Search results for: wolof word classification

Authors: Svetlana Ignatjeva, Jelena Slesareva

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The aim of the study is development and adaptation of the method to analyze and quantify the indicators characterizing the relationship between a company and its employees. Diagnostics of such indicators is one of the most complex and actual issues in psychology of labour. The offered method is based on the questionnaire; its indicators reflect cognitive, affective and connotative components of socio-psychological attitude of employees to be as efficient as possible in their professional activities. This approach allows measure not only the selected factors but also such parameters as cognitive and behavioural dissonances. Adaptation of the questionnaire includes factor structure analysis and suitability analysis of phenomena indicators measured in terms of internal consistency of individual factors. Structural validity of the questionnaire was tested by exploratory factor analysis. Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. Factor analysis allows reduce dimension of the phenomena moving from the indicators to aggregative indexes and latent variables. Aggregative indexes are obtained as the sum of relevant indicators followed by standardization. The coefficient Cronbach's Alpha was used to assess the reliability-consistency of the questionnaire items. The two-step cluster analysis in the space of allocated factors allows classify employees according to their attitude to work in the company. The results of psychometric testing indicate possibility of using the developed technique for the analysis of employees’ attitude towards their work in companies and development of recommendations on their optimization.

Keywords: involved in the organization, loyalty, organizations, method

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Authors: Rodolfo Lorbieski, Silvia Modesto Nassar

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Many supervised machine learning tasks require decision making across numerous different classes. Multi-class classification has several applications, such as face recognition, text recognition and medical diagnostics. The objective of this article is to analyze an adapted method of Stacking in multi-class problems, which combines ensembles within the ensemble itself. For this purpose, a training similar to Stacking was used, but with three levels, where the final decision-maker (level 2) performs its training by combining outputs from the tree-based pair of meta-classifiers (level 1) from Bayesian families. These are in turn trained by pairs of base classifiers (level 0) of the same family. This strategy seeks to promote diversity among the ensembles forming the meta-classifier level 2. Three performance measures were used: (1) accuracy, (2) area under the ROC curve, and (3) time for three factors: (a) datasets, (b) experiments and (c) levels. To compare the factors, ANOVA three-way test was executed for each performance measure, considering 5 datasets by 25 experiments by 3 levels. A triple interaction between factors was observed only in time. The accuracy and area under the ROC curve presented similar results, showing a double interaction between level and experiment, as well as for the dataset factor. It was concluded that level 2 had an average performance above the other levels and that the proposed method is especially efficient for multi-class problems when compared to binary problems.

Keywords: stacking, multi-layers, ensemble, multi-class

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Authors: Zhi Hao Chow, Cian Mulligan, Jack Walsh, Antonio Garzon Vico, Dimitar Krastev

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Drug development is resource-intensive, time-consuming, and increasingly expensive with each developmental stage. The success rates of drug development are also relatively low, and the resources committed are wasted with each failed candidate. As such, a reliable method of predicting the success of drug development is in demand. The hypothesis was that some examples of failed drug candidates are pushed through developmental pipelines based on false confidence and may possess common linguistic features identifiable through sentiment analysis. Here, the concept of using text analysis to discover such features in research publications and investor reports as predictors of success was explored. R studios were used to perform text mining and lexicon-based sentiment analysis to identify affective phrases and determine their frequency in each document, then using SPSS to determine the relationship between our defined variables and the accuracy of predicting outcomes. A total of 161 publications were collected and categorised into 4 groups: (i) Cancer treatment, (ii) Neurodegenerative disease treatment, (iii) Vaccines, and (iv) Others (containing all other drugs that do not fit into the 3 categories). Text analysis was then performed on each document using 2 separate datasets (BING and AFINN) in R within the category of drugs to determine the frequency of positive or negative phrases in each document. A relative positivity and negativity value were then calculated by dividing the frequency of phrases with the word count of each document. Regression analysis was then performed with SPSS statistical software on each dataset (values from using BING or AFINN dataset during text analysis) using a random selection of 61 documents to construct a model. The remaining documents were then used to determine the predictive power of the models. Model constructed from BING predicts the outcome of drug performance in clinical trials with an overall percentage of 65.3%. AFINN model had a lower accuracy at predicting outcomes compared to the BING model at 62.5% but was not effective at predicting the failure of drugs in clinical trials. Overall, the study did not show significant efficacy of the model at predicting outcomes of drugs in development. Many improvements may need to be made to later iterations of the model to sufficiently increase the accuracy.

