Search results for: positive behavior recognition

Authors: C. V. Aravinda, H. N. Prakash

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In this paper, we tried to convey fusion and state of art pertaining to SIL character recognition systems. In the first step, the text is preprocessed and normalized to perform the text identification correctly. The second step involves extracting relevant and informative features. The third step implements the classification decision. The three stages which involved are Data acquisition and preprocessing, Feature extraction, and Classification. Here we concentrated on two techniques to obtain features, Feature Extraction & Feature Selection. Edge-hinge distribution is a feature that characterizes the changes in direction of a script stroke in handwritten text. The edge-hinge distribution is extracted by means of a windowpane that is slid over an edge-detected binary handwriting image. Whenever the mid pixel of the window is on, the two edge fragments (i.e. connected sequences of pixels) emerging from this mid pixel are measured. Their directions are measured and stored as pairs. A joint probability distribution is obtained from a large sample of such pairs. Despite continuous effort, handwriting identification remains a challenging issue, due to different approaches use different varieties of features, having different. Therefore, our study will focus on handwriting recognition based on feature selection to simplify features extracting task, optimize classification system complexity, reduce running time and improve the classification accuracy.

Keywords: word segmentation and recognition, character recognition, optical character recognition, hand written character recognition, South Indian languages

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Authors: Hee Soo Kim, Ha Young Kyung

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This paper examines the role of positive emotions in human psychology. By understanding Fredrickson and Lyubomirsky et al.’s on positive emotions, one can better understand people’s intuitive understanding, mental health and well-being. Fredrickson asserts that positive emotions create positive affects and personal resources, and Lyubomirsky et al. relate such positive resources to the creation of happiness and personal development. This paper finds that positive emotions play a significant role in the learning process, and they are instrumental in creating a long-lasting repertoire of personal resources and play an essential role in the development of the intuitive understanding of life variables, resilience in coping with life challenges, and ability to build more successful lives.

Keywords: Positive emotions, positive affects, personal resources, negative emotions, development

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Authors: John Lorenzo Bautista, Yoon-Joong Kim

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This paper presents the development of a Filipino speech recognition tool using the HTK System. The system was trained from a subset of the Filipino Speech Corpus developed by the DSP Laboratory of the University of the Philippines-Diliman. The speech corpus was both used in training and testing the system by estimating the parameters for phonetic HMM-based (Hidden-Markov Model) acoustic models. Experiments on different mixture-weights were incorporated in the study. The phoneme-level word-based recognition of a 5-state HMM resulted in an average accuracy rate of 80.13 for a single-Gaussian mixture model, 81.13 after implementing a phoneme-alignment, and 87.19 for the increased Gaussian-mixture weight model. The highest accuracy rate of 88.70% was obtained from a 5-state model with 6 Gaussian mixtures.

Keywords: Filipino language, Hidden Markov Model, HTK system, speech recognition

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Authors: Svitov David, Alyamkin Sergey

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The usage of convolutional neural networks (CNNs) in conjunction with the margin-based softmax approach demonstrates the state-of-the-art performance for the face recognition problem. Recently, lightweight neural network models trained with the margin-based softmax have been introduced for the face identification task for edge devices. In this paper, we propose a distillation method for lightweight neural network architectures that outperforms other known methods for the face recognition task on LFW, AgeDB-30 and Megaface datasets. The idea of the proposed method is to use class centers from the teacher network for the student network. Then the student network is trained to get the same angles between the class centers and face embeddings predicted by the teacher network.

Keywords: ArcFace, distillation, face recognition, margin-based softmax

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Authors: Mohammad Ehsani, Iman Zarei, Soudabeh Moazemigoudarzi

