Search results for: machine language

Authors: Gal Belsitzman, Rose Stamp, Atay Citron, Wendy Sandler

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Sign languages are considered endangered. The vitality of sign languages is compromised by its unique sociolinguistic situation, in which hearing parents that give birth to deaf children usually decide to cochlear implant their child. Therefore, these children don’t acquire their natural language – Sign Language. Despite this, many sign languages, such as Israeli Sign Language (ISL) are thriving. The continued survival of similar languages under threat has been associated with the remarkable resilience of the language community. In particular, deaf literary traditions are central in reminding the community of the importance of the language. One example of a deaf literary tradition which has received increased popularity in recent years is deaf theatre. The Ebisu Sign Language Theatre Laboratory, developed as part of the multidisciplinary Grammar of the Body Research Project, is the first deaf theatre company in Israel. Ebisu Theatre combines physical theatre and sign language research, to allow for a natural laboratory to analyze the creative use of the body. In this presentation, we focus on the recent theatre production called ‘Their language’ which tells of the struggle faced by the deaf community to use their own natural language in the education system. A thorough analysis unravels how linguistic properties are integrated with the use of poetic devices and physical theatre techniques in this performance, enabling wider access by both deaf and hearing audiences, without interpretation. Interviews with the audience illustrate the significance of this art form which serves a dual purpose, both as empowering for the deaf community and educational for the hearing and deaf audiences, by raising awareness of community-related issues.

Keywords: deaf theatre, empowerment, language revitalization, sign language

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Authors: Y. Bablu Singh, B. S. Purkayashtha, Chungkham Yashawanta Singh

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Morphological analysis forms the basic foundation in NLP applications including syntax parsing Machine Translation (MT), Information Retrieval (IR) and automatic indexing in all languages. It is the field of the linguistics; it can provide valuable information for computer based linguistics task such as lemmatization and studies of internal structure of the words. Computational Morphology is the application of morphological rules in the field of computational linguistics, and it is the emerging area in AI, which studies the structure of words, which are formed by combining smaller units of linguistics information, called morphemes: the building blocks of words. Morphological analysis provides about semantic and syntactic role in a sentence. It analyzes the Manipuri word forms and produces several grammatical information associated with the words. The Morphological Analyzer for Manipuri has been tested on 3500 Manipuri words in Shakti Standard format (SSF) using Meitei Mayek as source; thereby an accuracy of 80% has been obtained on a manual check.

Keywords: morphological analysis, machine translation, computational morphology, information retrieval, SSF

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Authors: May George

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Inference plays an important role in the learning process and it can lead to a rapid acquisition of a second language. When learning a non-native language, i.e., a critical language like Arabic, the students depend on the teacher’s support most of the time to learn new concepts. The students focus on memorizing the new vocabulary and stress on learning all the grammatical rules. Hence, the students became mechanical and cannot produce the language easily. As a result, they are unable to predict the meaning of words in the context by relying heavily on the teacher, in that they cannot link their prior knowledge or even identify the meaning of the words without the support of the teacher. This study explores how the teacher guides students learning during the inference process and what are the processes of learning that can direct student’s inference.

Keywords: inference, reading, Arabic, language acquisition

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Authors: Ricardo Pinto Mario Covele, Patricio V. Langa, Patrick Swanzy

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The English language has been recognized as a universal medium of instruction in academia, especially in Higher Education Institutions (HEIs) hence exerting enormous influence within the context of research and publication. By extension, the English Language has been embraced by scholars from non-English speaking countries. The purpose of this review was to synthesize the discussions using four databases. Discussion in the English language in the career development of academics, particularly in non-English speaking universities, is largely less visible. This paper seeks to fill this gap and to improve the visibility of the English language in the career development of academics focusing on non-English language speaking universities by undertaking a systematic literature review. More specifically, the paper addresses the language policy, English language learning model as a second language, sociolinguistic field and career development, methods, as well as its main findings. This review analyzed 75 relevant resources sourced from Western Cape’s Library, Scopus, Google scholar, and web of science databases from November 2020 to July 2021 using the PQRS framework as an analytical lens. The paper’s findings demonstrate that, while higher education continues to be under-challenges of English language usage, literature targeting non-English speaking universities remains less discussed than it is often described. The findings also demonstrate the dominance of English language policy, both for knowledge production and dissemination of literature challenging emerging scholars from non-English speaking HEIs. Hence, the paper argues for the need to reconsider the context of non-English language speakers in the English language in the career development of academics’ research, both as empirical fields and as emerging knowledge producers. More importantly, the study reveals two bodies of literature: (1) the instrumentalist approach to English Language learning and (2) Intercultural approach to the English Language for career opportunities, classified as the appropriate to explain the English language learning process and how is it perceived towards scholars’ academic careers in HEIs.

