Search results for: human action classifier

Authors: M. Govindarajan

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One of the major developments in machine learning in the past decade is the ensemble method, which finds highly accurate classifier by combining many moderately accurate component classifiers. In this research work, new ensemble classification methods are proposed with homogeneous ensemble classifier using bagging and heterogeneous ensemble classifier using arcing and their performances are analyzed in terms of accuracy. A Classifier ensemble is designed using Radial Basis Function (RBF) and Support Vector Machine (SVM) as base classifiers. The feasibility and the benefits of the proposed approaches are demonstrated by the means of standard datasets of intrusion detection. The main originality of the proposed approach is based on three main parts: preprocessing phase, classification phase, and combining phase. A wide range of comparative experiments is conducted for standard datasets of intrusion detection. The performance of the proposed homogeneous and heterogeneous ensemble classifiers are compared to the performance of other standard homogeneous and heterogeneous ensemble methods. The standard homogeneous ensemble methods include Error correcting output codes, Dagging and heterogeneous ensemble methods include majority voting, stacking. The proposed ensemble methods provide significant improvement of accuracy compared to individual classifiers and the proposed bagged RBF and SVM performs significantly better than ECOC and Dagging and the proposed hybrid RBF-SVM performs significantly better than voting and stacking. Also heterogeneous models exhibit better results than homogeneous models for standard datasets of intrusion detection. 

Keywords: data mining, ensemble, radial basis function, support vector machine, accuracy

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Authors: Dumasari, Pujiati Utami

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The bargaining position is important for a craftsman in every transaction. A strong bargaining position to encourage craftsmen to gain feasible prices on souvenirs tourism products are sold in several market segments. Some social actions of craftsmen turned out to also determine the conditions bargaining. The main goal of this study is to assess the range of social action to strengthen the bargaining position of craftsmen in marketing various products of tourism souvenir. Location of the study is set intentionally in the Sub-District of Baturaden, Banyumas Regency and also the Sub-District of Purbalingga Wetan, Purbalingga Regency. Both of them are located in the Central Java Province, Indonesia. The research method is the descriptive case study. The results showed that the craftsmen not only carry out one or two type of social action. They do all of the social action: the first is rational based instrumental, the second is rational based on the values, the third is affective, and the fourth is traditional. However, craftsmen also develop other social actions namely: collective, productive and creative action. At respondents in Baturaden dominant type of social action that is instrumentally rational, productive and creative. Meanwhile, respondents in Purbalingga more dominant social action collective, productive and creative. Some social actions implemented simultaneously by the respondents. Because of this, they concluded that the rational action that modified by themselves is more easily for strengthening the bargaining position when facing the craftsmen traders collectors. Collective and rationality social action has the highest sensitivity value for strengthening the bargaining position of craftsmen.

Keywords: bargaining position, craftsmen, strengthen, social actions, marketing of tourism souvenir

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Authors: Wafa' Slaibi Alsharafat

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Cloud computing is a modern approach in network environment. According to increased number of network users and online systems, there is a need to help these systems to be away from unauthorized resource access and detect any attempts for privacy contravention. For that purpose, Intrusion Detection System is an effective security mechanism to detect any attempts of attacks for cloud resources and their information. In this paper, Cloud Intrusion Detection System has been proposed in term of reducing or eliminating any attacks. This model concerns about achieving high detection rate after conducting a set of experiments using benchmarks dataset called KDD'99.

Keywords: IDS, cloud computing, anticipating classifier system, intrusion detection

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Authors: Saba Ebrahimi, Hedieh Ashrafi

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Predicting the cover type of forests is a challenge for natural resource managers. In this project, we aim to perform a comprehensive comparative study of two well-known classification methods, support vector machine (SVM) and decision tree (DT). The comparison is first performed among different types of each classifier, and then the best of each classifier will be compared by considering different evaluation metrics. The effect of boosting and bagging for decision trees is also explored. Furthermore, the effect of principal component analysis (PCA) and feature selection is also investigated. During the project, the forest cover-type dataset from the remote sensing and GIS program is used in all computations.

