Search results for: speech emotion recognition

Authors: Vaidehi Murarka, Sneha Mehta, Dishant Upadhyay

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Our project topic is “Alphabet Recognition using pixel probability distribution”. The project uses techniques of Image Processing and Machine Learning in Computer Vision. Alphabet recognition is the mechanical or electronic translation of scanned images of handwritten, typewritten or printed text into machine-encoded text. It is widely used to convert books and documents into electronic files etc. Alphabet Recognition based OCR application is sometimes used in signature recognition which is used in bank and other high security buildings. One of the popular mobile applications includes reading a visiting card and directly storing it to the contacts. OCR's are known to be used in radar systems for reading speeders license plates and lots of other things. The implementation of our project has been done using Visual Studio and Open CV (Open Source Computer Vision). Our algorithm is based on Neural Networks (machine learning). The project was implemented in three modules: (1) Training: This module aims “Database Generation”. Database was generated using two methods: (a) Run-time generation included database generation at compilation time using inbuilt fonts of OpenCV library. Human intervention is not necessary for generating this database. (b) Contour–detection: ‘jpeg’ template containing different fonts of an alphabet is converted to the weighted matrix using specialized functions (contour detection and blob detection) of OpenCV. The main advantage of this type of database generation is that the algorithm becomes self-learning and the final database requires little memory to be stored (119kb precisely). (2) Preprocessing: Input image is pre-processed using image processing concepts such as adaptive thresholding, binarizing, dilating etc. and is made ready for segmentation. “Segmentation” includes extraction of lines, words, and letters from the processed text image. (3) Testing and prediction: The extracted letters are classified and predicted using the neural networks algorithm. The algorithm recognizes an alphabet based on certain mathematical parameters calculated using the database and weight matrix of the segmented image.

Keywords: contour-detection, neural networks, pre-processing, recognition coefficient, runtime-template generation, segmentation, weight matrix

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Authors: Xu Han, Shanxiong Chen, Shiyu Zhu, Xiaoyu Lin, Fujia Zhao, Dingwang Wang

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Character detection is an important issue for character recognition of ancient Yi books. The accuracy of detection directly affects the recognition effect of ancient Yi books. Considering the complex layout, the lack of standard typesetting and the mixed arrangement between images and texts, we propose a character detection method for ancient Yi books based on connected components and regressive character segmentation. First, the scanned images of ancient Yi books are preprocessed with nonlocal mean filtering, and then a modified local adaptive threshold binarization algorithm is used to obtain the binary images to segment the foreground and background for the images. Second, the non-text areas are removed by the method based on connected components. Finally, the single character in the ancient Yi books is segmented by our method. The experimental results show that the method can effectively separate the text areas and non-text areas for ancient Yi books and achieve higher accuracy and recall rate in the experiment of character detection, and effectively solve the problem of character detection and segmentation in character recognition of ancient books.

Keywords: CCS concepts, computing methodologies, interest point, salient region detections, image segmentation

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Authors: Rachel C. F. Sun

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This study examined the predictive effects of moral competence, prosocial norms and positive behavior recognition on school misbehavior among Chinese junior secondary school students. Results of multiple regression analysis showed that students were more likely to misbehave in school when they had lower levels of moral competence and prosocial norms, and when they perceived their positive behavior being less likely recognized. Practical implications were discussed on how to guide students to make the right choices to behave appropriately in school. Implications for future research were also discussed.

Keywords: moral competence, positive behavior recognition, prosocial norms, school misbehavior

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Authors: Jianzhou Ni, Hua Fan

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It has been determined that supervisor support has a major influence on postgraduate students' academic emotions and is considered a method of successfully anticipating postgraduates' good psychological well-being levels. As a result, by assessing the mediating influence upon academic emotions for contemporary postgraduates in China, this study investigated the tight reciprocal relationship between psychological empowerment and positive mental well-being among postgraduates. To that end, a help enables a theoretical analysis of role clarity, academic emotion, and positive psychological health was developed, and its validity and reliability were demonstrated for the first time using the normalized postgrad relationship with supervisor scale, academic emotion scale, and positive mental scale, as well as questionnaire data from Chinese postgraduate students. This study used the cross-lagged (ARCL) panel model data to longitudinally measure 798 valid data from two survey questions polls taken in 2019 (T1) and 2021 (T2) to investigate the link between supervisor support and positive graduate student mental well-being in a bidirectional relationship of influence. The study discovered that mentor assistance could have a considerable beneficial impact on graduate students' academic emotions and, as a result, indirectly help learners attain positive mental health development. This verifies the theoretical premise that academic emotions partially mediate the effect of mentor support on positive mental health development and argues for the coexistence of the two. The outcomes of this study can help researchers gain a better knowledge of the dynamic interplay among three different research variables: supervisor support, academic emotions, and positive mental health, as well as fill gaps in previous research. In this regard, the study indicated that mentor assistance directly stimulates students' academic drive and assists graduate students in developing good academic emotions, which contributes to the development of positive mental health. However, given the restricted measurement time in this study's cross-lagged panel data and the potential effect of moderating effects other than academic mood on graduate students' good mental health, the results of this study need to be more fully understood and validated.