Keywords: English language, public and private universities, language policy, career development, non-English speaking countries

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Authors: Ng Liang Shen, Hau Yuan Wen

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Arrhythmia analysis of ECG signal plays a major role in diagnosing most of the cardiac diseases. Therefore, a single arrhythmia detection of an electrocardiographic (ECG) record can determine multiple pattern of various algorithms and match accordingly each ECG beats based on Machine Learning supervised learning. These researchers used different features and classification methods to classify different arrhythmia types. A major problem in these studies is the fact that the symptoms of the disease do not show all the time in the ECG record. Hence, a successful diagnosis might require the manual investigation of several hours of ECG records. The point of this paper presents investigations cardiovascular ailment in Electrocardiogram (ECG) Signals for Cardiac Arrhythmia utilizing examination of ECG irregular wave frames via heart beat as correspond arrhythmia which with Machine Learning Pattern Recognition.

Keywords: electrocardiogram, ECG, classification, machine learning, pattern recognition, detection, QRS

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Authors: Sinan Serkan Çağlı

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This study explores the effectiveness of incorporating storytelling tasks into language acquisition programs for young learners. The research investigates how storytelling, as a pedagogical tool, can contribute to the enhancement of language acquisition skills in children. Drawing upon relevant literature and empirical data, this article examines the impact of storytelling on vocabulary development, comprehension, and overall language proficiency in early childhood education in Turkey. The study adopts a qualitative approach, including classroom observations and interviews with teachers and students. Findings suggest that storytelling tasks not only foster linguistic competence but also stimulate cognitive and socio-emotional development in young learners. Additionally, the article explores various storytelling techniques and strategies suitable for different age groups. It is evident that integrating storytelling tasks into language learning environments can create engaging and effective opportunities for young learners to acquire language skills in a natural and enjoyable way. This research contributes valuable insights into the pedagogical practices that promote language acquisition in early childhood, emphasizing the significance of storytelling as a powerful educational tool, especially in Turkey for EFL students.

Keywords: storytelling, language acquisition, young learners, early childhood education, pedagogy, language proficiency

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Authors: Barbara Peric

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The study of acquiring a third and additional language has garnered significant focus within second language acquisition (SLA) research. Initially, it was commonly viewed as merely an extension of second language acquisition (SLA). However, in the last two decades, numerous researchers have emphasized the need to recognize the unique characteristics of third language acquisition (TLA). This recognition is crucial for understanding the intricate cognitive processes that arise from the interaction of more than two linguistic systems in the learner's mind. This study investigates cross-linguistic influences in the acquisition of Spanish as a fourth language by students who have Croatian as a first language (L1). English as a second language (L2), and Italian as a third language (L3). Observational data suggests that influence or transfer of linguistic elements can arise not only from one's native language (L1) but also from non-native languages. This implies that, for individuals proficient in multiple languages, the native language doesn't consistently hold a superior position. Instead, it should be examined alongside other potential sources of linguistic transfer. Earlier studies have demonstrated that high proficiency in a second language can significantly impact cross-linguistic influences when acquiring a third and additional language. Among the extensively examined factors, the typological relationship stands out as one of the most scrutinized variables. The goal of the present study was to explore whether language typology and formal similarity or proficiency in the second language had a more significant impact on L4 acquisition. Participants in this study were third-year undergraduate students at Rochester Institute of Technology’s subsidiary in Croatia (RIT Croatia). All the participants had exclusively Croatian as L1, English as L2, Italian as L3 and were learning Spanish as L4 at the time of the study. All the participants had a high level of proficiency in English and low level of proficiency in Italian. Based on the error analysis the findings indicate that for some types of lexical errors such as coinage, language typology had a more significant impact and Italian language was the preferred source of transfer despite the law proficiency in that language. For some other types of lexical errors, such as calques, second language proficiency had a more significant impact, and English language was the preferred source of transfer. On the other hand, Croatian, Italian, and Spanish are more similar in the area of morphology due to higher degree of inflection compared to English and the strongest influence of the Croatian language was precisely in the area of morphology. The results emphasize the need to consider linguistic resemblances between the native language (L1) and the third and additional language as well as the learners' proficiency in the second language when developing successful teaching strategies for acquiring the third and additional language. These conclusions add to the expanding knowledge in the realm of Second Language Acquisition (SLA) and offer practical insights for language educators aiming to enhance the effectiveness of learning experiences in acquiring a third and additional language.

