Abstract: The introduction of degradable plastic materials into
agricultural sectors has represented a promising alternative to
promote green agriculture and environmental friendly of modern
farming practices. Major challenges of developing degradable
agricultural films are to identify the most feasible types of
degradation mechanisms, composition of degradable polymers and
related processing techniques. The incorrect choice of degradable
mechanisms to be applied during the degradation process will cause
premature losses of mechanical performance and strength. In order to
achieve controlled process of agricultural film degradation, the
compositions of degradable agricultural film also important in order
to stimulate degradation reaction at required interval of time and to
achieve sustainability of the modern agricultural practices. A set of
photodegradable polyethylene based agricultural film was developed
and produced, following the selective optimization of processing
parameters of the agricultural film manufacturing system. Example of
agricultural films application for oil palm seedlings cultivation is
presented.
Abstract: This paper discusses the value theory in cultural
heritage and the value theory in environmental economics. Two
economic views of the value theory are compared, within the field of
cultural heritage maintenance and within the field of the environment.
The main aims are to find common features in these two differently
structured theories under the layer of differently defined terms as well
as really differing features of these two approaches; to clear the
confusion which stems from different terminology as in fact these
terms capture the same aspects of reality; and to show possible
inspiration these two perspectives can offer one another. Another aim
is to present these two value systems in one value framework. First,
important moments of the value theory from the economic
perspective are presented, leading to the marginal revolution of (not
only) the Austrian School. Then the theory of value within cultural
heritage and environmental economics are explored. Finally,
individual approaches are compared and their potential mutual
inspiration searched for.
Abstract: Incineration of municipal solid waste (MSW) is one of
the key scopes in the global clean energy strategy. A computational
fluid dynamics (CFD) model was established in order to reveal these
features of the combustion process in a fixed porous bed of MSW.
Transporting equations and process rate equations of the waste bed
were modeled and set up to describe the incineration process,
according to the local thermal conditions and waste property
characters. Gas phase turbulence was modeled using k-ε turbulent
model and the particle phase was modeled using the kinetic theory of
granular flow. The heterogeneous reaction rates were determined
using Arrhenius eddy dissipation and the Arrhenius-diffusion
reaction rates. The effects of primary air flow rate and temperature in
the burning process of simulated MSW are investigated
experimentally and numerically. The simulation results in bed are
accordant with experimental data well. The model provides detailed
information on burning processes in the fixed bed, which is otherwise
very difficult to obtain by conventional experimental techniques.
Abstract: This study analyzes the innovative orientation of the
Croatian entrepreneurs. Innovative orientation is represented by the
perceived extent to which an entrepreneur’s product or service or
technology is new, and no other businesses offer the same product.
The sample is extracted from the GEM Croatia Adult Population
Survey dataset for the years 2003-2013. We apply descriptive
statistics, t-test, Chi-square test and logistic regression. Findings
indicate that innovative orientations vary with personal, firm, meso
and macro level variables, and between different stages in
entrepreneurship process. Significant predictors are occupation of the
entrepreneurs, size of the firm and export aspiration for both early
stage and established entrepreneurs. In addition, fear of failure,
expecting to start a new business and seeing an entrepreneurial career
as a desirable choice are predictors of innovative orientation among
early stage entrepreneurs.
Abstract: Data mining idea is mounting rapidly in admiration
and also in their popularity. The foremost aspire of data mining
method is to extract data from a huge data set into several forms that
could be comprehended for additional use. The data mining is a
technology that contains with rich potential resources which could be
supportive for industries and businesses that pay attention to collect
the necessary information of the data to discover their customer’s
performances. For extracting data there are several methods are
available such as Classification, Clustering, Association,
Discovering, and Visualization… etc., which has its individual and
diverse algorithms towards the effort to fit an appropriate model to
the data. STATISTICA mostly deals with excessive groups of data
that imposes vast rigorous computational constraints. These results
trials challenge cause the emergence of powerful STATISTICA Data
Mining technologies. In this survey an overview of the STATISTICA
software is illustrated along with their significant features.
Abstract: In this paper, we discuss the performance of applying
hybrid spiral dynamic bacterial chemotaxis (HSDBC) optimisation
algorithm on an intelligent controller for a differential drive robot. A
unicycle class of differential drive robot is utilised to serve as a basis
application to evaluate the performance of the HSDBC algorithm. A
hybrid fuzzy logic controller is developed and implemented for the
unicycle robot to follow a predefined trajectory. Trajectories of
various frictional profiles and levels were simulated to evaluate the
performance of the robot at different operating conditions. Controller
gains and scaling factors were optimised using HSDBC and the
performance is evaluated in comparison to previously adopted
optimisation algorithms. The HSDBC has proven its feasibility in
achieving a faster convergence toward the optimal gains and resulted
in a superior performance.
