Not English In Los Adrenaline —– A biometric Perception

Don't English dissolve adrenaline ----- A biometric Professor Dr.S.Elangovan perception. PT Lee College of Engg & Tech, Kanchipuram


English language is not a bull on the native speakers as their familiar and as such they must take the bull by the horns. Learning a language is fun and not so formidable. Man is the master of language and language is not the master of the man .. If one wants to become proficient in English, he must "Linguistic dictator. In this context, biometrics is useful to diagnose the fear psychosis that is unnecessary. Biometrics recognition based on one or more intrinsic anatomical, physiological and psychological characteristics. Recently , electrography computational bio-based gas discharge visualization (GDV) technique has been proposed as one of the biometric tools for investigating the physiological and psycho-emotional functional states of an individual. In this paper we present a computational implementation of biometrics based GDV for visual and quantitative assessment of anxiety in the process of learning English as a Second Language (ESL). The integration of biometrics into the educational paradigm has been investigated in a pilot study with foreign students in the ESL course at the ESL Institute , VIT University. We have the electro-photonic emissions (also called GDV-grams) of students within reach before and after language activities, including listening comprehension tasks and showed that the fear index in listening paradigm corresponds to the increase of entropy level of the left matches the right hemisphere. Our pilot data confirm the recent findings of the correlation of right hemisphere involvement in second language acquisition at the level of language proficiency. Thus, biometrics-based GDV computational tool can be used to evaluate and potentially anxiety present identification of ESL learners. 1

Key Words

Adrenaline L, English, take the bull by the horns, Biometrics, Bio-electrography, GDV technique, Anxiety, ESL, entropy, Right hemisphere

1. Introduction

Biometrics is an automated process of recognition of individual facilities, based on one or more intrinsic anatomy, physiology and psychological characteristics. A typical biometric system consists of five parts: a sensor, signal processing algorithms, data storage, a matching algorithm and a decision process. The application of biometric identification models, identification and verification. Recognition is the knowledge of a previously registered person, identification is the process of determining the identity of an individual, where he is a verification process where the system confirms the

existence of an individual. Biometric models existing today are based for fingerprints, face, iris, voice, signature, hand geometry, palm and vascular pattern recognition, performance evaluation and new sensors [1, L 1

2]. For example, the palm and fingerprint models combine ridge flow, ridge characteristics and a ridge structure of the elevated portion of the epidermis. Vascular pattern recognition models use of near-far-infrared light reflected or images of the blood vessels of a hand or finger provided for personal recognition. Dynamic models use anatomical and behavioral characteristics for recognition purposes [3]. There are other models based on biometric speaker recognition, dynamic signature measures, keystroke dynamics, retina recognition, gate / body and facial recognition biometrics thermography.

The main areas of applications can be classified into the following four groups: 1) Medical biometrics, which is related to the use of biometrics in medical applications such as medical diagnosis and is based on the extraction of biomedical pattern and possible association with disease, 2) Forensic biometrics, which refers to the use of and body biometrics for criminal identification, 3) Convenience of biometrics, which is related to maintaining the level of convenience when using biometric services, 4) Security for biometrics to reduce fraud and control access to restricted areas [4]. L 1

Computational bio electrography has recently been proposed and used as a promising method for complex evaluation of the functional status of an individual using the fingertips and electro-photonic emission in a high intensity electromagnetic field [5]. The method consists of capturing and analyzing the electro-photonic emissions fingertips using an electro-photonic pulse analyzer based on gas discharge visualization technique (GDV) [5]. Several studies have tried to determine what exactly the fluorescent glow (also known GDV-grams) around finger shapes. Krizhanovsky et al. [6] that the human central nervous system play a crucial role in the formation of the skin glowing in a high intensity electromagnetic field plays. The ATP (adenosine tri-phosphate) molecule acts as a neurotransmitter in the autonomic neuromuscular junctions, the ganglia and central nervous system. Therefore, in the case of the normal functioning of the organism, L 1

the ATP diffusion exchange (and the electron flow) should be regularly, so that the regularity and uniformity of fluorescence (glow) that occurs during the interaction of the skin (ie a finger) with the high intensity electromagnetic field. Another study conducted by Williams [7] states that specific structural-protein complexes within the mass of the skin channels increased electron conductivity, measured at acupuncture points on the skin surface. Stimulated impulse emissions of the skin are mainly due to transport of electrons delocalized. Optical emission amplified in emissions are recorded by optical sensors in the electro-photonic pulse analyzer [7] . The field of application of the GDV technique in medicine, sport psychology and cognitive research. The correlation between the GDV data and the data obtained from other diagnostic tools showed that GDV is a very fast, at the same time, accurate real -time diagnostic technique [8-12]. 1

