English Alphabet Research Articles

Air Handwriting by Using CNN Model

Gesture recognition has been a popular research field under the trend of IoT and intelligent devices. Air-writing is the most challenging and crucial topic in the gesture recognition field. In this paper, we propose a wearable airwriting system that makes users can write the English alphabet in the three-dimensional space without any write rules. The proposed system is based on the Inertial Measurement Unit (IMU), and it uses dynamic time warping (DTW) as the main recognition algorithm. In addition, to improve the recognition accuracy and take a better advantage of the DTW algorithm, we present an adjustment system that gives some new optimization methods to the application of IMU and DTW. In the experiment, the accuracy of recognition is 84.6% for the uppercase alphabet (from „A‟ to „Z‟) in user-dependent case. And we also confirmed that the recognition method only based on the DTW algorithm is one kind of user-dependent methods, which means this method is heavily dependent on personalization.

Individual differences in distributional statistical learning: Better frequency "discriminators" are better "estimators".

People can easily extract and encode statistical information from their environment. However, research has primarily focused on conditional statistical learning (i.e., the ability to learn joint and conditional relationships between stimuli) and has largely neglected distributional statistical learning (i.e., the ability to learn the frequency and variability of distributions). For example, learning that "E" is more common in the English alphabet than "Z." In this article, we investigate how distributional learning can be measured by exploring the relationship between, and psychometric properties of, four different measures of distributional learning-from the ability to discriminate relative frequencies to the ability to estimate frequencies. We identified moderate relationships between four distributional learning measures and these tasks accounted for a substantial portion of the variance in performance across tasks (44.3%). A measure of divergent validity (intrinsic motivation) did not significantly correlate with any statistical learning measure and accounted for a separate portion of the variance across tasks. Our results suggest that distributional statistical learning encompasses the ability to discriminate between relative frequencies and estimating them.

Problems and prospects of developing spelling skills in schoolchildren with visual impairments in Uzbekistan

This article addresses issues concerning the development of accurate word pronunciation skills in English among students with visual impairments in Uzbekistan. The challenges include a scarcity of Braille literature, discrepancies in word writing and pronunciation between Uzbek and English, confusion stemming from similarities and differences in the Braille-based English alphabet and the Latin-script Uzbek alphabet, as well as a lack of educational materials and the production of essential and supplementary educational literature. The complexities associated with these issues are examined, with particular focus on psychological obstacles faced by students in the same demographic when learning English. Additionally, practical recommendations for enhancing this field will be formulated based on empirical research findings. Special attention is also given to the needs of consumers requiring educational materials for this demographic, adherence to academic standards, and the promotion of a conducive learning environment for students with visual impairments studying English.In addition, the issue of ensuring communication between schoolchildren with visual disabilities and their teachers, as well as assistants aiding in lesson preparation for the same group of students, in creating child-specific dictionaries and educational literature, is being addressed. There is also a need to coordinate the efforts of both state and non-state organizations on international and local levels to support the development of dictionaries and educational materials for teaching English to visually impaired students in Uzbekistan, along with establishing a system for delivering them and the necessary educational equipment

Evaluating Effects of Continuous Occlusion on Visual Letter Identification

Visual letter identification refers to humans’ use of a visual system to recognize the 26 letters in the English alphabet. Letters may be partially occluded by nonadjacent small occlusion blocks (called discrete occlusion) or a single occlusion block (called continuous occlusion) in the real world, thereby affecting visual letter identification. The effects caused by discrete occlusion have been investigated in existing research. The results indicate that humans possess the ability to identify partially occluded letters and a large occlusion ratio results in low identification accuracy. However, few studies have explored the effects caused by continuous occlusion and revealed precise reflections on occlusion effects. This study presents an evaluation to explore the effects of continuous occlusion on visual letter identification. A controlled experiment is designed to achieve two research goals: identifying the maximum extent of occlusion ratio (named upper bound) that does not affect visual letter identification and investigating the change patterns of the accuracy of occluded letter identification with the gradual increase in occlusion ratio. The experimental results are analyzed in detail, and three main findings are obtained. First, moderately occluded letters can be accurately identified in a continuous occlusion scene. Second, the precise upper bounds are obtained for each of the 26 letters. Lastly, the change patterns for the 26 letters present three nonlinear decline patterns. The findings could inspire technical advancements in the fields of visualization, computer vision, and healthcare.