Abstract: This article discusses ways to implement a
differentiated approach to developing academic motivation for
mathematical studies which relies on defining the primary structural
characteristics of motivation. The following characteristics are
considered: features of realization of cognitive activity, meaningmaking
characteristics, level of generalization and consistency of
knowledge acquired by personal experience. The assessment of the
present level of individual student understanding of each component
of academic motivation is the basis for defining the relevant
educational strategy for its further development.
Abstract: Adolescents with Autism Spectrum Disorders (ASD)
often experience social-communication difficulties that negatively
impact their social interactions with typical peers. However, unlike
other age and disability groups, there is little intervention research to
inform best practice for these students. One evidence-based strategy
for younger students with ASD is peer-mediated intervention (PMI).
PMI may be particularly promising for use with adolescents, as peers
are readily available and are natural experts for encouraging authentic
high school conversations. This paper provides a review of previous
research that evaluated the use of PMI to improve the socialcommunication
skills of students with ASD. Specific intervention
features associated with positive student outcomes are identified and
recommendations for future research are provided. Adolescents with
ASD are targeted due the critical importance of social conversation at
the high school level.
Abstract: Array-based gene expression analysis is a powerful
tool to profile expression of genes and to generate information on
therapeutic effects of new anti-cancer compounds. Anti-apoptotic
effect of thymoquinone was studied in MCF7 breast cancer cell line
using gene expression profiling with cDNA microarray. The purity
and yield of RNA samples were determined using RNeasyPlus Mini
kit. The Agilent RNA 6000 NanoLabChip kit evaluated the quantity
of the RNA samples. AffinityScript RT oligo-dT promoter primer
was used to generate cDNA strands. T7 RNA polymerase was used to
convert cDNA to cRNA. The cRNA samples and human universal
reference RNA were labelled with Cy-3-CTP and Cy-5-CTP,
respectively. Feature Extraction and GeneSpring softwares analysed
the data. The single experiment analysis revealed involvement of 64
pathways with up-regulated genes and 78 pathways with downregulated
genes. The MAPK and p38-MAPK pathways were
inhibited due to the up-regulation of PTPRR gene. The inhibition of
p38-MAPK suggested up-regulation of TGF-ß pathway. Inhibition of
p38-MAPK caused up-regulation of TP53 and down-regulation of
Bcl2 genes indicating involvement of intrinsic apoptotic pathway.
Down-regulation of CARD16 gene as an adaptor molecule regulated
CASP1 and suggested necrosis-like programmed cell death and
involvement of caspase in apoptosis. Furthermore, down-regulation
of GPCR, EGF-EGFR signalling pathways suggested reduction of
ER. Involvement of AhR pathway which control cytochrome P450
and glucuronidation pathways showed metabolism of Thymoquinone.
The findings showed differential expression of several genes in
apoptosis pathways with thymoquinone treatment in estrogen
receptor-positive breast cancer cells.
Abstract: The paper describes the OAS role in dispute
resolution. The authors make an attempt to identify a general pattern
of the OAS activities within the peaceful settlement of interstate
conflicts, in the beginning of 21st century, as well as to analyze some
features of Honduras–Belize, Nicaragua–Honduras, Honduras–El
Salvador, Costa-Rica–Nicaragua, Colombia–Ecuador cases.
Abstract: The building sector is responsible, in many
industrialized countries, for about 40% of the total energy
requirements, so it seems necessary to devote some efforts in this
area in order to achieve a significant reduction of energy
consumption and of greenhouse gases emissions.
The paper presents a study aiming at providing a design
methodology able to identify the best configuration of the system
building/plant, from a technical, economic and environmentally point
of view.
Normally, the classical approach involves a building's energy
loads analysis under steady state conditions, and subsequent selection
of measures aimed at improving the energy performance, based on
previous experience made by architects and engineers in the design
team. Instead, the proposed approach uses a sequence of two wellknown
scientifically validated calculation methods (TRNSYS and
RETScreen), that allow quite a detailed feasibility analysis.
To assess the validity of the calculation model, an existing,
historical building in Central Italy, that will be the object of
restoration and preservative redevelopment, was selected as a casestudy.
The building is made of a basement and three floors, with a
total floor area of about 3,000 square meters.
The first step has been the determination of the heating and
cooling energy loads of the building in a dynamic regime by means,
which allows simulating the real energy needs of the building in
function of its use. Traditional methodologies, based as they are on
steady-state conditions, cannot faithfully reproduce the effects of
varying climatic conditions and of inertial properties of the structure.