Keywords: data analysis, drug development, sentiment analysis, text-mining

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Authors: Pushpinder Syal

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Literary writing carries the stamp of the current language of its time. In translating such texts, it becomes a challenge to capture such reflections which may be evident at several levels: the level of dialectal use of language by characters in stories, the alterations in syntax as tools of writers’ individual stylistic choices, the insertion of quasi-proverbial and gnomic utterances, and even the level of the pragmatics of narrative discourse. Discourse strategies may differ between earlier and later texts, reflecting changing relationships between narrators and readers in changed cultural and social contexts. This paper is a consideration of these features by an approach that combines historicity with a description, contextualizing language change within a discourse framework. The process of translating a collection of writings of Punjabi literature spanning 100 years was undertaken for this study and it was observed that the factor of the historicity of language was seen to play a role. While intended for contemporary readers, the translation of literature over the span of a century poses the dual challenge of needing to possess both accessibility and immediacy as well as adherence to the 'old world' styles of communicating and narrating. The linguistic changes may be observed in a more obvious sense in the difference of diction and word formation – with evidence of more hybridized and borrowed forms in modern and contemporary writings, as compared to the older writings. The latter not only contain vestiges of proverbs and folk sayings, but are also closer to oral speech styles. These will be presented and analysed in the form of chronological listing and by these means, the social process of translation from orality to written text can be seen as traceable in the above-mentioned works. More subtle and underlying shifts can be seen through the analysis of speech acts and implicatures in the same literature, in which the social relationships underlying language use are evident as discourse systems of belief and understanding. They present distinct shifts in worldview as seen at different points in time. However, some continuities of language and style are also clearly visible, and these aid the translator in putting together a set of thematic links which identify the literature of a region and community, and constitute essential outcomes in the effort to preserve its distinctive nature.

Keywords: cultural change, dialect, historicity, stylistic variation

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Authors: Sagri Sharma

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Analysis of diseases integrating multi-factors increases the complexity of the problem and therefore, development of frameworks for the analysis of diseases is an issue that is currently a topic of intense research. Due to the inter-dependence of the various parameters, the use of traditional methodologies has not been very effective. Consequently, newer methodologies are being sought to deal with the problem. Supervised Learning Algorithms are commonly used for performing the prediction on previously unseen data. These algorithms are commonly used for applications in fields ranging from image analysis to protein structure and function prediction and they get trained using a known dataset to come up with a predictor model that generates reasonable predictions for the response to new data. Gene expression profiles generated by DNA analysis experiments can be quite complex since these experiments can involve hypotheses involving entire genomes. The application of well-known machine learning algorithm - Support Vector Machine - to analyze the expression levels of thousands of genes simultaneously in a timely, automated and cost effective way is thus used. The objectives to undertake the presented work are development of a methodology to identify genes relevant to Hepatocellular Carcinoma (HCC) from gene expression dataset utilizing supervised learning algorithms and statistical evaluations along with development of a predictive framework that can perform classification tasks on new, unseen data.

Keywords: artificial intelligence, biomarker, gene expression datasets, hepatocellular carcinoma, machine learning, supervised learning algorithms, support vector machine

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Authors: Dhiraj Dolai, Rupayan Bhattacharya

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In this study, a comparison of Range Of Motion (ROM) of middle and long-distance runners and swimmers has been made. The mobility of the various joints is essential for the quick movement of any sportsman. Knowledge of a ROM helps in preventing injuries, in repeating the movement, and in generating speed and power. ROM varies among individuals, and it is influenced by factors such as gender, age, and whether the motion is performed actively or passively. ROM for running and swimming, both performed with due consideration on speed, plays an important role. The time of generation of speed and mobility of the particular joints are very important for both kinds of athletes. The difficulties that happen during running and swimming in the direction of motion is changed. In this study, data were collected for a total of 102 subjects divided into three groups: control group (22), middle and long-distance runners (40), and swimmers (40), and their ages are between 12 to 18 years. The swimmers have higher ROM in shoulder joint flexion, extension, abduction, and adduction movement. Middle and long-distance runners have significantly greater ROM from Control Group in the left shoulder joint flexion with a 5.82 mean difference. Swimmers have significantly higher ROM from the Control Group in the left shoulder joint flexion with 24.84 mean difference and swimmers have significantly higher ROM from the Middle and Long distance runners in left shoulder flexion with 19.02 mean difference. The picture will be clear after a more detailed investigation.

