Search results for: learning Maltese as a second language

Authors: Nik Azmah Nik Yusuff, Faridah Hassan Basri, Rosnidar Mansor

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The purpose of the study is to find out the effectiveness of using Graphic calculators (GC) with Calculator Based Laboratory 2 (CBL2) in teaching and learning of form four biology for these topics: Nutrition, Respiration and Dynamic Ecosystem. Sixty form four science stream students were the participants of this study. The participants were divided equally into the treatment and control groups. The treatment group used GC with CBL2 during experiments while the control group used the ordinary conventional laboratory apparatus without using GC with CBL2. Instruments in this study were a set of pre-test and post-test and a questionnaire. T-Test was used to compare the student’s biology achievement while a descriptive statistic was used to analyze the outcome of the questionnaire. The findings of this study indicated the use of GC with CBL2 in biology had significant positive effect. The highest mean was 4.43 for item stating the use of GC with CBL2 had saved collecting experiment result’s time. The second highest mean was 4.10 for item stating GC with CBL2 had saved drawing and labelling graphs. The outcome from the questionnaire also showed that GC with CBL2 were easy to use and save time. Thus, teachers should use GC with CBL2 in support of efforts by Malaysia Ministry of Education in encouraging technology-enhanced lessons.

Keywords: biology experiments, Calculator-Based Laboratory 2 (CBL2), graphic calculators, Malaysia Secondary School, teaching/learning

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Authors: Satoko Yamasaki, Hiromi Kawasaki, Kotomi Yamashita, Susumu Fukita, Kei Sounai

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People are susceptible to rumors when the cause of their health problems is unknown or invisible. In order for individuals to be unaffected by rumors, they need basic knowledge and correct information. Community health nursing classes use cases where basic knowledge of radiation can be utilized on a regular basis, thereby teaching that basic knowledge is important in preventing anxiety caused by rumors. Nursing students need to learn that preventive activities are essential for public health nursing care. This is the same methodology used to reduce COVID-19 anxiety among individuals. This study verifies the learning effect concerning the basic knowledge of radiation necessary for case consultation by emergency distance learning. Sixty third-year nursing college students agreed to participate in this research. The knowledge tests conducted before and after classes were compared, with the chi-square test used for testing. There were five knowledge questions regarding distance lessons. This was considered to be 5% significant. The students’ reports which describe the results of responding to health consultations, were analyzed qualitatively and descriptively. In this case study, a person living in an area not affected by radiation was anxious about drinking water and, thus, consulted with a student. The contents of the lecture were selected the minimum amount of knowledge used for the answers of the consultant; specifically hot spots, internal exposure risk, food safety, characteristics of cesium-137, and precautions for counselors. Before taking the class, the most correctly answered question by students concerned daily behavior at risk of internal exposure (52.2%). The question with the fewest correct answers was the selection of places that are likely to be hot spots (3.4%). All responses increased significantly after taking the class (p < 0.001). The answers to the counselors, as written by the students, were 'Cesium is strongly bound to the soil, so it is difficult to transfer to water' and 'Water quality test results of tap water are posted on the city's website.' These were concrete answers obtained by using specialized knowledge. Even in emergency distance learning, the students gained basic knowledge regarding radiation and created a document to utilize said knowledge while assuming the situation concretely. It was thought that the flipped classroom method, even if conducted remotely, could maintain students' learning. It was thought that setting specific knowledge and scenes to be used would enhance the learning effect. By changing the case to concern that of the anxiety caused by infectious diseases, students may be able to effectively gain the basic knowledge to decrease the anxiety of residents due to infectious diseases.

Keywords: effect of class, emergency distance learning, nursing student, radiation

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Authors: Neneng Hayatul Milah

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The most important reading skill for students is comprehension. Understanding the reading text will have an impact on learning outcomes. However, reading comprehension instruction in Indonesian elementary schools is lacking. A more effective learning model is needed to enhance students' reading comprehension. This study aimed to evaluate the effectiveness of the CIRC (Cooperative Integrated Reading and Composition) model with Padlet integration in improving the reading comprehension skills of grade IV students in elementary schools in Cimahi City, Indonesia. This research methodology was quantitative with a pre-experiment research type and one group pretest-posttest research design. The sample of this study consisted of 30 students. The results of statistical analysis showed that there was a significant effect of using the CIRC learning model using Padlet on improving students' reading comprehension skills of narrative text. The mean score of students' pretest was 67.41, while the mean score of the posttest increased to 84.82. The paired sample t-test resulted in a t-count score of -13.706 with a significance score of <0.001, which is smaller than α = 0.05. This research is expected to provide useful insights for educational practitioners on how the use of the CIRC model using Padlet can improve the reading comprehension skills of elementary school students.

Keywords: reading comprehension skills, CIRC, Padlet, narrative text

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Authors: Youmen Chaaban, Abdallah Abu-Tineh

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This article examines the development of a professional development (PD) model for educator growth and learning that is embedded into the school context. The School based Support Program (SBSP), designed for the Qatari context, targets the practices, knowledge, and skills of both school leadership and teachers in an attempt to improve students’ learning outcomes. Key aspects of the model include the development of learning communities among teachers, strong leadership that supports school improvement activities, and the use of research-based PD to improve teacher practices and student achievement. This paper further presents the results of a qualitative study examining the perceptions of nineteen instructional coaches about the strengths of the PD program, the challenges they face in their day-to-day implementation of the program, and their suggestions for the betterment of the program’s implementation and outcomes. Data were collected from the instructional coaches through open-ended surveys followed by focus group interviews. The instructional coaches reported several strengths, which were compatible with the literature on effective PD. However, the challenges they faced were deeply rooted within the structure of the program, in addition to external factors operating at the school and Ministry of Education levels. Thus, a general consensus on the way the program should ultimately develop was reached.

