Abstract: This paper discusses the causal explanation capability
of QRIOM, a tool aimed at supporting learning of organic chemistry
reactions. The development of the tool is based on the hybrid use of
Qualitative Reasoning (QR) technique and Qualitative Process
Theory (QPT) ontology. Our simulation combines symbolic,
qualitative description of relations with quantity analysis to generate
causal graphs. The pedagogy embedded in the simulator is to both
simulate and explain organic reactions. Qualitative reasoning through
a causal chain will be presented to explain the overall changes made
on the substrate; from initial substrate until the production of final
outputs. Several uses of the QPT modeling constructs in supporting
behavioral and causal explanation during run-time will also be
demonstrated. Explaining organic reactions through causal graph
trace can help improve the reasoning ability of learners in that their
conceptual understanding of the subject is nurtured.
Abstract: In illumination variant face recognition, existing
methods extracting face albedo as light normalized image may lead to
loss of extensive facial details, with light template discarded. To
improve that, a novel approach for realistic facial texture
reconstruction by combining original image and albedo image is
proposed. First, light subspaces of different identities are established
from the given reference face images; then by projecting the original
and albedo image into each light subspace respectively, texture
reference images with corresponding lighting are reconstructed and
two texture subspaces are formed. According to the projections in
texture subspaces, facial texture with normal light can be synthesized.
Due to the combination of original image, facial details can be
preserved with face albedo. In addition, image partition is applied to
improve the synthesization performance. Experiments on Yale B and
CMUPIE databases demonstrate that this algorithm outperforms the
others both in image representation and in face recognition.
Abstract: In this paper a new approach to face recognition is presented that achieves double dimension reduction making the system computationally efficient with better recognition results. In pattern recognition techniques, discriminative information of image increases with increase in resolution to a certain extent, consequently face recognition results improve with increase in face image resolution and levels off when arriving at a certain resolution level. In the proposed model of face recognition, first image decimation algorithm is applied on face image for dimension reduction to a certain resolution level which provides best recognition results. Due to better computational speed and feature extraction potential of Discrete Cosine Transform (DCT) it is applied on face image. A subset of coefficients of DCT from low to mid frequencies that represent the face adequately and provides best recognition results is retained. A trade of between decimation factor, number of DCT coefficients retained and recognition rate with minimum computation is obtained. Preprocessing of the image is carried out to increase its robustness against variations in poses and illumination level. This new model has been tested on different databases which include ORL database, Yale database and a color database. The proposed technique has performed much better compared to other techniques. The significance of the model is two fold: (1) dimension reduction up to an effective and suitable face image resolution (2) appropriate DCT coefficients are retained to achieve best recognition results with varying image poses, intensity and illumination level.
Abstract: The human friendly interaction is the key function of a human-centered system. Over the years, it has received much attention to develop the convenient interaction through intention recognition. Intention recognition processes multimodal inputs including speech, face images, and body gestures. In this paper, we suggest a novel approach of intention recognition using a graph representation called Intention Graph. A concept of valid intention is proposed, as a target of intention recognition. Our approach has two phases: goal recognition phase and intention recognition phase. In the goal recognition phase, we generate an action graph based on the observed actions, and then the candidate goals and their plans are recognized. In the intention recognition phase, the intention is recognized with relevant goals and user profile. We show that the algorithm has polynomial time complexity. The intention graph is applied to a simple briefcase domain to test our model.
Abstract: In this era of competitiveness, there is a growing need for supply chains also to become competitive enough to handle pressures like varying customer’s expectations, low cost high quality products to be delivered at the minimum time and the most important is throat cutting competition at world wide scale. In the recent years, supply chain competitiveness has been, therefore, accepted as one of the most important philosophies in the supply chain literature. Various researchers and practitioners have tried to identify and implement strategies in supply chains which can bring competitiveness in the supply chains i.e. supply chain competitiveness. The purpose of this paper is to suggest select strategies for supply chain competitiveness in the Indian manufacturing sector using an integrated approach of literature review and exploratory interviews with eminent professionals from the supply chain area in various industries, academia and research. The aim of the paper is to highlight the important area of competitiveness in the supply chain and to suggest recommendations to the industry and managers of manufacturing sector.
Abstract: This paper presents development of an ignition system using spark electrodes for application in a research explosion vessel.
