Abstract: In addition to environmental parameters like rain,
temperature diseases on crop is a major factor which affects
production quality & quantity of crop yield. Hence disease
management is a key issue in agriculture. For the management of
disease, it needs to be detected at early stage. So, treat it properly &
control spread of the disease. Now a day, it is possible to use the
images of diseased leaf to detect the type of disease by using image
processing techniques. This can be achieved by extracting features
from the images which can be further used with classification
algorithms or content based image retrieval systems. In this paper,
color image is used to extract the features such as mean and standard
deviation after the process of region cropping. The selected features
are taken from the cropped image with different image size samples.
Then, the extracted features are taken in to the account for
classification using Fuzzy Inference System (FIS).
Abstract: The crude methanol extracts of five indigenous vegetables namely, Amarathus tricolor, Basella rubra L., Chochurus olitorius L., Ipomea batatas, and Momordica chuchinensis L., were examined for their phytochemical profile and antioxidant activity using 1,1-diphenyl-2-picrylhydrazyl (DPPH) free radical. The values for DPPH radical scavenging activity ranged from 7.6-89.53% with B. rubra and I. batatas having the lowest and highest values, respectively. The total flavonoid content of all five indigenous vegetables ranged from 74.65-277.3 mg quercetin equivalent per gram of dried vegetable material while the total phenolic content ranged from 1.93-6.15 mg gallic acid equivalent per gram dried material. Phytochemical screening revealed the presence of steroids, flavonoids, saponins, tannins, carbohydrates and reducing sugars, which may also be associated with the antioxidant activity shown by these indigenous vegetables.
Abstract: Obesity and osteoporosis are the two diseases whose
increasing prevalence and high impact on the global morbidity and
mortality, during the two recent decades, have gained a status of
major health threats worldwide. Obesity purports to affect the bone
metabolism through complex mechanisms. Debated data on the
connection between the bone mineral density and fracture prevalence
in the obese patients are widely presented in literature. There is
evidence that the correlation of weight and fracture risk is sitespecific.
This study is aimed at determining the connection between
the bone mineral density (BMD) and trabecular bone score (TBS)
parameters in Ukrainian women suffering from obesity. We
examined 1025 40-89-year-old women, divided them into the groups
according to their body mass index: Group A included 360 women
with obesity whose BMI was ≥30 kg/m2, and Group B – 665 women
with no obesity and BMI of
Abstract: By the evolvement in technology, the way of
expressing opinions switched direction to the digital world. The
domain of politics, as one of the hottest topics of opinion mining
research, merged together with the behavior analysis for affiliation
determination in texts, which constitutes the subject of this paper.
This study aims to classify the text in news/blogs either as
Republican or Democrat with the minimum number of features. As
an initial set, 68 features which 64 were constituted by Linguistic
Inquiry and Word Count (LIWC) features were tested against 14
benchmark classification algorithms. In the later experiments, the
dimensions of the feature vector reduced based on the 7 feature
selection algorithms. The results show that the “Decision Tree”,
“Rule Induction” and “M5 Rule” classifiers when used with “SVM”
and “IGR” feature selection algorithms performed the best up to
82.5% accuracy on a given dataset. Further tests on a single feature
and the linguistic based feature sets showed the similar results. The
feature “Function”, as an aggregate feature of the linguistic category,
was found as the most differentiating feature among the 68 features
with the accuracy of 81% in classifying articles either as Republican
or Democrat.
Abstract: Past literature on business incubators distinguished incubators based on their mission statements. However, more and more mission statements become a slogan rather than a reality. It is therefore more appropriate to identify business incubators based on their real activities, rather than the missions they declared. With a sample of technology business incubators (TBIs) in China, we try to investigate business incubators’ real activities by examining the incubation efficiency along the following five dimensions, i.e., survival of new ventures, technology transfer, local economic growth, job creation, and profit generation. Furthermore, we identified six types of business incubators. The results indicate that generally Chinese TBIs have a greater preference for acquiring profits over other dimensions.