Keywords: third and additional language acquisition, cross-linguistic influences, language proficiency, language typology

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Authors: Mohsen Maraoui

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In the aim of natural language processing applications improvement, such as information retrieval, machine translation, lexical disambiguation, we focus on statistical approach to semantic indexing for multilingual text documents based on conceptual network formalism. We propose to use this formalism as an indexing language to represent the descriptive concepts and their weighting. These concepts represent the content of the document. Our contribution is based on two steps. In the first step, we propose the extraction of index terms using the multilingual lexical resource Euro WordNet (EWN). In the second step, we pass from the representation of index terms to the representation of index concepts through conceptual network formalism. This network is generated using the EWN resource and pass by a classification step based on association rules model (in attempt to discover the non-taxonomic relations or contextual relations between the concepts of a document). These relations are latent relations buried in the text and carried by the semantic context of the co-occurrence of concepts in the document. Our proposed indexing approach can be applied to text documents in various languages because it is based on a linguistic method adapted to the language through a multilingual thesaurus. Next, we apply the same statistical process regardless of the language in order to extract the significant concepts and their associated weights. We prove that the proposed indexing approach provides encouraging results.

Keywords: concept extraction, conceptual network formalism, fuzzy association rules, multilingual thesaurus, semantic indexing

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Authors: Salahaeddine Sbai

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Air quality analysis using machine learning models is a method employed to assess and predict air pollution levels. This approach leverages the capabilities of machine learning algorithms to analyze vast amounts of air quality data and extract valuable insights. By training these models on historical air quality data, they can learn patterns and relationships between various factors such as weather conditions, pollutant emissions, and geographical features. The trained models can then be used to predict air quality levels in real-time or forecast future pollution levels. This application of machine learning in air quality analysis enables policymakers, environmental agencies, and the general public to make informed decisions regarding health, environmental impact, and mitigation strategies. By understanding the factors influencing air quality, interventions can be implemented to reduce pollution levels, mitigate health risks, and enhance overall air quality management. Climate change is having significant impacts on Morocco, affecting various aspects of the country's environment, economy, and society. In this study, we use some machine learning models under python environment to predict and analysis air quality change over North of Morocco to evaluate the climate change impact on agriculture.

Keywords: air quality, machine learning models, pollution, pollutant emissions

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Authors: Dorit Lemberger

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Wittgenstein directly used the term "metaphor" only infrequently and with reservations, but his writings include a number of metaphors that have become imprinted in the philosophical memory of Western thought. For example, the ladder in his book Tractatus, or in Philosophical investigations - the ancient city, the beetle in a box, the fly in the fly-bottle, and the duck-rabbit. In light of Wittgenstein's stressing, throughout his investigations, that the only language that exists is ordinary language, and that there is no "second-order" language, the question should be asked: How do these metaphors function, specifically, and in general, how are we to relate to language use that exceeds the normal? Wittgenstein did not disregard such phenomena, but he proposed viewing them in a different way, that would enable understanding them as uses in ordinary language, without necessarily exceeding such language. Two important terms that he coined in this context are "secondary sense" and "experience of meaning". Each denotes language use as reflective of a subjective element characteristic of the speaker, such as intent, experience, or emphasis of a certain aspect. More recent Wittgenstein scholars added the term "quasi-metaphor", that refers to his discussion of the possibility of aesthetic judgment. This paper will examine how, according to Wittgenstein, these terms function without exceeding ordinary language, and will illustrate how they can be applied, in an analysis of the poem "Butterfly" by Nelly Sachs.