Keywords: classification methods, support vector machine, decision tree, forest cover-type dataset

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Authors: Susana Almeida

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The right to adequate food is a human right protected under several international human rights treaties of universal or regional application. In addition, this social right is – as we intend to demonstrate – guaranteed under the Portuguese Constitution. Therefore, in order to assure the protection of this right, the Portuguese State must not only abstain from interfering with this human right (negative obligation) but also take action to secure the human right to adequate food (positive obligation). In this context, the Portuguese State has developed several governmental policies, such as taxing sugary drinks, setting the maximum amount of salt in the bread or creating the National Program for the Promotion of Healthy Food. Nevertheless, we intend to demonstrate that special attention should be given to advertising, as advertisements have an extreme influence on the consumers' decisions and hence on the food decisions. In this paper, besides explaining the cross construction of the human right to adequate food, we aim to examine the Advertising Portuguese Code and to study the several provisions that could be held by the Portuguese consumer to challenge some advertisements due to the violation of the right to health and the right to adequate food. Moreover, having in mind the influence of advertising on the food decisions and the serious problems that unhealthy food may bring (e.g., child obesity), one should ask if this legal framework should not be reviewed in order to lay out some restrictions on advertising, namely setting advices like in alcohol advertisements.

Keywords: advertising code, consumer law, right to adequate food, social human right

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Authors: Xiaosheng Chen, Jingjing Chen, Phil Reed, Dan Zhang

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Conscious intention can be a promising point cut to grasp consciousness and orient voluntary action. The current study adopted a random ratio (RR), yoked random interval (RI) reinforcement learning schedule instead of the previous highly repeatable and single decision point paradigms, aimed to induce voluntary action with the conscious intention that evolves from the interaction between short-range-intention and long-range-intention. Readiness potential (RP) -like-EEG amplitude and inter-trial-EEG variability decreased significantly prior to voluntary action compared to cued action for inter-trial-EEG variability, mainly featured during the earlier stage of neural activities. Notably, (RP) -like-EEG amplitudes decreased significantly prior to higher RI-reward rates responses in which participants formed a higher plane of conscious intention. The present study suggests the possible contribution of conscious intention-based processes to the neural activities from the earlier stage prior to voluntary action on reinforcement leanring schedule.

Keywords: Reinforcement leaning schedule, voluntary action, EEG, conscious intention, readiness potential

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Authors: Finn Lannon, Jenny Roth, Roland Deutsch, Eric Igou

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The world continues to be rife with economic inequality, which has an impact on how people think and behaves in response to large and often growing gaps in wealth. Large gaps in earnings between groups within a particular organization, area or society can create tension between groups. Collective action tendencies (to protest, sign a petition, vote on behalf of an ingroup etc.) are also a growing phenomenon globally. Research shows that economic inequality promotes social processes such as appraisals of illegitimacy, which are recognized antecedents of collective action. This paper examines different types of collective action intentions among middle-status group members in response to economic inequality in two studies. Study 1 (N = 72) demonstrates a causal link between high economic inequality and collective action intentions of middle-status group members both to reduce inequality and to improve group status. A second pre-registered study (N = 432) examines key drivers of these relationships, including illegitimacy appraisals and direction of intergroup comparison. Adding to the current understanding of the topic, distinctions between the illegitimacy of one’s group status and the illegitimacy of societal inequality are found to mediate key relationships between economic inequality and relevant collective action types. The direction of intergroup comparison (upwards vs. downwards) is also shown to have a significant impact on collective action intentions to improve group status. Findings add to the understanding of the consequences of economic inequality and drivers of collective action intentions.

Keywords: economic inequality, collective action, legitimacy, social psychology

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Authors: Dara Singh, Keikhosrow Firouzbakhsh, Mohammad Taghi Ahmadian

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In this study, a validated 3D finite volume model of human eye is developed to study the fluid flow and heat transfer in the human eye at steady state conditions. For this purpose, discretized bio-heat transfer equation coupled with Boussinesq equation is analyzed with different anatomical, environmental, and physiological conditions. It is demonstrated that the fluid circulation is formed as a result of thermal gradients in various regions of eye. It is also shown that posterior region of the human eye is less affected by the ambient conditions compared to the anterior segment which is sensitive to the ambient conditions and also to the way the gravitational field is defined compared to the geometry of the eye making the circulations and the thermal field complicated in transient states. The effect of variation in material and boundary conditions guides us to the conclusion that thermal field of a healthy and non-healthy eye can be distinguished via computer simulations.

