Search results for: Public emotion recognition

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: Wei Yang, Xiaohui Cui, Weiping Zhu, Liqun Liu

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The rapid development of the Confucius Institute is attracting more and more attention from mainstream media around the world. Mainstream media plays a large role in public information dissemination and public opinion. This study presents efforts to analyze the correlation and functional relationship between domestic and foreign mainstream media by analyzing the amount of reports on the Confucius Institute. Three kinds of correlation calculation methods, the Pearson correlation coefficient (PCC), the Spearman correlation coefficient (SCC), and the Kendall rank correlation coefficient (KCC), were applied to analyze the correlations among mainstream media from three regions: mainland of China; Hong Kong and Macao (the two special administration regions of China denoted as SARs); and overseas countries excluding China, such as the United States, England, and Canada. Further, the paper measures the functional relationships among the regions using a regression model. The experimental analyses found high correlations among mainstream media from the different regions. Additionally, we found that there is a linear relationship between the mainstream media of overseas countries and those of the SARs by analyzing the amount of reports on the Confucius Institute based on a data set obtained by crawling the websites of 106 mainstream media during the years 2004 to 2014.

Keywords: Confucius Institute, correlation analysis, mainstream media, regression model.

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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: Taner Ersoz, Filiz Ersoz

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This study was designed enable application of multivariate technique in the interpretation of categorical data for measuring health care services satisfaction in Turkey. The data was collected from a total of 17726 respondents. The establishment of the sample group and collection of the data were carried out by a joint team from The Ministry of Health and Turkish Statistical Institute (Turk Stat) of Turkey. The multiple correspondence analysis (MCA) was used on the data of 2882 respondents who answered the questionnaire in full. The multiple correspondence analysis indicated that, in the evaluation of health services females, public employees, younger and more highly educated individuals were more concerned and complainant than males, private sector employees, older and less educated individuals. Overall 53 % of the respondents were pleased with the improvements in health care services in the past three years. This study demonstrates the public consciousness in health services and health care satisfaction in Turkey. It was found that most the respondents were pleased with the improvements in health care services over the past three years. Awareness of health service quality increases with education levels. Older individuals and males would appear to have lower expectancies in health services.

Keywords: Multiple correspondence analysis, optimal scaling, multivariate categorical data, health care services, health satisfaction survey, statistical visualizing, Turkey.

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

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

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

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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: Siri-orn Champatong

Abstract:

The purpose of this research was to study five vital factors related to employees’ job performance. A total of 250 respondents were sampled from employees who worked at a public warehouse organization, Bangkok, Thailand. Samples were divided into two groups according to their work experience. The average working experience was about 9 years for group one and 28 years for group two. A questionnaire was utilized as a tool to collect data. Statistics utilized in this research included frequency, percentage, mean, standard deviation, t-test analysis, one way ANOVA, and Pearson Product-moment correlation coefficient. Data were analyzed by using Statistical Package for the Social Sciences. The findings disclosed that the majority of respondents were female between 23- 31 years old, single, and hold an undergraduate degree. The average income of respondents was less than 30,900 baht. The findings also revealed that the factors of organization chart awareness, job process and technology, internal environment, employee loyalty, and policy and management were ranked as medium level. The hypotheses testing revealed that difference in gender, age, and position had differences in terms of the awareness of organization chart, job process and technology, internal environment, employee loyalty, and policy and management in the same direction with low level.

Keywords: Employees, Factors Related, Job Performance, Public Warehouse Organization.

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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: Ahmad Mansoor Stanikzai, Yoshitaka Kajita

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This research is a very essential towards transportation planning of Kabul New City. In this research, the travel demand of Kabul metropolitan area (Existing and Kabul New City) are evaluated for three different target years (2015, current, 2025, mid-term, 2040, long-term). The outcome of this study indicates that, though currently the vehicle volume is less the capacity of existing road networks, Kabul city is suffering from daily traffic congestions. This is mainly due to lack of transportation management, the absence of proper policies, improper public transportation system and violation of traffic rules and regulations by inhabitants. On the other hand, the observed result indicates that the current vehicle to capacity ratio (VCR) which is the most used index to judge traffic status in the city is around 0.79. This indicates the inappropriate traffic condition of the city. Moreover, by the growth of population in mid-term (2025) and long-term (2040) and in the case of no development in the road network and transportation system, the VCR value will dramatically increase to 1.40 (2025) and 2.5 (2040). This can be a critical situation for an urban area from an urban transportation perspective. Thus, by introducing high-capacity public transportation system and the development of road network in Kabul New City and integrating these links with the existing city road network, significant improvements were observed in the value of VCR.

Keywords: Afghanistan, Kabul New City, planning, policy, urban transportation.

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Authors: Mostafa Alinezhad, Mehrdad Ahmadi Kamarposhti

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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: Ball J., Capanni N., Watt S.