Keywords: situated professional development, school reform, instructional coach, school based support program

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Authors: Sakshi Bhalla

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On the one hand, given their seemingly simplistic, near universal usage and understanding, emoji are discarded as a potential step back in the evolution of communication. On the other, their effectiveness, pervasiveness, and adaptability across and within contexts are undeniable. In this study, the responses of 40 people (categorized by age) were recorded based on a uniform two-part questionnaire where they were required to a) identify the meaning of 15 emoji when placed in isolation, and b) interpret the meaning of the same 15 emoji when placed in a context-defining posting on Twitter. Their responses were studied on the basis of deviation from their responses that identified the emoji in isolation, as well as the originally intended meaning ascribed to the emoji. Based on an analysis of these results, it was discovered that each of the five age categories uses, understands and perceives emoji differently, which could be attributed to the degree of exposure they have undergone. For example, in the case of the youngest category (aged < 20), it was observed that they were the least accurate at correctly identifying emoji in isolation (~55%). Further, their proclivity to change their response with respect to the context was also the least (~31%). However, an analysis of each of their individual responses showed that these first-borns of social media seem to have reached a point where emojis no longer inspire their most literal meanings to them. The meaning and implication of these emoji have evolved to imply their context-derived meanings, even when placed in isolation. These trends carry forward meaningfully for the other four groups as well. In the case of the oldest category (aged > 35), however, the trends indicated inaccuracy and therefore, a higher incidence of a proclivity to change their responses. When studied in a continuum, the responses indicate that slowly and steadily, emoji are evolving from pictograms to ideograms. That is to suggest that they do not just indicate a one-to-one relation between a singular form and singular meaning. In fact, they communicate increasingly complicated ideas. This is much like the evolution of ancient hieroglyphics on papyrus reed or cuneiform on Sumerian clay tablets, which evolved from simple pictograms to progressively more complex ideograms. This evolution within communication is parallel to and contingent on the simultaneous evolution of communication. What’s astounding is the capacity of humans to leverage different platforms to facilitate such changes. Twiterese, as it is now called, is one of the instances where language is adapting to the demands of the digital world. That it does not have a spoken component, an ostensible grammar, and lacks standardization of use and meaning, as some might suggest, may seem like impediments in qualifying it as the 'language' of the digital world. However, that kind of a declarative remains a function of time, and time alone.

Keywords: communication, emoji, language, Twitter

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Authors: V. Biasi, A. M. Ciraci, G. Domenici, N. Patrizi

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We present two studies centered on the teacher’s perception of self-efficacy and professional competences. The first study aims to evaluate the levels of self-efficacy as attitude in 200 teachers of primary and secondary schools. Teacher self-efficacy is related to many educational outcomes: such as teachers’ persistence, enthusiasm, commitment and instructional behavior. High level of teacher self-efficacy beliefs enhance student motivation and pupil’s learning level. On this theoretical and empirical basis we are planning a second study oriented to assess teacher self-perception of competences that are linked to teacher self-efficacy. With the CDVR Questionnaire, 287 teachers graduated in Education Sciences in e-learning mode, showed an increase in their self-perception of didactic-evaluation and relational competences and an increased confidence also in their own professionalism.

Keywords: teacher competence, teacher self-efficacy, selfperception, self-report evaluation

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Authors: Miranda Enesi, Helena Grillo Mukli

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The English word-stock is extremely rich in synonyms which can be largely accounted for by the abundant borrowing. Translation problems encountered by translators in general are usually ‘transfer problems’. They face more difficulties in the interpretation of meaning from the source language text than lexical differences between languages. The aim of the study is to inspect the various strategies used in translating from English into Albanian specific words in the ‘A Farwell to arms’ novel. For this purpose, examples translated from English into Albanian were examined. The Albanian equivalents have shown that various strategies were used in order to overcome the problem of rendering words and expressions into the target language. Employed strategies were synonymy, modulation, transposition, calque and word for word translation. In addition, this paper shows that the strategy of translating using synonymy is mostly used. In this paper, an attempt is made to examine the nature of contextual synonymy in order to investigate its problematic nature regarding translation. Types of synonymy are analyzed and then examples from English and Albanian versions are provided to examine the overlap between them.

Keywords: equivalence, literal translation, paraphrasing, transfer problems, synonymy

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Authors: Ogunnaiya Racheal Taiwo

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Children's formative years are crucial to their growth; it is, therefore, necessary for all the stakeholders to ensure that the pupils have an enabling quality of life which is essential for realizing their potential. For children to live and grow, they need a secure home, nutritious food, good health care, and quality education. This paper, therefore, investigates the implications of a depressed economy on the classroom learning of Nigerian children as it is clear that Nigeria is currently experiencing the worst economic depression in several decades, which affects a substantial proportion of children. The study is qualitative research, and it adopts a phenomenological approach where the experiences of respondents are examined qualitatively. Three senatorial districts in Oyo State were considered, and 50 teachers, both male, and female were chosen from each senatorial district for an interview through conversational key informants' interviews. The interviewees were recorded, transcribed, and presented using thematic analysis. Findings showed that more children have dropped out since the beginning of the year than in previous years. It was also recorded that learning has become challenging as children now find it harder to acquire learning materials. It was recommended that the government should reimburse early childhood schools to lessen the effect of the inability to purchase materials and pay school fees. It was also recommended that an intervention be made to approach and resolve issues associated with out-of-school children.

