Computer-assisted Language Learning Research Articles

Student’s Perception on the Use of Fun Vocabulary Multimedia in Enhancing Vocabulary Mastery for Elementary Level

The developments of multimedia language learning after Covid Pandemic. With the rise of the Internet and new technology, given students' perception about the use of Fun Vocabulary, their experience in the sector is critical for the successful development of academic programs, since the end user's perception toward the application of information technology is one of the most effective aspects. Hence this study was conducted in purpose to evaluate the students’ perception on the usage of multimedia Fun Vocabulary for grade IV elementary students as the implementation of Computer Assisted Language Learning (CALL). Twenty students filled the questionnaire survey after they experienced learning within the multimedia in case to assess the performance and qualities of a designed multimedia Fun Vocabulary. This study applied quantitative research to measure the users’ evaluation on platform usage through questionnaire which was as the instrument of collecting data. The result found that the students’ agreement showed positive perceptions prevailed over their disagreement or neutral responses in the questionnaire. Fun Vocabulary multimedia was designed and provided a variety of exercises and materials with interesting visual content which can enhance the understanding of vocabulary in English for elementary school level. It was very helpful for their motivation and interest to keep learning English via the platform and practice through its exercises. On the other side, the findings also indicated that the limitation of multimedia that cannot reach the next grade. On the other hand, other findings showed that the materials were very limited and could not reach more list of vocabulary provided in this multimedia. Otherwise, Fun Vocabulary multimedia simply can be used to learn English for students basically and can be useful for teacher as blended learning at class.

A novel sorbent based on electrospun for electrically-assisted solid phase microextraction of six non-steroid anti-inflammatory drugs, followed by quantitation with HPLC-UV in human plasma samples

BackgroundAlthough NSAIDs possess notable therapeutic and pharmaceutical qualities, it's essential to acknowledge that excessive doses can result in toxicity within the human body. Moreover, the importance lies in identifying and measuring their trace amounts. Due to their existence within intricate matrices, the creation of novel electrospun nanofibers as sorbents for electrically-assisted solidphase microextraction (EA-SPME) becomes vital. This innovation caters to the requirement for the effective pre-treatment of NSAID samples, providing a strategic approach to managing the complexities associated with trace quantities found in various matrices. ResultsFirst, polyvinylalcohol/casein/tannic acid/polyaniline/titanium dioxide nanoparticles (PVA/CAS/TA/PANI/TiO2 NPs) electrospun nanofibers were prepared for EA-SPME on pewter rode and then, trace amounts of six NSAIDs (Acetaminophen, Caffeine, Naproxen, Celecoxib, Ibuprofen and mefenamic acid) were adsorbed chemically on these nanofibers. In the next step, the desorption of six NSAIDs was electrochemically done from prepared electrospun nanofibers on a pewter rod which was as working electrode at three electrodes system. Finally, these drugs were quantified from different human plasma samples with HPLC-UV. The synthesis of electrospun nanofibers was confirmed through a series of analytical techniques including field emission-scanning electron microscopy (FE-SEM), energy-dispersive X-ray spectroscopy with elemental mapping analysis (EDX-Mapping), X-ray diffraction (XRD), and Fourier transform-infrared (FT-IR). The optimal percentage of additive compounds to PVA/CAS for electrospinning, as well as the factors influencing adsorption and desorption processes, were determined through both of Design Expert software and MATLAB programming language. SignificanceUnder optimum conditions, the wide linear range was 27–8000 ng mL−1 with R2≥ 0.9897, low detection limits were ranged from 8 to 27.3 ng mL−1 based on S/N = 3 and significant enrichment factors were acquired. The intra-day and inter-day RSDs% were obtained within the 4.51% - 5.68% and 4.28%–5.45%, respectively. Finally, The effectiveness of the EA-SPME-HPLC-UV method was assessed for determining NSAIDs in plasma samples, demonstrating good recoveries ranging from 90.2% to 105.2%.

