Abstract: The present work represents an investigation of the
hydrolysis of hull-less pumpkin (Cucurbita Pepo L.) oil cake protein
isolate (PuOC PI) by pepsin. To examine the effectiveness and
suitability of pepsin towards PuOC PI the kinetic parameters for
pepsin on PuOC PI were determined and then, the hydrolysis process
was studied using Response Surface Methodology (RSM). The
hydrolysis was carried out at temperature of 30°C and pH 3.00. Time
and initial enzyme/substrate ratio (E/S) at three levels were selected
as the independent parameters. The degree of hydrolysis, DH, was
mesuared after 20, 30 and 40 minutes, at initial E/S of 0.7, 1 and 1.3
mA/mg proteins. Since the proposed second-order polynomial model
showed good fit with the experimental data (R2 = 0.9822), the
obtained mathematical model could be used for monitoring the
hydrolysis of PuOC PI by pepsin, under studied experimental
conditions, varying the time and initial E/S. To achieve the highest
value of DH (39.13 %), the obtained optimum conditions for time
and initial E/S were 30 min and 1.024 mA/mg proteins.
Abstract: Intelligent Video-Surveillance (IVS) systems are
being more and more popular in security applications. The analysis
and recognition of abnormal behaviours in a video sequence has
gradually drawn the attention in the field of IVS, since it allows
filtering out a large number of useless information, which guarantees
the high efficiency in the security protection, and save a lot of human
and material resources. We present in this paper ADABeV, an
intelligent video-surveillance framework for event recognition in
crowded scene to detect the abnormal human behaviour. This
framework is attended to be able to achieve real-time alarming,
reducing the lags in traditional monitoring systems. This architecture
proposal addresses four main challenges: behaviour understanding in
crowded scenes, hard lighting conditions, multiple input kinds of
sensors and contextual-based adaptability to recognize the active
context of the scene.
Abstract: This paper describes a methodology for remote
performance monitoring of retail refrigeration systems. The proposed
framework starts with monitoring of the whole refrigeration circuit
which allows detecting deviations from expected behavior caused by
various faults and degradations. The subsequent diagnostics methods
drill down deeper in the equipment hierarchy to more specifically
determine root causes. An important feature of the proposed concept
is that it does not require any additional sensors, and thus, the
performance monitoring solution can be deployed at a low
installation cost. Moreover only a minimum of contextual
information is required, which also substantially reduces time and
cost of the deployment process.
Abstract: Different methods containing biometric algorithms are
presented for the representation of eigenfaces detection including
face recognition, are identification and verification. Our theme of this
research is to manage the critical processing stages (accuracy, speed,
security and monitoring) of face activities with the flexibility of
searching and edit the secure authorized database. In this paper we
implement different techniques such as eigenfaces vector reduction
by using texture and shape vector phenomenon for complexity
removal, while density matching score with Face Boundary Fixation
(FBF) extracted the most likelihood characteristics in this media
processing contents. We examine the development and performance
efficiency of the database by applying our creative algorithms in both
recognition and detection phenomenon. Our results show the
performance accuracy and security gain with better achievement than
a number of previous approaches in all the above processes in an
encouraging mode.
Abstract: This paper presents one of the best applications of wireless sensor network for campus Monitoring. With the help of PIR sensor, temperature sensor and humidity sensor, effective utilization of energy resources has been implemented in one of rooms of Sharda University, Greater Noida, India. The RISC microcontroller is used here for analysis of output of sensors and providing proper control using ZigBee protocol. This wireless sensor module presents a tremendous power saving method for any campus
Abstract: Diatoms are an important group of aquatic ecosystems and diatom-based indices are increasingly becoming important tools for the assessment of ecological conditions in lotic systems. Although the studies are very limited about Turkish rivers, diatom indices were used for monitoring rivers in different basins. In the present study, we used OMNIDIA program for estimation of stream quality. Some indices have less sensitive (IDP, WAT, LOBO, GENRE, TID, CEE, PT), intermediate sensitivities (IDSE, DESCY, IPS, DI-CH, SLA, IDAP), the others higher sensitivities (SID, IBD, SHE, EPI-D). Among the investigated diatom communities, only a few taxa indicated alfa-mesosaprobity and polysaprobity. Most of the sites were characterized by a great relative contribution of eutraphent and tolerant ones as well as oligosaprobic and betamesosaprobic diatoms. In general, SID and IBD indices gave the best results. This study suggests that the structure of benthic diatom communities and diatom indices, especially SID, can be applied for monitoring rivers in Southern Turkey.