Keywords: childhood, classroom, education, depressed economy, poverty

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Authors: Rewadee Ungpho

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The research on the musical culture of Sea Gypsies in Bulon archipelago, Satun Province, is considered as an anthropology research. Research objectives were to study the history and information culture and also to find the basis information for the restoration and preservation of the music culture of Sea Gypsies who live in Bulon archipelago. Findings of the research are as follows: 1) Musical characteristics of Sea Gypsies in Bulon archipelago is still traditional. It does not mix with any external musical influence such as musical instruments, language, and other musical characteristics. There are various kind of songs which can play a complete melody and rhythm, including a total of 8 songs as follows; Lagu-Ayam-Dide, Lagu-Sitipayong, Lagu-Bulong-pute, Lagu-Chemamat, Laguduwo, Lagu-Ma-I-nang, Lagu-Mana-Ikan. 2) The roles of culture/music in Bulon archipelago correlate with Urak Lawoi society. They use music in the ceremony of votive offering, in the floating ceremony held in Lipe Island and in various festivals. Therefore, music is a spiritual sacrifice and a spiritual instrument that conveys an Urak Lawoi, which makes the Urak Lawoi still unique and has a sense of ethnic identity. 3) The inheritance of Urak Lawoi music is still being made in a traditional way, as an oral tradition with no record. The teaching and learning must be one on one, and it required length of time to practice and accumulate the knowledge. Due to above mentioned reasons, a few people attend in the inheritance. Those who are interested may not be able to practice constantly. As a result, there is only a few, or even none, descendants left.

Keywords: sea gypsy, music, Bulon archipelago, ethnomusicology

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Authors: Naman Jain, Shaun Fernandes

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With the increasing prevalence of online healthcare services, selecting the most suitable doctor has become a complex task, requiring careful consideration of both public sentiment and personal preferences. This paper proposes a sentiment analysis-driven method that integrates public reviews with user-specific criteria and correlated attributes to recommend online doctors. By leveraging Natural Language Processing (NLP) techniques, public sentiment is extracted from online reviews, which is then combined with user-defined preferences such as specialty, years of experience, location, and consultation fees. Additionally, correlated attributes like education and certifications are incorporated to enhance the recommendation accuracy. Experimental results demonstrate that the proposed system significantly improves user satisfaction by providing personalized doctor recommendations that align with both public opinion and individual needs.

Keywords: sentiment analysis, online doctors, personal preferences, correlated attributes, recommendation system, healthcare, natural language processing

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Authors: Johan Loeckx, Joeri Bultheel

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Recently, the application of deep learning to music has gained popularity. Its true potential, however, has been largely unexplored. In this paper, a new idea for representing the dynamic behavior of music is proposed. A ”forward” conditional RBM takes into account not only preceding but also future samples during training. Though this may sound controversial at first sight, it will be shown that it makes sense from a musical and neuro-cognitive perspective. The model is applied to reconstruct music based upon the first notes and to improvise in the musical style of a composer. Different to expectations, reconstruction accuracy with respect to a regular CRBM with the same order, was not significantly improved. More research is needed to test the performance on unseen data.

Keywords: deep learning, restricted boltzmann machine, music generation, conditional restricted boltzmann machine (CRBM)

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Authors: Rakesh Bhatia

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Students often face significant challenges in understanding and applying trigonometric identities, primarily due to the overwhelming need to memorize numerous formulas. This often leads to confusion, frustration, and difficulty in effectively using these formulas across diverse types of problems. Traditional methods of learning trigonometry demand considerable time and effort, which can further hinder comprehension and application. Vedic Mathematics offers an innovative and simplified approach to overcoming these challenges. This paper explores how Baudhayan Numbers, can be used to derive trigonometric identities and simplify calculations related to height and distance. Unlike conventional approaches, this method minimizes the need for extensive paper-based calculations, promoting a conceptual understanding. Using Vedic Mathematics Sutras such as Anurupyena and Vilokanam, this approach enables the derivation of over 100 trigonometric identities through a single, unified approach. The simplicity and efficiency of this technique not only make learning trigonometry more accessible but also foster computational thinking. Beyond academics, the practical applications of this method extend to engineering fields such as bridge design and construction, where precise trigonometric calculations are critical. This exploration underscores the potential of Vedic Mathematics to revolutionize the learning and application of trigonometry by offering a streamlined, intuitive, and versatile framework.

Keywords: baudhayan numbers, anurupyena, vilokanam, sutras

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Authors: Mohd Afif Md Nasir, Mohd Faizal Amin Nur, Jamaluddin Hasim, Abd Samad Hasan Basari, Mohd Halim Sahelan

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This study is aimed to investigate the suitability of Computer-Based Training (CBT) as one of the approaches in skills competency development at the Centre of Instructor and Advanced Skills Training (CIAST) Shah Alam Selangor and National Youth Skills Institute (NYSI) Pagoh Muar Johor. This study has also examined the perception among trainees toward Virtual Learning Environment (VLE) as to realize the development of skills in Welding Technology. The significance of the study is to create a computer-based skills development approach in welding technology among new trainees in CIAST and IKBN as well as to cultivate the element of general skills among them. This study is also important in elevating the number of individual knowledge workers (K-Workers) working in manufacturing industry in order to achieve the national vision which is to be an industrial nation in the year 2020. The design is a survey of research which using questionnaires as the instruments and is conducted towards 136 trainees from CIAST and IKBN. Data from the questionnaires is proceeding in a Statistical Package for Social Science (SPSS) in order to find the frequency, mean and chi-square testing. The findings of the study show the welding technology skills have developed in the trainees as a result of the application of the Virtual Reality simulator at a high level (mean=3.90) and the respondents agreed the skills could be embedded through the application of the Virtual Reality simulator (78.01%). The Study also found that there is a significant difference between trainee skill characteristics through the application of the Virtual Reality simulator (p<0.05). Thereby, the Virtual Reality simulator is suitable to be used in the development of welding skills among trainees through the skills training institute.

