Search results for: Document recognition

Authors: Daesung Moon, Woo-Yong Choi, Kiyoung Moon

Abstract:

Fuzzy fingerprint vault is a recently developed cryptographic construct based on the polynomial reconstruction problem to secure critical data with the fingerprint data. However, the previous researches are not applicable to the fingerprint having a few minutiae since they use a fixed degree of the polynomial without considering the number of fingerprint minutiae. To solve this problem, we use an adaptive degree of the polynomial considering the number of minutiae extracted from each user. Also, we apply multiple polynomials to avoid the possible degradation of the security of a simple solution(i.e., using a low-degree polynomial). Based on the experimental results, our method can make the possible attack difficult 2192 times more than using a low-degree polynomial as well as verify the users having a few minutiae.

Keywords: Fuzzy vault, fingerprint recognition multiple polynomials.

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Authors: Khaled N. El-Hashmi, Omar K.Gnieber

Abstract:

The clinical laboratory has received considerable recognition globally due to the rapid development of advanced technology, economic demands and its role in a patient’s treatment cycle. Although various cross-domain experiments and practices with respect to clinical laboratory projects are ready for the full swing, the customer needs are still ambiguous and debatable. The purpose of this study is to apply Kano’s model and customer satisfaction matrix to categorize service quality attributes in order to see how well these attributes are able to satisfy customer needs. The result reveals that ten of the 26 service quality attributes have greater impacts on highly increasing customer’s satisfaction and should be taken in consideration firstly.

Keywords: Clinical laboratory, Customer satisfaction matrix, Kano’s Model, Quality Attributes, Voice of Customer.

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Authors: Jeong Hoon Lee, Jin Hwan Yu

Abstract:

The number of people using SNS with their mobile devices is soaring. This research focuses on the Twitter service that has the most third-party applications and delved into the fact that there were not sufficient studies on the UX design aspects of Twitter applications. Among social network services which have emerged as a major social topic lately, this research try to analyze the UX design of the Twitter application which is also called micro-blogging service. Therefore this research sets its goal to draw components of the UX design aspect of the Tweeter application on which there are not enough analysis yet. Moreover, this research suggests improvement of mobile application which will assure better users- experience. In order to analyze the UX design aspect of the mobile twitter application, with relevant document and user research, evaluating factors of the UX Design which would affect users- experience were organized. The subjects for cases were selected among six paid and free social networking applications that had been consistently ranked from 1st to 100th in the Korean application store during May, 2012 after closely monitoring the rank. From May 15th to May 11th in 2012, in accordance with the evaluating standard, surveys were conducted in a form of interviews with 20 subjects who have used the Twitter application to find out problems and solutions for the UX design of the mobile Twitter application.

Keywords: Social network service, twitter, user experience design, interface design.

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Authors: Nicolás H. Beltrán, Manuel A. Duarte-Mermoud, Víctor A. Soto, Sebastián A. Salah, and Matías A. Bustos

Abstract:

Results of Chilean wine classification based on the information provided by an electronic nose are reported in this paper. The classification scheme consists of two parts; in the first stage, Principal Component Analysis is used as feature extraction method to reduce the dimensionality of the original information. Then, Radial Basis Functions Neural Networks is used as pattern recognition technique to perform the classification. The objective of this study is to classify different Cabernet Sauvignon, Merlot and Carménère wine samples from different years, valleys and vineyards of Chile.

Keywords: Feature extraction techniques, Pattern recognitiontechniques, Principal component analysis, Radial basis functionsneural networks, Wine classification.

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Authors: Elisa Pautasso, Matteo Castagno, Michele Osella

Abstract:

In the last decade the emergence of new social needs as an effect of the economic crisis has stimulated the flourishing of business endeavours characterised by explicit social goals. Social start-ups, social enterprises or Corporate Social Responsibility operations carried out by traditional companies are quintessential examples in this regard. This paper analyses these kinds of initiatives in order to discover the main characteristics of social business models and to provide insights to social entrepreneurs for developing or improving their strategies. The research is conducted through the integration of literature review and case study analysis and, thanks to the recognition of the importance of both profits and social impacts as the key success factors for a social business model, proposes a framework for identifying indicators suitable for measuring the social impacts generated.

Keywords: Business model, case study, impacts, social business.

