Abstract: This paper aims to teach English (secondary language) by bridging the understanding between the Regional language (primary language) and the English Language (secondary language). Here primary language is the one a person has learned from birth or within the critical period, while secondary language would be any other language one learns or speaks. The paper also focuses on evolving old teaching methods to a contemporary participatory model of learning and teaching. Pilot studies were conducted to gauge an understanding of student’s knowledge of the English language. Teachers and students were interviewed and their academic curriculum was assessed as a part of the initial study. Extensive literature study and design thinking principles were used to devise a solution to the problem. The objective is met using a holistic learning kit/card game to teach children word recognition, word pronunciation, word spelling and writing words. Implication of the paper is a noticeable improvement in the understanding and grasping of English language. With increasing usage and applicability of English as a second language (ESL) world over, the paper becomes relevant due to its easy replicability to any other primary or secondary language. Future scope of this paper would be transforming the idea of participatory learning into self-regulated learning methods. With the upcoming govt. learning centres in rural areas and provision of smart devices such as tablets, the development of the card games into digital applications seems very feasible.
Abstract: This paper identifies a research gap in the literature on tourism entrepreneurship in Malawi, Africa, and investigates how entrepreneurs from the Malawian tourism sector discover and exploit business opportunities. In particular, the importance of prior experience and business networks in the opportunity development process is debated. Another area of empirical research examined here is the opportunity recognition-venture creation sequence. While Malawi presents fruitful business opportunities, exploiting these opportunities into fully realized business ideas is a real challenge due to the country’s difficult business environment and poor promotional and marketing efforts. The study concludes by calling for further research in Sub-Saharan Africa in order to develop our understanding of entrepreneurship in this (African) context.
Abstract: During the past two decades, photoinitiated polymerization has been attracting a great interest in terms of scientific and industrial activity. The wide recognition of UV treatment in the polymer industry results not only from its many practical applications but also from its advantage for low-cost processes. Unlike most thermal curing systems, radiation-curable systems can polymerize at room temperature without additional heat, and the curing is completed in a very short time. The advantage of cationic UV technology is that post-cure can continue in the ‘dark’ after radiation. In this study, bio-based acrylated epoxidized soybean oil (AESO) was cured with UV radiation using radicalic photoinitiator Irgacure 184. Triarylsulphonium hexafluoroantimonate was used as cationic photoinitiator for curing of 3,4-epoxycyclohexylmethyl-3,4-epoxycyclohexanecarboxylate. The effect of curing time and the amount of initiators on the curing degree and thermal properties were investigated. The thermal properties of the coating were analyzed after crosslinking UV irradiation. The level of crosslinking in the coating was evaluated by FTIR analysis. Cationic UV-cured coatings demonstrated excellent adhesion and corrosion resistance properties. Therefore, our study holds a great potential with its simple and low-cost applications.
Abstract: The large karstic Bell spring with a discharge ranging between 250 and 5300 lit/ sec is one of the most important springs of Kermanshah Province. This spring supplies drinking water of Nodsheh City and its surrounding villages. The spring is located in the reservoir of Daryan Dam and its mouth would be submerged after impounding under a water column of about 110 m height. This paper has aimed to render an account of the karstification pattern around the spring under consideration with the intention of preventing Bell Spring from being submerged in Daryan Dam Reservoir. The studies comprise engineering geology and hydrogeology investigations. Some geotechnical activities included in these studies include geophysical studies, drilling, excavation of exploratory gallery and shaft and diving. The results depict that Bell is a single-conduit siphon spring with 4 m diameter and 85 m height that 32 m of the conduit is located below the spring outlet. To survive the spring, it was decided to plug the outlet and convey the water to upper elevations under the natural pressure of the aquifer. After plugging, water was successfully conveyed to elevation 837 meter above sea level (about 120 m from the outlet) under the natural pressure of the aquifer. This signifies the accuracy of the studies done and proper recognition of the karstification pattern of Bell Spring. This is a unique experience in karst problems in Iran.
Abstract: A variety of techniques and methods are available to evaluate cognitive performance in Urban Search and Rescue (USAR) applications. However, traditional cognitive performance evaluation techniques typically incorporate either the conscious or systematic aspect, failing to take into consideration the subconscious or intuitive aspect. This leads to incomplete measures and produces ineffective designs. In order to fill the gaps in past research, this study developed a theoretical framework to facilitate the integration of situation awareness (SA) and intuitive pattern recognition (IPR) to enhance the cognitive performance representation in USAR applications. This framework provides guidance to integrate both SA and IPR in order to evaluate the cognitive performance of the USAR responders. The application of this framework will help improve the system design.