Abstract: Modern manufacturing facilities are large scale,
highly complex, and operate with large number of variables under
closed loop control. Early and accurate fault detection and diagnosis
for these plants can minimise down time, increase the safety of plant
operations, and reduce manufacturing costs. Fault detection and
isolation is more complex particularly in the case of the faulty analog
control systems. Analog control systems are not equipped with
monitoring function where the process parameters are continually
visualised. In this situation, It is very difficult to find the relationship
between the fault importance and its consequences on the product
failure. We consider in this paper an approach to fault detection and
analysis of its effect on the production quality using an adaptive
centring and scaling in the pickling process in cold rolling. The fault
appeared on one of the power unit driving a rotary machine, this
machine can not track a reference speed given by another machine.
The length of metal loop is then in continuous oscillation, this affects
the product quality. Using a computerised data acquisition system,
the main machine parameters have been monitored. The fault has
been detected and isolated on basis of analysis of monitored data.
Normal and faulty situation have been obtained by an artificial neural
network (ANN) model which is implemented to simulate the normal
and faulty status of rotary machine. Correlation between the product
quality defined by an index and the residual is used to quality
classification.
Abstract: Monitoring lightning electromagnetic pulses (sferics) and other terrestrial as well as extraterrestrial transient radiation signals is of considerable interest for practical and theoretical purposes in astro- and geophysics as well as meteorology. Managing a continuous flow of data, automation of the analysis and classification process is important. Features based on a combination of wavelet and statistical methods proved efficient for this task and serve as input into a radial basis function network that is trained to discriminate transient shapes from pulse like to wave like. We concentrate on signals in the Very Low Frequency (VLF, 3 -30 kHz) range in this paper, but the developed methods are independent of this specific choice.
Abstract: Cybercrime is now becoming a big challenge in Nigeria apart from the traditional crime. Inability to identify perpetrators is one of the reasons for the growing menace. This paper proposes a design for monitoring internet users’ activities in order to curbing cybercrime. It requires redefining the operations of Internet Service Providers (ISPs) which will now mandate users to be authenticated before accessing the internet. In implementing this work which can be adapted to a larger scale, a virtual router application is developed and configured to mimic a real router device. A sign-up portal is developed to allow users to register with the ISP. The portal asks for identification information which will include bio-data and government issued identification data like National Identity Card number, et cetera. A unique username and password are chosen by the user to enable access to the internet which will be used to reference him to an Internet Protocol Address (IP Address) of any system he uses on the internet and thereby associating him to any criminal act related to that IP address at that particular time. Questions such as “What happen when another user knows the password and uses it to commit crime?” and other pertinent issues are addressed.
Abstract: LABVIEW is a graphical programming language that has its roots in automation control and data acquisition. In this paper we have utilized this platform to provide a powerful toolset for process identification and control of nonlinear systems based on artificial neural networks (ANN). This tool has been applied to the monitoring and control of a lab-scale distillation column DELTALAB DC-SP. The proposed control scheme offers high speed of response for changes in set points and null stationary error for dual composition control and shows robustness in presence of externally imposed disturbance.
Abstract: Economic crime (i.e. corporate fraud) has a
significant impact on business. This study analyzes the fraud cases
reported by the Malaysian Securities Commission. Frauds involving
market manipulation and/or illegal share trading are the most
common types of fraud reported over the 6 years analyzed. The
highest number of frauds reported involved investment and fund
holding companies. Alarmingly the results indicate quite a high
number of frauds cases are committed by management. The higher
number of Chinese perpetrators may be due to fact that they are the
dominant group in Malaysian business. The result also shows that
more than half of companies involved with fraud are privately held
companies in the investment/fund/finance sector. The results of this
study highlight general characteristic of perpetrators (person and
company) that commit fraud which could help the regulators in their
monitoring and enforcement activities. To investors, this would help
in analyzing their business investment or portfolio risk.