Keywords: bio-heat, boussinesq, conduction, convection, eye

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Authors: Monica Alzate, Marcos Dono, Jose Manuel Sabucedo

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As long as collective action and its predictors constitute a big body of work in the field of political psychology, context-dependent studies and moral variables are a relatively new issue. The main goal of this presentation is to examine the differences in the predictors of collective action when taking into account two different types of protest, and also focus on the role of moral obligation as a predictor of collective action. To do so, we sampled both protesters and non-protesters from two mobilizations (N=376; N=563) of different nature (catalan Independence, and an 'indignados' march) and performed a logistic regression and a 2x2 MANOVA analysis. Results showed that the predictive variables that were more discriminative between protesters and non-protesters were identity, injustice, efficacy and moral obligation for the catalan Diada and injustice and moral obligation for the 'indignados'. Also while the catalans scored higher in the identification and efficacy variables, the indignados did so in injustice and moral obligation. Differences are evidenced between two types of collective action that coexist within the same protest cycle. The frames of injustice and moral obligation gain strength in the post-2010 mobilizations, a fact probably associated with the combination of materialist and post-materialist values that distinguish the movement. All of this emphasizes the need of studying protest from a contextual point of view. Besides, moral obligation emerges as key predictor of collective action engagement.

Keywords: collective action, identity, moral obligation, protest

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Authors: Shaukat Ali Shahee, Usha Ananthakumar

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A data set exhibits class imbalance problem when one class has very few examples compared to the other class, and this is also referred to as between class imbalance. The traditional classifiers fail to classify the minority class examples correctly due to its bias towards the majority class. Apart from between-class imbalance, imbalance within classes where classes are composed of a different number of sub-clusters with these sub-clusters containing different number of examples also deteriorates the performance of the classifier. Previously, many methods have been proposed for handling imbalanced dataset problem. These methods can be classified into four categories: data preprocessing, algorithmic based, cost-based methods and ensemble of classifier. Data preprocessing techniques have shown great potential as they attempt to improve data distribution rather than the classifier. Data preprocessing technique handles class imbalance either by increasing the minority class examples or by decreasing the majority class examples. Decreasing the majority class examples lead to loss of information and also when minority class has an absolute rarity, removing the majority class examples is generally not recommended. Existing methods available for handling class imbalance do not address both between-class imbalance and within-class imbalance simultaneously. In this paper, we propose a method that handles between class imbalance and within class imbalance simultaneously for binary classification problem. Removing between class imbalance and within class imbalance simultaneously eliminates the biases of the classifier towards bigger sub-clusters by minimizing the error domination of bigger sub-clusters in total error. The proposed method uses model-based clustering to find the presence of sub-clusters or sub-concepts in the dataset. The number of examples oversampled among the sub-clusters is determined based on the complexity of sub-clusters. The method also takes into consideration the scatter of the data in the feature space and also adaptively copes up with unseen test data using Lowner-John ellipsoid for increasing the accuracy of the classifier. In this study, neural network is being used as this is one such classifier where the total error is minimized and removing the between-class imbalance and within class imbalance simultaneously help the classifier in giving equal weight to all the sub-clusters irrespective of the classes. The proposed method is validated on 9 publicly available data sets and compared with three existing oversampling techniques that rely on the spatial location of minority class examples in the euclidean feature space. The experimental results show the proposed method to be statistically significantly superior to other methods in terms of various accuracy measures. Thus the proposed method can serve as a good alternative to handle various problem domains like credit scoring, customer churn prediction, financial distress, etc., that typically involve imbalanced data sets.

Keywords: classification, imbalanced dataset, Lowner-John ellipsoid, model based clustering, oversampling

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Authors: Lottie Lane

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It is habitually assumed and stated that the World Bank should engage and comply with international human rights standards. However, the basis for holding the Bank to such standards is unclear. Most advocates of the idea invoke aspects of international law to argue that the Bank has existing obligations to act in compliance with human rights standards. The Bank itself, however, does not appear to accept such arguments, despite having endorsed the importance of human rights for a considerable length of time. A substantial challenge is that under the current international human rights law framework, the World Bank is considered a non-state actor, and as such, has no direct human rights obligations. In the absence of clear legal duties for the Bank, it is necessary to look at the tools available beyond the international human rights framework to encourage the Bank to comply with human rights standards. This article critically examines several bases for arguing that the Bank should comply and engage with human rights through its policies and practices. Drawing on the Bank’s own ‘good governance’ approach as well as the United Nations’ ‘human rights-based-approach’ to development, a new basis is suggested. First, the relationship between the World Bank and human rights is examined. Three perspectives are considered: (1) the legal position – what the status of the World Bank is under international human rights law, and whether it can be said to have existing legal human rights obligations; (2) the Bank’s own official position – how the Bank envisages its relationship with and role in the protection of human rights; and (3) the relationship between the Bank’s policies and practices and human rights (including how its attitudes are reflected in its policies and how the Bank’s operations impact human rights enjoyment in practice). Here, the article focuses on two examples – the (revised) 2016 Environmental and Social Safeguard Policies and the 2012 case-study regarding Gambella, Ethiopia. Both examples are widely considered missed opportunities for the Bank to actively engage with human rights. The analysis shows that however much pressure is placed on the Bank to improve its human rights footprint, it is extremely reluctant to do so explicitly, and the legal bases available are insufficient for requiring concrete, ex ante action by the Bank. Instead, the Bank’s own ‘good governance’ approach to development – which it has been advocating since the 1990s – can be relied upon. ‘Good governance’ has been used and applied by many actors in many contexts, receiving numerous different definitions. This article argues that human rights protection can now be considered a crucial component of good governance, at least in the context of development. In doing so, the article explains the relationship and interdependence between the two concepts, and provides three rationales for the Bank to take a ‘human rights-based approach’ to good governance. Ultimately, this article seeks to look beyond international human rights law and take a governance approach to provide a convincing basis upon which to argue that the World Bank should comply with human rights standards.

