Letters Of Alphabet Research Articles

Arabic Sign Language Recognition System: Using an Image-Based hand Gesture Detection Method to help Deaf and Dump Children to Engage in Education

Hand gestures help individuals communicate in daily life. Sign languages, however, employ hand motions extensively. People with hearing impairments use sign language. Pattern recognition in computer vision may be used to interpret and translate Arabic Sign Language (ArSL) for deaf and dumb persons using image processing-based software systems. Arab hearing-impaired and deaf persons communicate with Arabic Sign Language Recognition (ArSLR).We propose an image-based ArSLR system employing gesture recognition to enable people with disabilities to engage with the outside world. This work proposes the design and development of an automated Arabic sign language-to-Arabic text translation system. This study extracts stem Arabic words and differentiates related terms. Hand motions capture alphabet letters in the proposed approach. Image isolation occurs after acquisition. Extraction, conclusion, and hand sign pattern characteristics comprise the third step. The fourth phase classifies hand gestures using a powerful classification algorithm. Finally, the sign language letter is interpreted and translated to the Arabic character.

The 2nd method Parfait-Hounsinou used to determine the overall water quality

The 2nd method Parfait-Hounsinou makes it possible to note the physico-chemical quality and the microbiological quality of water by two alphabetical letters representing respectively the Chemical Water Quality Index (CWQI) and the Microbiological Water Quality Index (MWQI). The steps of using this method are the measurement of the physico-chemical and microbiological parameters of the water samples, the calculation of the CWQI and MWQI, the deduction of the overall quality of the water samples and the construction and then the study of the 2nd Parfait-Hounsinou diagram which is 2 particulars diagrams of Spie chart use to show the detailed chemical quality of the water samples. We applied this method to the groundwater of the municipality of Abomey-Calavi in Benin and then we compared this method to the water quality assessment methods that are often the most used. The novelty of the 2nd method Parfait-Hounsinou is that it makes it possible to evaluate the global quality of water in a uniform way all over the world, in particular whatever the influence of temperature on the pH of the water.•The 2nd method Parfait-Hounsinou makes it possible to attribute to a water sample a score which characterizes all its physico-chemical and microbiological parameters.•Researchers, WHO and governments around the world can use the 2nd method Parfait-Hounsinou to monitor changes in the quality of water resources around the world.•The meanings of the scores assigned to water samples using the 2nd method Parfait-Hounsinou are easily understood and useful by journalists and the general public.

Value of Auditory Perception of Alphabet Letters Test (Arabic Standardized Version) in Evaluation of Arabic Speaking Bimodal Children

Value of Auditory Perception of Alphabet Letters Test (Arabic Standardized Version) in Evaluation of Arabic Speaking Bimodal Children

Aplikasi Game Edukasi Mengenal Bahasa Indonesia Alfabert dengan Algoritma Ascent Hill Climbing

Alphabet learning educational game is a game that is very popular with children who are new to Alphabet letters. This game uses the process of exchanging the position of the alphabet according to the correct alphabetical order. The problem in this study is the lack of interest in children learning the alphabet quickly, with the game system children who know the alphabet are happier and quickly understand the order of the alphabet. The benefit of this research is to improve the thinking power and creative patterns of children who are new to the alphabet quickly to catch how to memorize the alphabet correctly. This study uses the Ascent Hill Climbing Algorithm. How the Ascent Hill Climbing Algorithm works, namely a. The basic rule that must be done is to move an empty square to the top of the puzzle where if x>1 then (x-1,y) b. The basic rule that must be done is to move the empty square down Puzzle if x<3 then (x+1,y c. The basic rule to be done is to move the empty square to the right Puzzle if x<3 then (x+1,y) d The basic rule that must be done is to move the empty square to the left of the Puzzle if x>1 then (x,y-1). The final result of this study is that it takes 8 iterations to obtain the correct position for compiling the Puzzle so that it matches the goal state order so that the results are finished and terminated.