Keywords: computer-based training, virtual learning environment, welding technology, virtual reality simulator, virtual learning environment

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Authors: Omran Alharbi, Victor Lally

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In recent decades, a number of educational institutions around the world have come to depend on technology such as the Blackboard system to improve their educational environment. On the other hand, there are many factors that delay the usage of this technology, especially in developing nations such as Saudi Arabia. The goal of this study was to investigate learner’s views of the use of Blackboard in one Saudi university in order to gain a comprehensive view of the factors that delay the implementation of technology in Saudi institutions. This study utilizes a qualitative approach, with data being collected through semi-structured interviews. Six participants from different disciplines took part in this study. The findings indicated that there are two levels of factors that affect students’ use of the Blackboard system. These are factors at the institutional level, such as lack of technical support and lack of training support, which lead to insufficient training related to the Blackboard system. The second level of factors is at the individual level, for example, a lack of teacher motivation and encouragement. In addition, students do not have sufficient levels of skills or knowledge related to how to use the Blackboard in their learning. Conclusion: learners confronted and faced two main types of factors (at the institution level and individual level) that delayed and impeded their learning. Institutions in KSA should take steps and implement strategies to remove or reduce these factors in order to allow students to benefit from the latest technology in their learning.

Keywords: blackboard, factors, KSA, learners

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Authors: Firas Gerges, Frank Y. Shih

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Malignant melanoma, known simply as melanoma, is a type of skin cancer that appears as a mole on the skin. It is critical to detect this cancer at an early stage because it can spread across the body and may lead to the patient's death. When detected early, melanoma is curable. In this paper, we propose a deep learning model (convolutional neural networks) in order to automatically classify skin lesion images as malignant or benign. Images underwent certain pre-processing steps to diminish the effect of the normal skin region on the model. The result of the proposed model showed a significant improvement over previous work, achieving an accuracy of 97%.

Keywords: deep learning, skin cancer, image processing, melanoma

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Authors: Chien-Ho Lin, Ho-Ching Yang, Barbara Knowlton, Shin-Leh Huang, Ming-Chang Chiang

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Practicing motor tasks arranged in an interleaved order (interleaved practice, or IP) generally leads to better learning than practicing tasks in a repetitive order (repetitive practice, or RP), an example of how desirable difficulty during practice benefits learning. Greater difficulty during practice, e.g. IP, is associated with greater brain activity measured by higher blood-oxygen-level dependent (BOLD) signal in functional magnetic resonance imaging (fMRI) in the sensorimotor areas of the brain. In this study resting-state fMRI was applied to investigate whether increase in resting-state brain connectivity immediately after practice predicts the benefit of desirable difficulty to motor learning. 26 healthy adults (11M/15F, age = 23.3±1.3 years) practiced two sets of three sequences arranged in a repetitive or an interleaved order over 2 days, followed by a retention test on Day 5 to evaluate learning. On each practice day, fMRI data were acquired in a resting state after practice. The resting-state fMRI data was decomposed using a group-level spatial independent component analysis (ICA), yielding 9 independent components (IC) matched to the precuneus network, primary visual networks (two ICs, denoted by I and II respectively), sensorimotor networks (two ICs, denoted by I and II respectively), the right and the left frontoparietal networks, occipito-temporal network, and the frontal network. A weighted resting-state functional connectivity (wRSFC) was then defined to incorporate information from within- and between-network brain connectivity. The within-network functional connectivity between a voxel and an IC was gauged by a z-score derived from the Fisher transformation of the IC map. The between-network connectivity was derived from the cross-correlation of time courses across all possible pairs of ICs, leading to a symmetric nc x nc matrix of cross-correlation coefficients, denoted by C = (pᵢⱼ). Here pᵢⱼ is the extremum of cross-correlation between ICs i and j; nc = 9 is the number of ICs. This component-wise cross-correlation matrix C was then projected to the voxel space, with the weights for each voxel set to the z-score that represents the above within-network functional connectivity. The wRSFC map incorporates the global characteristics of brain networks measured by the between-network connectivity, and the spatial information contained in the IC maps measured by the within-network connectivity. Pearson correlation analysis revealed that greater IP-minus-RP difference in wRSFC was positively correlated with the RP-minus-IP difference in the response time on Day 5, particularly in brain regions crucial for motor learning, such as the right dorsolateral prefrontal cortex (DLPFC), and the right premotor and supplementary motor cortices. This indicates that enhanced resting brain connectivity during the early phase of memory consolidation is associated with enhanced learning following interleaved practice, and as such wRSFC could be applied as a biomarker that measures the beneficial effects of desirable difficulty on motor sequence learning.