A single spark is aimed to be discharged with quantifiable ignition energy. The spark electrode system would enable study of flame
propagation, ignitability of fuel-air mixtures and other fundamental characteristics of flames. The principle of the capacitive spark circuit
of ASTM is studied to charge an appropriate capacitance connected across the spark gap through a large resistor by a high voltage from
the source of power supply until the initiation of spark. Different spark energies could be obtained mainly by varying the value of the
capacitance and the supply current. The spark sizes produced are found to be affected by the spark gap, electrode size, input voltage
and capacitance value.
Abstract: Two commercial proteases from Bacillus
licheniformis (Alcalase 2.4 L FG and Alcalase 2.5 L, Type DX) were
screened for the production of Z-Ala-Phe-NH2 in batch reaction.
Alcalase 2.4 L FG was the most efficient enzyme for the C-terminal
amidation of Z-Ala-Phe-OMe using ammonium carbamate as
ammonium source. Immobilization of protease has been achieved by
the sol-gel method, using dimethyldimethoxysilane (DMDMOS) and
tetramethoxysilane (TMOS) as precursors (unpublished results). In
batch production, about 95% of Z-Ala-Phe-NH2 was obtained at
30°C after 24 hours of incubation. Reproducibility of different
batches of commercial Alcalase 2.4 L FG preparations was also
investigated by evaluating the amidation activity and the entrapment
yields in the case of immobilization. A packed-bed reactor (0.68 cm
ID, 15.0 cm long) was operated successfully for the continuous
synthesis of peptide amides. The immobilized enzyme retained the
initial activity over 10 cycles of repeated use in continuous reactor at
ambient temperature. At 0.75 mL/min flow rate of the substrate
mixture, the total conversion of Z-Ala-Phe-OMe was achieved after 5
hours of substrate recycling. The product contained about 90%
peptide amide and 10% hydrolysis byproduct.
Abstract: Tumor classification is a key area of research in the
field of bioinformatics. Microarray technology is commonly used in
the study of disease diagnosis using gene expression levels. The
main drawback of gene expression data is that it contains thousands
of genes and a very few samples. Feature selection methods are used
to select the informative genes from the microarray. These methods
considerably improve the classification accuracy. In the proposed
method, Genetic Algorithm (GA) is used for effective feature
selection. Informative genes are identified based on the T-Statistics,
Signal-to-Noise Ratio (SNR) and F-Test values. The initial candidate
solutions of GA are obtained from top-m informative genes. The
classification accuracy of k-Nearest Neighbor (kNN) method is used
as the fitness function for GA. In this work, kNN and Support Vector
Machine (SVM) are used as the classifiers. The experimental results
show that the proposed work is suitable for effective feature
selection. With the help of the selected genes, GA-kNN method
achieves 100% accuracy in 4 datasets and GA-SVM method
achieves in 5 out of 10 datasets. The GA with kNN and SVM
methods are demonstrated to be an accurate method for microarray
based tumor classification.
Abstract: Open and distance learning is a fairly new concept in
Malawi. The major public provider, the Malawi College of Distance
Education, rolled out its activities only about 40 years ago. Over the
years, the demand for distance education has tremendously increased.
The present government has displayed positive political will to uplift
ODL as outlined in the Malawi Growth and Development Strategy as
well as the National Education Sector Plan. A growing national
interest in education coupled with political stability and a booming
ICT industry also raise hope for success. However, a fragile economy
with a GNI per capita of -US$ 200 over the last decade, poor public
funding, erratic power supply and lack of expertise put strain on
efforts towards the promotion of ODL initiatives. Despite the
challenges, the nation appears determined to go flat out and explore
all possible avenues that could revolutionise education access and
equity through ODL.
Abstract: One astonishing capability of humans is to recognize thousands of different objects visually, and to learn the semantic association between those objects and words referring to them. This work is an attempt to build a computational model of such capacity,simulating the process by which infants learn how to recognize objects and words through exposure to visual stimuli and vocal sounds.One of the main fact shaping the brain of a newborn is that lights and colors come from entities of the world. Gradually the visual system learn which light sensations belong to same entities, despite large changes in appearance. This experience is common between humans and several other mammals, like non-human primates. But humans only can recognize a huge variety of objects, most manufactured by himself, and make use of sounds to identify and categorize them. The aim of this model is to reproduce these processes in a biologically plausible way, by reconstructing the essential hierarchy of cortical circuits on the visual and auditory neural paths.