Abstract: Electrohydraulic servo system have been used in industry in a wide number of applications. Its dynamics are highly nonlinear and also have large extent of model uncertainties and external disturbances. In this paper, a robust back-stepping control (RBSC) scheme is proposed to overcome the problem of disturbances and system uncertainties effectively and to improve the tracking performance of EHS systems. In order to implement the proposed control scheme, the system uncertainties in EHS systems are considered as total leakage coefficient and effective oil volume. In addition, in order to obtain the virtual controls for stabilizing system, the update rule for the system uncertainty term is induced by the Lyapunov control function (LCF). To verify the performance and robustness of the proposed control system, computer simulation of the proposed control system using Matlab/Simulink Software is executed. From the computer simulation, it was found that the RBSC system produces the desired tracking performance and has robustness to the disturbances and system uncertainties of EHS systems.
Abstract: The present study is concerned with the problem of determining the shape of the free surface flow in a hydraulic channel which has an uneven bottom. For the mathematical formulation of the problem, the fluid of the two-dimensional irrotational steady flow in water is assumed inviscid and incompressible. The solutions of the nonlinear problem are obtained by using the usual conformal mapping theory and Hilbert’s technique. An experimental study, for comparing the obtained results, has been conducted in a hydraulic channel (subcritical regime and supercritical regime).
Abstract: Advance in techniques of image and video processing has enabled the development of intelligent video surveillance systems. This study was aimed to automatically detect moving human objects and to analyze events of dual human interaction in a surveillance scene. Our system was developed in four major steps: image preprocessing, human object detection, human object tracking, and motion trajectory analysis. The adaptive background subtraction and image processing techniques were used to detect and track moving human objects. To solve the occlusion problem during the interaction, the Kalman filter was used to retain a complete trajectory for each human object. Finally, the motion trajectory analysis was developed to distinguish between the interaction and non-interaction events based on derivatives of trajectories related to the speed of the moving objects. Using a database of 60 video sequences, our system could achieve the classification accuracy of 80% in interaction events and 95% in non-interaction events, respectively. In summary, we have explored the idea to investigate a system for the automatic classification of events for interaction and non-interaction events using surveillance cameras. Ultimately, this system could be incorporated in an intelligent surveillance system for the detection and/or classification of abnormal or criminal events (e.g., theft, snatch, fighting, etc.).
Abstract: To explore how the brain may recognise objects in its
general,accurate and energy-efficient manner, this paper proposes the
use of a neuromorphic hardware system formed from a Dynamic
Video Sensor (DVS) silicon retina in concert with the SpiNNaker
real-time Spiking Neural Network (SNN) simulator. As a first step
in the exploration on this platform a recognition system for dynamic
hand postures is developed, enabling the study of the methods used
in the visual pathways of the brain. Inspired by the behaviours of
the primary visual cortex, Convolutional Neural Networks (CNNs)
are modelled using both linear perceptrons and spiking Leaky
Integrate-and-Fire (LIF) neurons.
In this study’s largest configuration using these approaches, a
network of 74,210 neurons and 15,216,512 synapses is created and
operated in real-time using 290 SpiNNaker processor cores in parallel
and with 93.0% accuracy. A smaller network using only 1/10th of the
resources is also created, again operating in real-time, and it is able
to recognise the postures with an accuracy of around 86.4% - only
6.6% lower than the much larger system. The recognition rate of the
smaller network developed on this neuromorphic system is sufficient
for a successful hand posture recognition system, and demonstrates
a much improved cost to performance trade-off in its approach.
Abstract: For this study, a town based soil database created in
Gümüsçay District of Biga Town, Çanakkale, Turkey. Crop and
livestock production are major activities in the district. Nutrient
management is mainly based on commercial fertilizer application
ignoring the livestock manure. Within the boundaries of district, 122
soil sampling points determined over the satellite image. Soil samples
collected from the determined points with the help of handheld
Global Positioning System. Labeled samples were sent to a
commercial laboratory to determine 11 soil parameters including
salinity, pH, lime, organic matter, nitrogen, phosphorus, potassium,
iron, manganese, copper and zinc. Based on the test results soil maps
for mentioned parameters were developed using remote sensing, GIS,
and geostatistical analysis. In this study we developed a GIS database
that will be used for soil nutrient management. Methods were
explained and soil maps and their interpretations were summarized in
the study.