Individual differences in computer-assisted language learning research

In the era of rapid technological expansion, the integration of various technologies into the process of second and foreign language (L2) learning and teaching has become pervasive, making computer-assisted language learning (CALL) a well-established field (Golonka et al., 2014). There is now a consensus that individual differences (IDs) significantly influence the process and product of L2 learning (Pawlak, 2020). With a plethora of technology-based options and functionalities, CALL provides learners with a high degree of autonomy (Pawlak et al., 2016), making it an environment that is ripe for capitalizing on learners’ individuality (p. 17). However, despite their critical role, IDs have not garnered the attention they genuinely merit in this context (Pawlak, 2022). To address this issue, Mirosław Pawlak and Mariusz Kruk put together the volume Individual Differences in Computer-Assisted Language Learning Research, providing timely and insightful guidelines for the exploration of IDs in CALL and the broader realm of second language acquisition (SLA) research.

Mechanism of Bazhen decoction in the treatment of colorectal cancer based on network pharmacology, molecular docking, and experimental validation.

Bazhen Decoction (BZD) is a common adjuvant therapy drug for colorectal cancer (CRC), although its anti-tumor mechanism is unknown. This study aims to explore the core components, key targets, and potential mechanisms of BZD treatment for CRC. The Traditional Chinese Medicine Systems Pharmacology (TCMSP) was employed to acquire the BZD's active ingredient and targets. Meanwhile, the Drugbank, Therapeutic Target Database (TTD), DisGeNET, and GeneCards databases were used to retrieve pertinent targets for CRC. The Venn plot was used to obtain intersection targets. Cytoscape software was used to construct an "herb-ingredient-target" network and identify core targets. GO and KEGG pathway enrichment analyses were conducted using R language software. Molecular docking of key ingredients and core targets of drugs was accomplished using PyMol and Autodock Vina software. Cell and animal research confirmed Bazhen Decoction efficacy and mechanism in treating colorectal cancer. BZD comprises 173 effective active ingredients. Using four databases, 761 targets related to CRC were identified. The intersection of BZD and CRC yielded 98 targets, which were utilized to construct the "herb-ingredient-target" network. The four key effector components with the most targets were quercetin, kaempferol, licochalcone A, and naringenin. Protein-protein interaction (PPI) analysis revealed that the core targets of BZD in treating CRC were AKT1, MYC, CASP3, ESR1, EGFR, HIF-1A, VEGFR, JUN, INS, and STAT3. The findings from molecular docking suggest that the core ingredient exhibits favorable binding potential with the core target. Furthermore, the GO and KEGG enrichment analysis demonstrates that BZD can modulate multiple signaling pathways related to CRC, like the T cell receptor, PI3K-Akt, apoptosis, P53, and VEGF signaling pathway. In vitro, studies have shown that BZD dose-dependently inhibits colon cancer cell growth and invasion and promotes apoptosis. Animal experiments have shown that BZD treatment can reverse abnormal expression of PI3K, AKT, MYC, EGFR, HIF-1A, VEGFR, JUN, STAT3, CASP3, and TP53 genes. BZD also increases the ratio of CD4+ T cells to CD8+ T cells in the spleen and tumor tissues, boosting IFN-γ expression, essential for anti-tumor immunity. Furthermore, BZD has the potential to downregulate the PD-1 expression on T cell surfaces, indicating its ability to effectively restore T cell function by inhibiting immune checkpoints. The results of HE staining suggest that BZD exhibits favorable safety profiles. BZD treats CRC through multiple components, targets, and metabolic pathways. BZD can reverse the abnormal expression of genes such as PI3K, AKT, MYC, EGFR, HIF-1A, VEGFR, JUN, STAT3, CASP3, and TP53, and suppresses the progression of colorectal cancer by regulating signaling pathways such as PI3K-AKT, P53, and VEGF. Furthermore, BZD can increase the number of T cells and promote T cell activation in tumor-bearing mice, enhancing the immune function against colorectal cancer. Among them, quercetin, kaempferol, licochalcone A, naringenin, and formaronetin are more highly predictive components related to the T cell activation in colorectal cancer mice. This study is of great significance for the development of novel anti-cancer drugs. It highlights the importance of network pharmacology-based approaches in studying complex traditional Chinese medicine formulations.

