techniques which increase CAPEX. Meanwhile,
investment in shale gas development projects is sensitive to gas price
and technical and geological risks. Using a Two-Factor Model, the
economics of the Bowland shale wells were analyzed and the
operational conditions under which fracking is profitable in the UK
was characterized. We find that there is a great degree of flexibility
about Opex spending; hence Opex does not pose much threat to the
fracking industry in the UK. However, we discover Bowland shale
gas wells fail to add value at gas price of $8/ Mmbtu. A minimum gas
price of $12/Mmbtu at Opex of no more than $2/ Mcf and no more
than $14.95M Capex are required to create value within the present
petroleum tax regime, in the UK fracking industry.
Abstract: Growth and remodeling of biological structures have
gained lots of attention over the past decades. Determining the
response of living tissues to mechanical loads is necessary for a wide
range of developing fields such as prosthetics design or computerassisted
surgical interventions. It is a well-known fact that biological
structures are never stress-free, even when externally unloaded. The
exact origin of these residual stresses is not clear, but theoretically,
growth is one of the main sources. Extracting body organ’s shapes
from medical imaging does not produce any information regarding
the existing residual stresses in that organ. The simplest cause of such
stresses is gravity since an organ grows under its influence from
birth. Ignoring such residual stresses might cause erroneous results in
numerical simulations. Accounting for residual stresses due to tissue
growth can improve the accuracy of mechanical analysis results. This
paper presents an original computational framework based on gradual
growth to determine the residual stresses due to growth. To illustrate
the method, we apply it to a finite element model of a healthy human
face reconstructed from medical images. The distribution of residual
stress in facial tissues is computed, which can overcome the effect of
gravity and maintain tissues firmness. Our assumption is that tissue
wrinkles caused by aging could be a consequence of decreasing
residual stress and thus not counteracting gravity. Taking into
account these stresses seems therefore extremely important in
maxillofacial surgery. It would indeed help surgeons to estimate
tissues changes after surgery.
Abstract: Recently, traffic monitoring has attracted the attention
of computer vision researchers. Many algorithms have been
developed to detect and track moving vehicles. In fact, vehicle
tracking in daytime and in nighttime cannot be approached with the
same techniques, due to the extreme different illumination conditions.
Consequently, traffic-monitoring systems are in need of having a
component to differentiate between daytime and nighttime scenes. In
this paper, a HSV-based day/night detector is proposed for traffic
monitoring scenes. The detector employs the hue-histogram and the
value-histogram on the top half of the image frame. Experimental
results show that the extraction of the brightness features along with
the color features within the top region of the image is effective for
classifying traffic scenes. In addition, the detector achieves high
precision and recall rates along with it is feasible for real time
applications.
Abstract: Data fusion technology can be the best way to extract
useful information from multiple sources of data. It has been widely
applied in various applications. This paper presents a data fusion
approach in multimedia data for event detection in twitter by using
Dempster-Shafer evidence theory. The methodology applies a mining
algorithm to detect the event. There are two types of data in the
fusion. The first is features extracted from text by using the bag-ofwords
method which is calculated using the term frequency-inverse
document frequency (TF-IDF). The second is the visual features
extracted by applying scale-invariant feature transform (SIFT). The
Dempster - Shafer theory of evidence is applied in order to fuse the
information from these two sources. Our experiments have indicated
that comparing to the approaches using individual data source, the
proposed data fusion approach can increase the prediction accuracy
for event detection. The experimental result showed that the proposed
method achieved a high accuracy of 0.97, comparing with 0.93 with
texts only, and 0.86 with images only.
Abstract: Nowadays, education cannot be imagined without digital technologies. It broadens the horizons of teaching learning processes. Several universities are offering online courses. For evaluation purpose, e-examination systems are being widely adopted in academic environments. Multiple-choice tests are extremely popular. Moving away from traditional examinations to e-examination, Moodle as Learning Management Systems (LMS) is being used. Moodle logs every click that students make for attempting and navigational purposes in e-examination. Data mining has been applied in various domains including retail sales, bioinformatics. In recent years, there has been increasing interest in the use of data mining in e-learning environment. It has been applied to discover, extract, and evaluate parameters related to student’s learning performance. The combination of data mining and e-learning is still in its babyhood. Log data generated by the students during online examination can be used to discover knowledge with the help of data mining techniques. In web based applications, number of right and wrong answers of the test result is not sufficient to assess and evaluate the student’s performance. So, assessment techniques must be intelligent enough. If student cannot answer the question asked by the instructor then some easier question can be asked. Otherwise, more difficult question can be post on similar topic. To do so, it is necessary to identify difficulty level of the questions. Proposed work concentrate on the same issue. Data mining techniques in specific clustering is used in this work. This method decide difficulty levels of the question and categories them as tough, easy or moderate and later this will be served to the desire students based on their performance. Proposed experiment categories the question set and also group the students based on their performance in examination. This will help the instructor to guide the students more specifically. In short mined knowledge helps to support, guide, facilitate and enhance learning as a whole.