Abstract: The conceptual framework of International Financial Reporting Standards determines the basic principles of accounting. The said principles have multiple applications, with professional judgments being one of those. Recognition and assessment of the information contained in financial reporting, especially so the somewhat uncertain events and transactions and/or the ones regarding which there is no standard or interpretation are based on professional judgments. Professional judgments aim at the formulation of expert assumptions regarding the specifics of the circumstances and events to be entered into the report based on the conceptual framework terms and principles. Experts have to make a choice in favor of one of the aforesaid and simulate the situations applying multi-variant accounting estimates and judgment. In making the choice, one should consider all the factors, which may help represent the information in the best way possible. Professional judgment determines the relevance and faithful representation of the presented information, which makes it more useful for the existing and potential investors. In order to assess the prospected net cash flows, the information must be predictable and reliable. The publication contains critical analysis of the aforementioned problems. The fact that the International Financial Reporting Standards are developed continuously makes the issue all the more important and that is another point discussed in the study.
Abstract: The main purpose of this paper is to examine the effect of diversity sensitive orientation on job satisfaction and turnover intention. Diversity sensitive orientation is the attitude of the individual to respect and accommodate diversity. This is focused on an individual’s perception of diversity. Although being made from the most diversity related research team and organizational level, this study deals with diversity issues at the individual level. To test the proposed research model and hypothesis, the data were collected from 291 Korean employees. The study conducted a confirmatory factor analysis for the validity test. Furthermore, structural equation modeling (SEM) was employed to test the hypothesized relationship in the conceptual model. The results of this paper were as followings: First, diversity sensitive orientation was positively related to job satisfaction. Second, diversity sensitive orientation was negatively related to turnover intention. In other words, the positive influence of the diversity sensitive orientation has been verified. Based on the findings, this study suggested implications and directions for future research.
Abstract: In this paper, an attribute weighting method called fuzzy C-means clustering based attribute weighting (FCMAW) for classification of Diabetes disease dataset has been used. The aims of this study are to reduce the variance within attributes of diabetes dataset and to improve the classification accuracy of classifier algorithm transforming from non-linear separable datasets to linearly separable datasets. Pima Indians Diabetes dataset has two classes including normal subjects (500 instances) and diabetes subjects (268 instances). Fuzzy C-means clustering is an improved version of K-means clustering method and is one of most used clustering methods in data mining and machine learning applications. In this study, as the first stage, fuzzy C-means clustering process has been used for finding the centers of attributes in Pima Indians diabetes dataset and then weighted the dataset according to the ratios of the means of attributes to centers of theirs. Secondly, after weighting process, the classifier algorithms including support vector machine (SVM) and k-NN (k- nearest neighbor) classifiers have been used for classifying weighted Pima Indians diabetes dataset. Experimental results show that the proposed attribute weighting method (FCMAW) has obtained very promising results in the classification of Pima Indians diabetes dataset.
Abstract: With the aging of the world population and the
continuous growth in technology, service robots are more and more
explored nowadays as alternatives to healthcare givers or personal
assistants for the elderly or disabled people. Any service robot
should be capable of interacting with the human companion, receive
commands, navigate through the environment, either known or
unknown, and recognize objects. This paper proposes an approach
for object recognition based on the use of depth information and
color images for a service robot. We present a study on two of the
most used methods for object detection, where 3D data is used to
detect the position of objects to classify that are found on horizontal
surfaces. Since most of the objects of interest accessible for service
robots are on these surfaces, the proposed 3D segmentation reduces
the processing time and simplifies the scene for object recognition.
The first approach for object recognition is based on color histograms,
while the second is based on the use of the SIFT and SURF feature
descriptors. We present comparative experimental results obtained
with a real service robot.
Abstract: The problem of emotion recognition is a challenging problem. It is still an open problem from the aspect of both intelligent systems and psychology. In this paper, both voice features and facial features are used for building an emotion recognition system. A Support Vector Machine classifiers are built by using raw data from video recordings. In this paper, the results obtained for the emotion recognition are given, and a discussion about the validity and the expressiveness of different emotions is presented. A comparison between the classifiers build from facial data only, voice data only and from the combination of both data is made here. The need for a better combination of the information from facial expression and voice data is argued.
Abstract: The P300 from Event related potential (ERP) explains the psycho-physiological phenomenon in human body. The present study aims to identify the differences of amplitude and latency of P300 component from auditory stimuli, between ambiversion and extraversion types of personality. Ambivert (N=20) and extravert (N=20) undergoing ERP recording at the Hospital Universiti Sains Malaysia (HUSM) laboratory. Electroencephalogram data was recorded with oddball paradigm, counting auditory standard and target tones, from nine electrode sites (Fz, Cz, Pz, T3, T4, T5, T6, P3 and P4) by using the 128 HydroCel Geodesic Sensor Net. The P300 latency of the target tones at all electrodes were insignificant. Similarly, the P300 latency of the standard tones were also insignificant except at Fz and T3 electrode. Likewise, the P300 amplitude of the target and standard tone in all electrode sites were insignificant. Extravert and ambivert indicate similar characteristic in cognition processing from auditory task.