Keywords: World Bank, international human rights law, good governance, human rights-based approach

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Authors: Amira D. Ali

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Action research studies in education often address learners’ needs and empower practitioner-researcher to effectively change instructional practices and school communities. A systematic review of action research (AR) studies undertaken in EFL/ESL settings was conducted in this paper to systematically analyze empirical studies on action research published within a ten-year period (between 2010 and 2019). The review also aimed at investigating the focal strategies in teaching the language skills at school level and evaluating the overall quality of AR studies concerning focus, purpose, methodology and contribution. Inclusion criteria were established and 41 studies that fit were finally selected for the systematic review. Garrard’s (2007) Matrix Method was used to structure and synthesize the literature. Results showed a significant diversity in teaching strategies and implementation of the AR model. Almost a quarter of the studies focused on improving writing skills at elementary school level. In addition, findings revealed that (44%) of the studies used a mixed approach followed by qualitative method approach (41%), whereas only (15%) employed quantitative methodology. Research gaps for future action research in developing language skills were pointed out, and recommendations were offered.

Keywords: action research, EFL/ESL context, language skills, systematic review

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Authors: Gabriel Sunday Ayayia

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The paper argues that Ubuntu, as a philosophy that emphasizes the interconnectedness of all living things and importance of community and mutual support, can be used as a social framework to address the problems of climate change and promote environmental sustainability. The research demonstrate that Ubuntu is an ideological concept that encourages collective action on climate change, with the emphasis on individual and collective commitment to taking concrete action to address the problems of climate change. The paper shows that Ubuntu can be employed as a social tool that would enhance the cultivation of shared identity and promote the sense of shared response responsibility to develop the resilience to cope with climate change. Using qualitative and quantitative methodologies, the study establishes the imperativeness of mutual support and cooperation through the lens of Ubuntu as a human-centered scalable response to the debacle of climate change. It recommends that we can build a society that values the environment and promotes sustainable practices by encouraging community involvement in sustainable initiatives by integrating Ubuntu-based principles to our decision-making processes, collaboration, leadership, human agency and governance.

Keywords: ubuntu, climate change, humanity, collective actions, community-based

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Authors: Neha Singh, Ananya Arora

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Facial expression measurement plays a crucial role in the identification of emotion. Facial expression plays a key role in psychophysiology, neural bases, and emotional disorder, to name a few. The Facial Action Coding System (FACS) has proven to be the most efficient and widely used of the various systems used to describe facial expressions. Coders can manually code facial expressions with FACS and, by viewing video-recorded facial behaviour at a specified frame rate and slow motion, can decompose into action units (AUs). Action units are the most minor visually discriminable facial movements. FACS explicitly differentiates between facial actions and inferences about what the actions mean. Action units are the fundamental unit of FACS methodology. It is regarded as the standard measure for facial behaviour and finds its application in various fields of study beyond emotion science. These include facial neuromuscular disorders, neuroscience, computer vision, computer graphics and animation, and face encoding for digital processing. This paper discusses the conceptual basis for FACS, a numerical listing of discrete facial movements identified by the system, the system's psychometric evaluation, and the software's recommended training requirements.