Keywords: range of motion, runners, swimmers, significance

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Authors: Durata Haciu, Elif Sena Tekin, Gokce Ozturk, Patricia Ramey Balcı

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Coastal zones are under increasing threat due to anthropogenic activities that introduce considerable pollutants such as heavy metals into marine ecosystems. As part of a larger experimental study examining species responses to contaminated marine sediments, surface sediments (top 5cm) were analysed for major trace elements at three locations in Istanbul Straight. Samples were randomly collected by divers (May 2018) using hand-corers from Istinye (n=4), Garipce (n=10) and Poyrazköy (n=6), at water depths of 4-8m. Twelve metals were examined: As, arsenic; Pb, lead; Cd, cadmium; Cr, chromium; Cu, Copper; Fe, Iron; Ni, Nickel; Zn, Zinc; V, vanadium; Mn, Manganese; Ba, Barium; and Ag, silver by wavelength-dispersive X-ray fluorescence spectrometry (WDXRF) and Inductively Coupled Plasma/Mass Spectroscopy (ICP/MS). Preliminary results indicate that the average concentrations of metals (mg kg⁻¹) varied considerably among locations. In general, concentrations were relatively lower at Garipce compared to either Istinye or Poyrazköy. For most metals mean concentrations were highest at Poyrazköy and Ag and Cd were below detection limits (exception= Ag in a few samples). While Cd and As were undetected in all stations, the concentrations of Fe and Ni fall in the criteria of moderately polluted range and the rest of the metals in the range of low polluted range as compared to Effects Range Low (ERL) and Effects Range median (ERM) values determined by US Environmental Protection Agency (EPA).

Keywords: effect-range classification, ICP/MS, marine sediments, XRF

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Authors: Taghreed Alghamdi, Wendy Hall, David Millard

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Massive Open Online Courses (MOOCs) have recently gained widespread interest in the academic world, starting a wide range of discussion of a number of issues. One of these issues, using MOOCs in teaching and learning in the higher education by integrating MOOCs’ contents with traditional face-to-face activities in blended learning format, is called blended MOOCs (bMOOCs) and is intended not to replace traditional learning but to enhance students learning. Most research on MOOCs has focused on students’ perception and institutional threats whereas there is a lack of published research on academics’ experiences and practices. Thus, the first aim of the study is to develop a classification of blended MOOCs models by conducting a systematic literature review, classifying 19 different case studies, and identifying the broad types of bMOOCs models namely: Supplementary Model and Integrated Model. Thus, the analyses phase will emphasize on these different types of bMOOCs models in terms of adopting MOOCs by lecturers. The second aim of the study is to improve the understanding of lecturers’ acceptance of bMOOCs by investigate the factors that influence academics’ acceptance of using MOOCs in traditional learning by distributing an online survey to lecturers who participate in MOOCs platforms. These factors can help institutions to encourage their lecturers to integrate MOOCs with their traditional courses in universities.

Keywords: acceptance, blended learning, blended MOOCs, higher education, lecturers, MOOCs, professors

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Authors: Ali Zazi, Ouiza Cherifi

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The Catalysts materials Ni-SiO₂, Ni-Co-SiO₂ and Ni-Ce-SiO₂ were synthetized by classical method impregnation and supported by silica. This involves combing the silica with an adequate rate of the solution of nickel nitrates, or nickel nitrate and cobalt nitrate, or nickel nitrate and cerium nitrate, mixed, dried and calcined at 700 ° c. These catalysts have been characterized by different physicochemical analysis techniques. The atomic absorption spectrometry indicates that the real contents of nickel, cerium and cobalt are close to the theoretical contents previously assumed, which let's say that the nitrate solutions have impregnated well the silica support. The BET results show that the surface area of the specific surfaces decreases slightly after impregnation with nickel nitrates or Co and Ce metals and a further slight decrease after the reaction. This is likely due to coke deposition. X-ray diffraction shows the presence of the different SiO₂ and NiO phases for all catalysts—theCoO phase for that promoted by Co and the Ce₂O₂ phase for that promoted by Ce. The methane steam reforming reaction was carried out on a quartz reactor in a fixed bed. Reactants and products of the reaction were analyzed by a gas chromatograph. This study shows that the metal addition of Cerium or Cobalt improves the majority of the catalytic performance of Ni for the steam reforming reaction of methane. And we conclude the classification of our Catalysts in order of decreasing activity and catalytic performances as follows: Ni-Ce / SiO₂ >Ni-Co / SiO₂> Ni / SiO₂ .