Development of Reading Ability in Childhood by the Example of Georgian Language

Reading as a skill is divided into many subskills, which take almost entire early childhood to develop. Children go through stages of getting comprehension of phonemes and grammar structure until they can connect letters to sounds and read without problems. Learning how to read in second language is usually harder because of new sets of phonemes and differences in alphabet. On the other hand, learning how to read Georgian Language might be easier than most other languages. Georgian Language has 33 phonemes and 33 letters of alphabet, which directly correspond to each other. Reading is straightforward due to no differences between what is written and how it should be pronounced. The article will be covering how reading skill develops in children and how these aspects might be connected to learning to read Georgian.

Automatic Placement of Punctuation Marks by Using Neural Networks

The problem of automatically placing punctuation marks in a text divided into sentences is solved. The positions of punctuation marks such as comma, dash, colon, exclamation, and question marks are determined. Two approaches to solving the problem are considered. In the first one, the task is reduced to the classification of n-grams. The class of an n-gram is determined by the type of punctuation marks after its k-th token (n = 5, k = 3). A multilayer perceptron is used as a classifier, the input of which receives vector representations of n-grams formed using the word2vec model. In the second one, a neural network with a transformer architecture that receives an input sequence of tokens (IS) freed from punctuation marks is trained to generate a target sequence of tokens (TS) that allows punctuation marks to be placed in the original sentence. The TS is generated by the IS as a result of replacing tokens associated with punctuation marks with corresponding markers. The IS tokens that are not associated with punctuation marks are transferred to the TS without changes. To reduce the dictionary of tokens, word forms are replaced by lemmas, and text elements containing characters other than letters of the Russian alphabet are replaced by special tokens. In addition, for the same purpose, names, patronymics, surnames, toponyms, and numerals are replaced by special tokens. The classifier of word forms is proposed as a tool that defines parts of speech and named entities. Two types of IS and TS are considered. The IS of the second type is formed by the IS of the first type as a result of adding part of speech designations to the lemmas. TS differ in the way the tokens associated with commas are replaced by the corresponding markers. In TS of the first type, the token and the subsequent comma are replaced by a marker; in the TS of the second type, the token and the preceding comma are replaced by a marker. The effectiveness of the models is estimated by the precision and F1 indicators, which are calculated for each class and then averaged. The value of F1 is equal to 0.77 and 0.86 in the cases of using a classifier and transformer, respectively.

Garrano Horses Perceive Letters of the Alphabet on a Touchscreen System: A Pilot Study.

This study aimed to use a computer-controlled touchscreen system to examine visual discrimination in Garrano horses (Equus caballus), an endangered breed of pony belonging to the Iberian horse family. This pilot study focused on the perceptual similarity among letters of the alphabet. We tested five horses in a one-male unit (OMU) living permanently in a semi-free enclosure near their natural habitat in Serra d'Arga, northern Portugal. Horses were trained to nose-touch black circles that appeared on the screen. Then, they were tested for discrimination of five letters of the Latin alphabet in Arial font, namely O, B, V, Z, and X, using a two-choice discrimination task. The confusion matrix of letter pairs was used to show the MDS and to identify the relative contribution of shape features. The results showed perceptual similarities among letters with curvatures pitted against those of straight lines. Shape perception in horses seems to share features with that of humans and other animals living in different niches. The touchscreen system proved to be an objective and innovative way of studying cognition in the socially organized group of horses. The automated system can promote the welfare of captive horses by maximizing their freedom of movement.