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Authors: M. Kosandi, V. Susanti, N. I. Subono, E. Kartini

Abstract:

This paper discusses the risk of glorification trap in combating human trafficking, as it is shown in the case of Indonesia. Based on a research on Indonesian combat against trafficking in 2017-2018, this paper shows the tendency of misinterpretation and misapplication of the Indonesian anti-trafficking law into misusing the law for glorification, to create an image of certain extent of achievement in combating human trafficking. The objective of this paper is to explain the persistent occurrence of human trafficking crimes despite the significant progress of anti-trafficking efforts of Indonesian government. The research was conducted in 2017-2018 by qualitative approach through observation, depth interviews, discourse analysis, and document study, applying the three-dimensional model for analyzing human trafficking in the source country. This paper argues that the drive for glorification of achievement in the combat against trafficking has trapped Indonesian government in the loop of misinterpretation, misapplication, and misuse of the anti-trafficking law. In return, the so-called crime against humanity remains high and tends to increase in Indonesia.

Keywords: Human trafficking, anti-trafficking policy, transnational crime, source country, glorification trap.

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Authors: Elteyeb Eljack, Takashi Ohta

Abstract:

Proper orthogonal decomposition (POD) is used to reconstruct spatio-temporal data of a fully developed turbulent channel flow with density variation at Reynolds number of 150, based on the friction velocity and the channel half-width, and Prandtl number of 0.71. To apply POD to the fully developed turbulent channel flow with density variation, the flow field (velocities, density, and temperature) is scaled by the corresponding root mean square values (rms) so that the flow field becomes dimensionless. A five-vector POD problem is solved numerically. The reconstructed second-order moments of velocity, temperature, and density from POD eigenfunctions compare favorably to the original Direct Numerical Simulation (DNS) data.

Keywords: Pattern Recognition, POD, Coherent Structures, Low dimensional modelling.

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Authors: B. Q. Huang, Tarik Rashid, M-T. Kechadi

Abstract:

this paper presents a multi-context recurrent network for time series analysis. While simple recurrent network (SRN) are very popular among recurrent neural networks, they still have some shortcomings in terms of learning speed and accuracy that need to be addressed. To solve these problems, we proposed a multi-context recurrent network (MCRN) with three different learning algorithms. The performance of this network is evaluated on some real-world application such as handwriting recognition and energy load forecasting. We study the performance of this network and we compared it to a very well established SRN. The experimental results showed that MCRN is very efficient and very well suited to time series analysis and its applications.

Keywords: Gradient descent method, recurrent neural network, learning algorithms, time series, BP

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Authors: S, Rosnafisah, M.S., Siti Salbiah., A, Mohd Sharifuddin

Abstract:

Research in e-Business has been growing tremendously covering all related aspects such as adoption issues, e- Business models, strategies, etc. This research aims to explore the potential of adopting e-Business for a micro size business operating from home called home-based businesses (HBBs). In Malaysia, the HBB industry started many years ago and were mostly monopolized by women or housewives managed as a part-time job to support their family economy. Today, things have changed. The availability of the Internet technology and the emergence of e-Business concept promote the evolution of HBBs, which have been adopted as another alternative as a professional career for women without neglecting their family needs especially the children. Although this study is confined to a limited sample size and within geographical biasness, the findings show that it concurs with previous large scale studies. In this study, both qualitative and quantitative methods were used and data were gathered using triangulation methods via interview, direct observation, document analysis and survey questionnaires. This paper discusses the literature review, research methods and findings pertaining to e-Business adoption factors that influence the HBBs in Malaysia.

Keywords: e-Business, HBB, adoption factor, qualitative andquantitative

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Authors: Chau-Kuang Chen, John Hughes, Jr., A. Dexter Samuels

Abstract:

The prediction models for the United States Medical Licensure Examination (USMLE) Steps 1 and 2 performances were constructed by the Monte Carlo simulation modeling approach via linear regression. The purpose of this study was to build robust simulation models to accurately identify the most important predictors and yield the valid range estimations of the Steps 1 and 2 scores. The application of simulation modeling approach was deemed an effective way in predicting student performances on licensure examinations. Also, sensitivity analysis (a/k/a what-if analysis) in the simulation models was used to predict the magnitudes of Steps 1 and 2 affected by changes in the National Board of Medical Examiners (NBME) Basic Science Subject Board scores. In addition, the study results indicated that the Medical College Admission Test (MCAT) Verbal Reasoning score and Step 1 score were significant predictors of the Step 2 performance. Hence, institutions could screen qualified student applicants for interviews and document the effectiveness of basic science education program based on the simulation results.

Keywords: Prediction Model, Sensitivity Analysis, Simulation Method, USMLE.