Keywords: cerium, cobalt, heterogeneous catalysis, hydrogen, methane, steam reforming, synthesis gas

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Authors: Maggie Hui

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Risk management is not a new concept; however, it is an uncharted area as applied to the translation process and translator training. Serving as one of the self-discovery activities in their practicum course, a two-cycle experiment was carried out with a class of 13 MA translation students with an attempt to explore their risk management while translating in a simulated setting that involves translator-client relations. To test the effects of the main variable of translators’ interaction with the simulated clients, the researcher employed control-group translators and two experiment groups (with Group A being the translator in Cycle 1 and the client in Cycle 2, and Group B on the client position in Cycle 1 and the translator position in Cycle 2). Experiment cycle 1 aims to explore if there would be any behavioral difference in risk management between translators with interaction with the simulated clients, i.e. experiment group A, and their counterparts without such interaction, i.e. control group. Design of Cycle 2 concerns the order of playing different roles of the translator and client in the experiment, and provides information to compare behavior of translators of the two experiment groups. Since this is process-oriented research, it is necessary to hypothesize what was happening in the translators’ minds. The researcher made use of a user-friendly screen-voice recording freeware to record subjects’ screen activities, including every word the translator typed and every change they made to the rendition, the websites they browsed and the reference tools they used, in addition to the verbalization of their thoughts throughout the process. The research observes the translation procedures subjects considered and finally adopted, and looks into the justifications for their procedures, in order to interpret their risk management. The qualitative and quantitative results of this study have some implications for translator training: (a) the experience of being a client seems to reinforce the translator’s risk aversion; (b) the use of role-playing simulation can empower students’ learning by enhancing their attitudinal or psycho-physiological competence, interpersonal competence and strategic competence; and (c) the screen-voice recordings serve as a helpful tool for learners to reflect on their rendition processes, i.e. what they performed satisfactorily and unsatisfactorily while translating and what they could do for improvement in future translation tasks.

Keywords: risk management, screen-voice recordings, simulated translator-client relations, translation pedagogy, translation process-oriented research

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Authors: Deborah Idowu

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This research delves into the effectiveness of explicitly teaching productive non-cognate French suffixes to English beginner learners of the French language. It is widely accepted that cognates, especially orthographic ones, can be inferred by learners from their first language (in this case, English). The same is the case for derived French words with cognate suffixes, provided the learner is familiar with the lemma, which can either be cognate or non-cognate. However, the same cannot be said for derived French words with non-cognate suffixes. These suffixes often pose challenges to learners, even when the base word is familiar to them. The primary goal of this research is to enhance the vocabulary comprehension and expansion of English-speaking beginners in French by focusing on the recognition of derived French words that may not align with their L1 knowledge. The methodology employed in this study of derivational morphology involves an experimental group receiving explicit instruction on productive non-cognate suffixes, while a control group does not. By utilizing confidence ratings and other analytical tools, the analysis aims to measure the impact of this targeted instruction on the learners' ability to understand and incorporate non-cognate suffixes into their French vocabulary. Through this experimental approach, the research seeks to provide valuable insights into how explicit instruction on non-cognate suffixes can benefit beginner French learners, ultimately aiding them in navigating the intricacies of French derivational morphology. The objectives of this research are as follows: i. to investigate the impact of explicitly teaching productive non-cognate suffixes on the vocabulary comprehension and expansion of beginner learners of the French language; ii. to assess the effectiveness of targeted instruction on non-cognate suffixes in aiding English-speaking learners in recognizing and understanding derived French words that may not align with their native language knowledge, iii. to compare the vocabulary acquisition and retention of beginner French learners who receive explicit instruction on non-cognate suffixes with those who do not to determine the effectiveness of this instructional approach, iv. to analyze the confidence ratings and other analytical methods to gauge the learners' ability to integrate non-cognate suffixes into their French vocabulary and comprehend the meaning of derived words more effectively, v. to contribute insights into how explicit instruction on non-cognate suffixes can enhance the overall language learning experience for beginner learners of French, particularly in the area of French derivational morphology.

Keywords: suffixes, derivational morphology, non-cognates, vocabulary acquisition, French language learners

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Authors: Ashish Jaiswal, Ashwin Ramesh Babu, Mohammad Zaki Zadeh, Fillia Makedon, Glenn Wylie

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Functional magnetic resonance imaging (fMRI) is a neuroimaging technique that records neural activations in the brain by capturing the blood oxygen level in different regions based on the task performed by a subject. Given fMRI data, the problem of predicting the state of cognitive fatigue in a person has not been investigated to its full extent. This paper proposes tackling this issue as a multi-class classification problem by dividing the state of cognitive fatigue into six different levels, ranging from no-fatigue to extreme fatigue conditions. We built a spatio-temporal model that uses convolutional neural networks (CNN) for spatial feature extraction and a long short-term memory (LSTM) network for temporal modeling of 4D fMRI scans. We also applied a self-supervised method called MoCo (Momentum Contrast) to pre-train our model on a public dataset BOLD5000 and fine-tuned it on our labeled dataset to predict cognitive fatigue. Our novel dataset contains fMRI scans from Traumatic Brain Injury (TBI) patients and healthy controls (HCs) while performing a series of N-back cognitive tasks. This method establishes a state-of-the-art technique to analyze cognitive fatigue from fMRI data and beats previous approaches to solve this problem.