Abstract: This paper describes an ab-initio design, development and calibration results of an Optical Sensor Ground Reaction Force Measurement Platform (OSGRFP) for gait and geriatric studies. The developed system employs an array of FBG sensors to measure the respective ground reaction forces from all three axes (X, Y and Z), which are perpendicular to each other. The novelty of this work is two folded. One is in its uniqueness to resolve the tri axial resultant forces during the stance in to the respective pure axis loads and the other is the applicability of inherently advantageous FBG sensors which are most suitable for biomechanical instrumentation. To validate the response of the FBG sensors installed in OSGRFP and to measure the cross sensitivity of the force applied in other directions, load sensors with indicators are used. Further in this work, relevant mathematical formulations are presented for extracting respective ground reaction forces from wavelength shifts/strain of FBG sensors on the OSGRFP. The result of this device has implications in understanding the foot function, identifying issues in gait cycle and measuring discrepancies between left and right foot. The device also provides a method to quantify and compare relative postural stability of different subjects under test, which has implications in post-surgical rehabilitation, geriatrics and optimizing training protocols for sports personnel.
Abstract: In the deep south of Thailand, checkpoints for people
verification are necessary for the security management of risk zones,
such as official buildings in the conflict area. In this paper, we
propose an automatic checkpoint system that verifies persons using
information from ID cards and facial features. The methods for a
person’s information abstraction and verification are introduced
based on useful information such as ID number and name, extracted
from official cards, and facial images from videos. The proposed
system shows promising results and has a real impact on the local
society.
Abstract: Medicinal and aromatic plants are promising and are characterized by the biosynthesis of odorous molecules that make up the so-called essential oils (EO), which have long been known for their antiseptic and therapeutic activity in folk medicine. Essential oils have many therapeutic properties. In herbal medicine, they are used for their antiseptic properties against infectious diseases of fungal origin, against dermatophytes, those of bacterial origin. The objective of this study was to evaluate the influence of drying in the shade on the water content and on the content of essential oils extracted from leaves of Eucalyptus camendulensis for better quality control of medicinal and aromatic plants. The water content of the Eucalyptus camendulensis plant material decreases during the drying process. It decreased from 100% to 0.006% for the drying in the shade after ten days. The moisture content is practically constant at the end of the drying period. The drying in the shade increases the concentration of essential oils of Eucalyptus camendulensis. When the leaves of Eucalyptus camendulensis plant are in the shade, the maximum of the essential oil content was obtained on the eighth day, the recorded value was 1.43% ± 0.01%. Beyond these periods, the content continuously drop in before stabilizing. The optimum drying time is between 6 and 9 days.
Abstract: In order to retrieve images efficiently from a large
database, a unique method integrating color and texture features
using genetic programming has been proposed. Opponent color
histogram which gives shadow, shade, and light intensity invariant
property is employed in the proposed framework for extracting color
features. For texture feature extraction, fast discrete curvelet
transform which captures more orientation information at different
scales is incorporated to represent curved like edges. The recent
scenario in the issues of image retrieval is to reduce the semantic gap
between user’s preference and low level features. To address this
concern, genetic algorithm combined with relevance feedback is
embedded to reduce semantic gap and retrieve user’s preference
images. Extensive and comparative experiments have been conducted
to evaluate proposed framework for content based image retrieval on
two databases, i.e., COIL-100 and Corel-1000. Experimental results
clearly show that the proposed system surpassed other existing
systems in terms of precision and recall. The proposed work achieves
highest performance with average precision of 88.2% on COIL-100
and 76.3% on Corel, the average recall of 69.9% on COIL and 76.3%
on Corel. Thus, the experimental results confirm that the proposed
content based image retrieval system architecture attains better
solution for image retrieval.
Abstract: Multiple Sclerosis (MS) is a disease which affects the
central nervous system and causes balance problem. In clinical, this
disorder is usually evaluated using static posturography. Some linear
or nonlinear measures, extracted from the posturographic data (i.e.
center of pressure, COP) recorded during a balance test, has been
used to analyze postural control of MS patients. In this study, the
trend (TREND) and the sample entropy (SampEn), two nonlinear
parameters were chosen to investigate their relationships with the
expanded disability status scale (EDSS) score. 40 volunteers with
different EDSS scores participated in our experiments with eyes open
(EO) and closed (EC). TREND and 2 types of SampEn (SampEn1
and SampEn2) were calculated for each combined COP’s position
signal. The results have shown that TREND had a weak negative
correlation to EDSS while SampEn2 had a strong positive correlation
to EDSS. Compared to TREND and SampEn1, SampEn2 showed a
better significant correlation to EDSS and an ability to discriminate
the MS patients in the EC case. In addition, the outcome of the study
suggests that the multi-dimensional nonlinear analysis could provide
some information about the impact of disability progression in MS on
dynamics of the COP data.