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This paper argues that fostering mutual understanding in landscape planning is as much about the planners educating stakeholder groups as the stakeholders educating the planners. In other words it is an epistemological agreement as to the meaning and nature of place, especially where an effort is made to go beyond the quantitative aspects, which can be achieved by the phenomenological experience of the Virtual Reality (VR) environment. This education needs to be a bi-directional process in which distance can be both temporal as well as spatial separation of participants, that there needs to be a common framework of understanding in which neither 'side' is disadvantaged during the process of information exchange and it follows that a medium such as VR offers an effective way of overcoming some of the shortcomings of traditional media by taking advantage of continuing technological advances in Information, Technology and Communications (ITC). In this paper we make particular reference to this as an extension to Geographical Information Systems (GIS). VR as a two-way communication tool offers considerable potential particularly in the area of Public Participation GIS (PPGIS). Information rich virtual environments that can operate over broadband networks are now possible and thus allow for the representation of large amounts of qualitative and quantitative information 'side-by-side'. Therefore, with broadband access becoming standard for households and enterprises alike, distributed virtual reality environments have great potential to contribute to enabling stakeholder participation and mutual learning within the planning context.

Keywords: 3D, communication, geographical information systems, planning, public participation, virtual reality, visualisation.

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Authors: R. Haghighat far, H. Yarahmadi

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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

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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

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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

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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: David J. Russell SC

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Widespread use of asbestos over the last century has left a terrible legacy of lung disease. Doctors knew of the health risks long ago, but almost nothing was done to protect workers and the public. Some aspects of nanotechnology may have risks similar to asbestos.

Keywords: Asbestos, causation, nanotechnology.

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

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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

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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

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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

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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

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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

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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: Surinder Deswal, Vineet Verma

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Air Quality Index (AQI) is used as a tool to indicate the level of severity and disseminate the information on air pollution to enable the public to understand the health and environmental impacts of air pollutant concentration levels. The annual and seasonal variation of criteria air pollutants concentration based on the National Ambient Air Quality Monitoring Programme has been conducted for a period of nine years (2006-2014) using the AQI system. AQI was calculated using IND-AQI methodology and Maximum Operator Concept is applied. An attempt has been made to quantify the variations in AQI on an annual and seasonal basis over a period of nine years. Further, year-wise frequency of occurrence of AQI in each category for all the five stations is analysed, which presents in depth analysis of trends over the period of study. The best air quality was observed in the Noida residential area, followed by Noida industrial area during the study period; whereas, Bulandshahar industrial area and Faridabad residential area were observed to have the worst air quality. A shift in the worst air quality from winter to summer season has also been observed during the study period. Further, the level of Respirable Suspended Particulate Matter was found to be above permissible limit at all the stations. The present study helps in enhancing public awareness and calls for the need of immediate measures to be taken to counter-effect the cause of the increasing level of air pollution.

Keywords: Air quality index, annual trends, criteria pollutants, seasonal variation.

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Authors: Ming-Ta Yang, Jin-Lung Guan, Jhy-Cherng Gu

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The purpose of this paper is to solve the problem of protecting aerial lines from high impedance faults (HIFs) in distribution systems. This investigation successfully applies 3I0 zero sequence current to solve HIF problems. The feature extraction system based on discrete wavelet transform (DWT) and the feature identification technique found on statistical confidence are then applied to discriminate effectively between the HIFs and the switch operations. Based on continuous wavelet transform (CWT) pattern recognition of HIFs is proposed, also. Staged fault testing results demonstrate that the proposed wavelet based algorithm is feasible performance well.

Keywords: Continuous wavelet transform, discrete wavelet transform, high impedance faults, statistical confidence.

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Authors: Semeh Ben Salem, Sami Naouali, Moetez Sallami

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The increasing amount of collected data has limited the performance of the current analyzing algorithms. Thus, developing new cost-effective algorithms in terms of complexity, scalability, and accuracy raised significant interests. In this paper, a modified effective k-means based algorithm is developed and experimented. The new algorithm aims to reduce the computational load without significantly affecting the quality of the clusterings. The algorithm uses the City Block distance and a new stop criterion to guarantee the convergence. Conducted experiments on a real data set show its high performance when compared with the original k-means version.

Keywords: Pattern recognition, partitional clustering, K-means clustering, Manhattan distance, terrorism data analysis.

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Authors: Paul N. Napari, Patrick B. Cobbinah

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The 21^st century has been characterized by rapid urbanization with its associated environmental sanitation challenges especially in developing countries. However, studies have focused largely on institutional capacity and the resources needed to manage environmental sanitation challenges, with few insights on the attitudes of city residents. This paper analyzes the environmental sanitation situation in a rapidly urbanizing Tamale metropolis, examines how city residents’ attitudes have contributed to poor environmental sanitation and further reviews approaches that have been employed to manage environmental sanitation. Using secondary and empirical data sources, the paper reveals that only 7.5 tons of 150 tons of total daily solid wastes generated is effectively managed. The findings suggest that the poor sanitation in the city is influenced by two factors; poor attitudes of city residents and weak institutions. While poor attitudes towards environmental sanitation has resulted in indiscriminate disposal of waste, weak institutions have resulted in lack of capacity and pragmatic interventions to manage the environmental sanitation challenges in the city. The paper recommends public education on environmental sanitation, public private partnership, increased stakeholder engagement and preparation and implementation of environmental sanitation plan as mechanisms to ensure effective environmental sanitation management in the Tamale metropolis.

Keywords: Environmental sanitation, developing countries, waste management, developing countries, Tamale, urbanization.

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