Keywords: desirable difficulty, functional magnetic resonance imaging, independent component analysis, resting-state networks

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Authors: Mohammed Hussein Ahmed, Bahar Mohammed Kareem

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This study is concerned with the pragmatic discoursal study of hedging constructions in English language. Hedging is a mitigated word used to lessen the impact of the utterance uttered by the speakers. Hedging could be either adverbs, adjectives, verbs and sometimes it may consist of clauses. It aims at finding out the extent to which speakers and participants of the discourse use hedging constructions during their conversations. The study also aims at finding out whether or not there are any significant differences in the types and functions of the frequency of hedging constructions employed by male and female. It is hypothesized that hedging constructions are frequent in English discourse more than any other languages due to its formality and that the frequency of the types and functions are influenced by the gender of the participants. To achieve the aims of the study, two types of procedures have been followed: theoretical and practical. The theoretical procedure consists of presenting a theoretical background of hedging topic which includes its definitions, etymology and theories. The practical procedure consists of selecting a sample of texts and analyzing them according to an adopted model. A number of conclusions will be drawn based on the findings of the study.

Keywords: hedging, pragmatics, politeness, theoretical

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Authors: Sang-Keun Moon, Hong-Rok Lim, Jin-O Kim

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This paper presents a Power Quality (PQ) modeling and filtering processes for the distribution system disturbances using recognition learning methods. Typical PQ waveforms with mathematical applications and gathered field data are applied to the proposed models. The objective of this paper is analyzing PQ data with respect to monitoring, discriminating, and evaluating the waveform of power disturbances to ensure the system preventative system failure protections and complex system problem estimations. Examined signal filtering techniques are used for the field waveform noises and feature extractions. Using extraction and learning classification techniques, the efficiency was verified for the recognition of the PQ disturbances with focusing on interactive modeling methods in this paper. The waveform of selected 8 disturbances is modeled with randomized parameters of IEEE 1159 PQ ranges. The range, parameters, and weights are updated regarding field waveform obtained. Along with voltages, currents have same process to obtain the waveform features as the voltage apart from some of ratings and filters. Changing loads are causing the distortion in the voltage waveform due to the drawing of the different patterns of current variation. In the conclusion, PQ disturbances in the voltage and current waveforms indicate different types of patterns of variations and disturbance, and a modified technique based on the symmetrical components in time domain was proposed in this paper for the PQ disturbances detection and then classification. Our method is based on the fact that obtained waveforms from suggested trigger conditions contain potential information for abnormality detections. The extracted features are sequentially applied to estimation and recognition learning modules for further studies.

Keywords: power quality recognition, PQ modeling, waveform feature extraction, disturbance trigger condition, PQ signal filtering

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Authors: Seah Siok Peh, Hashimah Mohd Yunus, Nor Hashimah Hashim, Mariam Mohamad

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A country needs a workforce that encompasses knowledge, skilled labourers to generate innovation, productivity and being able to solve problems creatively via technology. Science education experts believe that the mastery of science skills help preschoolers to generate such knowledge on scientific concepts by providing constructive experiences. Science process skills are skills used by scientists to study or investigate a problem, issue, problem or phenomenon of science. In line with the skills used by scientists. The purpose of this study is to investigate the basic science process skill and interest in learning early science through mobile application. This study aimed to explore six spesific basic science process skills by the use of a mobile application as a learning support tool. The descriptive design also discusses on the extent of the use of mobile application in improving basic science process skill in young children. This study consists of six preschoolers and two preschool teachers from two different classes located in Perak, Malaysia. Techniques of data collection are inclusive of observations, interviews and document analysis. This study will be useful to provide information and give real phenomena to policy makers especially Ministry of education in Malaysia.

Keywords: science education, basic science process skill, interest, early science, mobile application

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Authors: Muhammed Unais

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The holy Quran is a pure Arabic book completely ensured the absence of non Arabic term. If it was revealed in a multilingual way including various foreign languages besides the Arabic, it can be easily misunderstood that the Arabs became helpless to compile such a work positively responding to the challenge of Allah due to their lack of knowledge in other languages in which the Quran is compiled. As based on the presence of some non Arabic terms in Quran like Istabrq, Saradiq, Rabbaniyyoon, etc. some oriental scholars argued that the holy Quran is not a book revealed in Arabic. We can see some Muslim scholars who either support or deny the presence of foreign terms in Quran but all of them agree that the roots of these words suspected as non Arabic are from foreign languages and are assimilated to the Arabic and using as same in that foreign language. After this linguistic assimilation was occurred and the assimilated non Arabic words became familiar among the Arabs, the Quran revealed as using these words in such a way stating that all words it contains are Arabic either pure or assimilated. Hence the two of opinions around the authenticity and reliability of etymology of these words are right. Those who argue the presence of foreign words he is right by the way of the roots of that words are from foreign and those who argue its absence he is right for that are assimilated and changed as the pure Arabic. The possibility of multilingualism in a monolingual book is logically negative but its significance is being changed according to time and place. The problem of multilingualism in Quran is the misconception raised by some oriental scholars that the Arabs became helpless to compile a book equal to Quran not because of their weakness in Arabic but because the Quran is revealed in languages they are ignorant on them. Really, the Quran was revealed in pure Arabic, the most literate language of the Arabs, and the whole words and its meaning were familiar among them. If one become positively aware of the linguistic and cultural assimilation ever found in whole civilizations and cultural sets he will have not any question in this respect. In this paper the researcher intends to shed light on the possibility of multilingualism in a monolingual book and debates among scholars in this issue, foreign terms in Quran and the logical justifications along with the exclusive features of Quran.