Computer-Assisted Autonomous Linguistic Learning: A Novel Approach to Second Language Expertise

The invention of the microchip and access to digital devices has altered the way people perceive education and how it is supposed to be practiced. New generations of students, who are the digital natives of today, are more than ready to be educated through the advancements offered by digital learning environments. Language learning is not an exception to these fast-paced technological improvements, and the use of technological devices is slowly altering the way students practice and learn languages. With the advancement of available digital devices, computer-assisted learning has become a reality for today’s learners. Within the context of this research study, an accomplished learner’s think-aloud process and autoethnography function as data to internalize how a learner can transform from a language learner to a language expert through autonomous computer-assisted language learning strategies. This ethnographic study attempts to reveal the keen language learning attitude and self-invented digital learning techniques of an autonomous learner of multiple foreign languages. Thus, it explores and exemplifies the possibility of independent and autonomous language learning without the need for formal education.

Effect of CICARE communication nursing model combined with motivational psychological intervention in patients with post-intensive care unit syndrome.

Post-intensive care syndrome (PICS) is a term used to describe a constellation of new or worsened dysfunctions in the physical, cognitive, or mental health status of critically ill patients after their discharge from the intensive care unit (ICU). These dysfunctions persist beyond the acute phase of illness and have a significant impact on both the patient and their family. Connect, Introduce, Communicate, Ask, Respond, Exit (CICARE) communication advocates that patients should be respected and accepted when receiving medical services. Clinicians should attach importance to the communication mode of feelings, including connection, introduction, communication, ask, response, and exit 6 steps. To assess the impact of CICARE communication on the reduction of anxiety, depression, and post-traumatic stress disorder (PTSD) symptoms in patients transitioning from the ICU to other care settings. This prospective, randomized, controlled study was performed between October 2021 and March 2023. Intensive Care Unit Memory Tool was used to evaluate patients' ICU memory. The Hospital Anxiety and Depression Scale was employed to determine the presence of anxiety or depression symptoms. Impact of Event Scale-Revised was utilized to assess the presence of PTSD. All data were processed and analyzed using R language software version 4.1.0. The measurement data were expressed as mean ± SD, and the t test was used. The count data were analyzed by the χ2 test and expressed as [n (%)]. In total, 248 subjects were included in this study. Among them, 206 were successfully followed up for three months after transfer from the ICU, and 42 cases were lost to follow-up. There was no significant difference in the composition of ICU memory between the two groups. The application of the CICARE communication nursing model combined with the motivational psychological intervention nursing model, as well as the adoption of only the motivational psychological intervention nursing model, demonstrated favorable effects on PICS. Both groups of patients showed a reduction in anxiety scores, depression scores, and PTSD scores following the implementation of these two nursing models. However, it is noteworthy that the experimental group exhibited greater improvements compared to the control group. Our findings suggest that CICARE communication nursing mode may have good influence on relieving PICS.

The Role of Automated Corrective Feedback in Improving EFL Learners' Mastery of the Writing Aspects

