Abstract: This paper presented a collaborative education model,
which consists four parts: collaborative teaching, collaborative
working, collaborative training and interaction. Supported by an
e-learning platform, collaborative education was practiced in a data
structure e-learning course. Data collected shows that most of students
accept collaborative education. This paper goes one step attempting to
determine which aspects appear to be most important or helpful in
collaborative education.
Abstract: A simple and easy algorithm is presented for a fast calculation of kernel functions which required in fluid simulations using the Smoothed Particle Hydrodynamic (SPH) method. Present proposed algorithm improves the Linked-list algorithm and adopts the Pair-Wise Interaction technique, which are widely used for evaluating kernel functions in fluid simulations using the SPH method. The algorithm is easy to be implemented without any complexities in programming. Some benchmark examples are used to show the simulation time saved by using the proposed algorithm. Parametric studies on the number of divisions for sub-domains, smoothing length and total amount of particles are conducted to show the effectiveness of the present technique. A compact formulation is proposed for practical usage.
Abstract: Facial expression analysis plays a significant role for
human computer interaction. Automatic analysis of human facial
expression is still a challenging problem with many applications. In
this paper, we propose neuro-fuzzy based automatic facial expression
recognition system to recognize the human facial expressions like
happy, fear, sad, angry, disgust and surprise. Initially facial image is
segmented into three regions from which the uniform Local Binary
Pattern (LBP) texture features distributions are extracted and
represented as a histogram descriptor. The facial expressions are
recognized using Multiple Adaptive Neuro Fuzzy Inference System
(MANFIS). The proposed system designed and tested with JAFFE
face database. The proposed model reports 94.29% of classification
accuracy.
Abstract: There has been a strong link between computermediated education and constructivism learning and teaching theory.. Acknowledging how well the constructivism doctrine would work online, it has been established that constructivist views of learning would agreeably correlate with the philosophy of open and distance learning. Asynchronous and synchronous communications have placed online learning on the right track of a constructive learning path. This paper is written based on the social constructivist framework, where knowledge is constructed from social communication and interaction. The study explores the possibility of practicing this theory through incorporating online discussion in the syllabus and the ways it can be implemented to contribute to young people-s personality and social development by addressing some aspects that may contribute to the social problem such as prejudice, ignorance and intolerance.
Abstract: In this paper, a simple microfluidic device for monitoring algal cell behavior is proposed. An array of algal microwells is fabricated by PDMS soft-lithography using X-ray LIGA mold, placed on a glass substrate. Two layers of replicated PDMS and substrate are attached by oxygen plasma bonding, creating a microchannel for the microfluidic system. Algal cell are loaded into the microfluidic device, which provides positive charge on the bottom surface of wells. Algal cells, which are negative charged, can be attracted to the bottom of the wells via electrostatic interaction. By varying the concentration of algal cells in the loading suspension, it is possible to obtain wells with a single cell. Liquid medium for cells monitoring are flown continuously over the wells, providing nutrient and waste exchange between the well and the main flow. This device could lead to the uncovering of the quantitative biology of the algae, which is a key to effective and extensive algal utilizations in the field of biotechnology, food industry and bioenergy research and developments.
Abstract: Modeling the behavior of the dialogue management in
the design of a spoken dialogue system using statistical methodologies
is currently a growing research area. This paper presents a work
on developing an adaptive learning approach to optimize dialogue
strategy. At the core of our system is a method formalizing dialogue
management as a sequential decision making under uncertainty whose
underlying probabilistic structure has a Markov Chain. Researchers
have mostly focused on model-free algorithms for automating the
design of dialogue management using machine learning techniques
such as reinforcement learning. But in model-free algorithms there
exist a dilemma in engaging the type of exploration versus exploitation.
Hence we present a model-based online policy learning
algorithm using interconnected learning automata for optimizing
dialogue strategy. The proposed algorithm is capable of deriving
an optimal policy that prescribes what action should be taken in
various states of conversation so as to maximize the expected total
reward to attain the goal and incorporates good exploration and
exploitation in its updates to improve the naturalness of humancomputer
interaction. We test the proposed approach using the most
sophisticated evaluation framework PARADISE for accessing to the
railway information system.