Abstract: Social cognitive theory explains the power to inaugurate change is determined by the mutual influence of personal proclivity and social factors which will shape ones- motivations and expectations. In construction industry, green concept offers an opportunity to leave a lighter footprint on the environment. This opportunity, however, has not been fully grasped by many countries. As such, venturing into green construction for many practitioners would be their maiden experience. Decision to venture into new practice such as green construction will be influenced by certain drivers. This paper explores these drivers which is further expanded into motivational factors and later becomes the platform upon which expectation for green construction stands. This theoretical concept of motivation and expectations, which is adapted from social cognitive theory, focus on developers- view because of their crucial role in green application. This conceptual framework, which serves as the basis for further research, will benefit the industry as it elucidate cognitive angles to attract more new entrants to green business.
Abstract: In view of geological origin, formation of the shallow
gas reservoir of the Hangzhou Bay, northern Zhejiang Province,
eastern China, and original occurrence characteristics of the gassy
sand are analyzed. Generally, gassy sand in scale gas reservoirs is in
the state of residual moisture content and the approximate scope of
initial matric suction of sand ranges about from 0kPa to100kPa.
Results based on GDS triaxial tests show that the classical shear
strength formulas of unsaturated soil can not effectively describe basic
strength characteristics of gassy sand; the relationship between
apparent cohesion and matric suction of gassy sand agrees well with
the power function, which can reasonably be used to describe the
strength of gassy sand. In the stress path of gas release, shear strength
of gassy sand will increase and experimental results show the formula
proposed in this paper can effectively predict the strength increment.
When saturated strength indexes of the sand are used in engineering
design, moderate reduction should be considered.
Abstract: With the rapid growth and development of information and communication technology, the Internet has played a definite and irreplaceable role in people-s social lives in Taiwan like in other countries. In July 2008, on a general social website, an unexpected phenomenon was noticed – that there were more than one hundred users who started forming clubs voluntarily and having face-to-face gatherings for specific purposes. In this study, it-s argued whether or not teenagers- social contact on the Internet is involved in their life context, and tried to reveal the teenagers- social preferences, values, and needs, which merge with and influence teenagers- social activities. Therefore, the study conducts multiple user experience research methods, which include practical observations and qualitative analysis by contextual inquiries and in-depth interviews. Based on the findings, several design implications for software related to social interactions and cultural inheritance are offered. It is concluded that the inherent values of a social behaviors might be a key issue in developing computer-mediated communication or interaction designs in the future.
Abstract: Pipeline infrastructures normally represent high cost of investment and the pipeline must be free from risks that could cause environmental hazard and potential threats to personnel safety. Pipeline integrity such monitoring and management become very crucial to provide unimpeded transportation and avoiding unnecessary production deferment. Thus proper cleaning and inspection is the key to safe and reliable pipeline operation and plays an important role in pipeline integrity management program and has become a standard industry procedure. In view of this, understanding the motion (dynamic behavior), prediction and control of the PIG speed is important in executing pigging operation as it offers significant benefits, such as estimating PIG arrival time at receiving station, planning for suitable pigging operation, and improves efficiency of pigging tasks. The objective of this paper is to review recent developments in speed control system of pipeline PIGs. The review carried out would serve as an industrial application in a form of quick reference of recent developments in pipeline PIG speed control system, and further initiate others to add-in/update the list in the future leading to knowledge based data, and would attract active interest of others to share their view points.
Abstract: In face recognition, feature extraction techniques
attempts to search for appropriate representation of the data. However,
when the feature dimension is larger than the samples size, it brings
performance degradation. Hence, we propose a method called
Normalization Discriminant Independent Component Analysis
(NDICA). The input data will be regularized to obtain the most
reliable features from the data and processed using Independent
Component Analysis (ICA). The proposed method is evaluated on
three face databases, Olivetti Research Ltd (ORL), Face Recognition
Technology (FERET) and Face Recognition Grand Challenge
(FRGC). NDICA showed it effectiveness compared with other
unsupervised and supervised techniques.