Purpose. Automated Corrective Feedback (ACF) is one of the techniques used in EFL writing instruction and assessment. This technique has been widely employed to improve students’ writing skills over the last few decades. Adopting a mixed-method design with data triangulation, this study was conducted to investigate the effect of utilizing WRITER, one of the ACF software, on critical writing aspects including use and mechanics, vocabulary, structural organization, and content.
 Methods and procedure. A pre-post quasi-experimental research design was arranged to collect data from 44 Arab EFL learners assigned to four groups: two peer and self-editing control groups and two automated peer and self-editing experimental groups. While the two control groups were required to perform conventional self- or peer-editing tasks, the two experimental groups used WRITER, an ACF software, to edit both their own essays and those written by peers. Statistical analysis was run to examine differences in the writing aspects across the groups.
 Findings. The analysisиindicated significant differences among these four groups. Students involved in the peer-editing experimental group outperformed all groups on mechanics and structural organization. In addition, the self-editing experimental group did better than other groups in improving their vocabulary. Nonetheless, students in the self-editing control group, who did not utilize any type of ACF to improve their writing, performed better than all other groups in terms of the content aspect. Overall results revealed that ACF could increase the productivity of class time; provide valuable feedback on grammar, word choice, structural organization, use and mechanics and enhance students’ self-confidence in their compositions. These results suggest that ACF has a significant effect on EFL writing and can be an effective tool for improving writing skills. 
 Conclusions. This study examined the impact of ACF of WRITER, a type of computer-assisted language learning tool, on enhancing EFL learners’ knowledge of the writing aspects. The findings of the study have some practical implications in the EFL writing classroom, as they inspire educators to incorporate ACF in self- and peer-editing activities and help their students improve language competency.

Answerability in computer-assisted language learning: a critical examination of social justice research from a decolonial perspective

Abstract In this conceptual article, the author introduces decolonization as an alternative to social justice frameworks. As stakeholders in second language (L2) teaching, the author stresses decolonization as a means for L2 researchers to work against colonial practices in educational research, which negatively impact historically disenfranchised communities. Specifically, Patel’s (Patel, Leigh. 2016. Decolonizing educational research: From ownership to answerability. New York: Routledge) answerability framework is introduced as a practical method to support decolonization in L2 research. The article is made up of four main sections. The first section explains the concept of settler colonialism and highlights how it is ingrained in educational research. In the second section, the author defines decolonization and distinguishes it from the more popular social justice movement. In the third section, the author summarizes four computer-assisted language learning (CALL) papers which were featured in a recent special issue on the topic of social justice. The author then provides a critical analysis of the reviewed studies from a decolonial perspective in the fourth and final section, while also suggesting ways in which researchers and educators can re-orient their work towards decolonization.

Artificial intelligence technologies and applications for language learning and teaching

Abstract Artificial intelligence (AI) is changing many aspects of education and is gradually being introduced to language education. This article reviews the literature to examine main trends and common findings in relation to AI technologies and applications for second and foreign language learning and teaching. With special reference to computer-assisted language learning (CALL), the article explores natural language processing (NLP), data-driven learning (DDL), automated writing evaluation (AWE), computerized dynamic assessment (CDA), intelligent tutoring systems (ITSs), automatic speech recognition (ASR), and chatbots. It contributes to discussions on understanding and using AI-supported language learning and teaching. It suggests that AI will be continuously integrated into language education and AI technologies and applications will have a profound impact on language learning and teaching. Language educators need to ensure that AI is effectively used to support language learning and teaching in AI-powered contexts. More rigorous research on AI-supported language learning and teaching is recommended to maximise second and foreign language learning and teaching with AI.

Linear programming the Ramsar convention's criterion IV (case study: Shadegan Wetland, West Asia).

Wetland ecosystems provide critical ecological services to both humans and wildlife. However, many wetlands around the world are facing challenges that threaten their ecological integrity and jeopardize their status as Ramsar Convention sites. The Shadegan Wetland, a Ramsar site since 1975, has been on the Montreux Record since 1993 due to changing conditions in the wetland. This study aims to utilize linear programming (LP) techniques to evaluate the status of criterion IV of the Ramsar Convention within the Shadegan Wetland. Using mathematical language and Excel software, we defined criterion IV and developed a linear model. The Lingo software was employed to verify the model by setting constraints for proxy variables (X variables). We selected constraints based on extreme climatic conditions, such as energy and water limitations, during the study period while considering the trend of each variable. By identifying effective interventions for promoting sustainable use of the wetland while preserving its ecological balance, the LP can support the efforts to re-nominate the Shadegan Wetland as a Ramsar site. Considering the critical conditions, the lowest value of Z in the studied period unravels the critical year as the target. Based on the result, 2015 with the lowest value of the Z index (-0.36) was identified as the critical year in the entire study period starting from 2001-2019. In the critical year itself, the population of birds equals 50,000 birds, while the average population of birds over the course of the past 20 years was nearly 37,000 birds.