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The aim of this study is to determine Pro-Environmental Behavioral Intention of Mountain Hikers to the Theory of Planned Behavior. According to many researchers nature-based recreation activities play a significant role in the tourism industry and have provided myriad opportunities for the protection of natural areas. It is essential to investigate individuals' behavior during such activities to avoid further damage to precious and dwindling natural resources. This study develops a robust model that provides a comprehensive understanding of the formation of pro-environmental behavioral intentions among climbers of Mount Damavand National Park in Iran. To this end, we combined the theory of planned behavior (TPB), value-belief-norm theory (VBN), and a hierarchical model of leisure constraints to predict individuals’ pro-environmental hiking behavior during outdoor recreation. It was used structural equation modeling to test the theoretical framework. A sample of 787 climbers was analyzed. Among the theory of planned behavior variables, perceived behavioral control showed the strongest association with behavioral intention (β = .57). This relationship indicates that if people feel they can have fewer negative impacts on national resources while hiking, it will result in more environmentally acceptable behavior. Subjective norms had a moderate positive impact on behavioral intention, indicating the importance of other people on the individual's behavior. Attitude had a small positive effect on intention. Ecological worldview positively influenced attitude and personal belief. Personal belief (awareness of consequences and ascribed responsibility) showed a positive association with TPB variables. Although the data showed a high average score in awareness of consequences (mean = 4.219 out of 5), evidence from Damavand Mount shows that there are many environmental issues that need addressing (e.g., vast amounts of garbage). National park managers need to make sure that their solutions result in awareness about proenvironmental behavior (PEB). Findings showed that negative relationship between constraints and all TPB predictors. Providing proper restrooms and parking spaces in campgrounds, strategies controlling limiting capacity and solutions for removing waste from high altitudes are helpful to decrease the negative impact of structural constraints. In order to address intrapersonal constraints, managers should provide opportunities to interest individuals in environmental activities, such as environmental celebrations or making documentaries about environmental issues. Moreover, promoting a culture of environmental protection in the Damavand Mount area would reduce interpersonal constraints. Overall, the proposed model improved the explanatory power of the TPB by predicting 64.7% of intention compared to the original TPB that accounted for 63.8% of the variance in intention.

Keywords: theory of planned behavior, pro-environmental behavior, national park, constraints

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Authors: Yang-Keun Ahn, Kwang-Soon Choi, Young-Choong Park, Kwang-Mo Jung

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Vision based user interfaces to control TVs and PCs have the advantage of being able to perform natural control without being limited to a specific device. Accordingly, various studies on hand gesture recognition using RGB cameras or depth cameras have been conducted. However, such cameras have the disadvantage of lacking in accuracy or the construction cost being large. The proposed method uses a low cost IR camera to accurately differentiate between the hand and the background. Also, complicated learning and template matching methodologies are not used, and the correlation between the fingertips extracted through curvatures is utilized to recognize Click and Move gestures.

Keywords: recognition, hand gestures, infrared camera, RGB cameras

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Authors: Jong Han Joo, Jung Hoon Lee, Young Sun Kim, Jae Young Kang, Seung Ho Choi

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In this study, we propose a novel technique for acoustic echo suppression (AES) during speech recognition under barge-in conditions. Conventional AES methods based on spectral subtraction apply fixed weights to the estimated echo path transfer function (EPTF) at the current signal segment and to the EPTF estimated until the previous time interval. We propose a new approach that adaptively updates weight parameters in response to abrupt changes in the acoustic environment due to background noises or double-talk. Furthermore, we devised a voice activity detector and an initial time-delay estimator for barge-in speech recognition in communication networks. The initial time delay is estimated using log-spectral distance measure, as well as cross-correlation coefficients. The experimental results show that the developed techniques can be successfully applied in barge-in speech recognition systems.

Keywords: acoustic echo suppression, barge-in, speech recognition, echo path transfer function, initial delay estimator, voice activity detector

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Authors: Annamarija Paula

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Modern psychology is divided into three distinct domains: cognition, affect, and conation. Historically, psychology devalued the importance of studying the effect in order to explain human behavior as it supposedly lacked both rational thought and a scientific foundation. As a result, affect remained the least studied domain for years to come. However, the last 30 years have marked a significant change in perspective, claiming that not only is affect highly adaptive, but it also plays a crucial role in cognitive processes. Affective states have a crucial impact on human behavior, which led to fundamental advances in the study of affective states on perception and judgment. Positive affect and negative affect are distinct entities and have different effects on social information processing. In addition, emotions of the same valence are manifested in distinct and unique physiological reactions indicating that not all forms of positive or negative affect are the same or serve the same purpose. The effect plays a vital role in perception and judgments, which impacts the validity and reliability of memory retrieval. The research paper analyzes key findings from the past three decades of observational and empirical research on affective states and cognition. The paper also addresses the limitations connected to the findings and proposes suggestions for possible future research.