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Authors: M. Nemissi, H. Seridi, H. Akdag

Abstract:

This paper presents and evaluates a new classification method that aims to improve classifiers performances and speed up their training process. The proposed approach, called labeled classification, seeks to improve convergence of the BP (Back propagation) algorithm through the addition of an extra feature (labels) to all training examples. To classify every new example, tests will be carried out each label. The simplicity of implementation is the main advantage of this approach because no modifications are required in the training algorithms. Therefore, it can be used with others techniques of acceleration and stabilization. In this work, two models of the labeled classification are proposed: the LMLP (Labeled Multi Layered Perceptron) and the LNFC (Labeled Neuro Fuzzy Classifier). These models are tested using Iris, wine, texture and human thigh databases to evaluate their performances.

Keywords: Artificial neural networks, Fusion of neural networkfuzzysystems, Learning theory, Pattern recognition.

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Authors: Bouttout Abdelouahab, Amara Mohamed, Djakabe Saad, Remram Youcef

Abstract:

This paper presents the results of an evaluation of acoustic comfort such as background noise and reverberation time in teaching rooms in Height National School of Civil Engineering, Algeria. Four teaching rooms are evaluated: conference room, two classroom and amphitheatre. The acoustic quality of the classrooms has been analyzed based on measurements of sound pressure level inside room and reverberations time. The measurement results show that impulse decays dependent on the position of the microphone inside room and the background noise is with agreement of National Official Journal of Algeria published in July 1993. Therefore there exists a discrepancy between the obtained reverberation time value and recommended reverberation time in some classrooms. Three methods have been proposed to reduce the reverberation time values in such room. We developed a program with FORTRAN 6.0 language based on the absorption acoustic values of the Technical Document Regulation (DTR C3.1.1). The important results of this paper can be used to regulate the construction and execute the acoustic rehabilitations of teaching room in Algeria, especially the classrooms of the pupils in primary and secondary schools.

Keywords: Room acoustic, reverberation time, background noise, absorptions materials.

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Authors: R. Xu, X. Zhao, X. Li, C. Kwan, C.-I Chang

Abstract:

An image texture analysis and target recognition approach of using an improved image texture feature coding method (TFCM) and Support Vector Machine (SVM) for target detection is presented. With our proposed target detection framework, targets of interest can be detected accurately. Cascade-Sliding-Window technique was also developed for automated target localization. Application to mammogram showed that over 88% of normal mammograms and 80% of abnormal mammograms can be correctly identified. The approach was also successfully applied to Synthetic Aperture Radar (SAR) and Ground Penetrating Radar (GPR) images for target detection.

Keywords: Image texture analysis, feature extraction, target detection, pattern classification.

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Authors: S. Kherchaoui, A. Houacine

Abstract:

This paper presents a facial expression recognition system. It performs identification and classification of the seven basic expressions; happy, surprise, fear, disgust, sadness, anger, and neutral states. It consists of three main parts. The first one is the detection of a face and the corresponding facial features to extract the most expressive portion of the face, followed by a normalization of the region of interest. Then calculus of curvelet coefficients is performed with dimensionality reduction through principal component analysis. The resulting coefficients are combined with two ratios; mouth ratio and face edge ratio to constitute the whole feature vector. The third step is the classification of the emotional state using the SVM method in the feature space.

Keywords: Facial expression identification, curvelet coefficients, support vector machine (SVM).

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Authors: Yoshimoto Kurihara, Tad Gonsalves

Abstract:

Currently, in the field of object posture estimation, there is research on estimating the position and angle of an object by storing a 3D model of the object to be estimated in advance in a computer and matching it with the model. However, in this research, we have succeeded in creating a module that is much simpler, smaller in scale, and faster in operation. Our 6D pose estimation model consists of two different networks – a classification network and a regression network. From a single RGB image, the trained model estimates the class of the object in the image, the coordinates of the object, and its rotation angle in 3D space. In addition, we compared the estimation accuracy of each camera position, i.e., the angle from which the object was captured. The highest accuracy was recorded when the camera position was 75°, the accuracy of the classification was about 87.3%, and that of regression was about 98.9%.

Keywords: AlexNet, Deep learning, image recognition, 6D posture estimation.