The L GDV technique has been successfully used in psychology and cognitive studies, especially for the psycho-emotional state of an individual to assess the changes taking place in a human body over a period of time to evaluate. GDV Based on parameters such as shape and size of electro-photonic emissions, symmetry and proportion of the captured image with the rest of the GDV-grams of all fingertips, the presence or absence of aggressive signs and weaknesses of the agencies / organ systems can be predicted and therefore it is possible to conclude about the functional status of an individual at the time of the study [13, 14] L 1.

Second language learning is a process by which a person learns a language besides their mother tongue. English is the lingua franca of communication present in the modern era of globalization and has been widely studied for adaptation as an international language [15]. In the United States of America, a majority of the population speaks English as their mother tongue. International students often experience culture shock when exposed to a native English environment, such as the United States, and it takes time for them to language barriers to overcome. It has been shown that native English speakers significantly outperform non-native English speakers in all major subtests (in writing, reading and listening) of an English language test [16]. The relatively poor performance of non-native speakers of English is mainly attributed to anxiety, which is a prominent documented psychological phenomenon in second language learn. recently reported that one third to one half of international students experience at the level of fear debilitating while performing in their second language [17]. L 1

The anxiety phenomenon in second language learning is the focal point of the different

studies and research . It is established that (i) anxiety can occur at any stage of language acquisition and the speed and accuracy with learning, (ii) language anxiety can be one of the predictors of language ability, (iii) students with higher language anxiety to avoid interactive communication more often than less anxious learners, (iv) fear of arousal negatively impact the communication output influence as it can be interrupted by the "freeze" moments that students experience when they are frightened to (v) language learning under fearful circumstances become traumatic to the identity of a student. [18] Young [19, 20] number of elements as possible connected sources of anxiety from the perspective of the student, the teacher and educational process. Therefore, he argues that the possible causes of fear of being may (i) personal and interpersonal anxiety, (ii) learner beliefs about language learning, (iii) instructor beliefs about language learning, (iv) instructor-student interactions, (v) classroom procedures and (vi) language testing .

In this paper, we assume that language activities such as listening, speaking, reading and writing may fear factor that can be quantified and visualized using the GDV method involved. The psycho-emotional aspects of language learning and performance, such as anxiety and stress, manifested at the physiological level by excessive sweating of the palms and fingers and muscle tension. An electro-photonic pulse analyzer based on GDV can use these expressions, especially those revealed by the fingertips, for quantifying and visualizing the anxiety level of an ESL (English as a Second Language) student. The GDV technique is noninvasive and provides a real-time measurement of signals from the sympathetic and parasympathetic nervous system [21]. So, the use of these biometric model of GDV will be able to quantify and unique biological characteristics to visualize the psychological and physiological parameters related to anxiety regarding the ESL learning. The rest of the paper is organized as follows: Section 2 discusses the literature on the relationship between learning English as a second language and fear. Section 3 gives an overview of the origins of computational bio-electrography using the GDV technique and describes the actual procedure used to obtain the GDV-gram. We describe the analysis of the GDV-gram using the built-in software of the electro-photonic impuls GDV analyzer. Chapter 4 describes a pilot study, the first of its nature, carried out by us to quantify the level of anxiety student learners of English as a second language to visualize at Jackson State University. paper.

2 Section 5 concludes. Anxiety

With English as a second language and the rise in popularity of English language in the world and its use in almost all areas the social, economic and cultural life, the need to learn English as a Second Language (ESL) has increased among the population whose mother tongue is other than English. Education aims pursued by non-native students in English speaking countries, such as the United States of America, require certain level of English proficiency that can be achieved through the preparation and taking a TOEFL test. Some students have to study English at the level of the beginner start slowly and advance to the particularities of their cultural background. For example, it is found that the English-language learners of Confucian Heritage Cultures (CHCs), such as China, Korea and Japan, are more anxious in learning, performing and communication in ESL [22 ]. It is a very challenging task for teachers and caregivers in the U.S. schools to address specific needs of students for whom English is not a native language.