Keywords: supervisor support, academic emotions, positive mental health, interaction effects, longitudinal cross-lagged measurements

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Authors: Kashika P. H.

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The development of computer vision systems has been greatly aided by the efficient and precise detection of images and videos. Although the ability to recognize and comprehend images is a strength of the human brain, employing technology to tackle this issue is exceedingly challenging. In the past few years, the use of Deep Learning algorithms to treat object detection has dramatically expanded. One of the key issues in the realm of image recognition is the recognition and detection of certain notable people from randomly acquired photographs. Face recognition uses a way to identify, assess, and compare faces for a variety of purposes, including user identification, user counting, and classification. With the aid of an accessible deep learning-based API, this article intends to recognize various faces of people and their facial descriptors more accurately. The purpose of this study is to locate suitable individuals and deliver accurate information about them by using the Amazon Rekognition system to identify a specific human from a vast image dataset. We have chosen the Amazon Rekognition system, which allows for more accurate face analysis, face comparison, and face search, to tackle this difficulty.

Keywords: Amazon rekognition, API, deep learning, computer vision, face detection, text detection

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Authors: Alexander N. Savostyanov, Tatiana A. Dolgorukova, Elena A. Esipenko, Mikhail S. Zaleshin, Margherita Malanchini, Anna V. Budakova, Alexander E. Saprygin, Tatiana A. Golovko, Yulia V. Kovas

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EEG correlates of mathematical and trait anxiety level were studied in 52 healthy Russian-speakers during execution of error-recognition tasks with lexical, arithmetic and algebraic conditions. Event-related spectral perturbations were used as a measure of brain activity. The ERSP plots revealed alpha/beta desynchronizations within a 500-3000 ms interval after task onset and slow-wave synchronization within an interval of 150-350 ms. Amplitudes of these intervals reflected the accuracy of error recognition, and were differently associated with the three conditions. The correlates of anxiety were found in theta (4-8 Hz) and beta2 (16-20 Hz) frequency bands. In theta band the effects of mathematical anxiety were stronger expressed in lexical, than in arithmetic and algebraic condition. The mathematical anxiety effects in theta band were associated with differences between anterior and posterior cortical areas, whereas the effects of trait anxiety were associated with inter-hemispherical differences. In beta1 and beta2 bands effects of trait and mathematical anxiety were directed oppositely. The trait anxiety was associated with increase of amplitude of desynchronization, whereas the mathematical anxiety was associated with decrease of this amplitude. The effect of mathematical anxiety in beta2 band was insignificant for lexical condition but was the strongest in algebraic condition. EEG correlates of anxiety in theta band could be interpreted as indexes of task emotionality, whereas the reaction in beta2 band is related to tension of intellectual resources.

Keywords: EEG, brain activity, lexical and numerical error-recognition tasks, mathematical and trait anxiety

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Authors: Mounia El Jaouhari, Mira Goral, Samir Diouny

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Introduction: Previous research has indicated that language impairments are recognized as a feature of many neurodegenerative disorders, including non-language-led dementia subtypes such as Alzheimer´s disease (AD). In this preliminary study, the focal aim is to quantify the semantic content of naming and connected speech samples of Moroccan patients diagnosed with AD using two tasks taken from the culturally adapted and validated Moroccan version of the Boston Diagnostic Aphasia Examination. Methods: Five individuals with AD and five neurologically healthy individuals matched for age, gender, and education will participate in the study. Participants with AD will be diagnosed on the basis of the Moroccan version of the Diagnostic and Statistial Manual of Mental Disorders (DSM-4) screening test, the Moroccan version of the Mini Mental State Examination (MMSE) test scores, and neuroimaging analyses. The participants will engage in two tasks taken from the MDAE-SF: 1) Picture description and 2) Naming. Expected findings: Consistent with previous studies conducted on English speaking AD patients, we expect to find significant word production and retrieval impairments in AD patients in all measures. Moreover, we expect to find category fluency impairments that further endorse semantic breakdown accounts. In sum, not only will the findings of the current study shed more light on the locus of word retrieval impairments noted in AD, but also reflect the nature of Arabic morphology. In addition, the error patterns are expected to be similar to those found in previous AD studies in other languages.