Keywords: facial action, action units, coding, machine learning

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Authors: Mekha Mathew, Varun P Gopi

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Wireless Capsule Endoscopy (WCE) has become a great device in Gastrointestinal (GI) tract diagnosis, which can examine the entire GI tract, especially the small intestine without invasiveness and sedation. Bleeding in the digestive tract is a symptom of a disease rather than a disease itself. Hence the detection of bleeding is important in diagnosing many diseases. In this paper we proposes a novel method for distinguishing bleeding regions from normal regions based on Contourlet transform and Local Binary Pattern (LBP). Experiments show that this method provides a high accuracy rate of 96.38% in CIE XYZ colour space for k-Nearest Neighbour (k-NN) classifier.

Keywords: Wireless Capsule Endoscopy, local binary pattern, k-NN classifier, contourlet transform

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Authors: Sumaya Saqr

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Although many teachers regard academic research as the inclusive domain of academic researchers, teachers should contribute to the body of research guiding their own practice. Drawing on the qualitative analysis of 20 teachers’ reflection journals and interviews, this case study sheds light on the personal and professional benefits of teachers’ applications of collaborative action research in English language teaching context. The findings reveal that several aspects of teacher identity and classroom practice were changed. The present paper aspires to reveal the way in which collaborative action research process, as a learner-centered approach to staff development, would help teachers to become more independent and professionally autonomous and hence effecting change that is far greater than its initial purpose.

Keywords: change, collaborative action research, personal and professional benefits, professional development

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Authors: Lorenzo Buti

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This paper investigates the nature of democratic action through a critical reading of Claude Lefort’s notion of the democratic ‘regime’. Lefort provides one of the most innovative accounts of the essential features of a democratic regime. According to him, democracy is a political regime that acknowledges the indeterminacy of a society and stages it as a contestation between competing political actors. As such, democracy provides the symbolic markers of society’s openness towards the future. However, despite their democratic features, the recent decades in late capitalist societies attest to a sense of the future becoming fixed and predetermined. This suggests that Lefort’s conception of democracy harbours a misunderstanding of the character and experience of democratic action. This paper examines this underlying tension in Lefort’s work. It claims that Lefort underestimates how a democratic regime, next to its symbolic function, also takes a materially constituted form with its particular dynamics of power relations. Lefort’s systematic dismissal of this material dimension for democratic action can lead to the contemporary paradoxical situation where democracy’s symbolic markers are upheld (free elections, public debate, dynamic between government and opposition in parliament,…) but the room for political decision-making is constrained due to a myriad of material constraints (e.g., market pressures, institutional inertias). The paper draws out the implications for the notion of democratic action. Contra Lefort, it argues that democratic action necessarily targets the material conditions that impede the capacity for decision-making on the basis of equality and liberty. This analysis shapes our understanding of democratic action in two ways. First, democratic action takes an asymmetrical, insurgent form, as a contestation of material power relations from below. Second, it reveals an ambivalent position vis-à-vis the political regime: democratic action is symbolically made possible by the democratic dispositive, but it contests the constituted form that the democratic regime takes.

Keywords: Claude Lefort, democratic action, material constitution, political regime

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Authors: Regina Chua

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To reduce the costs of re-fielding a large survey, a Random Forest classifier was applied to measure the accuracy of classifying individuals into their assigned segments with the fewest possible questions. Given a long survey, one needed to determine the most predictive ten or fewer questions that would accurately assign new individuals to custom segments. Furthermore, the solution needed to be quick in its classification and usable in non-Python environments. In this paper, a supervised Random Forest classifier was modeled on a dataset with 7,000 individuals, 60 questions, and 254 features. The Random Forest consisted of an iterative collection of individual decision trees that result in a predicted segment with robust precision and recall scores compared to a single tree. A random 70-30 stratified sampling for training the algorithm was used, and accuracy trade-offs at different depths for each segment were identified. Ultimately, the Random Forest classifier performed at 87% accuracy at a depth of 10 with 20 instead of 254 features and 10 instead of 60 questions. With an acceptable accuracy in prioritizing feature selection, new tools were developed for non-Python environments: a worksheet with a formulaic version of the algorithm and an embedded function to predict the segment of an individual in real-time. Random Forest was determined to be an optimal classification model by its feature selection, performance, processing speed, and flexible application in other environments.

Keywords: machine learning, supervised learning, data science, random forest, classification, prediction, predictive modeling

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Authors: Romany Wagih Farag Zaky

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The relationship between development and human rights has long been the subject of academic debate. To understand the dynamics between these two concepts, various principles are adopted, from the right to development to development-based human rights. Despite the initiatives taken, the relationship between development and human rights remains unclear. However, the overlap between these two views and the idea that efforts should be made in the field of human rights have increased in recent years. It is then evaluated whether the right to sustainable development is acceptable or not. The article concludes that the principles of sustainable development are directly or indirectly recognized in various human rights instruments, which is a good answer to the question posed above. This book therefore cites regional and international human rights agreements such as , as well as the jurisprudence and interpretative guidelines of human rights institutions, to prove this hypothesis.