Keywords: metaphor, quasi-metaphor, secondary sense, experience of meaning

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Authors: J. Lück, S. Rudman

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Language has long been a site of struggle in South Africa with an educational language policy that favoured English and Afrikaans as high status languages and positioned other language users in deficit ways. Furthermore, a segregationist past led to individuals viewing each other as racial beings and racial categorisations still prevail in private and public life. It has been argued that it is important to explore how South African youth identities are being constructed, if past discourses still shape their identities or if they are negotiating new ways of being. The paper probes the role of language, discourse and embedded ideologies in the persistence or not of youth linguistic identities and discourses, the implications for their lived realities and for their construction of other language users and the possibilities of shifts occurring with an awareness of such discourses. It finds that past discourses continue to shape youth identities and are surging in the light of what is happening in the country today.

Keywords: discourse, ideologies, language, linguistic identities

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Authors: Syed Romat Ali Shah, Bilal Shoaib, Saleem Akhtar, Munib Ahmad, Shahan Sadiqui

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Classification is a data mining technique, which is recognizedon Machine Learning (ML) algorithm. It is used to classifythe individual articlein a knownofinformation into a set of predefinemodules or group. Web mining is also a portion of that sympathetic of data mining methods. The main purpose of this paper to analysis and compare the performance of Naïve Bayse Algorithm, Decision Tree, K-Nearest Neighbor (KNN), Artificial Neural Network (ANN)and Support Vector Machine (SVM). This paper consists of different ML algorithm and their advantages and disadvantages and also define research issues.

Keywords: Data Mining, Web Mining, classification, ML Algorithms

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Authors: Huseyin Demir

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Foreign language learners are able to make mistakes in their pronunciation and writing when they encounter with alphabetical indications that are not available in their own language. The fifth-grade students who learn Turkish language at Demirel College in Georgia constitute the concrete example. ‘F’, ‘y’, ‘ö’, ‘ü’ letters in the Turkish alphabet are the most common mistakes they make. After a careful comparative linguistic study, it was found out that the mistakes caused by the fact that these signs were not available in Georgian. These problems have been tried to be solved through comparative language teaching method by using the pronunciation possibilities in other languages, which are spoken or known by students. First of all, other languages known by students are identified, the similar pronunciation difficulties in Turkish are also found in those languages in order to minimize the pronunciation problem in Turkish, pronunciation possibilities are that are available in those language are utilized. In this context, visual animations are made for pronunciation of English words such as year (yr), earn (örn), fair (fêir) and made student familiar with pronunciation with these words through repetition. With this study, it is observed that student’s motivation has been increased and with these indications, student’s mistakes are minimized.

Keywords: pronunciation, Demirel college, motivations, Turkish as a foreign language

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Authors: S. B. Rathna Kumar, Sale Kranthi, Sandya K. Varudhini

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The precise perception of spoken language is influenced by several variables, including the listeners’ native language, distance between speaker and listener, reverberation and background noise. When noise is present in an acoustic environment, it masks the speech signal resulting in reduction in the redundancy of the acoustic and linguistic cues of speech. There is strong evidence that bilinguals face difficulty in speech perception for their second language compared with monolingual speakers under adverse listening conditions such as presence of background noise. This difficulty persists even for speakers who are highly proficient in their second language and is greater in those who have learned the second language later in life. The present study aimed to assess the performance of monolingual (Telugu speaking) and bilingual (Tamil as first language and Telugu as second language) speakers on Telugu speech perception task under quiet and noisy environments. The results indicated that both the groups performed similar in both quiet and noisy environments. The findings of the present study are not in accordance with the findings of previous studies which strongly report poorer speech perception in adverse listening conditions such as noise with bilingual speakers for their second language compared with monolinguals.