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Authors: Mostafa Alinezhad, Mehrdad Ahmadi Kamarposhti

Abstract:

According to the increasing utilization in power system, the transmission lines and power plants often operate in stability boundary and system probably lose its stable condition by over loading or occurring disturbance. According to the reasons that are mentioned, the prediction and recognition of voltage instability in power system has particular importance and it makes the network security stronger.This paper, by considering of power system contingencies based on the effects of them on Mega Watt Margin (MWM) and maximum loading point is focused in order to analyse the static voltage stability using continuation power flow method. The study has been carried out on IEEE 14-Bus Test System using Matlab and Psat softwares and results are presented.

Keywords: Contingency, Continuation Power Flow, Static Voltage Stability, Voltage Collapse.

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Authors: Yang-Keun Ahn, Min-Wook Kim, Young-Choong Park, Kwang-Soon Choi, Woo-Chool Park, Hae-Moon Seo, Kwang-Mo Jung

Abstract:

Active research is underway on virtual touch screens that complement the physical limitations of conventional touch screens. This paper discusses a virtual touch screen that uses a multi-layer perceptron to recognize and control three-dimensional (3D) depth information from a time of flight (TOF) camera. This system extracts an object-s area from the image input and compares it with the trajectory of the object, which is learned in advance, to recognize gestures. The system enables the maneuvering of content in virtual space by utilizing human actions.

Keywords: Gesture Recognition, Depth Sensor, Virtual Touch Screen

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Authors: Tudor Barbu

Abstract:

An automatic moment-based texture segmentation approach is proposed in this paper. First, we describe the related work in this computer vision domain. Our texture feature extraction, the first part of the texture recognition process, produces a set of moment-based feature vectors. For each image pixel, a texture feature vector is computed as a sequence of area moments. Then, an automatic pixel classification approach is proposed. The feature vectors are clustered using an unsupervised classification algorithm, the optimal number of clusters being determined using a measure based on validation indexes. From the resulted pixel classes one determines easily the desired texture regions of the image.

Keywords: Image segmentation, moment-based texture analysis, automatic classification, validity indexes.

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Authors: R. Haghighat far, H. Yarahmadi

Abstract:

A mobile agent is a software which performs an action autonomously and independently as a person or an organizations assistance. Mobile agents are used for searching information, retrieval information, filtering, intruder recognition in networks, and so on. One of the important issues of mobile agent is their security. It must consider different security issues in effective and secured usage of mobile agent. One of those issues is the integrity-s protection of mobile agents. In this paper, the advantages and disadvantages of each method, after reviewing the existing methods, is examined. Regarding to this matter that each method has its own advantage or disadvantage, it seems that by combining these methods, one can reach to a better method for protecting the integrity of mobile agents. Therefore, this method is provided in this paper and then is evaluated in terms of existing method. Finally, this method is simulated and its results are the sign of improving the possibility of integrity-s protection of mobile agents.

Keywords: Integrity, Mobile Agent, Security.

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Authors: Sera Syarmila Sameon, Rohaini Ramli

Abstract:

A trustworthy voting process in democratic is important that each vote is recorded with accuracy and impartiality. The accuracy and impartiality are tallied in high rate with biometric system. One of the sign is a fingerprint. Fingerprint recognition is still a challenging problem, because of the distortions among the different impression of the same finger. Because of the trustworthy of biometric voting technologies, it may give a great effect on numbers of voter-s participation and outcomes of the democratic process. Hence in this study, the authors are interested in designing and analyzing the Electronic Voting System and the participation of the users. The system is based on the fingerprint minutiae with the addition of person ID number. This is in order to enhance the accuracy and speed of the voting process. The new design is analyzed by conducting pilot election among a class of students for selecting their representative.

Keywords: Biometric, FAR and FRR, democratic, voting

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Authors: H. El Fadili, K. Zenkouar, H. Qjidaa

Abstract:

This paper proposes a neural network weights and topology optimization using genetic evolution and the backpropagation training algorithm. The proposed crossover and mutation operators aims to adapt the networks architectures and weights during the evolution process. Through a specific inheritance procedure, the weights are transmitted from the parents to their offsprings, which allows re-exploitation of the already trained networks and hence the acceleration of the global convergence of the algorithm. In the preprocessing phase, a new feature extraction method is proposed based on Legendre moments with the Maximum entropy principle MEP as a selection criterion. This allows a global search space reduction in the design of the networks. The proposed method has been applied and tested on the well known MNIST database of handwritten digits.

Keywords: Genetic algorithm, Legendre Moments, MEP, Neural Network.