Keywords: sustainable development, human rights, the right to development, the human rights-based approach to development, environmental rights, economic development, social sustainability human rights protection, human rights violations, workers’ rights, justice, security

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Authors: Gajendra Kumar Mourya, Dinesh Bhatia, Akash Handique, Sunita Warjri, Syed Achaab Amir

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Nowadays, Medical imaging has become an integral part of modern healthcare. Abdominal CT images are an invaluable mean for abdominal organ investigation and have been widely studied in the recent years. Diagnosis of liver pathologies is one of the major areas of current interests in the field of medical image processing and is still an open problem. To deeply study and diagnose the liver, segmentation of liver is done to identify which part of the liver is mostly affected. Manual segmentation of the liver in CT images is time-consuming and suffers from inter- and intra-observer differences. However, automatic or semi-automatic computer aided segmentation of the Liver is a challenging task due to inter-patient Liver shape and size variability. In this paper, we present a technique for automatic segmenting the liver from CT images using Random Forest Classifier. Random forests or random decision forests are an ensemble learning method for classification that operate by constructing a multitude of decision trees at training time and outputting the class that is the mode of the classes of the individual trees. After comparing with various other techniques, it was found that Random Forest Classifier provide a better segmentation results with respect to accuracy and speed. We have done the validation of our results using various techniques and it shows above 89% accuracy in all the cases.

Keywords: CT images, image validation, random forest, segmentation

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Authors: F. Jiménez, R. Jódar, M. Martín, G. Sánchez, G. Sciavicco

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Abstract—Attribute or feature selection is one of the basic strategies to improve the performances of data classification tasks, and, at the same time, to reduce the complexity of classifiers, and it is a particularly fundamental one when the number of attributes is relatively high. Its application to unsupervised classification is restricted to a limited number of experiments in the literature. Evolutionary computation has already proven itself to be a very effective choice to consistently reduce the number of attributes towards a better classification rate and a simpler semantic interpretation of the inferred classifiers. We present a feature selection wrapper model composed by a multi-objective evolutionary algorithm, the clustering method Expectation-Maximization (EM), and the classifier C4.5 for the unsupervised classification of data extracted from a psychological test named BASC-II (Behavior Assessment System for Children - II ed.) with two objectives: Maximizing the likelihood of the clustering model and maximizing the accuracy of the obtained classifier. We present a methodology to integrate feature selection for unsupervised classification, model evaluation, decision making (to choose the most satisfactory model according to a a posteriori process in a multi-objective context), and testing. We compare the performance of the classifier obtained by the multi-objective evolutionary algorithms ENORA and NSGA-II, and the best solution is then validated by the psychologists that collected the data.

Keywords: evolutionary computation, feature selection, classification, clustering

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Authors: Bruno T. Gomes, José A. Menezes, Giordano Cabral

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With the popularity of smartphones, mobile apps emerge to meet the diverse needs, however the resources at the disposal are limited, either by the hardware, due to the low computing power, or the software, that does not have the same robustness of desktop environment. For example, in automatic audio classification (AC) tasks, musical information retrieval (MIR) subarea, is required a fast processing and a good success rate. However the mobile platform has limited computing power and the best AC tools are only available for desktop. To solve these problems the fast classifier suits, to mobile environments, the most widespread MIR technologies, seeking a balance in terms of speed and robustness. At the end we found that it is possible to enjoy the best of MIR for mobile environments. This paper presents the results obtained and the difficulties encountered.

Keywords: audio classification, audio extraction, environment mobile, musical information retrieval