Abstract: Measuring the complexity of software has been an
insoluble problem in software engineering. Complexity measures can
be used to predict critical information about testability, reliability,
and maintainability of software systems from automatic analysis of
the source code. During the past few years, many complexity
measures have been invented based on the emerging Cognitive
Informatics discipline. These software complexity measures,
including cognitive functional size, lend themselves to the approach
of the total cognitive weights of basic control structures such as loops
and branches. This paper shows that the current existing calculation
method can generate different results that are algebraically
equivalence. However, analysis of the combinatorial meanings of this
calculation method shows significant flaw of the measure, which also
explains why it does not satisfy Weyuker's properties. Based on the
findings, improvement directions, such as measures fusion, and
cumulative variable counting scheme are suggested to enhance the
effectiveness of cognitive complexity measures.
Abstract: The intelligent fuzzy input estimator is used to estimate
the input force of the rigid bar structural system in this study. The
fuzzy Kalman filter without the input term and the fuzzy weighting
recursive least square estimator are two main portions of this method.
The practicability and accuracy of the proposed method were verified
with numerical simulations from which the input forces of a rigid bar
structural system were estimated from the output responses. In order to
examine the accuracy of the proposed method, a rigid bar structural
system is subjected to periodic sinusoidal dynamic loading. The
excellent performance of this estimator is demonstrated by comparing
it with the use of difference weighting function and improper the
initial process noise covariance. The estimated results have a good
agreement with the true values in all cases tested.
Abstract: The communication networks development and
advancement during two last decades has been toward a single goal
and that is gradual change from circuit-switched networks to packed
switched ones. Today a lot of networks operates are trying to
transform the public telephone networks to multipurpose packed
switch. This new achievement is generally called "next generation
networks". In fact, the next generation networks enable the operators
to transfer every kind of services (sound, data and video) on a
network. First, in this report the definition, characteristics and next
generation networks services and then ad-hoc networks role in the
next generation networks are studied.
Abstract: The paper considers a novel modular and intrinsically safe redundant robotic system with biologically inspired actuators (pneumatic artificial muscles and rubber bellows actuators). Similarly to the biological systems, the stiffness of the internal parallel modules, representing 2 DOF joints in the serial robotic chains, is controlled by co-activation of opposing redundant actuator groups in the null-space of the module Jacobian, without influencing the actual robot position. The decoupled position/stiffness control allows the realization of variable joint stiffness according to different force-displacement relationships. The variable joint stiffness, as well as limited pneumatic muscle/bellows force ability, ensures internal system safety that is crucial for development of human-friendly robots intended for human-robot collaboration. The initial experiments with the system prototype demonstrate the capabilities of independently, simultaneously controlling both joint (Cartesian) motion and joint stiffness. The paper also presents the possible industrial applications of snake-like robots built using the new modules.
Abstract: Technology transfer of renewable energy technologies is very often unsuccessful in the developing world. Aside from challenges that have social, economic, financial, institutional and environmental dimensions, technology transfer has generally been misunderstood, and largely seen as mere delivery of high tech equipment from developed to developing countries or within the developing world from R&D institutions to society. Technology transfer entails much more, including, but not limited to: entire systems and their component parts, know-how, goods and services, equipment, and organisational and managerial procedures. Means to facilitate the successful transfer of energy technologies, including the sharing of lessons are subsequently extremely important for developing countries as they grapple with increasing energy needs to sustain adequate economic growth and development. Improving the success of technology transfer is an ongoing process as more projects are implemented, new problems are encountered and new lessons are learnt. Renewable energy is also critical to improve the quality of lives of the majority of people in developing countries. In rural areas energy is primarily traditional biomass. The consumption activities typically occur in an inefficient manner, thus working against the notion of sustainable development. This paper explores the implementation of technology transfer in the developing world (sub-Saharan Africa). The focus is necessarily on RETs since most rural energy initiatives are RETs-based. Additionally, it aims to highlight some lessons drawn from the cited RE projects and identifies notable differences where energy technology transfer was judged to be successful. This is done through a literature review based on a selection of documented case studies which are judged against the definition provided for technology transfer. This paper also puts forth research recommendations that might contribute to improved technology transfer in the developing world. Key findings of this paper include: Technology transfer cannot be complete without satisfying pre-conditions such as: affordability, maintenance (and associated plans), knowledge and skills transfer, appropriate know how, ownership and commitment, ability to adapt technology, sound business principles such as financial viability and sustainability, project management, relevance and many others. It is also shown that lessons are learnt in both successful and unsuccessful projects.