Abstract: In the present study, the incorporation of graphene
into blends of acrylonitrile-butadiene-styrene terpolymer with
polypropylene (ABS/PP) was investigated focusing on the
improvement of their thermomechanical characteristics and the effect
on their rheological behavior. The blends were prepared by melt
mixing in a twin-screw extruder and were characterized by measuring
the MFI as well as by performing DSC, TGA and mechanical tests.
The addition of graphene to ABS/PP blends tends to increase their
melt viscosity, due to the confinement of polymer chains motion.
Also, graphene causes an increment of the crystallization temperature
(Tc), especially in blends with higher PP content, because of the
reduction of surface energy of PP nucleation, which is a consequence
of the attachment of PP chains to the surface of graphene through the
intermolecular CH-π interaction. Moreover, the above nanofiller
improves the thermal stability of PP and increases the residue of
thermal degradation at all the investigated compositions of blends,
due to the thermal isolation effect and the mass transport barrier
effect. Regarding the mechanical properties, the addition of graphene
improves the elastic modulus, because of its intrinsic mechanical
characteristics and its rigidity, and this effect is particularly strong in
the case of pure PP.
Abstract: Organizational communication is an administrative
function crucial especially for executives in the implementation of
organizational and administrative functions. Executives spend a
significant part of their time on communicative activities. Doing his or her daily routine, arranging meeting schedules, speaking on the telephone, reading or replying to business correspondence, or
fulfilling the control functions within the organization, an executive typically engages in communication processes.
Efficient communication is the principal device for the adequate implementation of administrative and organizational activities. For
this purpose, management needs to specify the kind of
communication system to be set up and the kind of communication
devices to be used. Communication is vital for any organization.
In conventional offices, communication takes place within the hierarchical pyramid called the organizational structure, and is known as formal or informal communication. Formal communication
is the type that works in specified structures within the organizational rules and towards the organizational goals. Informal communication, on the other hand, is the unofficial type taking place among staff as
face-to-face or telephone interaction.
Communication in virtual as well as conventional offices is
essential for obtaining the right information in administrative
activities and decision-making. Virtual communication technologies
increase the efficiency of communication especially in virtual teams.
Group communication is strengthened through an inter-group central
channel. Further, ease of information transmission makes it possible
to reach the information at the source, allowing efficient and correct decisions. Virtual offices can present as a whole the elements of information which conventional offices produce in different
environments.
At present, virtual work has become a reality with its pros and
cons, and will probably spread very rapidly in coming years, in line
with the growth in information technologies.
Abstract: Proteomics is one of the largest areas of research for
bioinformatics and medical science. An ambitious goal of proteomics
is to elucidate the structure, interactions and functions of all proteins
within cells and organisms. Predicting Protein-Protein Interaction
(PPI) is one of the crucial and decisive problems in current research.
Genomic data offer a great opportunity and at the same time a lot of
challenges for the identification of these interactions. Many methods
have already been proposed in this regard. In case of in-silico
identification, most of the methods require both positive and negative
examples of protein interaction and the perfection of these examples
are very much crucial for the final prediction accuracy. Positive
examples are relatively easy to obtain from well known databases. But
the generation of negative examples is not a trivial task. Current PPI
identification methods generate negative examples based on some
assumptions, which are likely to affect their prediction accuracy.
Hence, if more reliable negative examples are used, the PPI prediction
methods may achieve even more accuracy. Focusing on this issue, a
graph based negative example generation method is proposed, which
is simple and more accurate than the existing approaches. An
interaction graph of the protein sequences is created. The basic
assumption is that the longer the shortest path between two
protein-sequences in the interaction graph, the less is the possibility of
their interaction. A well established PPI detection algorithm is
employed with our negative examples and in most cases it increases
the accuracy more than 10% in comparison with the negative pair
selection method in that paper.