Keywords: memory, affect, perception, judgement, mood congruency effect

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Authors: Vaishali P. Joshi, Pallav Joshi

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The objective of this study is to examine the differences fashion innovators and non-fashion innovators in their fashion consumption behavior in terms of their pre-purchase behavior, purchase behavior and post purchase behavior. The questionnaire was distributed to a female college student for data collection for achieving the objective of the first part of the study. Question-related to fashion innovativeness and fashion consumption behavior was asked. The sample was comprised of 81 college females ages 18 through 30 who were attending Business Management degree. A series of attitude questions was used to categorize respondents on the Innovativeness Scale. 32 respondents with a score of 21 and above were designated as Fashion innovators and the remainder (49) as Non-fashion innovators. Findings showed that there exist significant differences between innovators and non-innovators in their fashion consumption behavior. Data was analyzed through frequency distribution table. Many differences were found in the behavior of innovators and non-innovators in terms of their pre-purchase, actual purchase, and post-purchase behavior.

Keywords: fashion, innovativeness, consumption behavior, purchase

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Authors: Bin Liu

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Protein remote homology detection and fold recognition are two most important tasks in protein sequence analysis, which is critical for protein structure and function studies. In this study, we combined the profile-based features with various string kernels, and constructed several computational predictors for protein remote homology detection and fold recognition. Experimental results on two widely used benchmark datasets showed that these methods outperformed the competing methods, indicating that these predictors are useful computational tools for protein sequence analysis. By analyzing the discriminative features of the training models, some interesting patterns were discovered, reflecting the characteristics of protein superfamilies and folds, which are important for the researchers who are interested in finding the patterns of protein folds.

Keywords: protein remote homology detection, protein fold recognition, profile-based features, Support Vector Machines (SVMs)

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Authors: Kahandawala Arachchige Thani Chathurika Kahandawala

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This research is attempted to analyse, Sri Lanka’s current situation regarding the recognition and enforcement of international commercial arbitration awards. Sri Lanka has been involved with commercial arbitration for a long time period. But there are good and bad legal practices in place in proceedings in Sri Lanka legal system. The common perception and reality of Sri Lanka’s arbitration law and practices regarding recognition and enforcement of international arbitral awards is far behind the international standards. Therefore arbitration as a dispute resolution method has become a time-consuming and costly method in Sri Lanka. This research is employed with the qualitative method based on both primary and secondary resources. This carried out the comparative analysis of recognition and enforcement in international arbitration laws established jurisdiction in Singapore and the United Kingdom, which are known as best counties as a seat of arbitration in Asia and Europe. International conventions, act and all the legal proceedings regarding recognition and enforcement of an international arbitral award in Sri Lanka are going to be discussed in the research. In the Jurisdiction of Sri Lanka, critically need to value an international arbitral award in the domestic legal system. Therefore an award has to be recognised in Sri Lanka. Otherwise, it doesn’t have any value. After recognizing it, court can enforce it. This research intends to provide a comparative analysis to overcome the drawbacks.

Keywords: arbitration, alternative dispute method, recognition and enforcement, foreign arbitral awards, Sri Lankan legal system, arbitral award in Singapore

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Authors: Alessandra Turini Bolsoni-Silva, Sonia Regina Loureiro

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It is important to evaluate such variables simultaneously and differentiating types of behavior problems: internalizing, externalizing and with comorbidity of internalizing and externalizing. The objective was to compare, correlate and predict teacher educational practices (educational social skills and negative practices) and children's behaviors (social skills and behavior problems) of children with internalizing, externalizing and combined internalizing and externalizing problems, controlling variables of child (gender and education). A total of 262 children were eligible to compose the participants, considering preschool age from 3 to 5 years old (n = 109) and school age from 6 to 11 (n = 153) years old, and their teachers who were distributed, in designs case-control, non-clinical, with internalizing, externalizing problems and internalizing and externalizing comorbidity, using the Teacher's Report Form (TRF) as a criterion. The instruments were applied with the teachers, after consent from the parents/guardians: a) Teacher’s Report Form (TRF); b) Educational Social Skills Interview Guide for Teachers (RE-HSE-Pr); (c) Socially Skilled Response Questionnaire – Teachers (QRSH-Pr). The data were treated by univariate and multivariate analyses, proceeding with comparisons, correlations and predictions regarding the outcomes of children with and without behavioral problems, considering the types of problems. As main results stand out: (a) group comparison studies: in the Inter group there is emphasis on behavior problems in affection interactions, which does not happen in the other groups; as for positive practices, they discriminate against groups with externalizing and combined problems and not in internalizing ones, positive educational practices – hse are more frequent in the G-Exter and G-Inter+Exter groups; negative practices differed only in the G-Exter and G-Inter+Exter groups; b) correlation studies: it can be seen that the Inter+Exter group presents a greater number of correlations in the relationship between behavioral problems/complaints and negative practices and between children's social skills and positive practices/contexts; c) prediction studies: children's social skills predict internalizing, externalizing and combined problems; it is also verified that the negative practices are in the multivariate model for the externalizing and combined ones. This investigation collaborates in the identification of risk and protective factors for specific problems, helping in interventions for different problems.

