Abstract: The effects of different parameters on the
hydrodynamics of trickle bed reactors were discussed for Newtonian
and non-Newtonian foaming systems. The varying parameters are
varying liquid velocities, gas flow velocities and surface tension. The
range for gas velocity is particularly large, thanks to the use of dense
gas to simulate very high pressure conditions. This data bank has
been used to compare the prediction accuracy of the different
trendlines and transition points from the literature. More than 240
experimental points for the trickle flow (GCF) and foaming pulsing
flow (PF/FPF) regime were obtained for present study.
Hydrodynamic characteristics involving dynamic liquid saturation
significantly influenced by gas and liquid flow rates. For 15 and 30
ppm air-aqueous surfactant solutions, dynamic liquid saturation
decreases with higher liquid and gas flow rates considerably in high
interaction regime. With decrease in surface tension i.e. for 45 and 60
ppm air-aqueous surfactant systems, effect was more pronounced
with decreases dynamic liquid saturation very sharply during regime
transition significantly at both low liquid and gas flow rates.
Abstract: Judgment is affected by many agents and distortion in this assessment is unpreventable. Personality dimensions are among those factors that interfere with the distortion. In this research, the relations between personality dimensions of subject and his judgment on friends- personality dimensions is investigated. One-hundred friend couples completed both NEO Five Factor Inventory (NEOFFI) and Ahvaz Reality Distortion Inventory (ARDI) to make judgments about themselves and their friends. Observations show that judge-s Agreement and Neuroticism dimensions are impressed by reality distortion. On the other hand, this reality distortion interferes with one-s evaluation of his friend-s Agreement, Neuroticism, and Conscientiousness dimensions. Conscientiousness with suppressive effect on judge-s other dimensions plays the irrelevant role on personality judgment. Therefore, observer-rating tools which are used as a conventional criterion seem to be not valid because of the reality distortion due to judge-s personality dimensions.
Abstract: Economic dispatch (ED) has been considered to be one of the key functions in electric power system operation which can help to build up effective generating management plans. The practical ED problem has non-smooth cost function with nonlinear constraints which make it difficult to be effectively solved. This paper presents a novel heuristic and efficient optimization approach based on the new Bat algorithm (BA) to solve the practical non-smooth economic dispatch problem. The proposed algorithm easily takes care of different constraints. In addition, two newly introduced modifications method is developed to improve the variety of the bat population when increasing the convergence speed simultaneously. The simulation results obtained by the proposed algorithms are compared with the results obtained using other recently develop methods available in the literature.
Abstract: With the rapid growth in business size, today's businesses orient towards electronic technologies. Amazon.com and e-bay.com are some of the major stakeholders in this regard. Unfortunately the enormous size and hugely unstructured data on the web, even for a single commodity, has become a cause of ambiguity for consumers. Extracting valuable information from such an everincreasing data is an extremely tedious task and is fast becoming critical towards the success of businesses. Web content mining can play a major role in solving these issues. It involves using efficient algorithmic techniques to search and retrieve the desired information from a seemingly impossible to search unstructured data on the Internet. Application of web content mining can be very encouraging in the areas of Customer Relations Modeling, billing records, logistics investigations, product cataloguing and quality management. In this paper we present a review of some very interesting, efficient yet implementable techniques from the field of web content mining and study their impact in the area specific to business user needs focusing both on the customer as well as the producer. The techniques we would be reviewing include, mining by developing a knowledge-base repository of the domain, iterative refinement of user queries for personalized search, using a graphbased approach for the development of a web-crawler and filtering information for personalized search using website captions. These techniques have been analyzed and compared on the basis of their execution time and relevance of the result they produced against a particular search.
Abstract: In modern literary criticism the problem of genre is one of discussion. Genre is a phenomenon, located in the intersection of the synchronous and diachronic processes in the development of literature, and this is due to the complexity of its solutions. It defines the place of contact between literary works and literary process.
Abstract: Finite element method was applied to model damage
development in the femoral neck during a sideways fall. The femoral
failure was simulated using the maximum principal strain criterion.
The evolution of damage was consistent with previous studies. It was
initiated by compressive failure at the junction of the superior aspect
of the femoral neck and the greater trochanter. It was followed by
tensile failure that occurred at the inferior aspect of the femoral neck
before a complete transcervical fracture was observed. The estimated
failure line was less than 50° from the horizontal plane (Pauwels type
II).
Abstract: In recent years, tuned mass damper (TMD) control systems for civil engineering structures have attracted considerable attention. This paper emphasizes on the application of particle swarm application (PSO) to design and optimize the parameters of the TMD control scheme for achieving the best results in the reduction of the building response under earthquake excitations. The Integral of the Time multiplied Absolute value of the Error (ITAE) based on relative displacement of all floors in the building is taken as a performance index of the optimization criterion. The problem of robustly TMD controller design is formatted as an optimization problem based on the ITAE performance index to be solved using the PSO technique which has a story ability to find the most optimistic results. An 11- story realistic building, located in the city of Rasht, Iran is considered as a test system to demonstrate effectiveness of the proposed method. The results analysis through the time-domain simulation and some performance indices reveals that the designed PSO based TMD controller has an excellent capability in reduction of the seismically excited example building.