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Authors: Erik Kuravsky

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One of the problems with a post-structuralist account of agency is that it appears to reject the freedom of an acting subject, thus seeming to deny the very phenomenon of agency. However, this is only a problem if we think that human beings can be agents exclusively in terms of being subjects, that is, if we think agency subjectively. Indeed, we tend to understand traditional theories of human freedom (e.g., Plato’s or Kant’s) in terms of a peculiar ability of the subject. The paper suggests to de-subjectivize agency with the help of Heidegger’s later thought. To do it, ir argues that classical theories of agency may indeed be interpreted as subject-oriented (sometimes even by their authors), but do not have to be read as such. Namely, the claim is that what makes agency what it is, what is essential in agency, is not its belonginess to a subject, but its ontological configuration. We may say that agency “happens,” and that there is a very specific ontological characteristics to this happening. The argument of the paper is that we can find these characteristic in the classical accounts of agency and that these characteristics are sufficient to distinguish human freedom from other natural phenomena. In particular, it offers to think agency not as one of human characteristics, but as an ontological event in which human beings take part. Namely, agency is a (non-human) characteristic of the different modes in which the experienceable existence of beings is determined by Being. To be an agent then is to participate in such ontological determination. What enables this participation is the ways human beings non-thematically understand the ontological difference. For example, for Plato, one acts freely only if one is led by an idea of the good, while for Kant the imperative for free action is categorial. The agency of an agent is thus dependent on the differentiation between ideas/categories and beings met in experience – one is “free” from contingent sensibility in terms of what is different from it ontologically. In this light, modern dependence on subjectivity is evident in the fact that the ontological difference is thought as belonging to one’s thinking, consciousness etc. That is, it is taken subjectively. A non-subjective account of agency, on the other hand, requires thinking this difference as belonging to Being itself, and thinking human beings as a medium within which occurs the non-human force of ontological differentiation.

Keywords: Heidegger, freedom, agency, poststructuralism

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Authors: Jefferson Camacho Mejía, Jenny Paola Forero Pachón, Luis Carlos Gómez Flórez

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Action research is a qualitative research methodology, which leads the researcher to delve into the problems of a community in order to understand its needs in depth and finally, to propose actions that lead to a change of social paradigm. Although this methodology had its beginnings in the human sciences, it has attracted increasing interest and acceptance in the field of information systems research since the 1990s. The countless possibilities offered nowadays by the use of Information Technologies (IT) in the development of different socio-economic activities have meant a change of social paradigm and the emergence of the so-called information and knowledge society. According to this, governments, large corporations, small entrepreneurs and in general, organizations of all kinds are using IT to virtualize their processes, taking them from the physical environment to the digital environment. However, there is a potential risk for organizations related with exposing valuable information without an appropriate framework for protecting it. This paper shows progress in the development of a methodological design to manage the information security risks associated with the IT-based processes virtualization, by applying the principles of the action research methodology and it is the result of a systematic review of the scientific literature. This design consists of seven fundamental stages. These are distributed in the three stages described in the action research methodology: 1) Observe, 2) Analyze and 3) Take actions. Finally, this paper aims to offer an alternative tool to traditional information security management methodologies with a view to being applied specifically in the planning stage of IT-based process virtualization in order to foresee risks and to establish security controls before formulating IT solutions in any type of organization.

Keywords: action research, information security, information technology, methodological design, process virtualization, risk management

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Authors: Rohit Gupta, Ravinder Agarwal

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Surface electromyographic (sEMG) signal has the potential to identify the human activities and intention. This potential is further exploited to control the artificial limbs using the sEMG signal from residual limbs of amputees. The paper deals with the development of multichannel cost efficient sEMG signal interface for research application, along with evaluation of proposed class dependent statistical approach of the feature selection method. The sEMG signal acquisition interface was developed using ADS1298 of Texas Instruments, which is a front-end interface integrated circuit for ECG application. Further, the sEMG signal is recorded from two lower limb muscles for three locomotions namely: Plane Walk (PW), Stair Ascending (SA), Stair Descending (SD). A class dependent statistical approach is proposed for feature selection and also its performance is compared with 12 preexisting feature vectors. To make the study more extensive, performance of five different types of classifiers are compared. The outcome of the current piece of work proves the suitability of the proposed feature selection algorithm for locomotion recognition, as compared to other existing feature vectors. The SVM Classifier is found as the outperformed classifier among compared classifiers with an average recognition accuracy of 97.40%. Feature vector selection emerges as the most dominant factor affecting the classification performance as it holds 51.51% of the total variance in classification accuracy. The results demonstrate the potentials of the developed sEMG signal acquisition interface along with the proposed feature selection algorithm.

Keywords: classifiers, feature selection, locomotion, sEMG

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Authors: T. Hari Prasath, P. Ithaya Rani

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In the world of visual technology, recognizing emotions from the face images is a challenging task. Several related methods have not utilized the dynamic facial features effectively for high performance. This paper proposes a method for emotions recognition using dynamic facial features with high performance. Initially, local features are captured by Gabor filter with different scale and orientations in each frame for finding the position and scale of face part from different backgrounds. The Gabor features are sent to the ensemble classifier for detecting Gabor facial features. The region of dynamic features is captured from the Gabor facial features in the consecutive frames which represent the dynamic variations of facial appearances. In each region of dynamic features is normalized using Z-score normalization method which is further encoded into binary pattern features with the help of threshold values. The binary features are passed to Multi-class AdaBoost classifier algorithm with the well-trained database contain happiness, sadness, surprise, fear, anger, disgust, and neutral expressions to classify the discriminative dynamic features for emotions recognition. The developed method is deployed on the Ryerson Multimedia Research Lab and Cohn-Kanade databases and they show significant performance improvement owing to their dynamic features when compared with the existing methods.