With this model is possible to obtain quite accurate and reliable
results that allow identifying effective combinations building-HVAC
system.
The second step has consisted of using output data obtained as
input to the calculation model, which enables to compare different
system configurations from the energy, environmental and financial
point of view, with an analysis of investment, and operation and
maintenance costs, so allowing determining the economic benefit of
possible interventions.
The classical methodology often leads to the choice of
conventional plant systems, while our calculation model provides a
financial-economic assessment for innovative energy systems and
low environmental impact.
Computational analysis can help in the design phase, particularly
in the case of complex structures with centralized plant systems, by
comparing the data returned by the calculation model for different
design options.
Abstract: Nowadays, huge amount of multimedia repositories
make the browsing, retrieval and delivery of video contents very slow
and even difficult tasks. Video summarization has been proposed to
improve faster browsing of large video collections and more efficient
content indexing and access. In this paper, we focus on approaches to
video summarization. The video summaries can be generated in many
different forms. However, two fundamentals ways to generate
summaries are static and dynamic. We present different techniques
for each mode in the literature and describe some features used for
generating video summaries. We conclude with perspective for
further research.
Abstract: Offering a Product-Service System (PSS) is a
well-accepted strategy that companies may adopt to provide a set of
systemic solutions to customers. PSSs were initially provided in a
simple form but now take diversified and complex forms involving
multiple services, products and technologies. With the growing
interest in the PSS, frameworks for the PSS development have been
introduced by many researchers. However, most of the existing
frameworks fail to examine various relations existing in a complex
PSS. Since designing a complex PSS involves full integration of
multiple products and services, it is essential to identify not only
product-service relations but also product-product/ service-service
relations. It is also equally important to specify how they are related
for better understanding of the system. Moreover, as customers tend to
view their purchase from a more holistic perspective, a PSS should be
developed based on the whole system’s requirements, rather than
focusing only on the product requirements or service requirements.
Thus, we propose a framework to develop a complex PSS that is
coordinated fully with the requirements of both worlds. Specifically,
our approach adopts a multi-domain matrix (MDM). A MDM
identifies not only inter-domain relations but also intra-domain
relations so that it helps to design a PSS that includes highly desired
and closely related core functions/ features. Also, various dependency
types and rating schemes proposed in our approach would help the
integration process.
Abstract: Pulmonary Function Tests are important non-invasive
diagnostic tests to assess respiratory impairments and provides
quantifiable measures of lung function. Spirometry is the most
frequently used measure of lung function and plays an essential role
in the diagnosis and management of pulmonary diseases. However,
the test requires considerable patient effort and cooperation,
markedly related to the age of patients resulting in incomplete data
sets. This paper presents, a nonlinear model built using Multivariate
adaptive regression splines and Random forest regression model to
predict the missing spirometric features. Random forest based feature
selection is used to enhance both the generalization capability and the
model interpretability. In the present study, flow-volume data are
recorded for N= 198 subjects. The ranked order of feature importance
index calculated by the random forests model shows that the
spirometric features FVC, FEF25, PEF, FEF25-75, FEF50 and the
demographic parameter height are the important descriptors. A
comparison of performance assessment of both models prove that, the
prediction ability of MARS with the `top two ranked features namely
the FVC and FEF25 is higher, yielding a model fit of R2= 0.96 and
R2= 0.99 for normal and abnormal subjects. The Root Mean Square
Error analysis of the RF model and the MARS model also shows that
the latter is capable of predicting the missing values of FEV1 with a
notably lower error value of 0.0191 (normal subjects) and 0.0106
(abnormal subjects) with the aforementioned input features. It is
concluded that combining feature selection with a prediction model
provides a minimum subset of predominant features to train the
model, as well as yielding better prediction performance. This
analysis can assist clinicians with a intelligence support system in the
medical diagnosis and improvement of clinical care.
Abstract: MSMEs are regarded as the sunrise sector of the
Indian economy in view of its large potential for growth and likely
socio economic impact specifically on employment and income
generation. In today’s competitive business environment, global
competition forces companies to continuously seek ways of
improving their products and services. The pressure on organizations
to adapt to new technologies and external threats requires
resourcefulness, creativity and innovation. Market has become more
open, competitive and customers more demanding. Without
continuous technology innovation, no organization can ever remain
competitive. Innovations reflect a critical way in which organizations
respond to either technological or market challenges. The need of the
market is to deliver high quality products through continuous
changing in features in product, improve existing products, reduce
their cost, and improve employee skills, training, technology
infrastructure and financial policies. Therefore, the key factor of
organization’s ability to change is innovation. The study presents a
detailed review of literature on the role of technology innovation in
improving manufacturing performance of industries.