Keywords: Quran, foreign Terms, multilingualism, language

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Authors: Jacky Liu

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This paper develops a team sports outcome prediction system with potential for wide-ranging applications across various disciplines. Despite significant advancements in predictive analytics, existing studies in sports outcome predictions possess considerable limitations, including insufficient feature engineering and underutilization of advanced machine learning techniques, among others. To address these issues, we extend the Sports Cross Industry Standard Process for Data Mining (SRP-CRISP-DM) framework and propose a unique, comprehensive predictive system, using National Basketball Association (NBA) data as an example to test this extended framework. Our approach follows a holistic methodology in feature engineering, employing both Time Series and Non-Time Series Data, as well as conducting Explanatory Data Analysis and Feature Selection. Furthermore, we contribute to the discourse on target variable choice in team sports outcome prediction, asserting that point spread prediction yields higher profits as opposed to game-winner predictions. Using machine learning algorithms, particularly XGBoost, results in a significant improvement in predictive accuracy of team sports outcomes. Applied to point spread betting strategies, it offers an astounding annual return of approximately 900% on an initial investment of $100. Our findings not only contribute to academic literature, but have critical practical implications for sports betting. Our study advances the understanding of team sports outcome prediction a burgeoning are in complex system predictions and pave the way for potential profitability and more informed decision making in sports betting markets.

Keywords: machine learning, team sports, game outcome prediction, sports betting, profits simulation

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Authors: Camilla Simoncelli

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The connection between language and cognition has been one of the main interests of linguistics from several years. According to the Sapir-Whorf Linguistic Relativity Theory, the way we perceive reality depends on the language we speak which in turn has a central role in the human cognition. This paper is in line with this research work with the aim of analyzing how language structures reflect on our cognitive abilities even in the description of space, which is generally considered as a human natural and universal domain. The main objective is to identify the differences in the encoding of spatial inclusion relationships in French and Italian speakers to make evidence that a significant variation exists at various levels even in two similar systems. Starting from the constitution a corpora, the first step of the study has been to establish the relevant complex prepositions marking an inclusion relation in French and Italian: au centre de, au cœur de, au milieu de, au sein de, à l'intérieur de and the opposition entre/parmi in French; al centro di, al cuore di, nel mezzo di, in seno a, all'interno di and the fra/tra contrast in Italian. These prepositions had been classified on the base of the type of Noun following them (e.g. mass nouns, concrete nouns, abstract nouns, body-parts noun, etc.) following the Collostructional Analysis of lexemes with the purpose of analyzing the preferred construction of each preposition comparing the relations construed. Comparing the Italian and the French results it has been possible to define the degree of representativeness of each target Noun for the chosen preposition studied. Lexicostatistics and Statistical Association Measures showed the values of attraction or repulsion between lexemes and a given preposition, highlighting which words are over-represented or under-represented in a specific context compared to the expected results. For instance, a Noun as Dibattiti has a negative value for the Italian Al cuore di (-1,91), but it has a strong positive representativeness for the corresponding French Au cœur de (+677,76). The value, positive or negative, is the result of a hypergeometric distribution law which displays the current use of some relevant nouns in relations of spatial inclusion by French and Italian speakers. Differences on the kind of location conceptualization denote syntactic and semantic constraints based on spatial features as well as on linguistic peculiarity, too. The aim of this paper is to demonstrate that the domain of spatial relations is basic to human experience and is linked to universally shared perceptual mechanisms which create mental representations depending on the language use. Therefore, linguistic coding strongly correlates with the way spatial distinctions are conceptualized for non-verbal tasks even in close language systems, like Italian and French.

Keywords: cognitive semantics, cross-linguistic variations, locational terms, non-verbal spatial representations

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Authors: Jian Zheng, Yoshiyasu Takahashi, Yuichi Kobayashi, Tatsuhiro Sato

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In the study, we present a conceptual framework for developing a scheduling system that can generate self-explanatory and easy-understanding schedules. To this end, a user interface is conceived to help planners record factors that are considered crucial in scheduling, as well as internal and external sources relating to such factors. A hybrid approach combining machine learning and constraint programming is developed to generate schedules and the corresponding factors, and accordingly display them on the user interface. Effects of the proposed system on scheduling are discussed, and it is expected that scheduling efficiency and system understandability will be improved, compared with previous scheduling systems.

Keywords: constraint programming, factors considered in scheduling, machine learning, scheduling system

Procedia PDF Downloads 328

Authors: Alireza Karimi

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Artificial Intelligence (AI) is reshaping various industries, and accounting is no exception. With the ability to process vast amounts of data quickly and accurately, AI is revolutionizing how financial professionals manage, analyze, and report financial information. In this article, we will explore the diverse applications of AI in accounting and its profound impact on the field. Automation of Repetitive Tasks: One of the most significant contributions of AI in accounting is automating repetitive tasks. AI-powered software can handle data entry, invoice processing, and reconciliation with minimal human intervention. This not only saves time but also reduces the risk of errors, leading to more accurate financial records. Pattern Recognition and Anomaly Detection: AI algorithms excel at pattern recognition. In accounting, this capability is leveraged to identify unusual patterns in financial data that might indicate fraud or errors. AI can swiftly detect discrepancies, enabling auditors and accountants to focus on resolving issues rather than hunting for them. Real-Time Financial Insights: AI-driven tools, using natural language processing and computer vision, can process documents faster than ever. This enables organizations to have real-time insights into their financial status, empowering decision-makers with up-to-date information for strategic planning. Fraud Detection and Prevention: AI is a powerful tool in the fight against financial fraud. It can analyze vast transaction datasets, flagging suspicious activities and reducing the likelihood of financial misconduct going unnoticed. This proactive approach safeguards a company's financial integrity. Enhanced Data Analysis and Forecasting: Machine learning, a subset of AI, is used for data analysis and forecasting. By examining historical financial data, AI models can provide forecasts and insights, aiding businesses in making informed financial decisions and optimizing their financial strategies. Artificial Intelligence is fundamentally transforming the accounting profession. From automating mundane tasks to enhancing data analysis and fraud detection, AI is making financial processes more efficient, accurate, and insightful. As AI continues to evolve, its role in accounting will only become more significant, offering accountants and finance professionals powerful tools to navigate the complexities of modern finance. Embracing AI in accounting is not just a trend; it's a necessity for staying competitive in the evolving financial landscape.