Keywords: fMRI, brain imaging, deep learning, self-supervised learning, contrastive learning, cognitive fatigue

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Authors: Jeevan Jyoti Mohindroo, Umesh Kumar Garg

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The district of Tarntaran is located25 km south of Amritsar city in Punjab State of Northwestern India. It is 5059 Sq. Km in area. It is surrounded by Amritsar in the North, Kapurthala in the East, and Ferozepur in the South and Pakistan in the West. Patti Town is a municipal council of the Tarntaran district of the Indian state of Punjab, located 45 km from Amritsar its geographical coordinates are 310 16' 51" north to 740 51' 25" East Longitude. The town spreads over an area of 50sq. Km. Moisture content is very less in the air, falling within the semiarid region and frequently facing water scarcity as well as water quality problems. The major sources of employment are agriculture, horticulture and animal husbandry engaging almost 80% of the workforce. Water samples are collected from 400 locations in 20 villages on the Patti –Khem Karan highway with 20 samples from each village, and were subjected to analysis of chemical characteristics. The type of water that predominates in the study area is Ca-Mg-HCO3 type, based on hydro-chemical analysis. Besides, suitability of water for irrigation is evaluated based on the sodium adsorption ratio (SAR), residual sodium carbonate, sodium percent and salinity hazard. Other Physico-chemical parameters such as pH, TDS, conductance, etc. were also determined using a water analysis kit. Analysis of water samples for heavy metal analysis was also carried out in the present study.

Keywords: groundwater, chemical classification, SAR, RSC, USSL diagram

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Authors: Yu-Hsiu Lin, Wen-Chun Lin, Yen-Chang Cheng, Chia-Ju Yeh, Yu-Chuan Chen, Tai-You Li

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Demand-Side Management (DSM) has the potential to reduce electricity costs and carbon emission, which are associated with electricity used in the modern society. A home Energy Management System (EMS) commonly used by residential consumers in a down-stream sector of a smart grid to monitor, control, and optimize energy efficiency to domestic appliances is a system of computer-aided functionalities as an energy audit for residential DSM. Implementing fault detection and classification to domestic appliances monitored, controlled, and optimized is one of the most important steps to realize preventive maintenance, such as residential air conditioning and heating preventative maintenance in residential/industrial DSM. In this study, a cloud intelligence-based green EMS that comes up with an Internet of Things (IoT) technology stack for residential DSM is developed. In the EMS, Arduino MEGA Ethernet communication-based smart sockets that module a Real Time Clock chip to keep track of current time as timestamps via Network Time Protocol are designed and implemented for readings of load phenomena reflecting on voltage and current signals sensed. Also, a Network-Attached Storage providing data access to a heterogeneous group of IoT clients via Hypertext Transfer Protocol (HTTP) methods is configured to data stores of parsed sensor readings. Lastly, a desktop computer with a WAMP software bundle (the Microsoft® Windows operating system, Apache HTTP Server, MySQL relational database management system, and PHP programming language) serves as a data science analytics engine for dynamic Web APP/REpresentational State Transfer-ful web service of the residential DSM having globally-Advanced Internet of Artificial Intelligence (AI)/Computational Intelligence. Where, an abstract computing machine, Java Virtual Machine, enables the desktop computer to run Java programs, and a mash-up of Java, R language, and Python is well-suited and -configured for AI in this study. Having the ability of sending real-time push notifications to IoT clients, the desktop computer implements Google-maintained Firebase Cloud Messaging to engage IoT clients across Android/iOS devices and provide mobile notification service to residential/industrial DSM. In this study, in order to realize edge intelligence that edge devices avoiding network latency and much-needed connectivity of Internet connections for Internet of Services can support secure access to data stores and provide immediate analytical and real-time actionable insights at the edge of the network, we upgrade the designed and implemented smart sockets to be embedded AI Arduino ones (called embedded AIduino). With the realization of edge analytics by the proposed embedded AIduino for data analytics, an Arduino Ethernet shield WizNet W5100 having a micro SD card connector is conducted and used. The SD library is included for reading parsed data from and writing parsed data to an SD card. And, an Artificial Neural Network library, ArduinoANN, for Arduino MEGA is imported and used for locally-embedded AI implementation. The embedded AIduino in this study can be developed for further applications in manufacturing industry energy management and sustainable energy management, wherein in sustainable energy management rotating machinery diagnostics works to identify energy loss from gross misalignment and unbalance of rotating machines in power plants as an example.