Keywords: development, educational practices, social skills, behavior problems, teacher

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Authors: M. Dabirinezhad, M. Bayat Pour, A. Dabirinejad

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Recognition of the color spectrum of the teeth plays a significant role in the dental laboratories to produce dentures. Since there are various types and colours of teeth for each patient, there is a need to specify the exact and the most suitable colour to produce a denture. Usually, dentists utilize pallets to identify the color that suits a patient based on the color of the adjacent teeth. Consistent with this, there can be human errors by dentists to recognize the optimum colour for the patient, and it can be annoying for the patient. According to the statistics, there are some claims from the patients that they are not satisfied by the colour of their dentures after the installation of the denture in their mouths. This problem emanates from the lack of sufficient accuracy during the colour recognition process of denture production. The colour recognition pen (CRP) is a technology to distinguish the colour spectrum of the intended teeth with the highest accuracy. CRP is equipped with a sensor that is capable to read and analyse a wide range of spectrums. It is also connected to a database that contains all the spectrum ranges, which exist in the market. The database is editable and updatable based on market requirements. Another advantage of this invention can be mentioned as saving time for the patients since there is no need to redo the denture production in case of failure on the first try.

Keywords: colour recognition pen, colour spectrum, dental laboratory, denture

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Authors: Hui Zhang, Ye Tian, Fang Ye, Ziming Guo

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Communication signal modulation recognition technology is one of the key technologies in the field of modern information warfare. At present, communication signal automatic modulation recognition methods are mainly divided into two major categories. One is the maximum likelihood hypothesis testing method based on decision theory, the other is a statistical pattern recognition method based on feature extraction. Now, the most commonly used is a statistical pattern recognition method, which includes feature extraction and classifier design. With the increasingly complex electromagnetic environment of communications, how to effectively extract the features of various signals at low signal-to-noise ratio (SNR) is a hot topic for scholars in various countries. To solve this problem, this paper proposes a feature extraction algorithm for the communication signal based on the improved Holder cloud feature. And the extreme learning machine (ELM) is used which aims at the problem of the real-time in the modern warfare to classify the extracted features. The algorithm extracts the digital features of the improved cloud model without deterministic information in a low SNR environment, and uses the improved cloud model to obtain more stable Holder cloud features and the performance of the algorithm is improved. This algorithm addresses the problem that a simple feature extraction algorithm based on Holder coefficient feature is difficult to recognize at low SNR, and it also has a better recognition accuracy. The results of simulations show that the approach in this paper still has a good classification result at low SNR, even when the SNR is -15dB, the recognition accuracy still reaches 76%.

Keywords: communication signal, feature extraction, Holder coefficient, improved cloud model

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Authors: Khansa Hayat

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Organizational stress is one of the vital phenomena which is having its roots deep down in has deep roots in management, psychology, and organizational behavior research. In the meanwhile, keeping its focus on the positive strength of humans rather than the traditional negativity oriented research, positive psychology has emerged as a separate branch of organizational behavior. The current study investigates the interactive effects of Challenge and hindrance stressors and core Self Evaluations (CSE’s) of the individual on job performances including the in-role performance and extra role performances. The study also aims to investigate the supporting/buffering role of the human dispositions (i.e., self esteem, self efficacy, locus of control and emotional stability). The results show that Challenge stressors have a significant positive effect on in role performance and extra role performance of the individual. The findings of the study indicate that Core Self evaluations strengthen the relationship between challenge stressors and in role performance of the individual. In case of Hindrance Stressors the Core self Evaluations lessen the negative impact of Hindrance stressors and they let the individual perform at a better and normal position even when the Hindrance stressors are high. The relationship and implication of conservation of resource theory are also discussed. The limitations, future research directions and implications of the study are also discussed.