Keywords: monolingual, bilingual, second language, speech perception, quiet, noise

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Authors: Medjadj Tarek, Ghribi Hayet

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This study aims to develop a flood sensitivity assessment tool using machine learning (ML) techniques and geographic information system (GIS). The importance of this study is integrating the geographic information systems (GIS) and machine learning (ML) techniques for mapping flood risks, which help decision-makers to identify the most vulnerable areas and take the necessary precautions to face this type of natural disaster. To reach this goal, we will study the case of the city of M'sila, which is among the areas most vulnerable to floods. This study drew a map of flood-prone areas based on the methodology where we have made a comparison between 3 machine learning algorithms: the xGboost model, the Random Forest algorithm and the K Nearest Neighbour algorithm. Each of them gave an accuracy respectively of 97.92 - 95 - 93.75. In the process of mapping flood-prone areas, the first model was relied upon, which gave the greatest accuracy (xGboost).

Keywords: Geographic information systems (GIS), machine learning (ML), emergency mapping, flood disaster management

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Authors: Vincenzo Capalbo, Gianpaolo Ghiani, Emanuele Manni

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Global e-commerce sales have reached unprecedented levels in the past few years. As this trend is only predicted to go up as we continue into the ’20s, new challenges will be faced by companies when planning and controlling e-commerce logistics. In this paper, we survey the related literature on Optimization and Machine Learning as well as on combined methodologies. We also identify the distinctive features of next-generation planning algorithms - namely scalability, model-and-run features and learning capabilities - that will be fundamental to cope with the scale and complexity of logistics in the next decade.

Keywords: e-commerce, hardware acceleration, logistics, machine learning, mixed integer programming, optimization

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Authors: Yasamiyan Alolaywi

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The sources of second language acquisition vary and depend on a learner’s preferences and choices; however, undoubtedly, the most effective methods provide authentic language input. This current study explores the effectiveness of watching movies as a means of English language acquisition. It explores university students’ views on the impact of this method in improving English language skills. The participants in this study were 74 students (25 males and 49 females) from the Department of English Language and Translation at Qassim University, Saudi Arabia. Data for this research were collected from questionnaires and individual interviews with several selected students. The findings of this study showed that many students watch movies frequently and for various purposes, the most important of which is entertainment. The students also admitted that movies help them acquire a great deal of vocabulary and develop their listening and writing skills. Also, the participants believed that exposure to a target language by native speakers helps enhance language fluency and proficiency. The students learn not only linguistic aspects from films but also other aspects, such as culture, lifestyle, and ways of thinking, in addition to learning other languages such as Spanish. In light of these results, some recommendations are proposed, such as verifying the feasibility of integrating media into a foreign language classroom. While this study covers aspects of the relationship between watching movies and English language acquisition, knowledge gaps remain that need to be filled by further research, such as on incorporating media into the educational process and how movie subtitles can improve learners’ language skills.

Keywords: language acquisition, English movies, EFL learners, perceptions

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Authors: Ioannis P. Panapakidis, Marios N. Moschakis

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The Greek Energy Market is structured as a mandatory pool where the producers make their bid offers in day-ahead basis. The System Operator solves an optimization routine aiming at the minimization of the cost of produced electricity. The solution of the optimization problem leads to the calculation of the System Marginal Price (SMP). Accurate forecasts of the SMP can lead to increased profits and more efficient portfolio management from the producer`s perspective. Aim of this study is to provide a comparative analysis of various machine learning models such as artificial neural networks and neuro-fuzzy models for the prediction of the SMP of the Greek market. Machine learning algorithms are favored in predictions problems since they can capture and simulate the volatilities of complex time series.

Keywords: deregulated energy market, forecasting, machine learning, system marginal price

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Authors: Aldan A. Sapargaliyev, Yerbol A. Sapargaliyev

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Since the invention, the electric machine (EM) can be defined as oEM – one-vector electric machine, as it works due to one-vector inductive coupling with use of one-vector electromagnet. The disadvantages of oEM are large size and limited efficiency at low and medium power applications. This paper describes multi-vector electric machine (mEM) based on multi-vector inductive coupling, which is characterized by the increased surface area of ​​the inductive coupling per EM volume, with a reduced share of inefficient and energy-consuming part of the winding, in comparison with oEM’s. Particularly, it is considered, calculated and compared the performance of three different electrical motors and their power at the same volumes and rotor frequencies. It is also presented the result of calculation of correlation between power density and volume for oEM and mEM. The method of multi-vector inductive coupling enables mEM to possess 1.5-4.0 greater density of power per volume and significantly higher efficiency, in comparison with today’s oEM, especially in low and medium power applications. mEM has distinct advantages, when used in transport vehicles such as electric cars and aircrafts.

