Abstract: Reciprocating compressors are flexible to handle wide capacity and condition swings, offer a very efficient method of compressing almost any gas mixture in wide range of pressure, can generate high head independent of density, and have numerous applications and wide power ratings. These make them vital component in various units of industrial plants. In this paper optimum reciprocating compressor configuration regarding interstage pressures, low suction pressure, non-lubricated cylinder, speed of machine, capacity control system, compressor valve, lubrication system, piston rod coating, cylinder liner material, barring device, pressure drops, rod load, pin reversal, discharge temperature, cylinder coolant system, performance, flow, coupling, special tools, condition monitoring (including vibration, thermal and rod drop monitoring), commercial points, delivery and acoustic conditions are presented.
Abstract: This study aims to propose three evaluation methods to
evaluate the Tokyo Cap and Trade Program when emissions trading is
performed virtually among enterprises, focusing on carbon dioxide
(CO2), which is the only emitted greenhouse gas that tends to increase.
The first method clarifies the optimum reduction rate for the highest
cost benefit, the second discusses emissions trading among enterprises
through market trading, and the third verifies long-term emissions
trading during the term of the plan (2010-2019), checking the validity
of emissions trading partly using Geographic Information Systems
(GIS). The findings of this study can be summarized in the following
three points.
1. Since the total cost benefit is the greatest at a 44% reduction rate, it
is possible to set it more highly than that of the Tokyo Cap and
Trade Program to get more total cost benefit.
2. At a 44% reduction rate, among 320 enterprises, 8 purchasing
enterprises and 245 sales enterprises gain profits from emissions
trading, and 67 enterprises perform voluntary reduction without
conducting emissions trading. Therefore, to further promote
emissions trading, it is necessary to increase the sales volumes of
emissions trading in addition to sales enterprises by increasing the
number of purchasing enterprises.
3. Compared to short-term emissions trading, there are few enterprises
which benefit in each year through the long-term emissions trading
of the Tokyo Cap and Trade Program. Only 81 enterprises at the
most can gain profits from emissions trading in FY 2019. Therefore,
by setting the reduction rate more highly, it is necessary to increase
the number of enterprises that participate in emissions trading and
benefit from the restraint of CO2 emissions.
Abstract: The Shanghai Cooperation Organization is one of the successful outcomes of China's foreign policy since the end of the Cold war. The expansion of multilateral ties all over the world by dint of pursuing institutional strategies as SCO, identify China as a more constructive power. SCO became a new model of cooperation that was formed on remains of collapsed Soviet system, and predetermined China's geopolitical role in the region. As the fast developing effective regional mechanism, SCO today has more of external impact on the international system and forms a new type of interaction for promoting China's grand strategy of 'peaceful rise'.
Abstract: This paper describes a system-level SoC energy
consumption estimation method based on a dynamic behavior of
embedded software in the early stages of the SoC development. A
major problem of SOC development is development rework caused by
unreliable energy consumption estimation at the early stages. The
energy consumption of an SoC used in embedded systems is strongly
affected by the dynamic behavior of the software. At the early stages
of SoC development, modeling with a high level of abstraction is
required for both the dynamic behavior of the software, and the
behavior of the SoC. We estimate the energy consumption by a UML
model-based simulation. The proposed method is applied for an actual
embedded system in an MFP. The energy consumption estimation of
the SoC is more accurate than conventional methods and this proposed
method is promising to reduce the chance of development rework in
the SoC development. ∈
Abstract: Information on weed distribution within the field is necessary to implement spatially variable herbicide application. Since hand labor is costly, an automated weed control system could be feasible. This paper deals with the development of an algorithm for real time specific weed recognition system based on Histogram Maxima with threshold of an image that is used for the weed classification. This algorithm is specifically developed to classify images into broad and narrow class for real-time selective herbicide application. The developed system has been tested on weeds in the lab, which have shown that the system to be very effectiveness in weed identification. Further the results show a very reliable performance on images of weeds taken under varying field conditions. The analysis of the results shows over 95 percent classification accuracy over 140 sample images (broad and narrow) with 70 samples from each category of weeds.
Abstract: Groups where the discrete logarithm problem (DLP) is believed to be intractable have proved to be inestimable building blocks for cryptographic applications. They are at the heart of numerous protocols such as key agreements, public-key cryptosystems, digital signatures, identification schemes, publicly verifiable secret sharings, hash functions and bit commitments. The search for new groups with intractable DLP is therefore of great importance.The goal of this article is to study elliptic curves over the ring Fq[], with Fq a finite field of order q and with the relation n = 0, n ≥ 3. The motivation for this work came from the observation that several practical discrete logarithm-based cryptosystems, such as ElGamal, the Elliptic Curve Cryptosystems . In a first time, we describe these curves defined over a ring. Then, we study the algorithmic properties by proposing effective implementations for representing the elements and the group law. In anther article we study their cryptographic properties, an attack of the elliptic discrete logarithm problem, a new cryptosystem over these curves.