Keywords: challenge-hindrance stressors, core self evaluations, in-role performance, extra-role performance

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Authors: Musarrat Jabeen Khan, Uzma Azam, Kainat Umar, Jazba Amber Satti, Aiman Shehzadi, Nimo Omer

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This study aimed to examine the comparison between substance abusers and non-abusers on anxiety, peer pressure, and risk-taking behavior among young adults. The sample consisted of 138 individuals including 64 female and 71 males, age range from 17-35 years, drawn from non-clinical population through convenient sampling. Questionnaire technique was used for the information assortment and the scales were susceptibility to peer pressure (Dieman, Pamella, Shope & Butchart, 1987), Zung self-rating anxiety scale (Zung, 1971), and risk-taking questionnaire (Gullone, Moore, Moss & Boyd, 2000) having alpha reliability of .54, .88, and .80 respectively. Results showed that anxiety negatively correlates with the risk-taking behavior. High level of anxiety stops an individual to involve himself in risk taking activities. Peer pressure have positive correlation with risk-taking behavior. Females are more susceptible to peer pressure irrespective of being abusers or non-abusers as compared to male abusers and non-abusers. Substance abusers have less anxiety as compared to non-abusers but are more susceptible to peer pressure and risk-taking behaviors.

Keywords: substance, substance abuse, anxiety, peer pressure, risk-taking behavior

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Authors: Sharon Cayzer-Haller, Shir Ginosar-Yaari, Ariel Knafo-Noam

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The 21st century emerged as the digital century, and it is marked by a wide range of technological developments and changes, followed by potential changes in human communication skills. This technological revolution has changed human means of communication in many different ways: children and adolescents are spending much of their time in front of screens, participating in all sorts of online activities (even more so since the outbreak of COVID-19). The current study focuses on the role of values in adolescents' online bystanders' behavior. Values are cognitive, abstract representations of desirable goals that motivate behavior, and we hypothesized finding significant associations between specific values and differential online bystanders' feelings and behavior. Data was collected through online questionnaires that measured the participants' values, using Schwartz's short version of the Portrait Values Questionnaire (Schwartz, 2012). Participants’ online behavior was assessed in a questionnaire addressing reactions to situations of cyber shaming and cyberbullying, and specifically positive feelings and pro-social behavior (e.g., more supportive reactions) toward the victims, as opposed to different offensive behavioral reactions (such as laughing at the victim or ignoring the situation). Participants were recruited with a commercial research panel company, and 308 Israeli adolescents' values and online behavior were examined (mean age 15.2). As hypothesized, results show significant associations between self-transcendence values (universalism and benevolence) and conservation values (conformity, tradition, and security). These two groups of values were positively correlated with pro-social bystanders' feelings and behavior. On the opposite side of the values scale, the value of power was negatively associated with the participants' pro-social behavior, and positively associated with offensive behavioral reactions. Further research is needed, but we conclude that values serve as crucial guiding factors in directing adolescents' online feelings and behavior.

Keywords: adolescents, values, cyberbullying, online behavior, power

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Authors: Diego Adrian Cardenas Jorge, Gerardo Mirando Guisado, Alfredo Barrientos Padilla

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A system based on Affective Computing can detect and interpret human information like voice, facial expressions and body movement to detect emotions and execute a corresponding response. This data is important due to the fact that a person can communicate more effectively with emotions than can be possible with words. This information can be processed through technological components like Facial Recognition, Gait Recognition or Gesture Recognition. As of now, solutions proposed using this technology only consider one component at a given moment. This research investigation proposes two solutions based on Affective Computing taking into account more than one component for emotion detection. The proposals reflect the levels of dependency between hardware devices and software, as well as the interaction process between the system and the user which implies the development of scenarios where both proposals will be put to the test in a live environment. Both solutions are to be developed in code by software engineers to prove the feasibility. To validate the impact on society and business interest, interviews with stakeholders are conducted with an investment mind set where each solution is labeled on a scale of 1 through 5, being one a minimum possible investment and 5 the maximum.

Keywords: affective computing, emotions, emotion detection, face recognition, gait recognition

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Authors: Muhammad Imran Ahmad, Ruzelita Ngadiran, Mohd Nazrin Md Isa, Nor Ashidi Mat Isa, Mohd ZaizuIlyas, Raja Abdullah Raja Ahmad, Said Amirul Anwar Ab Hamid, Muzammil Jusoh

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This paper presents two technique, local feature extraction using image spectrum and low frequency spectrum modelling using GMM to capture the underlying statistical information to improve the performance of face recognition system. Local spectrum features are extracted using overlap sub block window that are mapping on the face image. For each of this block, spatial domain is transformed to frequency domain using DFT. A low frequency coefficient is preserved by discarding high frequency coefficients by applying rectangular mask on the spectrum of the facial image. Low frequency information is non Gaussian in the feature space and by using combination of several Gaussian function that has different statistical properties, the best feature representation can be model using probability density function. The recognition process is performed using maximum likelihood value computed using pre-calculate GMM components. The method is tested using FERET data sets and is able to achieved 92% recognition rates.