CREATIVITY: SCULPTING THROUGH DIGITAL PLATFORMS AND NATIONAL EDUCATIONAL POLICY

Education as a platform makes learners develop their knowledge and makes them reach creative levels. It also makes the learner face the world with confidence. Education as a system has undergone many changes with the passage of time. Covid -19 had brought a major shift in the education system and the mode of education. It can be observed that learners from all over the world had shifted to Computer Assisted Language Learning (CALL) and Mobile Assisted Language Learning (MALL). The mode of regular chalk and talk method is completely shifted to Distance learning. The major shift to "MALL" for educational purposes was indeed tough for both the instructors and the learners. So, the major shift can be observed in the field of Ed-tech applications, language learning, and educational policy too., where learners preferred to enroll in online platforms for their growth simultaneously with enrolment in universities. Taking this into consideration the researchers try to examine the growth in the usage of Ed-tech applications with linkage to educational policy 2020. This paper also examines the advantages of online Ed-tech and digital applications.

Exosomal NOX1 promotes tumor-associated macrophage M2 polarization-mediated cancer progression by stimulating ROS production in cervical cancer: a preliminary study

BackgroundCervical cancer the fourth most frequently diagnosed cancer and the fourth leading cause of cancer death in women, with an estimated 604,000 new cases and 342,000 deaths worldwide in 2020 for high rates of recurrence and metastasis. Identification of novel targets could aid in the prediction and treatment of cervical cancer. NADPH oxidase 1 (NOX1) gene-mediated production of reactive oxygen species (ROS) could induce migration and invasion of cervical cancer cells. Tumor-associated macrophages (TAMs) play important roles in cervical cancer. Tumor cell-derived exosomes mediate signal transduction between the tumor and tumor microenvironment. Elucidation of the mechanisms of NOX1-carrying exosomes involved in the regulation of TAMs may provide valuable insights into the progression of cervical cancer.MethodsUniformly standardized mRNA data of pan-carcinoma from the UCSC database were downloaded. Expression of NOX1 in tumor and adjacent normal tissues for each tumor type was calculated using R language software and significant differences were analyzed. SNP data set were downloaded for all TCGA samples processed using MuTect2 software from GDC. Cell experiment and animal tumor formation experiment were used to evaluate whether exosomal NOX1 stimulating ROS production to promote M2 polarization of TAM in cervical cancer.ResultsNOX1 is highly expressed with a low mutational frequency in pan-carcinoma. Upregulation of NOX1 may be associated with infiltration of M2-type macrophages in cervical cancer tissues, and NOX1 promotes malignant features of cervical cancer cells by stimulating ROS production. Exosomal NOX1 promotes M2 polarization of by stimulating ROS production. Exosomal NOX1 enhances progression of cervical cancer and M2 polarization in vivo by stimulating ROS production.ConclusionExosomal NOX1 promotes TAM M2 polarization-mediated cancer progression through stimulating ROS production in cervical cancer.

Contrast-agent-based perfusion MRI code repository and testing framework: ISMRM Open Science Initiative for Perfusion Imaging (OSIPI).

Software has a substantial impact on quantitative perfusion MRI values. The lack of generally accepted implementations, code sharing and transparent testing reduces reproducibility, hindering the use of perfusion MRI in clinical trials. To address these issues, the ISMRM Open Science Initiative for Perfusion Imaging (OSIPI) aimed to establish a community-led, centralized repository for sharing open-source code for processing contrast-based perfusion imaging, incorporating an open-source testing framework. A repository was established on the OSIPI GitHub website. Python was chosen as the target software language. Calls for code contributions were made to OSIPI members, the ISMRM Perfusion Study Group, and publicly via OSIPI websites. An automated unit-testing framework was implemented to evaluate the output of code contributions, including visual representation of the results. The repository hosts 86 implementations of perfusion processing steps contributed by 12 individuals or teams. These cover all core aspects of DCE- and DSC-MRI processing, including multiple implementations of the same functionality. Tests were developed for 52 implementations, covering five analysis steps. For T1 mapping, signal-to-concentration conversion and population AIF functions, different implementations resulted in near-identical output values. For the five pharmacokinetic models tested (Tofts, extended Tofts-Kety, Patlak, two-compartment exchange, and two-compartment uptake), differences in output parameters were observed between contributions. The OSIPI DCE-DSC code repository represents a novel community-led model for code sharing and testing. The repository facilitates the re-use of existing code and the benchmarking of new code, promoting enhanced reproducibility in quantitative perfusion imaging.