Air-Writing Recognition Enabled by a Flexible Dual-Network Hydrogel-Based Sensor and Machine Learning.

Accurate air-writing recognition is pivotal for advancing state-of-the-art text recognizers, encryption tools, and biometric technologies. However, most existing air-writing recognition systems rely on image-based sensors to track hand and finger motion trajectories. Additionally, users' writing is often guided by delimiters and imaginary axes which restrict natural writing movements. Consequently, recognition accuracy falls short of optimal levels, hindering performance and usability for practical applications. Herein, we have developed an approach utilizing a one-dimensional convolutional neural network (1D-CNN) algorithm coupled with an ionic conductive flexible strain sensor based on a sodium chloride/sodium alginate/polyacrylamide (NaCl/SA/PAM) dual-network hydrogel for intelligent and accurate air-writing recognition. Taking advantage of the excellent characteristics of the hydrogel sensor, such as high stretchability, good tensile strength, high conductivity, strong adhesion, and high strain sensitivity, alongside the enhanced analytical ability of the 1D-CNN machine learning (ML) algorithm, we achieved a recognition accuracy of ∼96.3% for in-air handwritten characters of the English alphabets. Furthermore, comparative analysis against state-of-the-art methods, such as the widely used residual neural network (ResNet) algorithm, demonstrates the competitive performance of our integrated air-writing recognition system. The developed air-writing recognition system shows significant potential in advancing innovative systems for air-writing recognition and paving the way for exciting developments in human-machine interface (HMI) applications.

Evaluating Handwritten Character Recognition with Hu Moments and K-Nearest Neighbors Algorithm

Handwritten character recognition remains a challenging task in various domains, including handwriting analysis and document digitization. This task poses a significant challenge because of the variability and complexity of handwriting. To address this, it is crucial to develop different methodologies that enhance accuracy and efficiency in recognition. This research evaluates the discrimination capacity of a classifier that combines together the Hu Moments features extraction technique and the k-nearest neighbors (KNN) algorithm for the purpose of handwritten character recognition. The authors worked with handwritten characters from the English alphabet where each character is represented in two handwritten forms. The average accuracy of recognition was 82.69%, that conforms the efficiency of the proposed classifier. This research contributes to the field of automated handwritten recognition and highlights the necessity for improved techniques in character analysis, which has implications for handwriting recognition in different contexts, linguistic studies, document digitization, and other applications where character recognition is crucial. This is the first study that aims to apply the combination of Hu Moments features extraction technique in combination with the KNN algorithm for purpose of handwritten character recognition.

Kombucha–Chlorella–Proteinoid Biosynthetic Classifiers of Audio Signals

ABSTRACTThis paper describes the development of a bioinspired composite material capable of audio classification applications. Hydrogel matrices produced by microorganisms combined with synthetic biology elements, allow for the development of adaptable bioelectronics that connect biology and technology in a customized way. In this study, a composite population of kombucha, chlorella, and proteinoids (thermal proteins) is utilized to respond to acoustic signals converted to electrical waveforms. The kombucha zoogleal mats, which are made and populated by over 60 species of yeasts and bacteria, offer a matrix at the micro level that is connected to the photosynthetic microalgae chlorella. Proteinoids formed through thermal condensation exhibit unique patterns of signaling kinetics. This living material has the ability to be electrically stimulated and can process signals in a way feasible for sensory applications. Using English alphabet audio inputs, a systematic analysis demonstrates the capability to differentiate audio waveforms based solely on biological composite responses. The use of spectral analysis allows for the identification of specific spike timing patterns that encode unique characteristics of individual letters. Moreover, network disturbances result in specific changes in output, so validating the ability to adjust waveform classification. The study demonstrates that kombucha–chlorella–proteinoid composites provide a durable and versatile bioelectronic platform for immediate auditory processing. The work represents progress toward the development of bioelectronic systems that can be customized based on the principles of biological sensory processing, cognition, and adaptation.