Abstract: High-voltage power transmission lines are the back
bone of electrical power utilities. The stability and continuous
monitoring of this critical infrastructure is pivotal. Nine-Sigma
representing Eskom Holding SOC limited, South Africa has a major
problem on proactive detection of fallen power lines and real time
sagging measurement together with slipping of such conductors. The
main objective of this research is to innovate RFID technology to
solve this challenge. Various options and technologies such as GPS,
PLC, image processing, MR sensors and etc., have been reviewed
and draw backs were made. The potential of RFID to give precision
measurement will be observed and presented. The future research
will look at magnetic and electrical interference as well as corona
effect on the technology.
Abstract: As one result of the project “Reactive Construction
Project Scheduling using Real Time Construction Logistic Data and
Simulation”, a procedure for using data about uncertain resource
availability assumptions in reactive scheduling processes has been
developed. Prediction data about resource availability is generated in
a formalized way using real-time monitoring data e.g. from auto-ID
systems on the construction site and in the supply chains. The paper
focusses on the formalization of the procedure for monitoring
construction logistic processes, for the detection of disturbance and
for generating of new and uncertain scheduling assumptions for the
reactive resource constrained simulation procedure that is and will be
further described in other papers.
Abstract: Recently, the issue of machine condition monitoring
and fault diagnosis as a part of maintenance system became global
due to the potential advantages to be gained from reduced
maintenance costs, improved productivity and increased machine
availability. The aim of this work is to investigate the effectiveness
of a new fault diagnosis method based on power spectral density
(PSD) of vibration signals in combination with decision trees and
fuzzy inference system (FIS). To this end, a series of studies was
conducted on an external gear hydraulic pump. After a test under
normal condition, a number of different machine defect conditions
were introduced for three working levels of pump speed (1000, 1500,
and 2000 rpm), corresponding to (i) Journal-bearing with inner face
wear (BIFW), (ii) Gear with tooth face wear (GTFW), and (iii)
Journal-bearing with inner face wear plus Gear with tooth face wear
(B&GW). The features of PSD values of vibration signal were
extracted using descriptive statistical parameters. J48 algorithm is
used as a feature selection procedure to select pertinent features from
data set. The output of J48 algorithm was employed to produce the
crisp if-then rule and membership function sets. The structure of FIS
classifier was then defined based on the crisp sets. In order to
evaluate the proposed PSD-J48-FIS model, the data sets obtained
from vibration signals of the pump were used. Results showed that
the total classification accuracy for 1000, 1500, and 2000 rpm
conditions were 96.42%, 100%, and 96.42% respectively. The results
indicate that the combined PSD-J48-FIS model has the potential for
fault diagnosis of hydraulic pumps.
Abstract: A study was conducted to formally characterize
notebook computer performance under various environmental and
usage conditions. Software was developed to collect data from the
operating system of the computer. An experiment was conducted to
evaluate the performance parameters- variations, trends, and
correlations, as well as the extreme value they can attain in various
usage and environmental conditions. An automated software script
was written to simulate user activity. The variability of each
performance parameter was addressed by establishing the empirical
relationship between performance parameters. These equations were
presented as baseline estimates for performance parameters, which
can be used to detect system deviations from normal operation and
for prognostic assessment. The effect of environmental factors,
including different power sources, ambient temperatures, humidity,
and usage, on performance parameters of notebooks was studied.
Abstract: REY area has been located in Tehran Province and several archaeological ruins of this area indicate that the settlement in this area has been started since several thousand years ago. In this paper, the main investigation items consist of analysis of oil components and groundwater quality inside the wells. By finding the contents of oil in the well, it is possible to find out the pollution source by comparing the oil contents of well with other oil products that are used inside and outside of the oil farm. Investigation items consist of analysis of BTEX (Benzene, Toluene, Ethyl-benzene, Xylene), Gas chromatographic distillation characteristics, Water content, Density, Sulfur content, Lead content, Atmospheric distillation, MTBE(Methyl tertiary butyl ether). Analysis of polluting oil components showed that except MW(Monitoring Well)10 and MW 15 that oil with slightly heavy components was detected in them; with a high possibility the polluting oil is light oil.