Scovel [23] was the first involving the inconsistency in the second language learning with fear. Horwitz was the first to provide a clear definition of foreign language anxiety. Horwitz Foreign Language Classroom Anxiety Scale (FLCAS) was the main contributor to the field of second language learning and acquisition [24]. The main routes of fear quantify behavioral observations and physiological evaluation, as heart rate and blood pressure, learners' self-report about their inner feelings and reactions as well as structured interviews, follow-up interviews and questionnaires [25, 26]. The negative relationship between anxiety and performance or performance has confirmed in several subsequent studies using all four language skills: speaking [27-29], write [30], reading [31] and listening [32, 33] L 1.

A student who suffers from the reading of anxiety may exhibit a variety the symptoms that result from the inhibition of their intellectual curiosity, aggression or independence. It has been shown [34] that (1) read fear a stronger negative correlation with reading achievement in relation to general anxiety, and ( 2), although the general anxiety and reading anxiety correlate strongly, reading anxiety measures something beyond general anxiety. Listening fear is a kind of fear that comes from listening to others, as a foreign language situation. So, listening anxiety can negatively affect learning and affect performance [35]. L 1

Foreign language learners typically experience much anxiety about taking tests listening. The results in [36] indicates that foreign language anxiety and listening anxiety are separate but related signs for both negatively correlated with performance. A English

Writing Anxiety Scale was developed in [37] and the four factors identified for writing anxiety in English: fear of writing tests, fear of making mistakes, fear of negative evaluation and low confidence in English writing. The results have shown that the scale has adequate psychometric properties. Another study [38] evaluated the anxiety of students over a period of ten years, using FLCAS. The FLCAS scores measured by the students 'perception of their language skills and showed that anxiety plays a primary role in the implementation and successful completion using a foreign / second language.

The first attempt [39] to GDV technology use in education was achieved in the experiment to teach listening skills in English as a foreign language. The eyes of the student participants in this experiment were closed. The GDV technique was used to the functional status of individuals and biological dynamics in the process of perception and processing the information in English [39] to assess. In 2007, Bulatova et. al. [40] reported the results of the examination of school children with GDV technique. According to the interpretation of the GDV-grams obtained in their study, only 36% of children had a normal psycho-emotional and physiological state, 42% shortage of electronic-photonic emission shown and 17% were in a critical condition. A positive correlation was found between the level of student performance and The results of GDV test. Children with a shortage of electro-photonic emissions had a lower level of performance. Through the active participation of psychologists, family, teachers and children themselves, over a period of five months of counseling, regime, daily exercise and proper nutrition, L 1

82% of the children had their electro-photonic emissions the

normal range. This experience has shown that GDV technique may be useful in the teaching process, mainly due to direct and real-time evaluation of the functional status of an individual but also anxiety and stress associated with a learning process. Taking cue from this study, we use the GDV method to the unique physiological and psycho-emotional signatures associated with anxiety in ESL learning to process.


3. Computational Bio electrography-Based Visualization on Gas

Discharge Technique

The first global discoveries of the phenomenon of the bright fluorescence around the human body in a high frequency electrical circuit belonging to Nicola Tesla in 1880. To understand the significance of this discovery began in 1939 when Russian Semion Kirlian technician's heyday around his fingers in restoring the high frequency equipment in the hospital saw. He and his wife Valentina studied this "mysterious glow" till

1978 and it was known as "Kirlian

Photography. During the year 1980, different approaches for

the applications of bio-electrographic technology in medicine have been developed (eg Dumitresku I. Romania, Germany P. Mandel, N. Milhomens in Brazil, France A. Lerner, H. Oldfield England, A. Konikevich in the U.S. and many others). Many books and scientific articles are published on Kirlian photography and statistical correlations with interesting observations about the world. In 1995, the gas discharge visualization (GDV) technique based on optical methods, modern electronics and computer processing of data, gave a new dimension to Kirlian photography and lead to the creation of a new scientific field called computational bio-electrography.