Abstract: Performance of millimeter-wave (mm-wave) multiband
orthogonal frequency division multiplexing (MB-OFDM) ultrawideband
(UWB) signal generation using frequency quadrupling
technique and transmission over fiber is experimentally investigated.
The frequency quadrupling is achived by using only one Mach-
Zehnder modulator (MZM) that is biased at maximum transmission
(MATB) point. At the output, a frequency quadrupling signal is
obtained then sent to a second MZM. This MZM is used for MBOFDM
UWB signal modulation. In this work, we demonstrate 30-
GHz mm-wave wireless that carries three-bands OFDM UWB
signals, and error vector magnitude (EVM) is used to analyze the
transmission quality. It is found that our proposed technique leads to
an improvement of 3.5 dB in EVM at 40% of local oscillator (LO)
modulation with comparison to the technique using two cascaded
MZMs biased at minimum transmission (MITB) point.
Abstract: The least mean square (LMS) algorithmis one of the
most well-known algorithms for mobile communication systems
due to its implementation simplicity. However, the main limitation
is its relatively slow convergence rate. In this paper, a booster
using the concept of Markov chains is proposed to speed up the
convergence rate of LMS algorithms. The nature of Markov
chains makes it possible to exploit the past information in the
updating process. Moreover, since the transition matrix has a
smaller variance than that of the weight itself by the central limit
theorem, the weight transition matrix converges faster than the
weight itself. Accordingly, the proposed Markov-chain based
booster thus has the ability to track variations in signal
characteristics, and meanwhile, it can accelerate the rate of
convergence for LMS algorithms. Simulation results show that the
LMS algorithm can effectively increase the convergence rate and
meantime further approach the Wiener solution, if the
Markov-chain based booster is applied. The mean square error is
also remarkably reduced, while the convergence rate is improved.
Abstract: In the classical buckling analysis of rectangular plates
subjected to the concurrent action of shear and uniaxial forces, the
Euler shear buckling stress is generally evaluated separately, so that
no influence on the shear buckling coefficient, due to the in-plane
tensile or compressive forces, is taken into account.
In this paper the buckling problem of simply supported rectangular
plates, under the combined action of shear and uniaxial forces, is
discussed from the beginning, in order to obtain new project formulas
for the shear buckling coefficient that take into account the presence
of uniaxial forces.
Furthermore, as the classical expression of the shear buckling
coefficient for simply supported rectangular plates is considered only
a “rough" approximation, as the exact one is defined by a system of
intersecting curves, the convergence and the goodness of the classical
solution are analyzed, too.
Finally, as the problem of the Euler shear buckling stress
evaluation is a very important topic for a variety of structures, (e.g.
ship ones), two numerical applications are carried out, in order to
highlight the role of the uniaxial stresses on the plating scantling
procedures and the goodness of the proposed formulas.
Abstract: In this paper, we propose a single sample path based
algorithm with state aggregation to optimize the average rewards of
singularly perturbed Markov reward processes (SPMRPs) with a
large scale state spaces. It is assumed that such a reward process
depend on a set of parameters. Differing from the other kinds of
Markov chain, SPMRPs have their own hierarchical structure. Based
on this special structure, our algorithm can alleviate the load in the
optimization for performance. Moreover, our method can be applied
on line because of its evolution with the sample path simulated.
Compared with the original algorithm applied on these problems of
general MRPs, a new gradient formula for average reward
performance metric in SPMRPs is brought in, which will be proved
in Appendix, and then based on these gradients, the schedule of the
iteration algorithm is presented, which is based on a single sample
path, and eventually a special case in which parameters only
dominate the disturbance matrices will be analyzed, and a precise
comparison with be displayed between our algorithm with the old
ones which is aim to solve these problems in general Markov reward
processes. When applied in SPMRPs, our method will approach a fast
pace in these cases. Furthermore, to illustrate the practical value of
SPMRPs, a simple example in multiple programming in computer
systems will be listed and simulated. Corresponding to some practical
model, physical meanings of SPMRPs in networks of queues will be
clarified.
Abstract: The importance of ensuring safe meat handling and
processing practices has been demonstrated in global reports on food
safety scares and related illness and deaths. This necessitated stricter
meat safety control strategies. Today, many countries have regulated
towards preventative and systematic control over safe meat
processing at abattoirs utilizing the Hazard Analysis Critical Control
Point (HACCP) principles. HACCP systems have been reported as
effective in managing food safety risks, if correctly implemented.
South Africa has regulated the Hygiene Management System (HMS)
based on HACCP principles applicable to abattoirs. Regulators utilise
the Hygiene Assessment System (HAS) to audit compliance at
abattoirs. These systems were benchmarked from the United
Kingdom (UK). Little research has been done them since inception as
of 2004. This paper presents a review of the two systems, its
implementation and comparison with HACCP. Recommendations are
made for future research to demonstrate the utility of the HMS and
HAS in assuring safe meat to consumers.