Augustin, The Present Researcher, I Say to My Wife “Hyeonhi, Thank You!” (033rd-048th)

French missionary Dallet (1874) wrote in his book that Korean language and Korean people is different from Chinese language and Chinese people. Several researchers studied the translation of ‘the thousand character essay’. The thousand character essay is called as ‘Tcheonzamun’ in Korea. Dallet (1874) described that ‘The thousand character essay’ (Tcheonzamun) was utilized for both Chinese people and Korean people for teaching their children for Chinese characters. It is reasonable that Tcheonzamun is translated through the meaning of Chinese character (Park et al., 2021a; Park et al., 2021b). But it is not be well explained why the Tcheonzamun is translated through Korean pronunciation. The present researcher utilized the book of ‘The thousand character essay’ which had been written by Han (1583). The thousand character essay is called as ‘Tcheonzamun’ in Korea. There are two methods for this translation. The first method is through the meaning of Chinese character. The second method is through Korean pronunciation. Here, in this study, the first method was adopted. And the method of deleting a same part (parts) of Chinese character was utilized. Deleting of same part for the two Chinese character was only on the same line. The line means four Chinese characters. For example, this <033-036 雲(Un) 騰(Deung) 致(Tchi) 雨(U)> is the same line. And the range of this study is (Tcheonzamun 033rd-048th). The title of this work is ‘Augustin, the present researcher, I say to my wife “Hyeonhi, thank you!” (033rd-048th)’. And the range of this is (Tcheonzamun 033rd-048th) of the thousand character essay (Tcheonzamun). The result obtained was described as follows. <Number in Tcheonzamun Chinese characters (the pronunciation on Korean language and written in English alphabet)> 033-036 雲(Un) 騰(Deung) 致(Tchi) 雨(U). 雲(Un)-雨=云 騰(Deung) 致(Tchi) 雨(U) -雨=(nothing). My darling, my husband! You already say to me “I am higher (騰) than you, my wife! And I want to speak (云) solely. Therefore, you must be silently as if you were not (nothing) here any more (致)!” 037-040 露(No) 結(Gyeol) 爲(Wi) 霜(Sang). 露(No)-雨=路 結(Gyeol) 爲(Wi) 霜(Sang)-雨=相. No, it is not so! My darling, my husband! We are married (結), and we are now one. And do you want to continue our life (路) together with me? You and me, I and you (相), we must do our best for two of us (爲) each other. 041-044 金(Geum) 生(Saeng) 麗(Ryeo) 水(Su). 金(Geum)-人=’玉 生(Saeng)-人=土 麗(Ryeo) 水(Su). My husband! You are an ordinary man like soil (土). I, your wife, want to make you to be the splendid man like a precious stone, the jewel (玉), like a shooting star (’). In order for you, my husband, to be such a great man, the water must be beautiful and wise. My dear husband, I am such a wise and beautiful water. I can wash and wash again you, the countrified man. Augustin, the present researcher, I say to my wife “Hyeonhi, thank you!” 045-048 玉(Ok) 出(Tchul) 崑(Gon) 岡(Gang). 玉(Ok) 出(Tchul)-山-山=(nothing) 崑(Gon)-山=昆 岡(Gang)-山=几小. My darling, you were the man who had nothing (nothing) before you met me your lover! I have wanted your success, and I have tried hard to make you such a precious man (玉). My husband, do you want to become such a man? Please make for me, your wife (小), to be able to take out of the vacant and miserable frame (几) of you. You have made the rigid frame for me. My husband, please consider me your wife as the ‘better half’ (昆) for you! My darling, please do not treat me as ‘nothing’ as shown in the first line of this poem (033-036). I, your wife, am wise!