Abstract: The present study was provided to examine the
vortical structures generated by two inclined impinging jets with
experimental and numerical investigations. The jets are issuing with a
pitch angle α=40° into a confined quiescent fluid. The experimental
investigation on flow patterns was visualized by using olive particles
injected into the jets illuminated by Nd:Yag laser light to reveal the
finer details of the confined jets interaction. It was observed that two
counter-rotating vortex pairs (CVPs) were generated in the near
region. A numerical investigation was also performed. First, the
numerical results were validates against the experimental results and
then the numerical model was used to study the effect of section ratio
on the evolution of the CVPs. Our results show promising agreement
with experimental data, and indicate that our model has the potential
to produce useful and accurate data regarding the evolution of CVPs.
Abstract: In this study, a high accuracy protein-protein interaction
prediction method is developed. The importance of the proposed
method is that it only uses sequence information of proteins while
predicting interaction. The method extracts phylogenetic profiles of
proteins by using their sequence information. Combining the phylogenetic
profiles of two proteins by checking existence of homologs
in different species and fitting this combined profile into a statistical
model, it is possible to make predictions about the interaction status
of two proteins.
For this purpose, we apply a collection of pattern recognition
techniques on the dataset of combined phylogenetic profiles of protein
pairs. Support Vector Machines, Feature Extraction using ReliefF,
Naive Bayes Classification, K-Nearest Neighborhood Classification,
Decision Trees, and Random Forest Classification are the methods
we applied for finding the classification method that best predicts
the interaction status of protein pairs. Random Forest Classification
outperformed all other methods with a prediction accuracy of 76.93%
Abstract: The purpose of this study is to explore how the emotions at the moment of conflict escalation are expressed nonverbally and how it can be detected by the parties involved in the conflicting situation. The study consists of two parts, in the first part it starts with the definition of "conflict" and "nonverbal communication". Further it includes the analysis of emotions and types of emotions, which may bring to the conflict escalation. Four types of emotions and emotion constructs are analyzed, particularly fear, anger, guilt and frustration. The second part of the study analyses the general role of nonverbal behavior in interaction and communication, which information it may give during communication to the person, who sends or receives those signals. The study finishes with the analysis of the nonverbal expression of analyzed emotions and on how it can be used during interaction.
Abstract: With advances in computer vision, non-contact gaze tracking systems are heading towards being much easier to operate and more comfortable for use, the technique proposed in this paper is specially designed for achieving these goals. For the convenience in operation, the proposal aims at the system with simple configuration which is composed of a fixed wide angle camera and dual infrared illuminators. Then in order to enhance the usability of the system based on single camera, a self-adjusting method which is called Real-time gaze Tracking Algorithm with head movement Compensation (RTAC) is developed for estimating the gaze direction under natural head movement and simplifying the calibration procedure at the same time. According to the actual evaluations, the average accuracy of about 1° is achieved over a field of 20×15×15 cm3.
Abstract: The goal of Gene Expression Analysis is to understand the processes that underlie the regulatory networks and pathways controlling inter-cellular and intra-cellular activities. In recent times microarray datasets are extensively used for this purpose. The scope of such analysis has broadened in recent times towards reconstruction of gene networks and other holistic approaches of Systems Biology. Evolutionary methods are proving to be successful in such problems and a number of such methods have been proposed. However all these methods are based on processing of genotypic information. Towards this end, there is a need to develop evolutionary methods that address phenotypic interactions together with genotypic interactions. We present a novel evolutionary approach, called Phenomic algorithm, wherein the focus is on phenotypic interaction. We use the expression profiles of genes to model the interactions between them at the phenotypic level. We apply this algorithm to the yeast sporulation dataset and show that the algorithm can identify gene networks with relative ease.
Abstract: This research adapts experimental design to investigate
the effect of conditioning or not and pre-exposure or not on brand
attitude, so it is a 2×2=4 factorial design. The results show that the
brand attitude of conditioning group is significantly higher than that of
unconditioning group. The brand attitude with pre-exposure is
significantly higher than that without pre-exposure. Conditioning or
not and pre-exposure or not have significant interaction. No matter the
celebrity is pre-exposure or not, the brand attitude is higher under
conditioning process.
Abstract: This calculation focus on the effect of exchange
interaction J and Coulomb interaction U on spin magnetic moments
(ms) of MnO by using the local spin density approximation plus the
Coulomb interaction (LSDA+U) method within full potential linear
muffin-tin orbital (FP-LMTO). Our calculated results indicated that
the spin magnetic moments correlated to J and U. The relevant
results exhibited the increasing spin magnetic moments with
increasing exchange interaction and Coulomb interaction.