Keywords: demand-side management, edge intelligence, energy management system, fault detection and classification

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Authors: Aliaksandr Huminski

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Semantic Role Labeling (SRL) as shallow semantic parsing approach includes recognition and labeling arguments of a verb in a sentence. Verb participants are linked with specific semantic roles (Agent, Patient, Instrument, Location, etc.). Thus, SRL can answer on key questions such as ‘Who’, ‘When’, ‘What’, ‘Where’ in a text and it is widely applied in dialog systems, question-answering, named entity recognition, information retrieval, and other fields of NLP. However, SRL has the following flaw: Two sentences with identical (or almost identical) meaning can have different semantic role structures. Let consider 2 sentences: (1) John put butter on the bread. (2) John buttered the bread. SRL for (1) and (2) will be significantly different. For the verb put in (1) it is [Agent + Patient + Goal], but for the verb butter in (2) it is [Agent + Goal]. It happens because of one of the most interesting and intriguing features of a verb: Its ability to capture participants as in the case of the verb butter, or their features as, say, in the case of the verb drink where the participant’s feature being liquid is shared with the verb. This capture looks like a total fusion of meaning and cannot be decomposed in direct way (in comparison with compound verbs like babysit or breastfeed). From this perspective, SRL looks really shallow to represent semantic structure. If the key point in semantic representation is an opportunity to use it for making inferences and finding hidden reasons, it assumes by default that two different but semantically identical sentences must have the same semantic structure. Otherwise we will have different inferences from the same meaning. To overcome the above-mentioned flaw, the following approach is suggested. Assume that: P is a participant of relation; F is a feature of a participant; Vcp is a verb that captures a participant; Vcf is a verb that captures a feature of a participant; Vpr is a primitive verb or a verb that does not capture any participant and represents only a relation. In another word, a primitive verb is a verb whose meaning does not include meanings from its surroundings. Then Vcp and Vcf can be decomposed as: Vcp = Vpr +P; Vcf = Vpr +F. If all Vcp and Vcf will be represented this way, then primitive verbs Vpr can be considered as a canonical form for SRL. As a result of that, there will be no hidden participants caught by a verb since all participants will be explicitly unfolded. An obvious example of Vpr is the verb go, which represents pure movement. In this case the verb drink can be represented as man-made movement of liquid into specific direction. Extraction and using primitive verbs for SRL create a canonical representation unique for semantically identical sentences. It leads to the unification of semantic representation. In this case, the critical flaw related to SRL will be resolved.

Keywords: decomposition, labeling, primitive verbs, semantic roles

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Authors: S. Rasti, M. A. Rajabzadeh

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Nickel-bearing laterites occur as two parallel belts along Sedimentary Zagros Orogenic (SZO) and Metamorphic Sanandaj-Sirjan (MSS) petrostructural zones, Fars Province, south Iran. An undisturbed vertical profile of these laterites includes protolith, saprolite, clay, and oxide horizons from base to top. Highly serpentinized harzburgite with relicts of olivine and orthopyroxene is regarded as the source rock. The laterites are unusual in lacking a significant saprolite zone with little development of Ni-silicates. Hematite, saponite, dolomite, smectite and clinochlore increase, while calcite, olivine, lizardite and chrysotile decrease from saprolite to oxide zones. Smectite and clinochlore with minor calcite are the major minerals in clay zone. Contacts of different horizons in laterite profiles are gradual and characterized by a decrease in Mg concentration ranging from 18.1 to 9.3 wt.% in oxide and saprolite, respectively. The maximum Ni concentration is 0.34 wt.% (NiO) in the base of the oxide zone, and goethite is the major Ni-bearing phase. From saprolite to oxide horizons, Al₂O₃, K₂O, TiO₂, and CaO decrease, while SiO₂, MnO, NiO, and Fe₂O₃ increase. Silica content reaches up to 45 wt.% in the upper part of the soil profile. There is a decrease in pH (8.44-8.17) and an increase in organic matter (0.28-0.59 wt.%) from base to top of the soils. The studied laterites are classified in the oxide clans which were derived from ophiolite ultramafic rocks under Mediterranean climate conditions.