Efficient Representation of Large-Alphabet Probability Distributions

A number of engineering and scientific problems require representing and manipulating probability distributions over large alphabets, which we may think of as long vectors of reals summing to 1. In some cases it is required to represent such a vector with only b bits per entry. A natural choice is to partition the interval 0,1 into 2b uniform bins and quantize entries to each bin independently. We show that a minor modification of this procedure – applying an entrywise non-linear function (compander) f(x) prior to quantization – yields an extremely effective quantization method. For example, for b=8(16) and 105-sized alphabets, the quality of representation improves from a loss (under KL divergence) of 0.5(0.1) bits/entry to 10-4(10-9) bits/entry. Compared to floating point representations, our compander method improves the loss from 10-1(10-6) to 10-4(10-9) bits/entry. These numbers hold for both real-world data (word frequencies in books and DNA k-mer counts) and for synthetic randomly generated distributions. Theoretically, we analyze a minimax optimality criterion and show that the closed-form compander f(x)ArcSinh(cK(KlogK)x) is (asymptotically as b∞) optimal for quantizing probability distributions over a -letter alphabet. Non-asymptotically, such a compander (substituting 1/2 for cfor simplicity) has KL-quantization loss bounded by ≤8∙2-2blog2. Interestingly, a similar minimax criterion for the quadratic loss on the hypercube shows optimality of the standard uniform quantizer. This suggests that the ArcSinh quantizer is as fundamental for KL-distortion as the uniform quantizer for quadratic distortion.

:Sound Writing: Experimental Modernism and the Poetics of Articulation

:<i>Sound Writing: Experimental Modernism and the Poetics of Articulation</i>

Optimal alphabet for single text compression

A text written using symbols from a given alphabet can be compressed using the Huffman code, which minimizes the length of the encoded text. It is necessary, however, to employ a text-specific codebook, i.e. the symbol-codeword dictionary, to decode the original text. Thus, the compression performance should be evaluated by the full code length, i.e. the length of the encoded text plus the length of the codebook. We studied several alphabets for compressing texts – letters, n-grams of letters, syllables, words, and phrases. If only sufficiently short texts are retained, an alphabet of letters or two-grams of letters is optimal. For the majority of Project Gutenberg texts, the best alphabet (the one that minimizes the full code length) is given by syllables or words, depending on the representation of the codebook. Letter 3 and 4-grams, having on average comparable length to syllables/words, perform noticeably worse than syllables or words. Word 2-grams also are never the best alphabet, on the account of having a very large codebook. We also show that the codebook representation is important – switching from a naive representation to a compact one significantly improves the matters for alphabets with large number of symbols, most notably the words.Thus, meaning-expressing elements of the language (syllables or words) provide the best compression alphabet.

Grammic monoids with three generators

Young tableaux are combinatorial objects whose construction can be achieved from words over a finite alphabet by row or column insertion as shown by Schensted sixty years ago. Recently Abram and Reutenauer studied the action of the free monoid on the set of columns defined by the famous insertion algorithm. Since the number of columns is finite, this action yields a finite transformation monoid. Here we consider the action on the set of rows. We investigate the corresponding infinite monoid in the case of a 3 letter alphabet. In particular we show that it is the quotient of the free monoid relative to a congruence generated by the classical Knuth rules plus a unique extra rule.

Deep Learning Based Recognition of Turkish Sign Language Letters with Unique Data Set

With its development, artificial intelligence has formed the basis for many studies aimed at facilitating people's lives. More successful results have been tried to be obtained with the increasing data and developing equipment in these studies. It is seen that these developments in artificial intelligence are reflected in the studies related to sign language conversion. In this study, a data set belonging to the letters in the Turkish Sign Language Alphabet was created, and the classification process was carried out with both the deep learning model we created and VGG16, Inceptionv3, Resnet, and Mobilnet models, which are frequently used in image classification. In addition, an open-source data set containing the letters in the American Sign Language Alphabet was organized similar to the data set containing the letters in the Turkish Sign Language Alphabet we created, and Deep Learning models were used to classify the letters in the American Sign Language Alphabet by using this data set. Performance evaluations of the classifications made by Deep Learning Models using both data sets were made. With this study, the results obtained from training Deep Learning methods with different data sets were compared. In addition, it is thought that the study will be useful in determining both the data set and the deep learning method to be used for the studies on the recognition of Sign Language Letters.