Keywords: alzheimer's disease, anomia, connected speech, semantic impairments, moroccan arabic

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Authors: Khayriniso Bakhtiyarovna Ganiyeva

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The article explores the significance of punctuation in achieving communicative competence. It underscores that effective communication goes beyond simply using punctuation correctly. In the successful completion of a communicative activity, it is important not that the writer correctly uses punctuation marks but that he was able to achieve a goal aimed at expressing a certain meaning. The unanimity of the writer and the reader in the mutual understanding of the text is of primary importance. It should also be taken into account that situational communication provides special informative content and expressiveness of speech. Also, the norms of the situation are determined by the nature of the information in the text, and the punctuation marks expressed in accordance with the norm perform logical-semantic, highlighting expressive-emotional and signaling functions. It is a mistake to classify the signs subject to the norm of the situation as created by the author because they functionally reflect the general stylistic features of different texts. Such signs are among the common signs that are codified only by the semantics and structure of the created text.

Keywords: communicative-pragmatic approach, expressiveness of speech, stylistic features, comparative analysis

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Authors: Armaghan Eslami, Nasrin Arshadi

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Scarce resources are the inseparable part of organization life. This fact that only small number of the employees can have these resources such as promotion, raise, and recognition can cause competition among employees, which create competitive climate. As well as any other competition, small number wins the reward, and a great number loses, one of the possible emotional reactions to this loss is negative emotions like malicious envy. In this case, the envious person may try to harm the envied person by reducing the prosocial behavior. Prosocial behavior is a behavior that aimed to benefit others. The main propose of this action is to maintain and increase well-being and well-fare of others. Therefore, one of the easiest ways for harming envied one is to suppress prosocial behavior. Prosocial behavior has positive and important implication for organizational efficiency. Our results supported our model and suggested that competitive climate has a significant effect on increasing workplace envy and on the other hand envy has significant negative impact on prosocial behavior. Our result also indicated that envy is the mediator in the relation between competitive climate and prosocial behavior. Organizational competitive climate can cause employees respond envy with negative emotion and hostile and damaging behavior toward envied person. Competition can lead employees to look out for proof of their self-worthiness; and, furthermore, they measure their self-worth, value and respect by the superiority that they gain in competitions. As a result, loss in competitions can harm employee’s self-definition and they try to protect themselves by devaluating envied other and being ‘less friendly’ to them. Some employees may find it inappropriate to engage in the harming behavior, but they may believe there is nothing against withholding the prosocial behavior.

Keywords: competitive climate, mediator, prosocial behavior, workplace envy

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Authors: M. Pramila Devi, N. V. N. Indra Kiran

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Control charts, predominantly in the form of X-bar chart, are important tools in statistical process control (SPC). They are useful in determining whether a process is behaving as intended or there are some unnatural causes of variation. A process is out of control if a point falls outside the control limits or a series of point’s exhibit an unnatural pattern. In this paper, a study is carried out on four training algorithms for CCPs recognition. For those algorithms optimal structure is identified and then they are studied for type I and type II errors for generalization without early stopping and with early stopping and the best one is proposed.

Keywords: control chart pattern recognition, neural network, backpropagation, generalization, early stopping

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Authors: Azwan Hamdan, Mohd Qayyum Ab Latip, Hasliza Abu Hassim, Tengku Rinalfi Putra Tengku Azizan, Hafandi Ahmad

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Animal cognition provides some evidence for self-recognition, which is described as the ability to recognize oneself as an individual separate from the environment and other individuals. The mirror self-recognition (MSR) or mark test is a behavioral technique to determine whether an animal have the ability of self-recognition or self-awareness in front of the mirror. It also describes the capability for an animal to be aware of and make judgments about its new environment. Thus, the objectives of this study are to measure and to compare the ability of wild and captive wildlife in mirror self-recognition. Wild animals from the Royal Belum Rainforest Malaysia were identified based on the animal trails and salt lick grounds. Acrylic mirrors with wood frame (200 x 250cm) were located near to animal trails. Camera traps (Bushnell, UK) with motion-detection infrared sensor are placed near the animal trails or hiding spot. For captive wildlife, animals such as Malayan sun bear (Helarctos malayanus) and chimpanzee (Pan troglodytes) were selected from Zoo Negara Malaysia. The captive animals were also marked using odorless and non-toxic white paint on its forehead. An acrylic mirror with wood frame (200 x 250cm) and a video camera were placed near the cage. The behavioral data were analyzed using ethogram and classified through four stages of MSR; social responses, physical inspection, repetitive mirror-testing behavior and realization of seeing themselves. Results showed that wild animals such as barking deer (Muntiacus muntjak) and long-tailed macaque (Macaca fascicularis) increased their physical inspection (e.g inspecting the reflected image) and repetitive mirror-testing behavior (e.g rhythmic head and leg movement). This would suggest that the ability to use a mirror is most likely related to learning process and cognitive evolution in wild animals. However, the sun bear’s behaviors were inconsistent and did not clearly undergo four stages of MSR. This result suggests that when keeping Malayan sun bear in captivity, it may promote communication and familiarity between conspecific. Interestingly, chimp has positive social response (e.g manipulating lips) and physical inspection (e.g using hand to inspect part of the face) when they facing a mirror. However, both animals did not show any sign towards the mark due to lost of interest in the mark and realization that the mark is inconsequential. Overall, the results suggest that the capacity for MSR is the beginning of a developmental process of self-awareness and mental state attribution. In addition, our findings show that self-recognition may be based on different complex neurological and level of encephalization in animals. Thus, research on self-recognition in animals will have profound implications in understanding the cognitive ability of an animal as an effort to help animals, such as enhanced management, design of captive individuals’ enclosures and exhibits, and in programs to re-establish populations of endangered or threatened species.