On low rank fusion rings

We present a method to generate all fusion rings of a specific rank and multiplicity. This method generated exhaustive lists of fusion rings up to order 9 for several multiplicities. We introduce a class of non-commutative fusion rings based on a group with transitive action on a set. This construction generalises the Tambara–Yamagami (TY) and Haagerup-Izumi (HI) fusion rings. We give an example of two such rings that are categorifiable and not of TY or HI type. The structure of non-commutative fusion rings with a subgroup is reviewed, and the one- and two-particle extensions of groups are classified. A website containing data on fusion rings is introduced, and an overview of a Wolfram Language package for working with these rings is given. We also applied several categorifiability criteria to the fusion rings. We provide a table of all multiplicity-free fusion rings up to rank 9 with info on the categorifiability of each ring.

The road System travelled: Five decades of technology in language education

Given that System is an internationally recognized journal dedicated to “the applications of educational technology and applied linguistics to problems of foreign language teaching and learning”, it is interesting to examine the role that technology has played in the journal’s evolution. Furthermore, investigating the interdependence between the development of computer-assisted language learning (CALL) and the evolution of System could provide valuable insights on the dynamic relationship between the advancements in educational technology and the scholarly discourse within System, illustrating how technological advancements have influenced the content and focus of the journal over time.

The Word’s Unity of Existence

Linguists do not agree on the origin of human language or the reasons for the human species’ unique possession of language faculty on the path of evolution. Any theoretical approach in cognitive science and linguistics eventually faces an impasse in its quest for the origin of language when reaching the realm of consciousness and mind which requires an accessibility beyond the physical inquiry. This article introduces Mohammad Ali Taheri’s theory of consciousness, T-Consciousness, as the gateway to the origin of language in the human mind. T-Consciousness stands for the non-material and non-energetic constituent of the universe, the third fundamental element which generates both matter and energy. Taheri theorizes that human beings have detected language rather than inventing it, following the Language Software’s primary activation in the human mind through an inter-T-Consciousness-level connection that extracts Fara-lingual information and adapts it into language. This study investigates Taheri’s language theory in relation to Chomsky’s UG theory, and offers a diversifying approach to UG theory, biolinguistics and psycholinguistics. The article introduces the Word’s Unity of Existence/ Vahdat-e Vojood-e Kalameh and conceptualizes the Unified Body of Languages, initiating an interdisciplinary discourse to revisit cognitive science, phenomenology, hermeneutics, and intertextuality.

Identification of the key mechanisms of action of Si-Ni-San in uveitis using bioinformatics and network pharmacology.