Mediated and non-mediated tactile fingerspelling: a comparative study

ABSTRACT In the development of communication devices for individuals who are Deafblind, a significant challenge is achieving a seamless transition from human-generated to technology-mediated communication. This study compares the intelligibility of the Australian Deafblind tactile fingerspelling alphabet rendered on the HaptiComm tactile communication device with the same alphabet articulated by a human signer. After a short training period, participants identified the 26 English alphabet letters in both the mediated (device) and non-mediated (human) conditions. Results indicated that while participants easily identified most letters in the non-mediated condition, the mediated condition was more difficult to decipher. Specifically, letters presented on the palm or near the index finger had significantly lower recognition rates. These findings highlight the need for further research on the tactile features of communication devices and emphasize the importance of refining these features to enhance the reliability and readability of mediated tactile communication produced through tactile fingerspelling.

Hand Gesture Recognition System Based on Indian Sign Language Using SVM and CNN

Hand gestures (HGs) have been extensively acknowledged as a communication standard for the deaf and dumb school system in the Indian sign language (ISL). We suggested an automated Indian sign language recognition (ISLR) method for English in this study. Initially, the hand region is segmented using the Grasshopper optimization algorithm (GOA) based on the skin color model method. The segmentation’s efficacy is further assessed using three techniques: GOA-based skin color detection algorithm (SCDA), particle swarm optimization-based SCDA (PSO-SCDA), and artificial bee colony-based SCDA (ABC-SCDA). Finally, a database for the retrieved motions representing distinct English alphabets is created. For gesture recognition, the system is trained, and a template-based matching approach is used. The classification technique employs the support vector machine (SVM) and the convolution neural network (CNN). Our suggested recognition method achieved the highest accuracy of 97.85% with GOA-SCDA, compared to 89.29% and 93.96% with PSO-SCDA and ABC-SCDA, respectively. Furthermore, CNN outperformed SVM in classification, with a high accuracy of 99.2% and precision of 81.8%.

Peran Mahasiswa PGMI Dalam Penguatan Materi Pronunciation Alfabet Melalui Media Flashcard di MIS Miftahul Huda II Kota Palangka Raya

This community service activity aims to improve the English alphabet pronunciation skills among students at MIS Miftahul Huda II in Palangka Raya City through the use of flashcard media. Students from the Elementary School Teacher Education (PGMI) program are actively involved in the planning, implementation, and evaluation of this program. The method used is a participatory approach, where PGMI students provide interactive learning using specially designed flashcards to help students recognize and correctly pronounce the alphabet. The results of this activity show a significant improvement in students' pronunciation skills and their enthusiasm for participating in the learning process. Additionally, the involvement of PGMI students in this program provides valuable practical experience in teaching and classroom management. Therefore, this activity is beneficial not only for the students but also for the professional competence development of PGMI students.

Multicolor Anti‐counterfeiting Strategy and Synchronous High Capacity Storage Based on Acidochromic Organic Fluorescent Materials

Comprehensive SummaryMany industries are plagued by economic losses and product failures caused by counterfeit goods. Therefore, advanced anti‐counterfeiting techniques are continuously needed. In this study, we constructed a series of acid‐base sensitive cyclic chalcone dyes A—F by modifying different electron‐donating groups. Differences in acid sensitivity of different structures are well rationalised by NMR and theoretical calculations. Aniline is difficult to protonate than fatty amines, so there is a difference in fluorescence. Hiding and anti‐counterfeiting of information is achieved by this phenomenon. Powder X and Y are the anti‐counterfeit fluorescent powder containing montmorillonite and cyclic chalcone, which have orange fluorescence and the very similar appearance. However, under the influence of acid the Powder X containing triphenylamine modified cyclic chalcone shows red shifted fluorescence and Powder Y containing morpholino and diethylamino groups modified cyclic chalcone shows blue shifted fluorescence. Therefore, the anti‐counterfeiting strategy based on cyclic chalcone is not only limited to UV‐irradiated fluorescence development, but also has more colorization and pattern variations with the aid of acid developer. Data encryption and decryption of numbers, English alphabets and Chinese characters have been realized using A—F, which have great potential for practical applications.