Keywords: mirror self-recognition (MSR), self-recognition, self-awareness, wildlife

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Authors: Alexander Scott English, Yilin Ma, Xiaoying Liu

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The widespread use of artificial intelligence in everyday life has triggered a fervent discussion covering a wide range of areas. However, to date, research on the influence of gender in various segments and factors from a social science perspective is still limited. This study aims to explore whether there are gender differences in human trust in AI for its application in basic everyday life and correlates with human perceived similarity, perceived emotions (including competence and warmth), and attractiveness. We conducted a study involving 321 participants using a two-subject experimental design with a two-factor (masculinized vs. feminized voice of the AI) multiplied by a two-factor (pitch level of the AI's voice) between-subject experimental design. Four contexts were created for the study and randomly assigned. The results of the study showed significant gender differences in perceived similarity, trust, and perceived emotion of the AIs, with females rating them significantly higher than males. Trust was higher in relation to AIs presenting the same gender (e.g., human female to female AI, human male to male AI). Mediation modeling tests indicated that emotion perception and similarity played a sufficiently mediating role in trust. Notably, although trust in AIs was strongly correlated with human gender, there was no significant effect on the gender of the AI. In addition, the study discusses the effects of subjects' age, job search experience, and job type on the findings.

Keywords: artificial intelligence, gender differences, human-robot trust, mediation modeling

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Authors: Sriraman Kothuri, Komal Teja Mattupalli

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In this paper we proposed a novel algorithm for recognizing hulls in a hand written digits. This is an extension to the work on “Digit Recognition Using Freeman Chain code”. In order to find out the hulls in a user given digit it is necessary to follow three steps. Those are pre-processing, Boundary Extraction and at last apply the Hull Detection system in a way to attain the better results. The detection of Hull Regions is mainly intended to increase the machine learning capability in detection of characters or digits. This can also extend this in order to get the hull regions and their intensities in Black Holes in Space Exploration.

Keywords: chain code, machine learning, hull regions, hull recognition system, SASK algorithm

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Authors: Ewa Kamarad

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Recent problems with adopting the EU Regulation on matrimonial property regimes have clearly proven that Member States are unable to agree on the scope of the Regulation and, therefore, on the definitions of matrimonial property and marriage itself. Taking into account that the Regulation on the law applicable to divorce and legal separation, as well as the Regulation on matrimonial property regimes, were adopted in the framework of enhanced cooperation, it is evident that lack of a unified definition of marriage has very wide-ranging consequences. The main problem with the unified definition of marriage is that the EU is not entitled to adopt measures in the domain of material family law, as this area remains under the exclusive competence of the Member States. Because of that, the legislation on marriage in domestic legal orders of the various Member States is very different. These differences concern not only issues such as form of marriage or capacity to enter into marriage, but also the most basic matter, namely the core of the institution of marriage itself. Within the 28 Member States, we have those that allow both different-sex and same-sex marriages, those that have adopted special, separate institutions for same-sex couples, and those that allow only marriage between a man and a woman (e.g. Hungary, Latvia, Lithuania, Poland, Slovakia). Because of the freedom of movement within the European Union, it seems necessary to somehow recognize the civil effects of a marriage that was concluded in another Member State. The most crucial issue is how far that recognition should go. The thesis presented in the presentation is that, at an absolute minimum, the authorities of all Member States must recognize the civil status of the persons who enter into marriage in another Member State. Lack of such recognition might cause serious problems, both for the spouses and for other individuals. The authorities of some Member States may treat the marriage as if it does not exist because it was concluded under foreign law that defines marriage differently. Because of that, it is possible for the spouse to obtain a certificate of civil status stating that he or she is single and thus eligible to enter into marriage – despite being legally married under the law of another Member State. Such certificate can then be used in another country to serve as a proof of civil status. Eventually the lack of recognition can lead to so-called “international bigamy”. The biggest obstacle to recognition of marriages concluded under the law of another Member State that defines marriage differently is the impossibility of transcription of a foreign civil certificate in the case of such a marriage. That is caused by the rule requiring that a civil certificate issued (or transcribed) under one country's law can contain only records of legal institutions recognized by that country's legal order. The presentation is going to provide possible solutions to this problem.