Abstract: Chemical industry project management involves
complex decision making situations that require discerning abilities
and methods to make sound decisions. Project managers are faced
with decision environments and problems in projects that are
complex. In this work, case study is Research and Development
(R&D) project selection. R&D is an ongoing process for forward
thinking technology-based chemical industries. R&D project
selection is an important task for organizations with R&D project
management. It is a multi-criteria problem which includes both
tangible and intangible factors. The ability to make sound decisions
is very important to success of R&D projects. Multiple-criteria
decision making (MCDM) approaches are major parts of decision
theory and analysis. This paper presents all of MCDM approaches
for use in R&D project selection. It is hoped that this work will
provide a ready reference on MCDM and this will encourage the
application of the MCDM by chemical engineering management.
Abstract: Combinatorial optimization problems arise in many scientific and practical applications. Therefore many researchers try to find or improve different methods to solve these problems with high quality results and in less time. Genetic Algorithm (GA) and Simulated Annealing (SA) have been used to solve optimization problems. Both GA and SA search a solution space throughout a sequence of iterative states. However, there are also significant differences between them. The GA mechanism is parallel on a set of solutions and exchanges information using the crossover operation. SA works on a single solution at a time. In this work SA and GA are combined using new technique in order to overcome the disadvantages' of both algorithms.
Abstract: In this study, a new root-finding method for solving nonlinear equations is proposed. This method requires two starting values that do not necessarily bracketing a root. However, when the starting values are selected to be close to a root, the proposed method converges to the root quicker than the secant method. Another advantage over all iterative methods is that; the proposed method usually converges to two distinct roots when the given function has more than one root, that is, the odd iterations of this new technique converge to a root and the even iterations converge to another root. Some numerical examples, including a sine-polynomial equation, are solved by using the proposed method and compared with results obtained by the secant method; perfect agreements are found.
Abstract: The literature reports a large number of approaches for
measuring the similarity between protein sequences. Most of these
approaches estimate this similarity using alignment-based techniques
that do not necessarily yield biologically plausible results, for two
reasons.
First, for the case of non-alignable (i.e., not yet definitively aligned
and biologically approved) sequences such as multi-domain, circular
permutation and tandem repeat protein sequences, alignment-based
approaches do not succeed in producing biologically plausible results.
This is due to the nature of the alignment, which is based on the
matching of subsequences in equivalent positions, while non-alignable
proteins often have similar and conserved domains in non-equivalent
positions.
Second, the alignment-based approaches lead to similarity measures
that depend heavily on the parameters set by the user for the alignment
(e.g., gap penalties and substitution matrices). For easily alignable
protein sequences, it's possible to supply a suitable combination of
input parameters that allows such an approach to yield biologically
plausible results. However, for difficult-to-align protein sequences,
supplying different combinations of input parameters yields different
results. Such variable results create ambiguities and complicate the
similarity measurement task.
To overcome these drawbacks, this paper describes a novel and
effective approach for measuring the similarity between protein
sequences, called SAF for Substitution and Alignment Free. Without
resorting either to the alignment of protein sequences or to substitution
relations between amino acids, SAF is able to efficiently detect the
significant subsequences that best represent the intrinsic properties of
protein sequences, those underlying the chronological dependencies of
structural features and biochemical activities of protein sequences.
Moreover, by using a new efficient subsequence matching scheme,
SAF more efficiently handles protein sequences that contain similar
structural features with significant meaning in chronologically
non-equivalent positions. To show the effectiveness of SAF, extensive
experiments were performed on protein datasets from different
databases, and the results were compared with those obtained by
several mainstream algorithms.
Abstract: In today's day and age, one of the important topics in
information security is authentication. There are several alternatives
to text-based authentication of which includes Graphical Password
(GP) or Graphical User Authentication (GUA). These methods stems
from the fact that humans recognized and remembers images better
than alphanumerical text characters. This paper will focus on the
security aspect of GP algorithms and what most researchers have
been working on trying to define these security features and
attributes. The goal of this study is to develop a fuzzy decision model
that allows automatic selection of available GP algorithms by taking
into considerations the subjective judgments of the decision makers
who are more than 50 postgraduate students of computer science. The
approach that is being proposed is based on the Fuzzy Analytic
Hierarchy Process (FAHP) which determines the criteria weight as a
linear formula.
Abstract: Literature reveals that many investors rely on technical trading rules when making investment decisions. If stock markets are efficient, one cannot achieve superior results by using these trading rules. However, if market inefficiencies are present, profitable opportunities may arise. The aim of this study is to investigate the effectiveness of technical trading rules in 34 emerging stock markets. The performance of the rules is evaluated by utilizing White-s Reality Check and the Superior Predictive Ability test of Hansen, along with an adjustment for transaction costs. These tests are able to evaluate whether the best model performs better than a buy-and-hold benchmark. Further, they provide an answer to data snooping problems, which is essential to obtain unbiased outcomes. Based on our results we conclude that technical trading rules are not able to outperform a naïve buy-and-hold benchmark on a consistent basis. However, we do find significant trading rule profits in 4 of the 34 investigated markets. We also present evidence that technical analysis is more profitable in crisis situations. Nevertheless, this result is relatively weak.