Keywords: local features modelling, face recognition system, Gaussian mixture models, Feret

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Authors: Ahmad Alwosheel, Ahmed Alqaraawi

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This work proposes an unsupervised text-independent probabilistic approach to recognize Quran reciter voice. It is an accurate approach that works on real time applications. This approach does not require a prior information about reciter models. It has two phases, where in the training phase the reciters' acoustical features are modeled using Gaussian Mixture Models, while in the testing phase, unlabeled reciter's acoustical features are examined among GMM models. Using this approach, a high accuracy results are achieved with efficient computation time process.

Keywords: Quran, speaker recognition, reciter recognition, Gaussian Mixture Model

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Authors: Fawaz S. Al-Anzi, Dia AbuZeina

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Speech recognition is of an important contribution in promoting new technologies in human computer interaction. Today, there is a growing need to employ speech technology in daily life and business activities. However, speech recognition is a challenging task that requires different stages before obtaining the desired output. Among automatic speech recognition (ASR) components is the feature extraction process, which parameterizes the speech signal to produce the corresponding feature vectors. Feature extraction process aims at approximating the linguistic content that is conveyed by the input speech signal. In speech processing field, there are several methods to extract speech features, however, Mel Frequency Cepstral Coefficients (MFCC) is the popular technique. It has been long observed that the MFCC is dominantly used in the well-known recognizers such as the Carnegie Mellon University (CMU) Sphinx and the Markov Model Toolkit (HTK). Hence, this paper focuses on the MFCC method as the standard choice to identify the different speech segments in order to obtain the language phonemes for further training and decoding steps. Due to MFCC good performance, the previous studies show that the MFCC dominates the Arabic ASR research. In this paper, we demonstrate MFCC as well as the intermediate steps that are performed to get these coefficients using the HTK toolkit.

Keywords: speech recognition, acoustic features, mel frequency, cepstral coefficients

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Authors: Sameh Abaza, Mohamed Ibrahim, Tarek Mahmoud

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Due to the development in the digital image processing, its wide use in many applications such as medical, security, and others, the need for more accurate techniques that are reliable, fast and robust is vehemently demanded. In the field of security, in particular, speed is of the essence. In this paper, a pattern recognition technique that is based on the use of Hidden Markov Model (HMM), K-means and the Sobel operator method is developed. The proposed technique is proved to be fast with respect to some other techniques that are investigated for comparison. Moreover, it shows its capability of recognizing the normal face (center part) as well as face boundary.

Keywords: HMM, K-Means, Sobel, accuracy, face recognition

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Authors: Vishwa Joshi

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The study of mood recognition in the field of music has gained a lot of momentum in the recent years with machine learning and data mining techniques and many audio features contributing considerably to analyze and identify the relation of mood plus music. In this paper we consider the same idea forward and come up with making an effort to build a system for automatic recognition of mood underlying the audio song’s clips by mining their audio features and have evaluated several data classification algorithms in order to learn, train and test the model describing the moods of these audio songs and developed an open source framework. Before classification, Preprocessing and Feature Extraction phase is necessary for removing noise and gathering features respectively.