Keywords: civil status, recognition of marriage, conflict of laws, private international law

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Authors: Sitong. Chen, Bing Wei

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As a sociocultural concept, identity has increasingly gained attention in educational research, and the notion of students’ science identity has been widely discussed in the field of science education. Science identity was proved to be a key indicator of students’ learning engagement, persistence, and career intentions in science-related and STEM fields. Thus, a great deal of educational effort has been made to promote students’ science identity in former studies. However, most of this research was focused on students’ identity development during undergraduate and graduate periods, except for a few studies exploring high school students’ identity formation. High school has been argued as a crucial period for promoting science identity. This study applied a qualitative method to explore how high school students have come to form their science identities in previous learning and living experiences. Semi-structured interviews were conducted with 8 newly enrolled undergraduate students majoring in science-related fields. As suggested by the narrative data from interviews, students’ formation of science identities was driven by their five interrelated experiences: growing self-recognition as a science person, achieving success in learning science, getting recognized by influential others, being interested in science subjects, and informal science experiences in various contexts. Specifically, students’ success and achievement in science learning could facilitate their interest in science subjects and others’ recognition. And their informal experiences could enhance their interest and performance in formal science learning. Furthermore, students’ success and interest in science, as well as recognition from others together, contribute to their self-recognition. Based on the results of this study, some practical implications were provided for science teachers and researchers in enhancing high school students’ science identities.

Keywords: high school students, identity formation, learning experiences, living experiences, science identity

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Authors: Ben Soltane Cheima, Ittansa Yonas Kelbesa

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Speaker Identification (SI) is the task of establishing identity of an individual based on his/her voice characteristics. The SI task is typically achieved by two-stage signal processing: training and testing. The training process calculates speaker specific feature parameters from the speech and generates speaker models accordingly. In the testing phase, speech samples from unknown speakers are compared with the models and classified. Even though performance of speaker identification systems has improved due to recent advances in speech processing techniques, there is still need of improvement. In this paper, a Closed-Set Tex-Independent Speaker Identification System (CISI) based on a Multiple Classifier System (MCS) is proposed, using Mel Frequency Cepstrum Coefficient (MFCC) as feature extraction and suitable combination of vector quantization (VQ) and Gaussian Mixture Model (GMM) together with Expectation Maximization algorithm (EM) for speaker modeling. The use of Voice Activity Detector (VAD) with a hybrid approach based on Short Time Energy (STE) and Statistical Modeling of Background Noise in the pre-processing step of the feature extraction yields a better and more robust automatic speaker identification system. Also investigation of Linde-Buzo-Gray (LBG) clustering algorithm for initialization of GMM, for estimating the underlying parameters, in the EM step improved the convergence rate and systems performance. It also uses relative index as confidence measures in case of contradiction in identification process by GMM and VQ as well. Simulation results carried out on voxforge.org speech database using MATLAB highlight the efficacy of the proposed method compared to earlier work.

Keywords: feature extraction, speaker modeling, feature matching, Mel frequency cepstrum coefficient (MFCC), Gaussian mixture model (GMM), vector quantization (VQ), Linde-Buzo-Gray (LBG), expectation maximization (EM), pre-processing, voice activity detection (VAD), short time energy (STE), background noise statistical modeling, closed-set tex-independent speaker identification system (CISI)

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Authors: Kh. Alaa, Sh. Sarah, J. Khowlah, S. Liyakathunsia

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Education has become very important nowadays and with the rapidly increasing number of student, taking the attendance manually is getting very difficult and time wasting. In order to solve this problem, an automated solution is required. An effective automated system can be implemented to manage student attendance in different ways. This research will discuss a unique class attendance system which integrates both Face Recognition and RFID technique. This system focuses on reducing the time spent on submitting of the lecture and the wastage of time on submitting and getting approval for the absence excuse and sick leaves. As a result, the suggested solution will enhance not only the time, also it will also be helpful in eliminating fake attendance.

Keywords: attendance system, face recognition, RFID, process model, cost, time

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Authors: Insaf Ajili, Malik Mallem, Jean-Yves Didier

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Human motion recognition has been extensively increased in recent years due to its importance in a wide range of applications, such as human-computer interaction, intelligent surveillance, augmented reality, content-based video compression and retrieval, etc. However, it is still regarded as a challenging task especially in realistic scenarios. It can be seen as a general machine learning problem which requires an effective human motion representation and an efficient learning method. In this work, we introduce a descriptor based on Laban Movement Analysis technique, a formal and universal language for human movement, to capture both quantitative and qualitative aspects of movement. We use Discrete Hidden Markov Model (DHMM) for training and classification motions. We improve the classification algorithm by proposing two DHMMs for each motion class to process the motion sequence in two different directions, forward and backward. Such modification allows avoiding the misclassification that can happen when recognizing similar motions. Two experiments are conducted. In the first one, we evaluate our method on a public dataset, the Microsoft Research Cambridge-12 Kinect gesture data set (MSRC-12) which is a widely used dataset for evaluating action/gesture recognition methods. In the second experiment, we build a dataset composed of 10 gestures(Introduce yourself, waving, Dance, move, turn left, turn right, stop, sit down, increase velocity, decrease velocity) performed by 20 persons. The evaluation of the system includes testing the efficiency of our descriptor vector based on LMA with basic DHMM method and comparing the recognition results of the modified DHMM with the original one. Experiment results demonstrate that our method outperforms most of existing methods that used the MSRC-12 dataset, and a near perfect classification rate in our dataset.