Abstract: This paper presented a proposed design for
transcutaneous inductive powering links. The design used to transfer
power and data to the implanted devices such as implanted
Microsystems to stimulate and monitoring the nerves and muscles.
The system operated with low band frequency 13.56 MHZ according
to industrial- scientific – medical (ISM) band to avoid the tissue
heating. For external part, the modulation index is 13 % and the
modulation rate 7.3% with data rate 1 Mbit/s assuming Tbit=1us. The
system has been designed using 0.35-μm fabricated CMOS
technology. The mathematical model is given and the design is
simulated using OrCAD P Spice 16.2 software tool and for real-time
simulation the electronic workbench MULISIM 11 has been used.
The novel circular plane (pancake) coils was simulated using
ANSOFT- HFss software.
Abstract: This paper describes the designs of a first and second
generation autonomous gas monitoring system and the successful
field trial of the final system (2nd generation). Infrared sensing
technology is used to detect and measure the greenhouse gases
methane (CH4) and carbon dioxide (CO2) at point sources. The
ability to monitor real-time events is further enhanced through the
implementation of both GSM and Bluetooth technologies to
communicate these data in real-time. These systems are robust,
reliable and a necessary tool where the monitoring of gas events in
real-time are needed.
Abstract: The objective of this paper is to design a model of human vital sign prediction for decreasing prediction error by using two states mapping based time series neural network BP (back-propagation) model. Normally, lot of industries has been applying the neural network model by training them in a supervised manner with the error back-propagation algorithm for time series prediction systems. However, it still has a residual error between real value and prediction output. Therefore, we designed two states of neural network model for compensation of residual error which is possible to use in the prevention of sudden death and metabolic syndrome disease such as hypertension disease and obesity. We found that most of simulations cases were satisfied by the two states mapping based time series prediction model compared to normal BP. In particular, small sample size of times series were more accurate than the standard MLP model. We expect that this algorithm can be available to sudden death prevention and monitoring AGENT system in a ubiquitous homecare environment.
Abstract: This paper presents the results of preliminary
assessment of water quality along the coastal areas in the vicinity of
Left Bank Outfall Drainage (LBOD) and Tidal Link Drain (TLD) in
Sindh province after the cyclone 2A occurred in 1999. The water
samples were collected from various RDs of Tidal Link Drain and
lakes during September 2001 to April 2002 and were analysed for
salinity, nitrite, phosphate, ammonia, silicate and suspended material
in water. The results of the study showed considerable variations in
water quality depending upon the location along the coast in the
vicinity of LBOD and RDs. The salinity ranged between 4.39–65.25
ppt in Tidal Link Drain samples whereas 2.4–38.05 ppt in samples
collected from lakes. The values of suspended material at various
RDs of Tidal Link Drain ranged between 56.6–2134 ppm and at the
lakes between 68–297 ppm. The data of continuous monitoring at
RD–93 showed the range of PO4 (8.6–25.2 μg/l), SiO3 (554.96–1462
μg/l), NO2 (0.557.2–25.2 μg/l) and NH3 (9.38–23.62 μg/l). The
concentration of nutrients in water samples collected from different
RDs was found in the range of PO4 (10.85 to 11.47 μg/l), SiO3 (1624
to 2635.08 μg/l), NO2 (20.38 to 44.8 μg/l) and NH3 (24.08 to 26.6
μg/l). Sindh coastal areas which situated at the north-western
boundary the Arabian Sea are highly vulnerable to flood damages
due to flash floods during SW monsoon or impact of sea level rise
and storm surges coupled with cyclones passing through Arabian Sea
along Pakistan coast. It is hoped that the obtained data in this study
would act as a database for future investigations and monitoring of
LBOD and Tidal Link Drain coastal waters.