Keywords: electric machine, electric motor, electromagnet, efficiency of electric motor

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Authors: Rodrigo S. Fonseca, Antônio C. P. Veiga

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Aiming at helping people with some movement limitation that makes typing and communication difficult, there is a need to customize an assistive tool with a learning environment that helps the user in order to optimize text input, identifying the error and providing the correction and possibilities of choice in the Portuguese language. The work presents an Orthographic and Grammatical System that can be incorporated into writing environments, improving and facilitating the use of an alphanumeric keyboard, using a prototype built using a genetic algorithm in addition to carrying out the prediction, which can occur based on the quantity and position of the inserted letters and even placement in the sentence, ensuring the sequence of ideas using a Long Short Term Memory (LSTM) neural network. The prototype optimizes data entry, being a component of assistive technology for the textual formulation, detecting errors, seeking solutions and informing the user of accurate predictions quickly and effectively through machine learning.

Keywords: genetic algorithm, neural networks, word prediction, machine learning

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Authors: Zhou Hong, Gu Xiao-Qing, Lıu Hong-Jiao, Leng Jing

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Seamless learning is becoming a research hotspot in recent years, and the emerging of micro-lectures, flipped classroom has strengthened the development of seamless learning. Based on the characteristics of the seamless learning across time and space and the course structure of the flipped classroom, and the theories of language learning, we put forward the language learning model which can support ‘seamless flipped’ environment (abbreviated as ‘S-F’). Meanwhile, the characteristics of the ‘S-F’ learning environment, the corresponding framework construction and the activity design of diversified corpora were introduced. Moreover, a language learning app named ‘Daily Speaking’ was developed to facilitate the practice of the language learning model in ‘S-F’ environment. In virtue of the learning case of Shanghai language, the rationality and feasibility of this framework were examined, expecting to provide a reference for the design of ‘S-F’ learning in different situations.

Keywords: seamless learning, flipped classroom, seamless-flipped environment, language learning model

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Authors: Anita Puspawati

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A failure in obtaining informed consent from patient occurs because there is not effective communication skill in doctors. Therefore, the language is very important in communication between doctor and patient. This study uses descriptive analysis method, that is a method used mainly in researching the status of a group of people, an object, a condition, a system of thought or a class of events in the present. The result of this study indicates that the communicative language between doctors and patients will increase the trust of patients to their doctors and accordingşy, patients will provide the informed consent voluntarily.

Keywords: communicative, language, doctor, patient

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Authors: Qi Wang

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Accurate pronunciation is the first condition of communication. Compared with the alphabetic languages, Chinese is more difficult for the foreigners to study as a second language, due to the tonal language with the meaningful characters as the written system, especially speaking. This research first presents the statistics of the typical errors of the pronunciations, based on the data of our two- year program of graduate students, which shown 90% of their speaking with strong foreign accents and no obvious change of the pitches, even if they could speak Chinese fluently. Second part, analyzed the caused reasons in the learning and teaching processes. Third part, this result of this research, based the theory of Chinese prosodic words, shown that the earlier the students get trained on prosodics at the beginning and suprasegmentals at intermediate and advanced levels, the better effects for them to communicate in Chinese as a second language.

Keywords: second language, prosodic word, foot, suprasegmental

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Authors: Nitin Shravan, Sudarsun Santhiappan, B. Sivaselvan

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Subsection identification, in the context of Electronic Health Records (EHRs), is identifying the important sections for down-stream tasks like auto-coding. In this work, we classify the text present in EHRs according to their information, using machine learning and deep learning techniques. We initially describe briefly about the problem and formulate it as a text classification problem. Then, we discuss upon the methods from the literature. We try two approaches - traditional feature extraction based machine learning methods and deep learning methods. Through experiments on a private dataset, we establish that the deep learning methods perform better than the feature extraction based Machine Learning Models.