Keywords: artificial intelligence, accounting automation, financial analysis, fraud detection, machine learning in finance

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Authors: Noury Bakrim

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Translatability is one of Walter Benjamin’s most influential notions, it is somehow representing the philosophy of language and history of what we might call and what we indeed coined as ‘the other German Speaking Modernity’ which could be shaped as a parallel thought form to the Marxian-Hegelian philosophy of history, the one represented by the school of Frankfurt. On the other hand, we should consider the influence of the plural German speaking identity and the Nietzschian and Goethean heritage, this last being focused on a positive will of power: the humanised human being. Having in perspective the benjaminian notion of translatability (Übersetzbarkeit), to be defined as an internal permanent hermeneutical possibility as well as a phenomenological potential of a translation relation, we are in fact touching this very double limit of both historical and linguistic reason. By life component, we mean the changing conditions of genetic and neurolinguistic post-partum functions, to be grasped as an individuation beyond the historical determinism and teleology of an event. It is, so to speak, the retrospective/introspective canettian auto-fiction, the benjaminian crystallization of the language experience in the now-time of writing/transmission. Furthermore, it raises various questioning points when it comes to translatability, they are basically related to psycholinguistic separate poles, the fatherly ladino Spanish and the motherly Vienna German, but relating more in particular to the permanent ontological quest of a world loss/belonging. Another level of this quest would be the status of Veza Canetti-Taubner Calderón, german speaking Author, Canetti’s ‘literary wife’, writer’s love, his inverted logos, protective and yet controversial ‘official private life partner’, the permanence of the jewish experience in the exiled german language. It sheds light on a traumatic relation of an inadequate/possible language facing the reconstruction of an oral life, the unconscious split of the signifier and above all on the frustrating status of writing in Canetti’s work : Using a suffering/suffered written German to save his remembered acquisition of his tongue/mother tongue by saving the vanishing spoken multilingual experience. While Canetti’s only novel ‘Die Blendung’ designates that fictional referential dynamics focusing on the nazi worldless horizon: the figure of Kien is an onomastic signifier, the anti-Canetti figure, the misunderstood legacy of Kant, the system without thought. Our postulate would be the double translatability of his auto-fiction inventing the bios oral signifier basing on the new praxemes created by Canetti’s german as observed in the English, French translations of his memory corpus. We aim at conceptualizing life component and translatability as two major features of a german speaking modernity.

Keywords: translatability, language biography, presentification, bioeme, life Order

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Authors: Foster Chilufya

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This study sought to determine factors that affect academic performance of mature age students in Science Education at University of Zambia. It was guided by Maslow’s Hierarchy of Needs. The theory provided relationship between achievement motivation and academic performance. A descriptive research design was used. Both Qualitative and Quantitative research methods were used to collect data from 88 respondents. Simple random and purposive sampling procedures were used to collect from the respondents. Concerning factors that motivate mature-age students to choose Science Education Programs, the following were cited: need for self-actualization, acquisition of new knowledge, encouragement from friends and family members, good performance at high school and diploma level, love for the sciences, prestige and desire to be promoted at places of work. As regards factors that affected the academic performance of mature-age students, both negative and positive factors were identified. These included: demographic factors such as age and gender, psychological characteristics such as motivation and preparedness to learn, self-set goals, self esteem, ability, confidence and persistence, student prior academic performance at high school and college level, social factors, institutional factors and the outcomes of the learning process. In order to address the factors that negatively affect academic performance of mature-age students, the following measures were identified: encouraging group discussions, encouraging interactive learning process, providing a conducive learning environment, reviewing Science Education curriculum and providing adequate learning materials. Based on these factors, it is recommended that, the School of Education introduces a program in Science Education specifically for students training to be teachers of science. Additionally, introduce majors in Physics Education, Biology Education, Chemistry Education and Mathematics Education relevant to what is taught in high schools.