Keywords: detecting face, Gabor filter, multi-class AdaBoost classifier, Z-score normalization

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Authors: Jyoti Bharti, Navneet Manjhi, M. K.Gupta, Bimi Jain

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A reliable gait features are required to extract the gait sequences from an images. In this paper suggested a simple method for gait identification which is based on moments. Moment values are extracted on different number of frames of gray scale and silhouette images of CASIA database. These moment values are considered as feature values. Fuzzy logic and nearest neighbour classifier are used for classification. Both achieved higher recognition.

Keywords: gait, fuzzy logic, nearest neighbour, recognition rate, moments

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Authors: Tobias Strübing, Fatemeh Ziaeetabar

Abstract:

Humans usually manipulate objects with their hands. To represent these actions in a simple and understandable way, we need to use a semantic framework. For this purpose, the Semantic Event Chain (SEC) method has already been presented which is done by consideration of touching and non-touching relations between manipulated objects in a scene. This method was improved by a computational model, the so-called enriched Semantic Event Chain (eSEC), which incorporates the information of static (e.g. top, bottom) and dynamic spatial relations (e.g. moving apart, getting closer) between objects in an action scene. This leads to a better action prediction as well as the ability to distinguish between more actions. Each eSEC manipulation descriptor is a huge matrix with thirty rows and a massive set of the spatial relations between each pair of manipulated objects. The current eSEC framework has so far only been used in the category of manipulation actions, which eventually involve two hands. Here, we would like to extend this approach to a whole body action descriptor and make a conjoint activity representation structure. For this purpose, we need to do a statistical analysis to modify the current eSEC by summarizing while preserving its features, and introduce a new version called Enhanced eSEC or (e2SEC). This summarization can be done from two points of the view: 1) reducing the number of rows in an eSEC matrix, 2) shrinking the set of possible semantic spatial relations. To achieve these, we computed the importance of each matrix row in an statistical way, to see if it is possible to remove a particular one while all manipulations are still distinguishable from each other. On the other hand, we examined which semantic spatial relations can be merged without compromising the unity of the predefined manipulation actions. Therefore by performing the above analyses, we made the new e2SEC framework which has 20% fewer rows, 16.7% less static spatial and 11.1% less dynamic spatial relations. This simplification, while preserving the salient features of a semantic structure in representing actions, has a tremendous impact on the recognition and prediction of complex actions, as well as the interactions between humans and robots. It also creates a comprehensive platform to integrate with the body limbs descriptors and dramatically increases system performance, especially in complex real time applications such as human-robot interaction prediction.

Keywords: enriched semantic event chain, semantic action representation, spatial relations, statistical analysis

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Authors: Chechen Liao, Yi-Jen Huang, Yu-Ting Lu

Abstract:

This study explores and complements digital aspects. In this study, we construct a research model based on the theory of reasoned action and extend it with the advantages and disadvantages of intangibility (convenience, perceived risk), some characteristics of digital products (price, variety, trialability), and factors related to entertainment (perceived playfulness) to predict what consumers really consider when they buy digital music. Eight hypotheses were tested and supported. Finally, we prove that the theory of reasoned action is still valid in the field of digital products.

Keywords: digital music, digital product, theory of reasoned action

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Authors: JoãO Paulo Estevam De Souza, Rob Dekkers

Abstract:

Particularly for the space sector the inclusion of sustainability in product development poses considerable challenges for practitioners. Outcomes of action research at two companies in this sector demonstrate how this contemporary theme could be included in methods for product and process development; this was supported by wider focus groups involving more companies. The working together with practitioners brought to the fore that holistic product life-cycle thinking needs further development, especially when firms are suppliers to original equipment manufacturers. Furthermore, the findings indicate that the social aspect of the triple-bottom-line causes remains elusive for companies; to this purpose, some pathways based on the action research and focus groups are proposed.

Keywords: aerospace, action research, product development, product life-cycle, sustainability, triple bottom-line

Procedia PDF Downloads 107