Keywords: Iran, laterite, mineralogy, ophiolite

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Authors: Laura Mclean

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A recurring point of interest in computational phylogenetic analysis of Indo-European family trees is the inference of a Germano-Italo-Celtic clade in some versions of the trees produced. The presence of this clade in the models is intriguing as there is little evidence for innovations shared among Germanic, Italic, and Celtic, the evidence generally used in the traditional method to construct a subgroup. One source of this unexpected outcome could be the input to the models. The datasets in the various models used so far, for the most part, take as their basis the Swadesh list, a list compiled by Morris Swadesh and then revised several times, containing up to 207 words that he believed were resistant to change among languages. The judgments made by Swadesh for this list, however, were subjective and based on his intuition rather than rigorous analysis. Some scholars used the Swadesh 200 list as the basis for their Indo-European dataset and made cognacy judgements for each of the words on the list. Another dataset is largely based on the Swadesh 207 list as well although the authors include additional lexical and non-lexical data, and they implement ‘split coding’ to deal with cases of polymorphic characters. A different team of scholars uses a different dataset, IECoR, which combines several different lists, one of which is the Swadesh 200 list. In fact, the Swadesh list is used in some form in every study surveyed and each dataset has three words that, when they are coded as cognates, seemingly contribute to the inference of a Germano-Italo-Celtic clade which could happen due to these clades sharing three words among only themselves. These three words are ‘fish’, ‘flower’, and ‘man’ (in the case of ‘man’, one dataset includes Lithuanian in the cognacy coding and removes the word ‘man’ from the screened data). This collection of cognates shared among Germanic, Italic, and Celtic that were deemed important enough to be included on the Swadesh list, without the ability to account for possible reasons for shared cognates that are not shared innovations, gives an impression of affinity between the Germanic, Celtic, and Italic branches without adequate methodological support. However, by changing how cognacy is defined (ie. root cognates, borrowings vs inherited cognates etc.), we will be able to identify whether these three cognates are significant enough to infer a clade for Germanic, Celtic, and Italic. This paper examines the question of what definition of cognacy should be used for phylogenetic datasets by examining the Germano-Italo-Celtic clade as a case study and offers insights into the reconstruction of a Germano-Italo-Celtic clade.

Keywords: historical, computational, Italo-Celtic, Germanic

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Authors: Mohiuddin Sakib, Fatin Nihal, Rabeya Akter, Anisul Haque, Munsur Rahman, Wasif-E-Elahi

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Surge generating cyclones are one of the deadliest natural disasters that threaten the life of coastal environment and communities worldwide. Due to the geographic location, ‘low lying alluvial plain, geomorphologic characteristics and 710 kilometers exposed coastline, Bangladesh is considered as one of the greatest vulnerable country for storm surge flooding. Bay of Bengal is possessing the highest potential of creating storm surge inundation to the coastal areas. Bangladesh is the most exposed country to tropical cyclone with an average of four cyclone striking every years. Frequent cyclone landfall made the country one of the worst sufferer within the world for cyclone induced storm surge flooding and casualties. During the years from 1797 to 2009 Bangladesh has been hit by 63 severe cyclones with strengths of different magnitudes. Though detailed studies were done focusing on the specific cyclone like Sidr or Aila, no study was conducted where vulnerable areas of exposed coast were identified based on the strength of cyclones. This study classifies the vulnerable areas of the exposed coast based on storm surge inundation depth and area due to cyclones of varying strengths. Classification of the exposed coast based on hazard induced cyclonic vulnerability will help the decision makers to take appropriate policies for reducing damage and loss.

Keywords: cyclone, landfall, storm surge, exposed coastline, vulnerability

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Authors: Ewa Kicko Walczak, Grazyna Rymarz

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In recent years, nanotechnology has been successfully applied for flame retardancy of polymers, in particular for construction materials. The consumption of thermoset resins as a construction polymers materials is approximately over one million tone word wide. Excellent mechanical, relatively high heat and thermal stability of their type of polymers are proven for variety applications, e.g. transportation, electrical, electronic, building part industry. Above applications in addition to the strength and thermal properties also requires -referring to the legal regulation or recommendation - an adequate level of flammability of the materials. This publication present the evaluation was made of effectiveness of flame retardancy of halogen-free hybrid flame retardants(FR) as compounds nitric/phosphorus modifiers that act with nanofillers (nano carbons, organ modified montmorillonite, nano silica, microsphere) in relation to unsaturated polyester/epoxy resins and glass-reinforced on base this resins laminates(GRP) as a final products. The analysis of the fire properties provided proof of effective flame retardancy of the tested composites by defining oxygen indices values (LOI), with the use of thermogravimetric methods (TGA) and combustion head (CH). An analysis of the combustion process with Cone Calorimeter (CC) method included in the first place N/P units and nanofillers with the observed phenomenon of synergic action of compounds. The fine-plates, phase morphology and rheology of composites were assessed by SEM/ TEM analysis. Polymer-matrix glass reinforced laminates with modified resins meet LOI over 30%, reduced in a decrease by 70% HRR (according to CC analysis), positive description of the curves TGA and values CH; no adverse negative impact on mechanical properties. The main objective of our current project is to contribute to the general understanding of the flame retardants mechanism and to investigate the corresponding structure/properties relationships. We confirm that nanotechnology systems are successfully concept for commercialized forms for non-flammable GRP pipe, concrete composites, and flame retardant tunnels constructions.