Handwritten Text Recognition in Machine Learning

In this machine learning project, we will recognize handwriting text (single English alphabet) this we are going to achieve by modelling a neural network that will have to be trained over a dataset containing images of alphabets. And used CNN algorithm for external input image prediction

Enhancing English alphabet handwriting skills in preschool children through digital game-based learning approach

ABSTRACT Early exposure to preschool literacy skills benefits children’s language development, and the rise of digital learning provides young children access to information and technology devices. This study investigated the effectiveness of using a tablet learning model combined with a Digital Game-Based Learning Approach and applied handwriting skills to enhance preschool children’s English literacy skills. A quasi-experimental design was used with an experimental group of 12 children and a control group of 12 children. Results showed that the experimental group had significantly higher achievement and correctness of shape in English alphabet handwriting and exhibited more active learning behavior. The study suggests that this approach could provide an innovative and engaging platform for young children to develop their language and literacy skills, potentially leading to better educational outcomes.

Imagined speech classification exploiting EEG power spectrum features.

Imagined speech recognition has developed as a significant topic of research in the field of brain-computer interfaces. This innovative technique has great promise as a communication tool, providing essential help to those with impairments. An imagined speech recognition model is proposed in this paper to identify the ten most frequently used English alphabets (e.g., A, D, E, H, I, N, O, R, S, T) and numerals (e.g., 0 to 9). A novel electroencephalogram (EEG) dataset was created by measuring the brain activity of 30 people while they imagined these alphabets and digits. As part of signal preprocessing, EEG signals are filtered before extracting delta, theta, alpha, and beta band power features. These features are used as input for classification using support vector machines, k-nearest neighbors, and random forest (RF) classifiers. It is identified that the RF classifier outperformed the others in terms of classification accuracy. Classification accuracies of 99.38% and 95.39% were achieved at the coarse-level and fine-level, respectively with the RF classifier. From our study, it is also revealed that the beta frequency band and the frontal lobe of the brain played crucial roles in imagined speech recognition. Furthermore, a comparative analysis against state-of-the-art techniques is conducted to demonstrate the efficacy of our proposed model.

THE ENGLISH ALPHABET AND ABSTRACTISM: THE METAMORPHOSIS OF TEXTS TO SYMBOLS

The 26 letters of the English alphabet are undoubtedly, within the scope of the most recognizable forms globally even some of the non-English speaking communities. The English alphabet has been subjected to varied elements from speaking to writing. The words used in most local parlances are formulated and written by means of the letters of the English alphabet. However, this English alphabet from the design perspective, as this paper intends to unravel, there is so much to be extracted from the letters of the English alphabet, which has not been addressed. Digital applications were used to harness the abstracted design concepts that emanated from this study. Finally, the recurrent issues of concept generation will be given a significant boost as intrinsic findings from this study show that the methodical exploitation of the letters of the English alphabet can be used to generate infinite thematic genre of abstracted art or flourishes worthy of a variety of elucidations.

Development of fuzzy search method for creating an efficient information search system in text data