Keywords: deep learning, machine learning, semantic clinical classification, subsection identification, text classification

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Authors: Simon Espigolé, Igor Shalyminov, Helen Hastie

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Deep machine learning techniques including deep neural networks (DNN) have been used to model language and dialogue for conversational agents to perform tasks, such as giving technical support and also for general chit-chat. They have been shown to be capable of generating long, diverse and coherent sentences in end-to-end dialogue systems and natural language generation. However, these systems tend to imitate the training data and will only generate the concepts and language within the scope of what they have been trained on. This work explores how deep neural networks can be used in a task that would normally require human creativity, whereby the human would read the movie description and/or watch the movie and come up with a compelling, interesting movie title. This task differs from simple summarization in that the movie title may not necessarily be derivable from the content or semantics of the movie description. Here, we train a type of DNN called a sequence-to-sequence model (seq2seq) that takes as input a short textual movie description and some information on e.g. genre of the movie. It then learns to output a movie title. The idea is that the DNN will learn certain techniques and approaches that the human movie titler may deploy that may not be immediately obvious to the human-eye. To give an example of a generated movie title, for the movie synopsis: ‘A hitman concludes his legacy with one more job, only to discover he may be the one getting hit.’; the original, true title is ‘The Driver’ and the one generated by the model is ‘The Masquerade’. A human evaluation was conducted where the DNN output was compared to the true human-generated title, as well as a number of baselines, on three 5-point Likert scales: ‘creativity’, ‘naturalness’ and ‘suitability’. Subjects were also asked which of the two systems they preferred. The scores of the DNN model were comparable to the scores of the human-generated movie title, with means m=3.11, m=3.12, respectively. There is room for improvement in these models as they were rated significantly less ‘natural’ and ‘suitable’ when compared to the human title. In addition, the human-generated title was preferred overall 58% of the time when pitted against the DNN model. These results, however, are encouraging given the comparison with a highly-considered, well-crafted human-generated movie title. Movie titles go through a rigorous process of assessment by experts and focus groups, who have watched the movie. This process is in place due to the large amount of money at stake and the importance of creating an effective title that captures the audiences’ attention. Our work shows progress towards automating this process, which in turn may lead to a better understanding of creativity itself.

Keywords: creativity, deep machine learning, natural language generation, movies

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Authors: Halima Musa Kamilu

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This paper discusses the effective strategies for teaching English language to learners in primary schools in Nigeria. English language development is the systematic use of instructional strategies designed to promote the acquisition of English by pupils in primary schools whose primary language is not English. Learning a second language is through total immersion. These strategies support this learning method, allowing pupils to have the knowledge of English language in a pattern similar to the way they learned their native language through regular interaction with others who already know the language. The focus is on fluency and learning to speak English in a social context with native speakers. The strategies allow for effective acquisition. The paper also looked into the following areas: visuals that reinforce spoken or written words, employ gestures for added emphasis, adjusting of speech, stressing of high-frequency vocabulary words, use of fewer idioms and clarifying the meaning of words or phrases in context, stressing of participatory learning and maintaining a low anxiety level and boosting of enthusiasm. It recommended that the teacher include vocabulary words that will make the content more comprehensible to the learner.

Keywords: effective, strategies, teaching, beginners and primary schools

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Authors: Bingchun Liu, Pei-Chann Chang, Natasha Huang, Dun Li

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Machine Learning and Data Mining are the two important tools for extracting useful information and knowledge from large datasets. In machine learning, classification is a wildly used technique to predict qualitative variables and is generally preferred over regression from an operational point of view. Due to the enormous increase in air pollution in various countries especially China, Air Quality Classification has become one of the most important topics in air quality research and modelling. This study aims at introducing a hybrid classification model based on information theory and Support Vector Machine (SVM) using the air quality data of four cities in China namely Beijing, Guangzhou, Shanghai and Tianjin from Jan 1, 2014 to April 30, 2016. China's Ministry of Environmental Protection has classified the daily air quality into 6 levels namely Serious Pollution, Severe Pollution, Moderate Pollution, Light Pollution, Good and Excellent based on their respective Air Quality Index (AQI) values. Using the information theory, information gain (IG) is calculated and feature selection is done for both categorical features and continuous numeric features. Then SVM Machine Learning algorithm is implemented on the selected features with cross-validation. The final evaluation reveals that the IG and SVM hybrid model performs better than SVM (alone), Artificial Neural Network (ANN) and K-Nearest Neighbours (KNN) models in terms of accuracy as well as complexity.