“Literacy is everywhere!”: using digital technology to broaden how parents view the home literacy environment

Parent–child engagement in constrained (e.g., learning alphabet letters or sounds) and unconstrained (e.g., storytelling, defining words) literacy activities are central components of the home literacy environment. Unconstrained activities are particularly important for children’s oral language and support school readiness. Yet, many parents do not recognize that unconstrained activities can promote learning. This study examines whether an immersive tool can help parents recognize the importance of unconstrained activities and how to embed learning into everyday home routines. N = 76 middle- to lower-income parents of three-year-old children were randomly assigned to a control condition or immersive “literacy scavenger hunt” where they self-explored opportunities to engage in unconstrained activities within everyday routines. The scavenger hunt was associated with an increase in parents’ endorsement of unconstrained activities and verbal communication within parent–child interactions. Results are discussed in terms of intervention approaches that build adult capacity around supporting children’s early literacy.

Fast computations on ordered nominal sets

Nominal automata are models for recognising languages over infinite alphabets, based on the algebraic notion of nominal set. Motivated by their use in automata theory, we show how to compute efficiently with nominal sets over the so-called total order symmetry, a variant which allows to compare alphabet letters for equality as well as their respective order. We develop an explicit finite representation of such nominal sets and basic constructions thereon. The approach is implemented as the library Ons (Ordered Nominal Sets), enabling programming with infinite sets. Returning to our motivation of nominal automata, we evaluate Ons in two applications: minimisation of automata and active automata learning. In both cases, Ons is competitive compared to existing implementations and outperforms them for certain classes of inputs.

Finger Motion Capture for Sign Language Interpretation

Abstract: Sign language is one of the oldest and most natural form of language and for the deaf and the mute, it is the most convenient form of communication. Though it is a convenient language, many people find it difficult to interpret. Therefore, there is a need of a solution which will make sign language interpretation easy for every common man. This paper presents a novel approach using web camera to capture the person’s sign gestures. These sign gestures for American Sign Language are created and translated into corresponding text in real time. A Convolutional Neural Network model is developed for Finger Motion based American Sign Language. The proposed model has 99.3% accuracy for the 26 letters of the English alphabet. The model interprets Sign Language indications into English sentences

Implementation of Gabor Wavelet and Support Vector Machine for Braille Recognition

Visually impaired people use braille letters to write and read, which not all people with normal vision can read. It causes parents of children with impaired vision to have difficulties in assisting them in learning at home. At the same time, the involvement of parents in children's learning assistance is needed to monitor their learning progress. In this research, braille letters are identified through images taken using a scanner as a tool to input the images. Then, the Canny edge detection method is used obtain all the edges of each braille dot. Feature extraction is applied to obtain all characteristics of each letter, and the method used is the Gabor Wavelet. The features which are utilized include standard deviation, mean, variance, and median with a theta angle of 00, 300, 450, 600, 1200, 1350, 1800 and wavelengths of 3, 6, 13, 28, and 58. These features are combined and used as test data and training data for the Support Vector Machine (SVM) classification stage and produce letters and words in alphabetic letter forms. Braille letters that can be identified in this research are small letters, capital letters, punctuation marks, and numbers. Tests are carried out using a multi-class confusion matrix scenario to determine the level of accuracy, precision, and recall. Based on the results of the tests conducted using 758 braille letters, the accuracy value is 98.15%; the precision value is 97.66%; and the recall value is 98.28%.