Figure 1: A setup of the electro-photonic Impulse

Analyzer exercised by a Laptop

Figure 2: actual procedure for covering the hand with a black cloth for EPE Capture

The GDV assess the functional status of an individual consists of static snapshots (also called GDV-grams) of the electro-photonic emissions (EPE) of 5 - fingers of each hand (a total of 10 finger EPE snapshots) collected with and without the use of filters to the surface of the electro-photonic Impulse

Analyzer. The filter is a thin plastic film which is the direct contact of the skin of the fingertip on the glass surface prevents the analyzer. The rationale behind the use of the filter is capturing the EPE that the physiological parameters of the person represents, the EPE caught without using the filter represents the psycho-emotional parameters of the individual. Figure 1 shows a set of electro-photonic Impulse Analyzer controlled by a laptop and Figure 2 illustrates the actual procedure of covering the hand with a black cloth to prevent the penetration of light on the glass surface. The GDV camera captures EPE under the electrodes (ie, GDV-grams) of the fingertips on the glass surface of the analyzer.

Figure 3: Example of GDV-grams of the thumb and index fingers on the left and right to illustrating the various sectors of the organ systems and their energy coefficients (L - Left, R - right) L 1

Figure 4: A Sample GDV chart obtained using the static GDV-grams of 10 fingertips

The electro-photonic pulse analyzer has a GDV-built software to the GDV-gram analysis. The GDV software quantifies the activity status of the different organs / organ systems in the form of energy coefficient. The energy coefficient of an organ / organ system in a GDV-grams is typical of the energy state (ie the activity) of the organ / organ system, obtained by normalizing the image to the standard GDV -gram. The GDV software that calculates numerical power coefficients previously calibrated with standard GDV-grams collected from about 10,000 people with normal health. The range of the energy coefficient values for one organ / organ system in normal condition [-0.6, ..., L 1

1.0] that the organs / organ systems energy

coefficient values below -0.6 is said that hypo-functional (low energy) and organs / organ systems with energy coefficient values greater than 1.0 is said to be hyper-functional (excess energy). Figure 3 illustrates the GDV-gram obtained for the (1) thumb and (2) index fingers on the left (L) and right (R) hands of a human subject. The energy status was observed for the organs / organ systems (Figure 3) visualized by stressing their energy coefficient values in green, pink and yellow colors - representative of normal, hypo-and hyper-functional respectively.

Using the functional states energy coefficients obtained from the GDV-grams of all the fingers of the left and right, the software builds a GDV GDV diagram, that a comprehensive overview of the energy states of all


the organs / bodies systems. The GDV-diagram of a person (an example is shown in Figure 4) is represented with two curves (red and blue) and each of these curves is divided into different sectors, whose radius corresponds to the energy coefficient values observed for the sector. Each sector in the GDV waveform characteristic of a particular organ / organ systems. The curve with the red color represents the GDV photograph taken without the use of the plastic filter and explains the functionality of the organs / organ systems characteristic of the psycho-emotional status of an individual. The curve with the blue color indicates the GDV image taken using the filter and captures the functionality of the organs / organ systems characteristic of the physiological status of the individual. For better visualization of the distribution coefficient, the circles in three colors: pink, green and yellow corresponding to the levels below standard (ie, hypo-functional), standard (normal) and above the standard (hyper-functional ) respectively.

In Besides static snapshots of the fingertips, one

could also collect dynamic GDV-grams of changes in physiological and psycho-emotional state of a person to follow while performing a particular activity. The dynamic GDV-grams can be used for an individual over a period of time to inspect certain activities, such as a video, test, public speaking, research on the psycho-physiological dynamics that may occur and correlate with the content . The GDV-gram is a series of static snapshots collected at the fingertips a

regular interval. In Figures 5 and 6, let a sequence of GDV-grams (collected for each minute), illustrating the energy changes the status of non-native and native speakers while watching a 3-minute film in English . A visual interpretation of the two sets of GDV-gram indicates that the non-native speakers severe changes in their energy states undergo while watching a movie that affects their emotional distress, whereas no significant changes in the energy states of native speakers to look the same movie.

Figure 5: Dynamic GDV-grams of a non-native speakers while watching a movie in English

Figure 6: Dynamic GDV-grams of a Native Speaker while watching a movie in English

4. Pilot study of ESL learning process using GDV Technique

Four international students of Turkish, Vietnamese and Chinese descent (right dominant) in English as a Second Language Institute (ELSI), Jackson State University, voluntarily participate in our study. We have chosen to understanding auditory fear first study because our suspicions that listening is the hardest skill to Master in second language learning. Our hypothesis in this pilot study is that its non-native speakers, these persons expression of anxiety associated with language functions in English have increased, especially with the listening comprehension section. All students were enrolled in the average level of English as a Second Language course at ELSI. Students have the consent form in accordance with human Institutional Review Board (IRB) and the purpose of the procedure was explained to them under the guidelines of the IRB human. Seven persons were recruited and participated in the first phase of GDV-images, but only four participants completed the experimental protocol. Three students did not show up because of a lack of understanding of the instructions in English language.