Abstract: This study was aimed to investigate the machining
stability of a spindle tool with different preloaded amount. To this end,
the vibration tests were conducted on the spindle unit with different
preload to assess the dynamic characteristics and machining stability
of the milling machine. Current results demonstrate that the tool tip
frequency response characteristics and the machining stabilities in X
and Y direction are affected to change due to the different preload of
spindle bearings. As found from the results, a high preloaded spindle
tool shows higher limited cutting depth at mid position, while a spindle
with low preload shows a higher limited depth. This indicates that the
machining stability of a milling machine is affected to vary by the
spindle unit when it was assembled with different bearing preload.
Abstract: Image segmentation and color identification is an
important process used in various emerging fields like intelligent
robotics. A method is proposed for the manipulator to grasp and place
the color object into correct location. The existing methods such as
PSO, has problems like accelerating the convergence speed and
converging to a local minimum leading to sub optimal performance.
To improve the performance, we are using watershed algorithm and
for color identification, we are using EPSO. EPSO method is used to
reduce the probability of being stuck in the local minimum. The
proposed method offers the particles a more powerful global
exploration capability. EPSO methods can determine the particles
stuck in the local minimum and can also enhance learning speed as
the particle movement will be faster.
Abstract: Whey is the lactose rich by-product of the dairy
industry, having good amount of nutrient reservoir. Most abundant
nutrients are lactose, soluble proteins, lipids and mineral salts.
Disposing of whey by most of milk plants which do not have proper
pre-treatment system is the major issue. As a result of which, there
can be significant loss of potential food and energy source. Thus,
whey has been explored as the substrate for the synthesis of different
value added products such as enzymes. β-galactosidase is one of the
important enzymes and has become the major focus of research due
to its ability to catalyze both hydrolytic as well as
transgalactosylation reaction simultaneously. The enzyme is widely
used in dairy industry as it catalyzes the transformation of lactose to
glucose and galactose, making it suitable for the lactose intolerant
people. The enzyme is intracellular in both bacteria and yeast,
whereas for molds, it has an extracellular location. The present work
was carried to utilize the whey for the production of β-galactosidase
enzyme using both yeast and fungal cultures. The yeast isolate
Kluyveromyces marxianus WIG2 and various fungal strains have
been used in the present study. Different disruption techniques have
also been investigated for the extraction of the enzyme produced
intracellularly from yeast cells. Among the different methods tested
for the disruption of yeast cells, SDS-chloroform showed the
maximum β-galactosidase activity. In case of the tested fungal
cultures, Aureobasidium pullulans NCIM 1050 was observed to be
the maximum extracellular enzyme producer.
Abstract: In this study, the pedestrian simulation VISWALK
integration and application platform ant algorithms written program
made to construct a renovation engineering schedule planning mode.
The use of simulation analysis platform construction site when the user
running the simulation, after calculating the user walks in the case of
construction delays, the ant algorithm to find out the minimum delay
time schedule plan, and add volume and unit area deactivated loss of
business computing, and finally to the owners and users of two
different positions cut considerations pick out the best schedule
planning. To assess and validate its effectiveness, this study
constructed the model imported floor of a shopping mall floor
renovation engineering cases. Verify that the case can be found from
the mode of the proposed project schedule planning program can
effectively reduce the delay time and the user's walking mall loss of
business, the impact of the operation on the renovation engineering
facilities in the building to a minimum.
Abstract: Aluminium matrix composites with alumina
reinforcements give superior mechanical & physical properties. Their
applications in several fields like automobile, aerospace, defense,
sports, electronics, bio-medical and other industrial purposes are
becoming essential for the last several decades. In the present work,
fabrication of hybrid composite was done by Stir casting technique
using Al 6061 as a matrix with alumina and silicon carbide (SiC) as
reinforcement materials. The weight percentage of alumina is varied
from 2 to 4% and the silicon carbide weight percentage is maintained
constant at 2%. Hardness and wear tests are performed in the as cast
and heat treated conditions. Age hardening treatment was performed
on the specimen with solutionizing at 550°C, aging at two
temperatures (150 and 200°C) for different time durations. Hardness
distribution curves are drawn and peak hardness values are recorded.
Hardness increase was very sensitive with respect to the decrease in
aging temperature. There was an improvement in wear resistance of
the peak aged material when aged at lower temperature. Also
increase in weight percent of alumina, increases wear resistance at
lower temperature but opposite behavior was seen when aged at
higher temperature.