Keywords: human motion recognition, motion representation, Laban Movement Analysis, Discrete Hidden Markov Model

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Authors: Iman A. Saad, Loay E. George

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Iris pattern is an important biological feature of human body; it becomes very hot topic in both research and practical applications. In this paper, an algorithm is proposed for iris recognition and a simple, efficient and fast method is introduced to extract a set of discriminatory features using first order gradient operator applied on grayscale images. The gradient based features are robust, up to certain extents, against the variations may occur in contrast or brightness of iris image samples; the variations are mostly occur due lightening differences and camera changes. At first, the iris region is located, after that it is remapped to a rectangular area of size 360x60 pixels. Also, a new method is proposed for detecting eyelash and eyelid points; it depends on making image statistical analysis, to mark the eyelash and eyelid as a noise points. In order to cover the features localization (variation), the rectangular iris image is partitioned into N overlapped sub-images (blocks); then from each block a set of different average directional gradient densities values is calculated to be used as texture features vector. The applied gradient operators are taken along the horizontal, vertical and diagonal directions. The low order norms of gradient components were used to establish the feature vector. Euclidean distance based classifier was used as a matching metric for determining the degree of similarity between the features vector extracted from the tested iris image and template features vectors stored in the database. Experimental tests were performed using 2639 iris images from CASIA V4-Interival database, the attained recognition accuracy has reached up to 99.92%.

Keywords: iris recognition, contrast stretching, gradient features, texture features, Euclidean metric

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Authors: Amin Nazerzadeh, Afsaneh Nouri Houshyar , Azadeh Noori Hoshyar

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With the rapid growing of information technology, the industry and manufacturing systems are becoming more automated. Therefore, achieving the highly accurate automatic systems with reliable security is becoming more critical. Biometrics that refers to identifying individual based on physiological or behavioral traits are unique identifiers provide high reliability and security in different industrial systems. As biometric cannot easily be transferred between individuals or copied, it has been receiving extensive attention. Due to the importance of security applications, this paper provides an overview on biometrics and discuss about background, types and applications of biometric as an effective tool for the industrial applications.

Keywords: Industial and manufacturing applications, intelligence and security, information technology, recognition; security technology; biometrics

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Authors: Chung-Kwei Wang, Kuo-Ying Lo

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The study is aimed to examine main and moderation effect of Chinese traditional social wisdom ‘Ren-qing Shi-kuon' the adjustment of social worker students during their practicum. Ren-qing Shi-ku as a social wisdom has been emphasized by collective-oriented Chinese society for thousand years. Based on interview and literature review, we operationalized the concept as four factors, including ‘harmonious interaction’, ‘understanding and tolerance’, ‘empathetic communication’ and ‘rule abiding’. We administer the scale to 96 social worker senior students before their summer practicums begins and collect their response on emotion labor, emotional exhaustion, work load, work satisfaction. We also ask their supervisors rated their performance on empathy, interpersonal relationships, performance on practicum and their Ren-qing Shi-ku performance. Results indicated that self-ratings of students on Ren-qing Shi-ku scale are correlated with rating from their supervisors. Students who have higher Ren-qing Shi-ku have better adjustment and higher ratings from their supervisor. Ren-qing Shi-ku also moderate effects of surface acting labor and work load on emotional exhaustion and work satisfaction. However, Ren-qing Shi-ku seems more beneficial under low work load situations. The finding of this study suggested traditional social skill training might be very effective for social service providers in a collective-oriented culture.

Keywords: emotion labor, ren-qing shi-ku, emotional exhaustion, work satisfaction and performance

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Authors: Anes Enakoa, Yawei Liang

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Question Answering (QA) system is one of the most important and demanding tasks in the field of Natural Language Processing (NLP). In QA systems, the answer generation task generates a list of candidate answers to the user's question, in which only one answer is correct. Answer selection is one of the main components of the QA, which is concerned with selecting the best answer choice from the candidate answers suggested by the system. However, the selection process can be very challenging especially in Arabic due to its particularities. To address this challenge, an approach is proposed to answer questions with multiple answer choices for Arabic QA systems based on Textual Entailment (TE) recognition. The developed approach employs a Support Vector Machine that considers lexical, semantic and syntactic features in order to recognize the entailment between the generated hypotheses (H) and the text (T). A set of experiments has been conducted for performance evaluation and the overall performance of the proposed method reached an accuracy of 67.5% with C@1 score of 80.46%. The obtained results are promising and demonstrate that the proposed method is effective for TE recognition task.