Furthermore, equations of spin magnetic moment, which h good
correspondence to the experimental data 4.58μB, are defined ms =
0.11J +4.52μB and ms = 0.03U+4.52μB. So, the relation of J and U
parameter is obtained, it is obviously, J = -0.249U+1.346 eV.
Abstract: A new strategy for oriented immobilization of proteins was proposed. The strategy contains two steps. The first step is to search for a docking site away from the active site on the protein surface. The second step is trying to find a ligand that is able to grasp the targeted site of the protein. To avoid ligand binding to the active site of protein, the targeted docking site is selected to own opposite charges to those near the active site. To enhance the ligand-protein binding, both hydrophobic and electrostatic interactions need to be included. The targeted docking site should therefore contain hydrophobic amino acids. The ligand is then selected through the help of molecular docking simulations. The enzyme α-amylase derived from Aspergillus oryzae (TAKA) was taken as an example for oriented immobilization. The active site of TAKA is surrounded by negatively charged amino acids. All the possible hydrophobic sites on the surface of TAKA were evaluated by the free energy estimation through benzene docking. A hydrophobic site on the opposite side of TAKA-s active site was found to be positive in net charges. A possible ligand, 3,3-,4,4- – Biphenyltetra- carboxylic acid (BPTA), was found to catch TAKA by the designated docking site. Then, the BPTA molecules were grafted onto silica gels and measured the affinity of TAKA adsorption and the specific activity of thereby immobilized enzymes. It was found that TAKA had a dissociation constant as low as 7.0×10-6 M toward the ligand BPTA on silica gel. The increase in ionic strength has little effect on the adsorption of TAKA, which indicated the existence of hydrophobic interaction between ligands and proteins. The specific activity of the immobilized TAKA was compared with the randomly adsorbed TAKA on primary amine containing silica gel. It was found that the orderly immobilized TAKA owns a specific activity twice as high as the one randomly adsorbed by ionic interaction.
Abstract: This case study investigates the effects of reactive
focus on form through negotiation on the linguistic development of
an adult EFL learner in an exclusive private EFL classroom. The
findings revealed that in this classroom negotiated feedback occurred
significantly more often than non-negotiated feedback. However, it
was also found that in the long run the learner was significantly more
successful in correcting his own errors when he had received nonnegotiated
feedback than negotiated feedback. This study, therefore,
argues that although negotiated feedback seems to be effective for
some learners in the short run, it is non-negotiated feedback which
seems to be more effective in the long run. This long lasting effect
might be attributed to the impact of schooling system which is itself
indicative of the dominant culture, or to the absence of other
interlocutors in the course of interaction.
Abstract: This paper addresses the development of an intelligent vision system for human-robot interaction. The two novel contributions of this paper are 1) Detection of human faces and 2) Localizing the eye. The method is based on visual attributes of human skin colors and geometrical analysis of face skeleton. This paper introduces a spatial domain filtering method named ?Fuzzily skewed filter' which incorporates Fuzzy rules for deciding the gray level of pixels in the image in their neighborhoods and takes advantages of both the median and averaging filters. The effectiveness of the method has been justified over implementing the eye tracking commands to an entertainment robot, named ''AIBO''.
Abstract: In order to increase in chickpea quality and
agroecosystem sustainability, field experiments were carried out in
2007 and 2008 growing seasons. In this research the effects of
different organic, chemical and biological fertilizers were
investigated on grain yield and quality of chickpea. Experimental
units were arranged in split-split plots based on randomized complete
blocks with three replications. The highest amounts of yield and yield
components were obtained in G1×N5 interaction. Significant
increasing of N, P, K, Fe and Mg content in leaves and grains
emphasized on superiority of mentioned treatment because each one
of these nutrients has an approved role in chlorophyll synthesis and
photosynthesis ability of the crop. The combined application of
compost, farmyard manure and chemical phosphorus (N5) had the
best grain quality due to high protein, starch and total sugar contents,
low crude fiber and reduced cooking time.