Uveitis is an eye disease with a high rate of blindness, whose pathogenesis is not completely understood. Si-Ni-San (SNS) has been used as a traditional medicine to treat uveitis in China. However, its mechanism of action remains unclear. This study explored the potential mechanisms of SNS in the treatment of uveitis through network pharmacology and bioinformatics. Using R language and Perl software, the active components and predicted targets of SNS, as well as the related gene targets of uveitis, were mined through the Traditional Chinese Medicine Systems Pharmacology, Therapeutic Target, Gene Expression Omnibus, GeneCards, and DrugBank databases. The network diagram of active components and intersection targets was constructed using Cytoscape software and the String database. The CytoNCA plug-in was used to conduct topological analysis on the network diagram and screen out the core compounds and key targets. The genes were analyzed for Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment. Chemoffice, Pymol, AutoDock, and Vina were used to analyze the molecular docking of key targets and core compounds of diseases through the PubChem database. JUN, RELA, and MAPK may play important roles in the treatment of uveitis by SNS. Kyoto encyclopedia of genes and genomes pathway enrichment analysis showed that core genes were mainly concentrated in MAPK, toll-like receptor, tumor necrosis factor, and nucleotide oligomerization domain-like receptor signaling pathways. In addition, molecular docking results showed that the bioactive compounds (kaempferol, luteolin, naringin, and quercetin) exhibited good binding ability to JUN, RELA, and MAPK. Based on these findings, SNS exhibits multi-component and multi-target synergistic action in the treatment of uveitis, and its mechanism may be related to anti-inflammatory and immune regulation.

Rise of artificial general intelligence: risks and opportunities.

Artificial intelligence is making extraordinary progress with an unprecedented rate, reaching and surpassing human capabilities in many tasks previously considered unattainable by machines, as language translation, music composition, object detection, medical diagnoses, software programming, and many others. Some people are excited about these results, while others are raising serious concerns for possible negative impacts in our society. This article addresses several questions that are often raised about intelligent machines: Will machines ever surpass human intellectual capacities? What will happen next? What will be the impact in our society? What are the jobs that artificial intelligence puts at risk? Reasoning about these questions is of fundamental importance to predict possible future scenarios and prepare ourselves to face the consequences.

An ensemble-based framework for mispronunciation detection of Arabic phonemes

Determination of mispronunciations and ensuring feedback to users are maintained by computer-assisted language learning (CALL) systems. In this work, we introduce an ensemble model that defines the mispronunciation of Arabic phonemes and assists learning of Arabic, effectively. To the best of our knowledge, this is the very first attempt to determine the mispronunciations of Arabic phonemes employing ensemble learning techniques and conventional machine learning models, comprehensively. In order to observe the effect of feature extraction techniques, mel-frequency cepstrum coefficients (MFCC), and Mel-spectrogram are blended with each learning algorithm. To show the success of proposed model, 29 letters in the Arabic phonemes, 8 of which are hafiz, are voiced by a total of 11 different person. The amount of data set has been enhanced employing the methods of adding noise, time shifting, time stretching, pitch shifting. Extensive experiment results demonstrate that the utilization of voting classifier as an ensemble algorithm with Mel-spectrogram feature extraction technique exhibits remarkable classification result with 95.9% of accuracy.

Pragmatic evidence of cross-language link detection: A systematic literature review

There is a rising trend for heterogeneous software applications involving multilingual source code. The key focus of reverse engineers is to unravel the cross-language links (XLLs) and their dependencies. This study aims to perform a systematic literature review (SLR) to compile different approaches, tools, techniques, and shortcomings of such techniques and understand the XLLs and their dependencies while performing reverse engineering on state-of-the-art software applications. This SLR selects 76 primary studies and uses them to create a ’go-to’ literature database, where professionals from software engineering could find all the content pertinent to the analysis and XLL detection for major multilingual applications like Java enterprise applications, Android applications, etc. It has been observed that traditional source code analysis mechanisms to reverse engineer contemporary software applications face scores of problems and limitations that need to be addressed. To assist the community in the above-mentioned goal, a general schema with definitions of XLLs and associated concepts is furnished. This study provides an SLR on XLLs, comprehensive taxonomy called cross-language analysis, which incorporates all the methods for XLL detection in multilingual source code. By pursuing future directions suggested in the end, researchers and practitioners can advance the field of multilingual applications; such as Enterprise resource planning (ERP) solutions, and cross-language software corpora, leading to improved software development practices and better understanding of language interactions in multilingual environments. The research data provided in the survey presents a comprehensive analysis of the complexities involved in working with diverse programming languages and frameworks, offering valuable insights for language technology researchers, software developers, academics, and decision-makers. This integration will enable them to identify and manage dependencies across diverse languages, leading to more efficient and reliable multilingual software systems.