EFFORTS IN 1ST GRADE OF MADRASAH IBTIDAIYAH NURUL IKHSAN PILANGSARI TO INCREASE THE ABILITY TO RECOGNIZE LETTERS THROUGH KARSUN (ARRANGEMENT-BASED CARTOON)

This research is based on the many types of student writing errors and the inability to distinguish letters in 1st grade at Madrasah Ibtidaiyah Nurul Ikhsan in Baleraja Village, Pilangsari Kasun. The purpose of this research was to improve children's ability to recognize letters of the alphabet by employing the use of media. This study is a Classroom Action Research (CAR) involving 13 students from Madrasah Ibtaaiyah Nurul Ikhsan, Class I. This study's instrument is an observation guide, and its technique is a descriptive quantitative approach. Using the KARSUN (arrangement-based cartoon) medium appears to improve the capacity to recognize alphabetic letters, as demonstrated by the study's findings. The results of the observation activity (pre-cycle) yielded a percentage of 7.7%, the results of the first cycle (pretest) yielded a percentage of 23.1%, and the results of the second cycle (posttest) yielded a larger percentage that met the criteria for developing as expected and exceedingly well, namely 53.8%. The ability of grade I (one) students of Madrasah Ibtaiyah Nurul Ikhsan to recognize the letters of the alphabet can thus be enhanced by employing KARSUN (arrangement-based cartoon) media.

Effectiveness of Strategies Used in Developing Accuracy and Coherence in Writing among Public Primary School Pupils in Namtumbo District, Tanzania

This study qualitatively explored the effectiveness of the strategies used by teachers in developing writing accuracy and coherence among public primary school pupils in Nantumbo District, Tanzania. It used the case study design involving the population of 736 purposefully sampled individuals including 16 teachers and 720 pupils from eight (8) schools in Namtumbo District Council. The study used classroom observation, focus group discussion, classroom continuous assessment and documentary review in data collection. Content analysis was adopted to analyses data and the findings revealed that teachers used various strategies in teaching how to write alphabetical letters including scaffolding, brief explicit lessons, alphabetic order, songs and teaching aids. It was further found out that some of these strategies such as using a talk-chalkboard strategy to teach punctuation marks were not effective to scaffold pupils and make them master writing. The study recommends teachers to use interactive strategies to enhance students’ acquisition of the writing skills.

The role of processing efficiency and selection history in the limit of visual awareness in shape perception

A growing body of research indicates that the limit in instant conscious awareness, or the unit of access, for some object features such as color, orientation, and direction of motion is more than one. In four experiments we explored the roles of processing efficiency and selection history in shape perception. Two targets, which were geometric shapes (less efficient) or alphabet letters (more efficient), were shown simultaneously or sequentially. The task was to judge whether a test probe matched one of the targets. In different experiments, the two types of trials were presented in separate blocks, interleaved couplets, or randomly within the same block during testing but regrouped in data analyses such that the same type of trials was either repeated or not repeated. Accuracy was higher in the sequential than simultaneous trials for geometric shapes, but not for upright letters, when the same trial type was blocked or in the repeated condition. These results suggest that processing efficiency and selection history both play a role in the unit of access in shape perception. They also underscore the flexibility of the visual system, which uses different factors to maximize conscious visual perception at a given time.

Penggunaan Media Adiktif (Animasi Media Interkatif) Untuk Pengenalan Huruf Abjad Pada Anak Usia Dini

The purpose of this study is to create new innovations to develop learning media for children so as to make children motivated and attract children's interest in learning the introduction of letters of the alphabet. This ADDICTIVE media was created through the Power Point Application. ADDICTIVE media is equipped with a display of alphabet letters that vary in color, there are animated images to attract children's interest, and is equipped with voice messages if children are still confused about the letters of the alphabet. This ADDICTIVE media was created to introduce the letters of the alphabet to early children and introduce children to technology.This study uses a development research model with Borg and Gall theory as a reference.The process of stages in this research, the researcher simplifies and restricts into three stages, namely: data collection, product design and design validation. The results of the calculation of the validation assessment of the acquisition of a value of more than 0.50 means that the value of valid requirements and product feasibility is obtained, then the product made by the researcher can be categorized as valid (feasible) and the acquisition of a value of less than 0.50 can be categorized as invalid (not feasible). Suggestions for further research is that the results of this research can be used as research references and to be taken into consideration to further deepen further research that is more interesting for early childhood.