Keywords: information retrieval, machine learning, natural language processing, question answering, textual entailment

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Authors: Ugbede Onalo, Mohd Lizam, Ahmad Kaseri, Otache Innocent

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Giving the paucity of studies on IFRS adoption and quality of banks accounting quality, particularly in emerging economies, this study is motivated to investigate whether the Nigeria decision to adopt IFRS beginning from 1 January 2012 is associated with high quality accounting measures. Consistent with prior literatures, this study measure quality of financial statement information using earnings measurement, timeliness of loss recognition and value relevance. A total of twenty Nigeria banks covering a period of six years (2008-2013) divided equally into three years each (2008, 2009, 2010) pre adoption period and (2011, 2012, 2013) post adoption period were investigated. Following prior studies eight models were in all employed to investigate earnings management, timeliness of loss recognition and value relevance of Nigeria bank accounting quality for the different reporting regimes. Results suggest that IFRS adoption is associated with minimal earnings management, timely recognition of losses and high value relevance of accounting information. Summarily, IFRS adoption engenders higher quality of banks financial statement information compared to local GAAP. Hence, this study recommends the global adoption of IFRS and that Nigeria banks should embrace good corporate governance practices.

Keywords: IFRS, SAS, quality of accounting information, earnings measurement, discretionary accruals, non-discretionary accruals, total accruals, Jones model, timeliness of loss recognition, value relevance

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Authors: Ming-Yen Chang, Sheng-Hung Ke

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This research focuses on the development of a speed bump identification system for real-time control of adjustable shock absorbers in vehicular suspension systems. The study initially involved the collection of images of various speed bumps, and rubber speed bump profiles found on roadways. These images were utilized for training and recognition purposes through the deep learning object detection algorithm YOLOv5. Subsequently, the trained speed bump identification program was integrated with an in-vehicle camera system for live image capture during driving. These images were instantly transmitted to a computer for processing. Using the principles of monocular vision ranging, the distance between the vehicle and an approaching speed bump was determined. The appropriate control distance was established through both practical vehicle measurements and theoretical calculations. Collaboratively, with the electronically adjustable shock absorbers equipped in the vehicle, a shock absorber control system was devised to dynamically adapt the damping force just prior to encountering a speed bump. This system effectively mitigates passenger discomfort and enhances ride quality.

Keywords: adjustable shock absorbers, image recognition, monocular vision ranging, ride

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Authors: Abe Degale D., Cheng Jian

Abstract:

When creating automated video surveillance systems, violent action recognition is crucial. In recent years, hand-crafted feature detectors have been the primary method for achieving violence detection, such as the recognition of fighting activity. Researchers have also looked into learning-based representational models. On benchmark datasets created especially for the detection of violent sequences in sports and movies, these methods produced good accuracy results. The Hockey dataset's videos with surveillance camera motion present challenges for these algorithms for learning discriminating features. Image recognition and human activity detection challenges have shown success with deep representation-based methods. For the purpose of detecting violent images and identifying aggressive human behaviours, this research suggested a deep representation-based model using the transfer learning idea. The results show that the suggested approach outperforms state-of-the-art accuracy levels by learning the most discriminating features, attaining 99.34% and 99.98% accuracy levels on the Hockey and Movies datasets, respectively.

Keywords: violence detection, faster RCNN, transfer learning and, surveillance video

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Authors: Mohammadamin Abbasnejad

Abstract:

The analysis of expression and facial Action Units (AUs) detection are very important tasks in fields of computer vision and Human Computer Interaction (HCI) due to the wide range of applications in human life. Many works have been done during the past few years which has their own advantages and disadvantages. In this work, we present a new model based on Gaussian Conditional Random Field. We solve our objective problem using ADMM and we show how well the proposed model works. We train and test our work on two facial expression datasets, CK+, and RU-FACS. Experimental evaluation shows that our proposed approach outperform state of the art expression recognition.

Keywords: Gaussian Conditional Random Field, ADMM, convergence, gradient descent

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Authors: Banazzouz Halima

Abstract:

Throughout the ages, language has been viewed not only as a simple code of communicating information but rather as the most powerful and versatile medium of maintaining relationships with other people. While,by the end of the 18th century, such matters of scientific investigation concerning the study of human language began to occur under the scope of “Linguistics” generally defined as the scientific study of language. Linguistics, thus, provides a growing body of scientific knowledge about language which can guide the activity of the language teacher and student as well. Moreover,as times passed, the linguistic development engaged language in a broadly practiced academic discipline having relationship with other sciences such as: psychology, sociology, anthropology etc. Therefore, “Sociolinguistics” was given birth during the 1960’s. In fact, the given abstract is mainly linguistic, inserted under the scope of “Sociolinguistics” and by far it highlights on the process of linguistic variation and language change to show that all languages change through time and linguistic systems may vary from one speech community to another providing there is a sense of vitality where people of different parts of the globe may mutually and intelligibly communicate and comprehend each other.