Abstract: In this research, we propose to conduct diagnostic and
predictive analysis about the key factors and consequences of urban
population relocation. To achieve this goal, urban simulation models
extract the urban development trends as land use change patterns from
a variety of data sources. The results are treated as part of urban big
data with other information such as population change and economic
conditions. Multiple data mining methods are deployed on this data to
analyze nonlinear relationships between parameters. The result
determines the driving force of population relocation with respect to
urban sprawl and urban sustainability and their related parameters.
This work sets the stage for developing a comprehensive urban
simulation model for catering to specific questions by targeted users. It
contributes towards achieving sustainability as a whole.
Abstract: In this paper, an approach for the liver tumor detection
in computed tomography (CT) images is represented. The detection
process is based on classifying the features of target liver cell to
either tumor or non-tumor. Fractional differential (FD) is applied for
enhancement of Liver CT images, with the aim of enhancing texture
and edge features. Later on, a fusion method is applied to merge
between the various enhanced images and produce a variety of
feature improvement, which will increase the accuracy of
classification. Each image is divided into NxN non-overlapping
blocks, to extract the desired features. Support vector machines
(SVM) classifier is trained later on a supplied dataset different from
the tested one. Finally, the block cells are identified whether they are
classified as tumor or not. Our approach is validated on a group of
patients’ CT liver tumor datasets. The experiment results
demonstrated the efficiency of detection in the proposed technique.
Abstract: Advances in spatial and spectral resolution of satellite
images have led to tremendous growth in large image databases. The
data we acquire through satellites, radars, and sensors consists of
important geographical information that can be used for remote
sensing applications such as region planning, disaster management.
Spatial data classification and object recognition are important tasks
for many applications. However, classifying objects and identifying
them manually from images is a difficult task. Object recognition is
often considered as a classification problem, this task can be
performed using machine-learning techniques. Despite of many
machine-learning algorithms, the classification is done using
supervised classifiers such as Support Vector Machines (SVM) as the
area of interest is known. We proposed a classification method,
which considers neighboring pixels in a region for feature extraction
and it evaluates classifications precisely according to neighboring
classes for semantic interpretation of region of interest (ROI). A
dataset has been created for training and testing purpose; we
generated the attributes by considering pixel intensity values and
mean values of reflectance. We demonstrated the benefits of using
knowledge discovery and data-mining techniques, which can be on
image data for accurate information extraction and classification from
high spatial resolution remote sensing imagery.
Abstract: With the advancement of knowledge about the utility
and impact of sustainability, its feasibility has been explored into
different walks of life. Scientists, however; have established their
knowledge in four areas viz environmental, economic, social and
cultural, popularly termed as four pillars of sustainability. Aspects of
environmental and economic sustainability have been rigorously
researched and practiced and huge volume of strong evidence of
effectiveness has been founded for these two sub-areas. For the social
and cultural aspects of sustainability, dependable evidence of
effectiveness is still to be instituted as the researchers and
practitioners are developing and experimenting methods across the
globe. Therefore, the present research aimed to identify globally used
practices of social and cultural sustainability and through evidence
synthesis assess their outcomes to determine the effectiveness of
those practices. A PICO format steered the methodology which
included all populations, popular sustainability practices including
walkability/cycle tracks, social/recreational spaces, privacy, health &
human services and barrier free built environment, comparators
included ‘Before’ and ‘After’, ‘With’ and ‘Without’, ‘More’ and
‘Less’ and outcomes included Social well-being, cultural coexistence,
quality of life, ethics and morality, social capital, sense of
place, education, health, recreation and leisure, and holistic
development. Search of literature included major electronic
databases, search websites, organizational resources, directory of
open access journals and subscribed journals. Grey literature,
however, was not included. Inclusion criteria filtered studies on the
basis of research designs such as total randomization, quasirandomization,
cluster randomization, observational or single studies
and certain types of analysis. Studies with combined outcomes were
considered but studies focusing only on environmental and/or
economic outcomes were rejected. Data extraction, critical appraisal
and evidence synthesis was carried out using customized tabulation,
reference manager and CASP tool. Partial meta-analysis was carried
out and calculation of pooled effects and forest plotting were done.
As many as 13 studies finally included for final synthesis explained
the impact of targeted practices on health, behavioural and social
dimensions. Objectivity in the measurement of health outcomes
facilitated quantitative synthesis of studies which highlighted the
impact of sustainability methods on physical activity, Body Mass
Index, perinatal outcomes and child health. Studies synthesized
qualitatively (and also quantitatively) showed outcomes such as
routines, family relations, citizenship, trust in relationships, social
inclusion, neighbourhood social capital, wellbeing, habitability and
family’s social processes. The synthesized evidence indicates slight
effectiveness and efficacy of social and cultural sustainability on the
targeted outcomes. Further synthesis revealed that such results of this
study are due weak research designs and disintegrated implementations. If architects and other practitioners deliver their
interventions in collaboration with research bodies and policy
makers, a stronger evidence-base in this area could be generated.