Abstract: This paper aims at presenting the biotechnology used
to obtain collagen-based gels from shark (Squalus acanthias) and brill
skin, marine fish growing in the Black Sea. Due to the structure of its
micro-fibres, collagen can be considered a nanomaterial; in order to
use collagen-based matrixes as biomaterial, rheological studies must
be performed first, to state whether they are stable or not. For the
triple-helix structure to remain stable within these gels at room or
human body temperature, they must be stabilized by reticulation.
Abstract: Software testing is important stage of software development cycle. Current testing process involves tester and electronic documents with test case scenarios. In this paper we focus on new approach to testing process using automated test case generation and tester guidance through the system based on the model of the system. Test case generation and model-based testing is not possible without proper system model. We aim on providing better feedback from the testing process thus eliminating the unnecessary paper work.
Abstract: In this study spatial-temporal speckle correlation techniques have been applied for the quality evaluation of three different Indian fruits namely apple, pear and tomato for the first time. The method is based on the analysis of variations of laser light scattered from biological samples. The results showed that crosscorrelation coefficients of biospeckle patterns change subject to their freshness and the storage conditions. The biospeckle activity was determined by means of the cross-correlation functions of the intensity fluctuations. Significant changes in biospeckle activity were observed during their shelf lives. From the study, it is found that the biospeckle activity decreases with the shelf-life storage time. Further it has been shown that biospeckle activity changes according to their respiration rates.
Abstract: We propose a fast and robust hierarchical face detection system which finds and localizes face images with a cascade of classifiers. Three modules contribute to the efficiency of our detector. First, heterogeneous feature descriptors are exploited to enrich feature types and feature numbers for face representation. Second, a PSO-Adaboost algorithm is proposed to efficiently select discriminative features from a large pool of available features and reinforce them into the final ensemble classifier. Compared with the standard exhaustive Adaboost for feature selection, the new PSOAdaboost algorithm reduces the training time up to 20 times. Finally, a three-stage hierarchical classifier framework is developed for rapid background removal. In particular, candidate face regions are detected more quickly by using a large size window in the first stage. Nonlinear SVM classifiers are used instead of decision stump functions in the last stage to remove those remaining complex nonface patterns that can not be rejected in the previous two stages. Experimental results show our detector achieves superior performance on the CMU+MIT frontal face dataset.
Abstract: The purpose of this paper is to examine the current
state of corporate social responsibility statements on corporate
websites of Malaysian and Singaporean corporations and analyze
how the CSR statements contribute in building a unique corporate
identity of corporations. Content analysis is employed to examine the
websites of Malaysian and Singaporean consumer corporations. It is
believed that generally most companies tend to publish and
communicate their CSR statements visibly to general stakeholders.
However, there is a significantly different outcome of the articulation
of CSR on practices on websites between Malaysian and Singaporean
consumer corporations. A number of Singaporean organizations were
found less concerned with CSR practices as compared to Malaysian
organizations. The findings indicate a need for corporations in
Malaysia and Singapore to orchestrate their core competence of CSR
activities in order to develop a unique corporate identity in a global
business environment.
Abstract: This paper presents the design related to the
electronic system design of the respiratory signal, including phases
for processing, followed by the transmission and reception of this
signal and finally display. The processing of this signal is added to
the ECG and temperature sign, put up last year. Under this scheme is
proposed that in future also be conditioned blood pressure signal
under the same final printed circuit and worked.
Abstract: A bond graph model of a hydroelectric plant is
proposed. In order to analyze the system some structural properties
of a bond graph are used. The structural controllability of
the hydroelctric plant is described. Also, the steady state of the
state variables applying the bond graph in a derivative causality
assignment is obtained. Finally, simulation results of the system
are shown.
Abstract: Public health surveillance system focuses on outbreak detection and data sources used. Variation or aberration in the frequency distribution of health data, compared to historical data is often used to detect outbreaks. It is important that new techniques be developed to improve the detection rate, thereby reducing wastage of resources in public health. Thus, the objective is to developed technique by applying frequent mining and outlier mining techniques in outbreak detection. 14 datasets from the UCI were tested on the proposed technique. The performance of the effectiveness for each technique was measured by t-test. The overall performance shows that DTK can be used to detect outlier within frequent dataset. In conclusion the outbreak detection technique using anomaly-based on frequent-outlier technique can be used to identify the outlier within frequent dataset.
Abstract: This paper presents the source extraction system which can extract only target signals with constraints on source localization in on-line systems. The proposed system is a kind of methods for enhancing a target signal and suppressing other interference signals. But, the performance of proposed system is superior to any other methods and the extraction of target source is comparatively complete. The method has a beamforming concept and uses an improved time-frequency (TF) mask-based BSS algorithm to separate a target signal from multiple noise sources. The target sources are assumed to be in front and test data was recorded in a reverberant room. The experimental results of the proposed method was evaluated by the PESQ score of real-recording sentences and showed a noticeable speech enhancement.