Abstract: We have developed a database for membrane protein functions, which has more than 3000 experimental data on functionally important amino acid residues in membrane proteins along with sequence, structure and literature information. Further, we have proposed different methods for identifying membrane proteins based on their functions: (i) discrimination of membrane transport proteins from other globular and membrane proteins and classifying them into channels/pores, electrochemical and active transporters, and (ii) β-signal for the insertion of mitochondrial β-barrel outer membrane proteins and potential targets. Our method showed an accuracy of 82% in discriminating transport proteins and 68% to classify them into three different transporters. In addition, we have identified a motif for targeting β-signal and potential candidates for mitochondrial β-barrel membrane proteins. Our methods can be used as effective tools for genome-wide annotations.
Abstract: Perturbed-Chain Statistical Association Fluid Theory (PC-SAFT) equation of state (EOS) is a modified SAFT EOS with three pure component specific parameters: segment number (m), diameter (σ) and energy (ε). These PC-SAFT parameters need to be determined for each component under the conditions of interest by fitting experimental data, such as vapor pressure, density or heat capacity. PC-SAFT parameters for propane, ethylene and hydrogen in supercritical region were successfully estimated by fitting experimental density data available in literature. The regressed PCSAFT parameters were compared with the literature values by means of estimating pure component density and calculating average absolute deviation between the estimated and experimental density values. PC-SAFT parameters available in literature especially for ethylene and hydrogen estimated density in supercritical region reasonably well. However, the regressed PC-SAFT parameters performed better in supercritical region than the PC-SAFT parameters from literature.
Abstract: Network reconfiguration in distribution system is realized by changing the status of sectionalizing switches to reduce the power loss in the system. This paper presents a new method which applies an artificial bee colony algorithm (ABC) for determining the sectionalizing switch to be operated in order to solve the distribution system loss minimization problem. The ABC algorithm is a new population based metaheuristic approach inspired by intelligent foraging behavior of honeybee swarm. The advantage of ABC algorithm is that it does not require external parameters such as cross over rate and mutation rate as in case of genetic algorithm and differential evolution and it is hard to determine these parameters in prior. The other advantage is that the global search ability in the algorithm is implemented by introducing neighborhood source production mechanism which is a similar to mutation process. To demonstrate the validity of the proposed algorithm, computer simulations are carried out on 14, 33, and 119-bus systems and compared with different approaches available in the literature. The proposed method has outperformed the other methods in terms of the quality of solution and computational efficiency.
Abstract: In this paper, based on linear matrix inequality (LMI), by using Lyapunov functional theory, the exponential stability criterion is obtained for a class of uncertain Takagi-Sugeno fuzzy Hopfield neural networks (TSFHNNs) with time delays. Here we choose a generalized Lyapunov functional and introduce a parameterized model transformation with free weighting matrices to it, these techniques lead to generalized and less conservative stability condition that guarantee the wide stability region. Finally, an example is given to illustrate our results by using MATLAB LMI toolbox.
Abstract: Despite of many scholars and practitioners recognize
the knowledge management implementation in an organizations but
insufficient attention has been paid by researchers to select suitable
knowledge portal system (KPS) selection. This study develops a
Multi Criteria Decision making model based on the fuzzy VIKOR
approach to help organizations in selecting KPS. The suitable portal
is the critical influential factors on the success of knowledge
management (KM) implementation in an organization.
Abstract: Link reliability and transmitted power are two important design constraints in wireless network design. Error control coding (ECC) is a classic approach used to increase link reliability and to lower the required transmitted power. It provides coding gain, resulting in transmitter energy savings at the cost of added decoder power consumption. But the choice of ECC is very critical in the case of wireless sensor network (WSN). Since the WSNs are energy constraint in nature, both the BER and power consumption has to be taken into count. This paper develops a step by step approach in finding suitable error control codes for WSNs. Several simulations are taken considering different error control codes and the result shows that the RS(31,21) fits both in BER and power consumption criteria.
Abstract: The technology usages of high speed Internet leads to
establish and start new era of online education. With the
advancement of the information technology and communication
systems new opportunities have been created. This leads universities
to have various online education channels to meet the demand of
different learners- needs. One of these channels is M-learning, which
can be used to improve the online education environment. With using
such mobile technology in learning both students and instructors can
easily access educational courses anytime from anywhere. The paper
first presents literature about mobile learning and to what extent this
approach can be utilized to enhance the overall learning system. It
provides a comparison between mobile learning and traditional elearning
showing the wide array of benefits of the new generation of
technology. The possible challenges and potential advantages of Mlearning
in the online education system are also discussed.