Keywords: music, mood, features, classification

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Authors: Ifeanyi Adigwe

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The influence of television on adolescents is prevalent and widespread because television is a powerful sex educator for adolescents. This study examined the relationship between viewing sexual content on television and sexual behaviour of adolescents in public senior secondary schools in Lagos, Nigeria. The study employed a survey research design with a structured questionnaire as instrument. The multi-stage sampling technique was adopted. Firstly, purposive sampling was adopted in selecting 3 educational districts namely: Agege, Maryland, and Agboju. These educational districts were chosen for convenience and its wide coverage area of public senior secondary schools in Lagos State. Secondly, the researcher adopted systematic sampling to select the schools. The schools were listed in alphabetical order in each district and every 10th school were selected, yielding 13 schools altogether. A total of 501 copies of questionnaire were administered to the students and a total 491 copies of the questionnaire were retrieved. Only 453 copies of the questionnaire met the inclusion criteria and were used for analysis. Data were analyzed using descriptive statistics, Pearson Correlation, Principal components analysis, and regression analysis. Results of correlation analysis showed a positive and significant relationship between adolescent sexual belief and their preference for sexual content in television (r =0.117, N =453, p=0.13), viewing sexual content on television and adolescent sexual behavior, (r =-0.112, N =453, p<0.05), adolescent television preference and their preference for sexual content in television (r =0.328, N =453, p<0.05), adolescent television preference and adolescent’s sexual behavior (r=0.093, N =453, p<0.05). However, a negative but significant relationship exists between adolescent’s sexual knowledge and their sexual behavior (r=-122, N=453, p=0.0009). Pearson’s correlation between adolescents’ sexual knowledge and sexual behavior shows that there is a positive significant but strong relationship between adolescent’s sexual knowledge and their sexual behavior (r=0.967, N=453, p<0.05). The results also show that adolescent’s preference for sexual content in television informs them about their sexuality, development and sexual health. The descriptive and inferential analysis of data revealed that the interaction among adolescent sexual belief, knowledge and adolescents’ preference of sexual in television and its resultant effect on adolescent sexual behavior is apparent because sexual belief and norms about sex of an adolescent can induce his television preference of sexual content on television. The study concludes that exposure to sexual content in television can impact on adolescent sexual behaviour. There is no doubt that the actual outcome of television viewing and adolescent sexual behavior remains controversial because adolescent sexual behavior is multifaceted and multi-dimensional. Since behavior is learned overtime, the frequency of exposure and nature of sexual content viewed overtime induces and hastens sexual activity.

Keywords: adolescent sexual behavior, Nigeria, sexual belief, sexual content, sexual knowledge, television preference

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Authors: Wale Agbaje

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The aim of this research study is to assess the impact of financial statement fraud on profitability of some selected Nigerian manufacturing firms covering (2002-2016). The specific objectives focused on to ascertain the effect of incorrect asset valuation on return on assets (ROA) and to ascertain the relationship between improper expense recognition and return on assets (ROA). To achieve these objectives, descriptive research design was used for the study while secondary data were collected from the financial reports of the selected firms and website of security and exchange commission. The analysis of covariance (ANCOVA) was used and STATA II econometric method was used in the analysis of the data. Altman model and operating expenses ratio was adopted in the analysis of the financial reports to create a dummy variable for the selected firms from 2002-2016 and validation of the parameters were ascertained using various statistical techniques such as t-test, co-efficient of determination (R2), F-statistics and Wald chi-square. Two hypotheses were formulated and tested using the t-statistics at 5% level of significance. The findings of the analysis revealed that there is a significant relationship between financial statement fraud and profitability in Nigerian manufacturing industry. It was revealed that incorrect assets valuation has a significant positive relationship and so also is the improper expense recognition on return on assets (ROA) which serves as a proxy for profitability. The implication of this is that distortion of asset valuation and expense recognition leads to decreasing profit in the long run in the manufacturing industry. The study therefore recommended that pragmatic policy options need to be taken in the manufacturing industry to effectively manage incorrect asset valuation and improper expense recognition in order to enhance manufacturing industry performance in the country and also stemming of financial statement fraud should be adequately inculcated into the internal control system of manufacturing firms for the effective running of the manufacturing industry in Nigeria.

Keywords: Althman's Model, improper expense recognition, incorrect asset valuation, return on assets

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Authors: Bamidele Samson Alobalorun, Ifedotun Roseline Idowu

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Biometrics technologies apply the human body parts for their unique and reliable identification based on physiological traits. The iris recognition system is a biometric–based method for identification. The human iris has some discriminating characteristics which provide efficiency to the method. In order to achieve this efficiency, there is a need for feature extraction of the distinct features from the human iris in order to generate accurate authentication of persons. In this study, an approach for an iris recognition system using 2D Gabor for feature extraction is applied to iris templates. The 2D Gabor filter formulated the patterns that were used for training and equally sent to the hamming distance matching technique for recognition. A comparison of results is presented using two iris image subjects of different matching indices of 1,2,3,4,5 filter based on the CASIA iris image database. By comparing the two subject results, the actual computational time of the developed models, which is measured in terms of training and average testing time in processing the hamming distance classifier, is found with best recognition accuracy of 96.11% after capturing the iris localization or segmentation using the Daughman’s Integro-differential, the normalization is confined to the Daugman’s rubber sheet model.