Keywords: machine learning, air quality classification, air quality index, information gain, support vector machine, cross-validation

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Authors: A. Şahinoğlu, R. Gürbüz, A. Güllü, M. Karhan

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This study in production machines, it is aimed that machine will automatically perceive cutting data and alter cutting parameters. The two most important parameters have to be checked in machine control unit are progress feed rate and speeds. These parameters are aimed to be controlled by sounds of machine. Optimum sound’s features introduced to computer. During process, real time data is received and converted by Matlab software. Data is converted into numerical values. According to them progress and speeds decreases/increases at a certain rate and thus optimum sound is acquired. Cutting process is made in respect of optimum cutting parameters. During chip remove progress, features of cutting tools, kind of cut material, cutting parameters and used machine; affects on various parameters. Instead of required parameters need to be measured such as temperature, vibration, and tool wear that emerged during cutting process; detailed analysis of the sound emerged during cutting process will provide detection of various data that included in the cutting process by the much more easy and economic way. The relation between cutting parameters and sound is being identified.

Keywords: cutting process, sound processing, intelligent late, sound analysis

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Authors: Chibuzor Dalmeida

Abstract:

This paper shall discuss the factors affecting English Language Acquisition and Learning for Primary School in Nigeria. Learning English language is a difficult task mostly those at the primary school level. Pupils find it more difficult on vocabulary, grammar and sentence structure, idioms, pronunciation etc. Researchers have discovered the reasons behind these discrepancies and have formulated theories that could be of utmost assistance to English language teachers and students. This paper further looked at the following factors that include Learner Characteristics and Personal Traits, Situational and Environmental Factors, Prior Language Development and Competence and Age and Brain Development. It further recommended that pupils must learn new vocabulary, rules for grammar and sentence structure, idioms, pronunciation. Pupils whose families and communities set high standards for language acquisition learn more quickly than those who do not. Exposure to high-quality programs also essential. Pupils do best when they are allowed to speak their native language.

Keywords: acquisition, affecting, factors, learning

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Authors: Paul Lam, Chi Him Chan, Alan Tse

Abstract:

Language laboratories have been widely used in language learning, starting in the middle of the last century as one of the earliest forms of educational technology. They are designed to assist students’ language learning with technological innovations. Traditional language laboratories provide individual workstations that allow students to access multimedia language resources. In this type of facility, students can train their listening and speaking abilities, and teachers can also assess the performance of an individual student. Although such a setting promotes a student-centered pedagogy by encouraging students to work at their own pace and according to their own needs, it still favours a traditional, behaviourist language learning pedagogy which focuses on repetitive drilling. The change of pedagogies poses challenges to both the teachers and the facilities. The peer-learning pedagogy advocates that language learning should focus on the social aspect, which emphasizes the importance of everyday communication in language learning. The self-access, individual workstation language laboratories may not be able to provide the flexibility for interaction in the new pedagogies. Modern advancement in technology is another factor that drove our language laboratory renovation. In particular, mobile and wireless technology enabled the use of smaller and more flexible devices, making possible much clever use of space. The Chinese University of Hong Kong (CUHK) renovated nine existing language laboratories to provide lighter and more advanced equipment, movable tables, and round desks. These facilities allow more flexibility and encourage students’ interaction. It is believed that the renovated language laboratories can serve different peer learning activities and thus support peer-learning pedagogies in language teaching and learning. A survey has been conducted to collect comments from the teachers who have used the renovated language laboratories and received forty-four response. The teachers’ comments reveal that they experienced different challenges in using the renovated language laboratories, and there is a need to provide guidance to teachers during the technological and pedagogical transition. For example, teachers need instruction on using the newly installed devices such as touch-monitor and visualizer. They also need advice on planning new teaching and learning activities. Nevertheless, teachers appreciated that the renovated language laboratories are flexible and provide more spaces for different learning activities.

Keywords: language laboratories, language learning, peer-learning, student interaction

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