Abstract: The most important elements of a novel are the characters, events and background. The background represents the time, place and situation that character appears, and conveys event and atmosphere more realistically. If readers have the proper knowledge about background of novels, it may be helpful for understanding the atmosphere of a novel and choosing a novel that readers want to read. In this paper, we are targeting Korean historical novels because spatio-temporal background especially performs an important role in historical novels among the genre of Korean novels. To the best of our knowledge, we could not find previous study that was aimed at Korean novels. In this paper, we build a Korean historical national dictionary. Our dictionary has historical places and temple names of kings over many generations as well as currently existing spatial words or temporal words in Korean history. We also present a method for recognizing spatio-temporal background based on patterns of phrasal words in Korean sentences. Our rules utilize postposition for spatial background recognition and temple names for temporal background recognition. The knowledge of the recognized background can help readers to understand the flow of events and atmosphere, and can use to visualize the elements of novels.
Abstract: Deconstruction is an approach that is entirely incompatible with the traditional prevalent architecture. Considering the fact that this approach attempts to put architecture in sharp contrast with its opposite events and transpires with attending to the neglected and missing aspects of architecture and deconstructing its stable structures. It also recklessly proceeds beyond the existing frameworks and intends to create a different and more efficient prospect for space. The aim of deconstruction architecture is to satisfy both the prospective and retrospective visions as well as takes into account all tastes of the present in order to transcend time. Likewise, it ventures to fragment the facts and symbols of the past and extract new concepts from within their heart, which coincide with today’s circumstances. Since this approach is an attempt to surpass the limits of the prevalent architecture, it can be employed to design places in which creative events occur and imagination and ambition flourish. Thought-provoking artistic events can grow and mature in such places and be represented in the best way possible to all people. The concept of event proposed in the plan grows out of the interaction between space and creation. In addition to triggering surprise and high impressions, it is also considered as a bold journey into the suspended realms of the traditional conflicts in architecture such as architecture-landscape, interior-exterior, center-margin, product-process, and stability-instability. In this project, at first, through interpretive-historical research method and examining the inputs and data collection, recognition and organizing takes place. After evaluating the obtained data using deductive reasoning, the data is eventually interpreted. Given the fact that the research topic is in its infancy and there is not a similar case in Iran with limited number of corresponding instances across the world, the selected topic helps to shed lights on the unrevealed and neglected parts in architecture. Similarly, criticizing, investigating and comparing specific and highly prized cases in other countries with the project under study can serve as an introduction into this architecture style.
Abstract: Recently, Automatic Speech Recognition (ASR) systems were used to assist children in language acquisition as it has the ability to detect human speech signal. Despite the benefits offered by the ASR system, there is a lack of ASR systems for Malay-speaking children. One of the contributing factors for this is the lack of continuous speech database for the target users. Though cross-lingual adaptation is a common solution for developing ASR systems for under-resourced language, it is not viable for children as there are very limited speech databases as a source model. In this research, we propose a two-stage adaptation for the development of ASR system for Malay-speaking children using a very limited database. The two stage adaptation comprises the cross-lingual adaptation (first stage) and cross-age adaptation. For the first stage, a well-known speech database that is phonetically rich and balanced, is adapted to the medium-sized Malay adults using supervised MLLR. The second stage adaptation uses the speech acoustic model generated from the first adaptation, and the target database is a small-sized database of the target users. We have measured the performance of the proposed technique using word error rate, and then compare them with the conventional benchmark adaptation. The two stage adaptation proposed in this research has better recognition accuracy as compared to the benchmark adaptation in recognizing children’s speech.
Abstract: With the rapid development of computer technology,
the design of computers and keyboards moves towards a trend of
slimness. The change of mobile input devices directly influences
users’ behavior. Although multi-touch applications allow entering
texts through a virtual keyboard, the performance, feedback, and
comfortableness of the technology is inferior to traditional keyboard,
and while manufacturers launch mobile touch keyboards and
projection keyboards, the performance has not been satisfying.
Therefore, this study discussed the design factors of slim
pressure-sensitive keyboards. The factors were evaluated with an
objective (accuracy and speed) and a subjective evaluation
(operability, recognition, feedback, and difficulty) depending on the
shape (circle, rectangle, and L-shaped), thickness (flat, 3mm, and
6mm), and force (35±10g, 60±10g, and 85±10g) of the keyboard.