Keywords: language change-sociolinguistics, social context-speech community, vitality of language, linguistic variation, urban dialectology, urban dialectology

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Authors: Shau-Ping Shiu, Shu-Ling Lin

Abstract:

Pregnancy lead a process of changing in the endocrine system. Either pregnancy itself or the surrounding affect such as the attitude of family to the pregnant lady can bring lots of stress. Sever stress may lead pregnant women display serious mental problem such as mood swings, impulsivity, and abnormal behavior. A method of self management of stress(SMS) has been proved that help patient of cancer in release their stress. This study were going to use SMS to help pregnant women. Methods: In this study, 42 ladies in the first to third months of pregnancy process applied to join SMS of program have divided into 21 participants in both control and experimental group by draw. 24 sessions of Yoga program were conducted once a week for 6 months for experimental group. Verbatim used to gather more feedbacks from the interview followed by each Yoga sessions. Brief symptom Rating scale also conducted pre and post experiment for 42 participations. Results: Overall score of Brief Symptom Rating Scale reduced 17.82 points and suicide drop 9 points in experimental group, compared to the control group increasing 10.24 point of overall score and suicide add 7 points. Feedback from interviews showed participations improved in emotion, physical health and stress management. They indicated having more positive emotion daily, having better gastrointestinal peristalsis movement, releasing back tention, well weight control, reducing stress and changing the quality of interpersonal relationships. Conclusion: SMS of Yoga program in this study included four key training directions which were stimulation, relaxation, awareness and pranayama lead a great improvment of stress management for pregnant lady. Throughout this Yoga program, women learned to ignite eustress, remove distress, create calmness and breath slows down. As the result, Yoga program has helped women in experiment group lower their tension, and bring the extra benifits in emotion and relationships. It support women to overcome their pregnancy. Suggestion: An unexpected result of this study showed all participants had no morning sickness since they engaged in SMS program, and no one absent from course due to the benefits of it. We strongly suggest that SMS of Yoga program can be a add of medication for women in pregnancy, however, the position of Forward in the SMS sequence has been point out pressing participant’s stomach, which can be replace to Bridge position to comfort participants.

Keywords: self-management of stress(SMS), yoga program, pregnant women, early pregnancy

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Authors: Christina Adly, Meena Abdelmeseeh, Tamer Basha

Abstract:

This paper proposes a system for hand movement recognition using multichannel surface EMG(sEMG) signals obtained from 40 subjects using 40 different exercises, which are available on the Ninapro(Non-Invasive Adaptive Prosthetics) database. First, we applied processing methods to the raw sEMG signals to convert them to their amplitudes. Second, we used deep learning methods to solve our problem by passing the preprocessed signals to Fully connected neural networks(FCNN) and recurrent neural networks(RNN) with Long Short Term Memory(LSTM). Using intrasubject evaluation, The accuracy using the FCNN is 72%, with a processing time for training around 76 minutes, and for RNN's accuracy is 79.9%, with 8 minutes and 22 seconds processing time. Third, we applied some postprocessing methods to improve the accuracy, like majority voting(MV) and Movement Error Rate(MER). The accuracy after applying MV is 75% and 86% for FCNN and RNN, respectively. The MER value has an inverse relationship with the prediction delay while varying the window length for measuring the MV. The different part uses the RNN with the intersubject evaluation. The experimental results showed that to get a good accuracy for testing with reasonable processing time, we should use around 20 subjects.

Keywords: hand movement recognition, recurrent neural network, movement error rate, intrasubject evaluation, intersubject evaluation

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Authors: Lowai Abed

Abstract:

The differences in languages play a big role in cross-cultural communication. If meanings are not translated accurately, the risk can be crucial not only on an interpersonal level, but also on the international and political levels. The use of metaphorical language by politicians can cause great confusion, often leading to statements being misconstrued. In these situations, it is the translators who struggle to put forward the intended meaning with clarity and this makes translation an important field to study and analyze when it comes to cross-cultural communication. Owing to the growing importance of language and the power of translation in politics, this research analyzes part of President Bush’s speech in 2001 in which he used the word “Crusade” which caused his statement to be misconstrued. The research uses a discourse analysis of cross-cultural communication literature which provides answers supported by historical, linguistic, and communicative perspectives. The first finding indicates that the word ‘crusade’ carries different meaning and significance in the narratives of the Western world when compared to the Middle East. The second one is that, linguistically, maintaining cultural meanings through translation is quite difficult and challenging. Third, when it comes to the cross-cultural communication perspective, the common and frequent usage of literal translation is a sign of poor strategies being followed in translation training. Based on the example of Bush’s speech, this paper hopes to highlight the weak practices in translation in cross-cultural communication which are still commonly used across the world. Translation studies have to take issues such as this seriously and attempt to find a solution. In every language, there are words and phrases that have cultural, historical and social meanings that are woven into the language. Literal translation is not the solution for this problem because that strategy is unable to convey these meanings in the target language.

Keywords: crusade, metaphor, mistranslation, war in terror

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