Abstract: Africa enjoys some of the best solar radiation levels in
the world averaging between 4-6 kWh/m2/day for most of the year
and the global economic and political conditions that tend to make
African countries more dependent on their own energy resources
have caused growing interest in renewable energy based
technologies. However to-date, implementation of modern Energy
Technologies in Africa is still very low especially the use of solar
conversion technologies. This paper presents literature review and
analysis relating to the techno-economic feasibility of solar
photovoltaic power generation in Africa. The literature is basically
classified into the following four main categories. Techno-economic
feasibility of solar photovoltaic power generation, design methods,
performance evaluations of various systems and policy of potential
future of technological development of photovoltaic (PV) in Africa
by exploring the impact of alternative policy instruments and
technology cost reductions on the financial viability of investing solar
photovoltaic in Africa.
Abstract: This paper addresses the issue of the autonomous
mobile robot (AMR) navigation task based on the hybrid control
modes. The novel hybrid control mode, based on multi-sensors
information by using the fuzzy approach, has been presented in this
research. The system operates in real time, is robust, enables the robot
to operate with imprecise knowledge, and takes into account the
physical limitations of the environment in which the robot moves,
obtaining satisfactory responses for a large number of different
situations. An experiment is simulated and carried out with a pioneer
mobile robot. From the experimental results, the effectiveness and
usefulness of the proposed AMR obstacle avoidance and navigation
scheme are confirmed. The experimental results show the feasibility,
and the control system has improved the navigation accuracy. The
implementation of the controller is robust, has a low execution time,
and allows an easy design and tuning of the fuzzy knowledge base.
Abstract: Electroencephalogram (EEG) is a noninvasive
technique that registers signals originating from the firing of neurons
in the brain. The Emotiv EEG Neuroheadset is a consumer product
comprised of 14 EEG channels and was used to record the reactions
of the neurons within the brain to two forms of stimuli in 10
participants. These stimuli consisted of auditory and visual formats
that provided directions of ‘right’ or ‘left.’ Participants were
instructed to raise their right or left arm in accordance with the
instruction given. A scenario in OpenViBE was generated to both
stimulate the participants while recording their data. In OpenViBE,
the Graz Motor BCI Stimulator algorithm was configured to govern
the duration and number of visual stimuli. Utilizing EEGLAB under
the cross platform MATLAB®, the electrodes most stimulated during
the study were defined. Data outputs from EEGLAB were analyzed
using IBM SPSS Statistics® Version 20. This aided in determining
the electrodes to use in the development of a brain-machine interface
(BMI) using real-time EEG signals from the Emotiv EEG
Neuroheadset. Signal processing and feature extraction were
accomplished via the Simulink® signal processing toolbox. An
Arduino™ Duemilanove microcontroller was used to link the Emotiv
EEG Neuroheadset and the right and left Mecha TE™ Hands.
Abstract: Carbon Deposits are often occurred inside the
industrial coke oven during coking process. Accumulation of carbon
deposits may cause a big issue, which seriously influences the coking
operation. The carbon is burning off by injecting fresh air through
pipes into coke oven which is an efficient way practically operated in
industries. The burning off carbon deposition in coke oven performed
by Computational Fluid Dynamics (CFD) method has provided an
evaluation of the feasibility study. A three dimensional, transient,
turbulent reacting flow simulation has performed with three different
injecting air flow rate and another kind of injecting configuration. The
result shows that injection higher air flow rate would effectively
reduce the carbon deposits. In the meantime, the opened charging
holes would suck extra oxygen from atmosphere to participate in
reactions. In term of coke oven operating limits, the wall temperatures
are monitored to prevent over-heating of the adiabatic walls during
burn-off process.
Abstract: This paper presents two techniques, local feature
extraction using image spectrum and low frequency spectrum
modelling using GMM to capture the underlying statistical
information to improve the performance of face recognition
system. Local spectrum features are extracted using overlap sub
block window that are mapped on the face image. For each of this
block, spatial domain is transformed to frequency domain using
DFT. A low frequency coefficient is preserved by discarding high
frequency coefficients by applying rectangular mask on the
spectrum of the facial image. Low frequency information is non-
Gaussian in the feature space and by using combination of several
Gaussian functions that has different statistical properties, the best
feature representation can be modelled using probability density
function. The recognition process is performed using maximum
likelihood value computed using pre-calculated GMM components.
The method is tested using FERET datasets and is able to achieved
92% recognition rates.