Keywords: academic, performance, in-service, science

Procedia PDF Downloads 312

Authors: Ekaterina A. Redkina

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The necessity and importance of teaching professionally oriented content in English needs no proof nowadays. Consequently, the ability to share personal ESP teaching experience seems of great importance. This paper is based on the 8-year ESP and EFL teaching experience at the Moscow State Linguistic University, Moscow, Russia, and presents theoretical analysis of specifics, possible problems, and perspectives of teaching Psychology in English to Russian psychology-students. The paper concerns different issues that are common for different ESP classrooms, and familiar to different teachers. Among them are: designing ESP curriculum (for psychologists in this case), finding the balance between content and language in the classroom, main teaching principles (the 4 C’s), the choice of assessment techniques and teaching material. The main objective of teaching psychology in English to Russian psychology students is developing knowledge and skills essential for professional psychologists. Belonging to international professional community presupposes high-level content-specific knowledge and skills, high level of linguistic skills and cross-cultural linguistic ability and finally high level of professional etiquette. Thus, teaching psychology in English pursues 3 main outcomes, such as content, language and professional skills. The paper provides explanation of each of the outcomes. Examples are also given. Particular attention is paid to the lesson structure, its objectives and the difference between a typical EFL and ESP lesson. There is also made an attempt to find commonalities between teaching ESP and CLIL. There is an approach that states that CLIL is more common for schools, while ESP is more common for higher education. The paper argues that CLIL methodology can be successfully used in ESP teaching and that many CLIL activities are also well adapted for professional purposes. The research paper provides insights into the process of teaching psychologists in Russia, real teaching experience and teaching techniques that have proved efficient over time.

Keywords: ESP, CLIL, content, language, psychology in English, Russian students

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Authors: Miguel Contreras, David Long, Will Bachman

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Background: Microscopy plays a central role in cell and developmental biology. In particular, fluorescence microscopy can be used to visualize specific cellular components and subsequently quantify their morphology through development of virtual-cell models for study of effects of mechanical forces on cells. However, there are challenges with these imaging experiments, which can make it difficult to quantify cell morphology: inconsistent results, time-consuming and potentially costly protocols, and limitation on number of labels due to spectral overlap. To address these challenges, the objective of this project is to develop an automatic computational machine learning pipeline to predict cellular components morphology for virtual-cell generation based on fluorescence cell membrane confocal z-stacks. Methods: Registered confocal z-stacks of nuclei and cell membrane of endothelial cells, consisting of 20 images each, were obtained from fluorescence confocal microscopy and normalized through software pipeline for each image to have a mean pixel intensity value of 0.5. An open source machine learning algorithm, originally developed to predict fluorescence labels on unlabeled transmitted light microscopy cell images, was trained using this set of normalized z-stacks on a single CPU machine. Through transfer learning, the algorithm used knowledge acquired from its previous training sessions to learn the new task. Once trained, the algorithm was used to predict morphology of nuclei using normalized cell membrane fluorescence images as input. Predictions were compared to the ground truth fluorescence nuclei images. Results: After one week of training, using one cell membrane z-stack (20 images) and corresponding nuclei label, results showed qualitatively good predictions on training set. The algorithm was able to accurately predict nuclei locations as well as shape when fed only fluorescence membrane images. Similar training sessions with improved membrane image quality, including clear lining and shape of the membrane, clearly showing the boundaries of each cell, proportionally improved nuclei predictions, reducing errors relative to ground truth. Discussion: These results show the potential of pre-trained machine learning algorithms to predict cell morphology using relatively small amounts of data and training time, eliminating the need of using multiple labels in immunofluorescence experiments. With further training, the algorithm is expected to predict different labels (e.g., focal-adhesion sites, cytoskeleton), which can be added to the automatic machine learning pipeline for direct input into Principal Component Analysis (PCA) for generation of virtual-cell mechanical models.

Keywords: cell morphology prediction, computational machine learning, fluorescence microscopy, virtual-cell models

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Authors: Preston Nabors, Nasseh Tabrizi

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Portable Document Format (PDF) files have gained significant popularity for sharing and distributing documents due to their universal compatibility. However, the widespread use of PDF files has made them attractive targets for cybercriminals, who exploit vulnerabilities to deliver malware and compromise the security of end-user systems. This paper reviews notable contributions in PDF malware detection, including static, dynamic, signature-based, and hybrid analysis. It presents a comprehensive examination of PDF malware detection techniques, focusing on the emerging threat of adversarial sampling and the need for robust defense mechanisms. The paper highlights the vulnerability of machine learning classifiers to evasion attacks. It explores adversarial sampling techniques in PDF malware detection to produce mimicry and reverse mimicry evasion attacks, which aim to bypass detection systems. Improvements for future research are identified, including accessible methods, applying adversarial sampling techniques to malicious payloads, evaluating other models, evaluating the importance of features to malware, implementing adversarial defense techniques, and conducting comprehensive examination across various scenarios. By addressing these opportunities, researchers can enhance PDF malware detection and develop more resilient defense mechanisms against adversarial attacks.

Keywords: adversarial attacks, adversarial defense, adversarial machine learning, intrusion detection, PDF malware, malware detection, malware detection evasion

Procedia PDF Downloads 43

Authors: Thomas Roche, Erica Wilson, Elizabeth Goode

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Universities across the globe are considering how to effect meaningful change in their higher education (HE) delivery in the face of increasingly diverse student cohorts and shifting student learning preferences. This paper reports on a descriptive case study of whole-of-institution curriculum reform at one regional Australian university, where more traditional 13-week semesters were replaced with a 6-week immersive block model drawing on active learning pedagogy. Based on a synthesis of literature in best practice HE pedagogy and principles, the case study draws on student performance data and senior management staff interviews (N = 5) to outline the key changes necessary for successful HE transformation to deliver increased student pass rates and retention. The findings from this case study indicate that an institutional transformation to an immersive block model requires both a considered change in institutional policy and process as well as the appropriate resourcing of roles, governance committees, technical solutions, and, importantly, communities of practice. Implications for practice at higher education institutions considering reforming their curriculum model are also discussed.

Keywords: student retention, immersive scheduling, block model, curriculum reform, active learning, higher education pedagogy, higher education policy

Procedia PDF Downloads 79