Abstract: This paper addresses a cutting edge method of
business demand forecasting, based on an empirical probability
function when the historical behavior of the data is random.
Additionally, it presents error determination based on the numerical
method technique ‘propagation of errors.’ The methodology was
conducted characterization and process diagnostics demand planning
as part of the production management, then new ways to predict its
value through techniques of probability and to calculate their mistake
investigated, it was tools used numerical methods. All this based on
the behavior of the data. This analysis was determined considering
the specific business circumstances of a company in the sector of
communications, located in the city of Bogota, Colombia. In
conclusion, using this application it was possible to obtain the
adequate stock of the products required by the company to provide its
services, helping the company reduce its service time, increase the
client satisfaction rate, reduce stock which has not been in rotation
for a long time, code its inventory, and plan reorder points for the
replenishment of stock.
Abstract: When neck pain is associated with pain, numbness, or
weakness in the arm, shoulder, or hand, further investigation is
needed as these are symptoms indicating pressure on one or more
nerve roots. Evaluation necessitates a neurologic examination and
imaging using an MRI/CT scan. A degenerating disc loses some
thickness and is less flexible, causing inter-vertebrae space to narrow.
A radiologist diagnoses an Intervertebral Disc Degeneration (IDD) by
localizing every inter-vertebral disc and identifying the pathology in
a disc based on its geometry and appearance. Accurate localizing is
necessary to diagnose IDD pathology. But, the underlying image
signal is ambiguous: a disc’s intensity overlaps the spinal nerve
fibres. Even the structure changes from case to case, with possible
spinal column bending (scoliosis). The inter-vertebral disc
pathology’s quantitative assessment needs accurate localization of the
cervical region discs. In this work, the efficacy of multilevel set
segmentation model, to segment cervical discs is investigated. The
segmented images are annotated using a simple distance matrix.
Abstract: The novel 3D SnO cabbages self-assembled by
nanosheets were successfully synthesized via template-free
hydrothermal growth method under facile conditions. The XRD
results manifest that the as-prepared SnO is tetragonal phase. The
TEM and HRTEM results show that the cabbage nanosheets are
polycrystalline structure consisted of considerable single-crystalline
nanoparticles. Two typical Raman modes A1g=210 and Eg=112 cm-1
of SnO are observed by Raman spectroscopy. Moreover, galvanostatic
cycling tests has been performed using the SnO cabbages as anode
material of lithium ion battery and the electrochemical results suggest
that the synthesized SnO cabbage structures are a promising anode
material for lithium ion batteries.
Abstract: Current research is targeting new molecular
mechanisms that underlie non-alcoholic fatty liver disease (NAFLD)
and associated metabolic disorders like non-alcoholic steatohepatitis
(NASH). Forty New Zealand White rabbits have been used and fed a
high protein (HP) and energy diet based on grains and containing
11.76 MJ/kg. Boron added to 3 experimental groups’ drinking waters
(30 mg boron/L) as boron compounds. Biochemical analysis
including boron levels, and nuclear magnetic resonance (NMR) based
metabolomics evaluation, and mRNA expression of peroxisome
proliferator-activated receptor (PPAR) family was performed. LDLcholesterol
concentrations alone were decreased in all the
experimental groups. Boron levels in serum and feces were increased.
Content of acetate was in about 2x higher for anhydrous borax group,
at least 3x higher for boric acid group. PPARα mRNA expression
was significantly decreased in boric acid group. Anhydrous borax
attenuated mRNA levels of PPARγ, which was further suppressed by
boric acid. Boron supplementation decreased the degenerative
alterations in hepatocytes. Except borax group other boron groups did
not have a pronounced change in tubular epithels of kidney. In
conclusion, high protein and energy diet leads hepatocytes’
degenerative changes which can be prevented by boron
supplementation. Boric acid seems to be more effective in this
situation.
Abstract: Image segmentation and edge detection is a fundamental section in image processing. In case of noisy images Edge Detection is very less effective if we use conventional Spatial Filters like Sobel, Prewitt, LOG, Laplacian etc. To overcome this problem we have proposed the use of Stochastic Gradient Mask instead of Spatial Filters for generating gradient images. The present study has shown that the resultant images obtained by applying Stochastic Gradient Masks appear to be much clearer and sharper as per Edge detection is considered.