Moreover, MANOVA and Taguchi methods (regarding
signal-to-noise ratios) were conducted to find the optimal level of each
design factor. The research participants, by their typing speed (30
words/ minute), were divided in two groups. Considering the
multitude of variables and levels, the experiments were implemented
using the fractional factorial design. A representative model of the
research samples were established for input task testing. The findings
of this study showed that participants with low typing speed primarily
relied on vision to recognize the keys, and those with high typing
speed relied on tactile feedback that was affected by the thickness and
force of the keys. In the objective and subjective evaluation, a
combination of keyboard design factors that might result in higher
performance and satisfaction was identified (L-shaped, 3mm, and
60±10g) as the optimal combination. The learning curve was analyzed
to make a comparison with a traditional standard keyboard to
investigate the influence of user experience on keyboard operation.
The research results indicated the optimal combination provided input
performance to inferior to a standard keyboard. The results could serve
as a reference for the development of related products in industry and
for applying comprehensively to touch devices and input interfaces
which are interacted with people.
Abstract: In this paper, we propose an improved face recognition algorithm using histogram-based features in spatial and frequency domains. For adding spatial information of the face to improve recognition performance, a region-division (RD) method is utilized. The facial area is firstly divided into several regions, then feature vectors of each facial part are generated by Binary Vector Quantization (BVQ) histogram using DCT coefficients in low frequency domains, as well as Local Binary Pattern (LBP) histogram in spatial domain. Recognition results with different regions are first obtained separately and then fused by weighted averaging. Publicly available ORL database is used for the evaluation of our proposed algorithm, which is consisted of 40 subjects with 10 images per subject containing variations in lighting, posing, and expressions. It is demonstrated that face recognition using RD method can achieve much higher recognition rate.
Abstract: In this paper, we present an algorithm for reconstruction from incomplete 2D scans for tifinagh characters. This algorithm is based on using correlation between the lost block and its neighbors. This system proposed contains three main parts: pre-processing, features extraction and recognition. In the first step, we construct a database of tifinagh characters. In the second step, we will apply “shape analysis algorithm”. In classification part, we will use Neural Network. The simulation results demonstrate that the proposed method give good results.
Abstract: The current trends in affect recognition research are
to consider continuous observations from spontaneous natural
interactions in people using multiple feature modalities, and to
represent affect in terms of continuous dimensions, incorporate
spatio-temporal correlation among affect dimensions, and provide
fast affect predictions. These research efforts have been propelled
by a growing effort to develop affect recognition system that
can be implemented to enable seamless real-time human-computer
interaction in a wide variety of applications. Motivated by these
desired attributes of an affect recognition system, in this work
a multi-dimensional affect prediction approach is proposed by
integrating multivariate Relevance Vector Machine (MVRVM) with
a recently developed Output-associative Relevance Vector Machine
(OARVM) approach. The resulting approach can provide fast
continuous affect predictions by jointly modeling the multiple affect
dimensions and their correlations. Experiments on the RECOLA
database show that the proposed approach performs competitively
with the OARVM while providing faster predictions during testing.
Abstract: Effective statistical feature extraction and classification are important in image-based automatic inspection and analysis. An automatic wood species recognition system is designed to perform wood inspection at custom checkpoints to avoid mislabeling of timber which will results to loss of income to the timber industry. The system focuses on analyzing the statistical pores properties of the wood images. This paper proposed a fuzzy-based feature extractor which mimics the experts’ knowledge on wood texture to extract the properties of pores distribution from the wood surface texture. The proposed feature extractor consists of two steps namely pores extraction and fuzzy pores management. The total number of statistical features extracted from each wood image is 38 features. Then, a backpropagation neural network is used to classify the wood species based on the statistical features. A comprehensive set of experiments on a database composed of 5200 macroscopic images from 52 tropical wood species was used to evaluate the performance of the proposed feature extractor. The advantage of the proposed feature extraction technique is that it mimics the experts’ interpretation on wood texture which allows human involvement when analyzing the wood texture. Experimental results show the efficiency of the proposed method.
Abstract: Human skin detection recognized as the primary step in most of the applications such as face detection, illicit image filtering, hand recognition and video surveillance. The performance of any skin detection applications greatly relies on the two components: feature extraction and classification method. Skin color is the most vital information used for skin detection purpose. However, color feature alone sometimes could not handle images with having same color distribution with skin color. A color feature of pixel-based does not eliminate the skin-like color due to the intensity of skin and skin-like color fall under the same distribution. Hence, the statistical color analysis will be exploited such mean and standard deviation as an additional feature to increase the reliability of skin detector. In this paper, we studied the effectiveness of statistical color feature for human skin detection. Furthermore, the paper analyzed the integrated color and texture using eight classifiers with three color spaces of RGB, YCbCr, and HSV. The experimental results show that the integrating statistical feature using Random Forest classifier achieved a significant performance with an F1-score 0.969.