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Authors: J. I. Asnor, S. Rosnah, Z. W. H. Wan, H. A. B. Badrul

Abstract:

Pineapples can be classified using an index with seven levels of maturity based on the green and yellow color of the skin. As the pineapple ripens, the skin will change from pale green to a golden or yellowish color. The issues that occur in agriculture nowadays are to do with farmers being unable to distinguish between the indexes of pineapple maturity correctly and effectively. There are several reasons for why farmers cannot properly follow the guideline provide by Federal Agriculture Marketing Authority (FAMA) and one of reason is that due to manual inspection done by experts, there are no specific and universal guidelines to be adopted by farmers due to the different points of view of the experts when sorting the pineapples based on their knowledge and experience. Therefore, an automatic system will help farmers to identify pineapple maturity effectively and will become a universal indicator to farmers.

Keywords: Artificial Neural Network, Image Processing, Index of Maturity, Pineapple

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Authors: Mohammad Reza Ayatollahzadeh Shirazi, Pooya Jaferian, Golnaz Elahi, Hamid Baghi, Babak Sadeghian

Abstract:

The world is moving rapidly toward the deployment of information and communication systems. Nowadays, computing systems with their fast growth are found everywhere and one of the main challenges for these systems is increasing attacks and security threats against them. Thus, capturing, analyzing and verifying security requirements becomes a very important activity in development process of computing systems, specially in developing systems such as banking, military and e-business systems. For developing every system, a process model which includes a process, methods and tools is chosen. The Rational Unified Process (RUP) is one of the most popular and complete process models which is used by developers in recent years. This process model should be extended to be used in developing secure software systems. In this paper, the Requirement Discipline of RUP is extended to improve RUP for developing secure software systems. These proposed extensions are adding and integrating a number of Activities, Roles, and Artifacts to RUP in order to capture, document and model threats and security requirements of system. These extensions introduce a group of clear and stepwise activities to developers. By following these activities, developers assure that security requirements are captured and modeled. These models are used in design, implementation and test activitie

Keywords:

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Authors: Boci J., Çabeli P., Shtylla T., Kumbe I.

Abstract:

The development of the poultry industry in Albania is mainly based on the existence of intensive modern farms with huge capacities, which often are mixed with other forms. Colibacillosis is commonly displayed regardless of the type of breeding, delivering high mortality in poultry industry. The mechanisms with which pathogen enterobacters are able to cause the infection in poultry are not yet clear. The routine diagnose in the field, followed by isolation of E. coli and species of Salmonella genres in reference laboratories cannot lead in classification or full recognition of circulative strains in a territory, if it is not performed a differentiation among the present microorganisms in intensive farms and those in rural areas. In this study were isolated 1.496 strains of E. coli and 378 Salmonella spp. This study, presents distribution of poultry pathogenosity of E.coli and Salmonella spp., based on the usage of innovative diagnostic methods.

Keywords: poultry, E.coli, Salmonella spp., Enterobacter

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Authors: Aravind Mohan Krishnan

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.

Keywords: Tourism, entrepreneurship, Malawi, business opportunities.

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Authors: Suk-Hyun Yu, Heeyong Kwon

Abstract:

Recently PM-10 has become a social and global issue. It is one of major air pollutants which affect human health. Therefore, it needs to be forecasted rapidly and precisely. However, PM-10 comes from various emission sources, and its level of concentration is largely dependent on meteorological and geographical factors of local and global region, so the forecasting of PM-10 concentration is very difficult. Neural network model can be used in the case. But, there are few cases of high concentration PM-10. It makes the learning of the neural network model difficult. In this paper, we suggest a simple input balancing method when the data distribution is uneven. It is based on the probability of appearance of the data. Experimental results show that the input balancing makes the neural networks’ learning easy and improves the forecasting rates.

Keywords: AI, air quality prediction, neural networks, pattern recognition, PM-10.

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Authors: Francis Deinmodei W. Poazi, Jasmine O. Tamunosiki-Amadi, Maurice Fems

Abstract:

In recent times the resource-based view (RBV) of strategic management has recorded a sizeable attention yet there has not been a considerable scholarly and managerial discourse, debate and attention. As a result, this paper gives special bit of critical reasoning as well as top-notch analyses and relationship between RBV and organizational innovation. The study examines those salient aspects of RBV that basically have the will power in ensuring the organization's capacity to go for innovative capability. In achieving such fit and standpoint, the paper joins other relevant academic discourse and empirical evidence. To this end, a reasonable amount of contributions in setting the ground running for future empirical researches would have been provided. More so, the study is guided and built on the following strength and significance: Firstly, RBV sees resources as heterogeneity which forms a strong point of strength and allows organisations to gain competitive advantage. In order words, competitive advantage can be achieved or delivered to the organization when resources are distinctively utilized in a valuable manner more than the envisaged competitors of the organization. Secondly, RBV is significantly influential in determining the real resources that are available in the organization with a view to locate capabilities within in order to attract more profitability into the organization when applied. Thus, there will be more sustainable growth and success in the ever competitive and emerging market. Thus, to have succinct description of the basic methodologies, the study adopts both qualitative as well as quantitative approach with a view to have a broad samples of opinion in establishing and identifying key and strategic organizational resources to enable managers of resources to gain a competitive advantage as well as generating a sustainable increase and growth in profit. Furthermore, a comparative approach and analysis was used to examine the performance of RBV within the organization. Thus, the following are some of the findings of the study: it is clear that there is a nexus between RBV and growth of competitively viable organizations. More so, in most parts, organizations have heterogeneous resources domiciled in their organizations but not all organizations as it was specifically and intelligently adopting the tenets of RBV to strengthen heterogeneity of resources which allows organisations to gain competitive advantage. Other findings of this study reveal that of managerial perception of RBV with respect to application and transformation of resources to achieve a profitable end. It is against this backdrop, the importance of RBV cannot be overemphasized; the study is strongly convinced and think that RBV view is one focal and distinct approach that is focused on internal to outside strategy which engenders sourcing or generating resources internally as well as having the quest to apply such internally sourced resources diligently to increase or gain competitive advantage.

Keywords: Competitive advantage, innovation, organisation, recognition, resource-based view.

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Authors: N. Greco, S. Impedovo, R.Modugno, G. Pirlo

Abstract:

This paper presents a new technique for generating sets of synthetic classifiers to evaluate abstract-level combination methods. The sets differ in terms of both recognition rates of the individual classifiers and degree of similarity. For this purpose, each abstract-level classifier is considered as a random variable producing one class label as the output for an input pattern. From the initial set of classifiers, new slightly different sets are generated by applying specific operators, which are defined at the purpose. Finally, the sets of synthetic classifiers have been used to estimate the performance of combination methods for abstract-level classifiers. The experimental results demonstrate the effectiveness of the proposed approach.

Keywords: Abstract-level Classifier, Dempster-Shafer Rule, Multi-expert Systems, Similarity Index, System Evaluation

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Authors: Young Geun Kim, Tae Woo Lee, Changmin Yeo, Jung min Yoo, Yeo Jin Kang, Tack-Joong Kim, Byungjo Jung, Ji Hun Cha, Chan Hoi Hur, Dong-Sup Kim, Ki Jung Park, Han Sung Kim

Abstract:

The intention of this lessons is to assess the probability of optical coherence tomography (OCT) for biometric recognition. The OCT is the foundation on an optical signal acquisition and processing method and has the micrometer-resolution. In this study, we used the porcine skin for verifying the abovementioned means. The porcine tissue was sound acknowledged for structural and immunohistochemical similarity with human skin, so it could be suitable for pre-clinical trial as investigational specimen. For this reason, it was tattooed by the tattoo machine with the tattoo-pigment. We detected the pattern of the tattooed skin by the OCT according to needle speed. The result was consistent with the histology images. This result showed that the OCT was effective to examine the tattooed skin section noninvasively. It might be available to identify morphological changes inside the skin.

Keywords: mechanical skin damage, optical coherence tomography, tattooed skin

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Authors: Ratima Damkham, Natasha Dejdumrong, Priyakorn Pusawiro

Abstract:

This paper explored the solution in game design to help game designers in the educational game designing using digital educational game model canvas (DEGMC) and digital educational game form (DEGF) based on Outcome-based Education program. DEGMC and DEGF can help designers develop an overview of the game while designing and planning their own game. The way to clearly assess players’ ability from learning outcomes and support their game learning design is by using the tools. Designers can balance educational content and entertainment in designing a game by using the strategies of the Business Model Canvas and design the gameplay and players’ ability assessment from learning outcomes they need by referring to the Constructive Alignment. Furthermore, they can use their design plan in this research to write their Game Design Document (GDD). The success of the research was evaluated by four experts’ perspectives in the education and computer field. From the experiments, the canvas and form helped the game designers model their game according to the learning outcomes and analysis of their own game elements. This method can be a path to research an educational game design in the future.

Keywords: Constructive alignment, constructivist theory, educational game, outcome-based education.

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