Keywords: Daugman rubber sheet, feature extraction, Hamming distance, iris recognition system, 2D Gabor wavelet transform

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Authors: Patrick Guggenberger

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Extant literature has highlighted the importance of individual employees in the entrepreneurial process, as they are those that come up with novel ideas and promote their implementation throughout the organization. However, research on antecedents of individual entrepreneurial behavior (IEB) is very limited. The present study takes an initial step to investigate the interplay between transformational leader behaviors of direct supervisors and employees’ ability and willingness to act entrepreneurial and sheds light on the moderating role of an individual’s hierarchical level. A theoretically derived research model is empirically tested, drawing on survey data of 450 individuals working in medium- and large-sized corporations in two countries. Findings indicate that various transformational leader behaviors have a strong positive impact on IEB, while the ability of direct supervisors to influence their followers’ entrepreneurial behavior depends strongly on their own hierarchical level. The study reveals that transformational leadership has most impact at lower hierarchical levels, where employees’ motivation to act entrepreneurial is the lowest.

Keywords: corporate entrepreneurship, hierarchy, individual entrepreneurial behavior, transformational leadership

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Authors: Maria Pavlova

Abstract:

In our days, it is possible to put the camera on different vehicles like quadcopter, train, airplane and etc. The camera also can be the input sensor in many different systems. That means the object recognition like non separate part of monitoring control can be key part of the most intelligent systems. The aim of this paper is to focus of the object recognition process during vehicles movement. During the vehicle’s movement the camera takes pictures from the environment without storage in Data Base. In case the camera detects a special object (for example human or animal), the system saves the picture and sends it to the work station in real time. This functionality will be very useful in emergency or security situations where is necessary to find a specific object. In another application, the camera can be mounted on crossroad where do not have many people and if one or more persons come on the road, the traffic lights became the green and they can cross the road. In this papers is presented the system has solved the aforementioned problems. It is presented architecture of the object recognition system includes the camera, Raspberry platform, GPS system, neural network, software and Data Base. The camera in the system takes the pictures. The object recognition is done in real time using the OpenCV library and Raspberry microcontroller. An additional feature of this library is the ability to display the GPS coordinates of the captured objects position. The results from this processes will be sent to remote station. So, in this case, we can know the location of the specific object. By neural network, we can learn the module to solve the problems using incoming data and to be part in bigger intelligent system. The present paper focuses on the design and integration of the image recognition like a part of smart systems.

Keywords: camera, object recognition, OpenCV, Raspberry

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Authors: Shih-Yu Lo

Abstract:

Stereotypes exist in almost every society, affecting how people interact with each other. However, to our knowledge, the influence of stereotypes was rarely explored in the context of basic perceptual processes. This study aims to explore how the gender stereotype affects object recognition. Participants were presented with a series of scene pictures, followed by a target display with a man or a woman, holding a weapon or a non-weapon object. The task was to identify whether the object in the target display was a weapon or not. Although the gender of the object holder could not predict whether he or she held a weapon, and was irrelevant to the task goal, the participant nevertheless tended to identify the object as a weapon when the object holder was a man than a woman. The analysis based on the signal detection theory showed that the stereotype effect on object recognition mainly resulted from the participant’s bias to make a 'weapon' response when a man was in the scene instead of a woman in the scene. In addition, there was a trend that the participant’s sensitivity to differentiate a weapon from a non-threating object was higher when a woman was in the scene than a man was in the scene. The results of this study suggest that the irrelevant social cues implied in the visual scene can be very powerful that they can modulate the basic object recognition process.

Keywords: gender stereotype, object recognition, signal detection theory, weapon

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Authors: Amin Derakhshan, Mohammad Mikaili, Mohammad Ali Khalilzadeh, Amin Mohammadian

Abstract:

This paper proposes a stress recognition system from multi-modal bio-potential signals. For stress recognition, Support Vector Machines (SVM) and LDA are applied to design the stress classifiers and its characteristics are investigated. Using gathered data under psychological polygraph experiments, the classifiers are trained and tested. The pattern recognition method classifies stressful from non-stressful subjects based on labels which come from polygraph data. The successful classification rate is 96% for 12 subjects. It means that facial thermal imaging due to its non-contact advantage could be a remarkable alternative for psycho-physiological methods.

Keywords: stress, thermal imaging, face, SVM, polygraph

Procedia PDF Downloads 456