We recorded two sets of static images of electro-L 1

photonic emissions around the students at your fingertips in a high intensity electromagnetic field generated by electro-L 1

photonic impulse analyzer, before and after listening tasks.

Figure 7.1: Activation Coefficient for Student 1

Figure 7.2: Activation Coefficient for Student 2

Figure 7.3: Activation Coefficient for Student 3

Figure 7.4: Activation Coefficient for Student 2

Figure 7: The distribution of the activation coefficient in the four ESL participants before and after taking the Listening Test

The recording of the images was done with and without filter. Two integral parameters, activation coefficient and integral entropy were analyzed and were considered as potential indicators of the level of anxiety of the student participants. According Korotkov

[5], activation coefficient is an average of the absolute magnitude of the difference of the energy coefficients of diagrams created using GDV images taken with and without filter dispersions.

The corresponding proposed scale of 0-10 of fear based on the

activation coefficient is divided into four parts: 0-2 (low level of anxiety), 2-4 (normal level of anxiety, 4-8 (high level of anxiety) and 8-10 (distress, altered state of consciousness). The activation rate of the four ESL participants before and after taking the listening test is shown in Figure 7. As shown in this figure, the activation coefficient of three of the four participants was high for the test and the low post-test . The activation rate of these participants decreased from 5.37 to 4.66 (a 13% decrease), from 2.43 to 2.12 (13% decrease) and 5.42 to 2.06 (62% decrease). The fourth participant, the activation coefficient increased after the test (from 2.97 3.28 for test after test -.. 10% increase), we would expect that fear to go up after listening activities, however, for 3 4 of the ESL participants, we did not observe an increase in activation rate after listening test.

Figure 8.1: Integral entropy for Student 1

Figure 8.2: Activation Coefficient for Student 2

Figure 8.3: Integral entropy for Student 3

Figure 8.4: Activation Coefficient for Student 4

Figure 8: The division of Integral Entropy in the four ESL participants before and after taking the Listening Test

Thus proposed Korotkov post 0-10 anxiety scale can not be used for evaluating anxiety in the ESL listening comprehension task, although we can not exclude the possibility of the activation coefficient as a measure of the assessment of anxiety for other language activities such as speaking, reading and writing.

On the other hand, the distribution of the integral entropy

has shown promising results. Integral entropy is a measure of the deviation from the physiological and psycho-emotional balance. The proposed level of anxiety on the basis of integral entropy is divided into four major parts: L 1

0-1 (low level of anxiety), 1-2 (normal level of anxiety, 2-1

4 L (high level of anxiety) and> 4 (very high level of anxiety). As indicated in Figure 8, the integral entropy level of all four ESL participants, measured by the GDV-grams for the left hand that matches the right half of the human brains, increased after the test compared to the values before the test. The integral entropy level of the student participants increased from 1.77 to 2.08 (18% increase), 1.77-1.90 (7% increase ), from 1.73 to 2.06 (19% increase) and to

1.76 1.58 (11% increase). Therefore we consider the use of integral entropy as a measure of the fear of learning English as second language, at least for listening tasks, justified by the results in our pilot study.

Our preference for integrated entropy as a measure of fear is also justified by the following observations from the literature on chaos / complexity science and second language acquisition [41] and The recent discovery in the literature that the right hemisphere is more involved in the second language learners who are less familiar and less educated in the language [42]. L 1

According to Larsen-Freeman [41], language learning

is a dynamic, complex, open, self-organizing, feedback sensitive task and is limited by strange attractors. It is complex because a multitude of interacting factors involved in the ESL learning. Learning new vocabulary is a nonlinear process, for example, the student the text to hear the familiar words and feel comfortable in the performance, but when the teacher introduces new words, instead of progress, the student's performance less capable, because after the introduction of new unknown words, the system

Share and Enjoy:
  • Print
  • Digg
  • StumbleUpon
  • Facebook
  • Yahoo! Buzz
  • Twitter
  • Google Bookmarks
  • Add to favorites

Leave a Reply

Spam protection by WP Captcha-Free