The object of research is the processes of effective search for information in a set of textual data. The subject of the research is the fuzzy search method, which will allow to effectively solve the problem of searching for information in a set of textual data. The paper considers the process of developing a fuzzy search method, which consists of 9 consecutive steps and is required for a quick search for matches in a large set of text data. Based on this method, it is proposed to create a fuzzy search system that will solve the problem of finding the most relevant documents from a set of such documents. The proposed fuzzy search method combines the advantages of algorithms based on deterministic finite automata and algorithms based on dynamic programming for calculating the Damerau-Levenshtein distance. Such a combination allows to implement the symbol similarity table in an optimal way. As part of the work, an approach for creating a symbol similarity table was proposed and an example of such a table was created for symbols from the English alphabet, which allows to find the degree of similarity between two symbols with constant asymptotics and to convert the current symbol into its basic counterpart. For document filtering, a metric was developed to evaluate the correspondence of text data to a search phrase, which simultaneously takes into account the number of found and not found characters and the number of found and not found words. The Damerau-Levenstein algorithm allows to find the edit distance between two words, taking into account the following types of errors: substitution, addition, deletion, and transposition of characters. The work proposed a modification of this algorithm by using a similarity table to more accurately estimate the editing distance between two words. The developed method makes it possible to create a fuzzy search system that will help find the desired results faster and increase the relevance of the obtained results by sorting them according to the values of the proposed test data similarity metric.

Recognition of sounds by ensembles of proteinoids

Proteinoids are artificial polymers that imitate certain characteristics of natural proteins, including self–organization, catalytic activity, and responsiveness to external stimuli. This paper examines the acoustic response properties of proteinoids microspheres when exposed to auditory stimuli. We convert sounds of English alphabet into waveforms of electrical potential, feed the waveforms into proteinoid solutions and record electrical responses of the proteinoids. We also undertake a detailed comparison of proteinoids’ electrical responses (frequencies, periods, and amplitudes) with original input signals. We found that responses of proteinoids are less regular, lower dominant frequency, wider distribution of proteinoids and less skewed distribution of amplitudes compared with input signals. We found that resonant acoustic excitation of proteinoids generates unique electrical impulse patterns dependent on sound frequency and amplitude. The finding will be used in further designs of organic electronic devices, based on ensembles of proteinoids, for sound processing and speech recognition. Our findings provide the first quantitative investigation into the potential of thermal proteinoid microspheres for bio–inspired sound processing and recognition applications. Using controlled speaker excitation on proteinoid samples, we create reliable markers of productive acoustic response capacities, paving the way for future advancement.

The Kazakh Language Requires Reform of its Writing

The article provides information about modern problems of writing the Kazakh language, the importance of its role and development in the context of mass digitization using artificial intelligence technologies and computational linguistics methods. The incorrectness of the current alphabet of the Kazakh language based on the Cyrillic alphabet is proved in connection with the inclusion of Cyrillic letters in it, denoting phonemes that are not included in its sound structure. The necessity of reforming the Kazakh writing by replacing the incorrect alphabet is substantiated. Errors and contradictions are shown in the approved version of the Kazakh alphabet based on the Latin alphabet, as well as the alphabet proposed as a replacement for the approved one, in which some previous errors are repeated. In both cases, no analysis and clarification of the sound system of the Kazakh language, which is the basis of any alphabet, is carried out. In this study, to clarify the sound system of the Kazakh language, experiments were carried out to determine the articulation and acoustic features of Kazakh sounds with the help the computer programs used for many natural languages. In the articulation analysis, special attention was paid to vowels, which give rise to various contradictions in the Kazakh letter. It is proposed to use a new classification of vowels according to four binary features, rather than the traditional classification according to three binary features. Acoustic analysis uses the method of formant analysis, which is aimed at identifying certain formants in the spectrogram. The formant is obtained using a spectrograph. Quantitatively, the formants correspond to the maxima in the speech spectrum and usually appear on spectrograms as horizontal bands. After determining the composition and classification of the sound system of the Kazakh language, two variants of the alphabet based on the Latin alphabet are proposed: the first one is based on the Turkish alphabet using diacritical marks; the second is based on the English alphabet using digraphs. The second option offers ways to solve problems that arise when using digraphs. In conclusion, information is provided on the ongoing and ongoing work in Kazakhstan related to the creation of smart systems in the Kazakh language based on the methods and technologies of artificial intelligence and computational linguistics, the results of which are reflected in the list of sources.

Definition and Automatic Extraction Performance Analysis of Stroke Elements in the English Alphabet

Definition and Automatic Extraction Performance Analysis of Stroke Elements in the English Alphabet