Keywords: fire retardants, FR, halogen-free FR nanofillers, non-flammable pipe/concrete, thermoset resins

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Authors: Luljeta Gashi, Naser Ramadani, Zana Deva, Dafina Gexha-Bunjaku

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The official HIV/AIDS data in Kosovo are based on HIV case reporting from health-care services, the blood transfusion system and Voluntary Counselling and Testing centres. Between 1986 and 2014, are reported 95 HIV and AIDS cases, of which 49 were AIDS, 46 HIV and 40 deaths. The majority (69%) of cases were men, age group 25 to 34 (37%) and route of transmission is: heterosexual (90%), MSM (7%), vertical transmission (2%) and IDU (1%). Based on existing data and the UNAIDS classification system, Kosovo is currently still categorised as having a low-level HIV epidemic. Even though with a low HIV prevalence, Kosovo faces a number of threatening factors, including increased number of drug users, a stigmatized and discriminated MSM community, high percentage of youth among general population (57% of the population under the age of 25), with changing social norms and especially the sexual ones. Methods: Data collection was done using self administered structured questionnaires amongst 249 high school students. Data were analysed using the Statistical Package for Social Sciences (SPSS). Results: The findings revealed that 68% of students know that HIV transmission can be reduced by having sex with only one uninfected partner who has no other partners, 94% know that the risk of getting HIV can be reduced by using a condom every time they have sex, 68% know that a person cannot get HIV from mosquito bites, 81% know that they cannot get HIV by sharing food with someone who is infected and 46% know that a healthy looking person can have HIV. Conclusions: Seventy one percent of high school students correctly identify ways of preventing the sexual transmission of HIV and who reject the major misconceptions about HIV transmission. The findings of the study indicate a need for more health education and promotion.

Keywords: Kosovo, KPAR, HIV, high school

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Authors: Shaira L. Kee, Michael Aaron G. Sy, Myles Joshua T. Tan, Hezerul Abdul Karim, Nouar AlDahoul

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Skin diseases are considered the fourth most common disease, with melanoma and non-melanoma skin cancer as the most common type of cancer in Caucasians. The alarming increase in Skin Cancer cases shows an urgent need for further research to improve diagnostic methods, as early diagnosis can significantly improve the 5-year survival rate. Machine Learning algorithms for image pattern analysis in diagnosing skin lesions can dramatically increase the accuracy rate of detection and decrease possible human errors. Several studies have shown the diagnostic performance of computer algorithms outperformed dermatologists. However, existing methods still need improvements to reduce diagnostic errors and generate efficient and accurate results. Our paper proposes an ensemble method to classify dermoscopic images into benign and malignant skin lesions. The experiments were conducted using the International Skin Imaging Collaboration (ISIC) image samples. The dataset contains 3,297 dermoscopic images with benign and malignant categories. The results show improvement in performance with an accuracy of 88% and an F1 score of 87%, outperforming other existing models such as support vector machine (SVM), Residual network (ResNet50), EfficientNetB0, EfficientNetB4, and VGG16.

Keywords: deep learning - VGG16 - efficientNet - CNN – ensemble – dermoscopic images - melanoma

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Authors: Umm-E-Hani, Faiza Babar, Hanif Durad

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Malware-detecting approaches suffer many limitations, due to which all anti-malware solutions have failed to be reliable enough for detecting zero-day malware. Signature-based solutions depend upon the signatures that can be generated only when malware surfaces at least once in the cyber world. Another approach that works by detecting the anomalies caused in the environment can easily be defeated by diligently and intelligently written malware. Solutions that have been trained to observe the behavior for detecting malicious files have failed to cater to the malware capable of detecting the sandboxed or protected environment. Machine learning and deep learning-based approaches greatly suffer in training their models with either an imbalanced dataset or an inadequate number of samples. AI-based anti-malware solutions that have been trained with enough samples targeted a selected feature vector, thus ignoring the input of leftover features in the maliciousness of malware just to cope with the lack of underlying hardware processing power. Our research focuses on producing an anti-malware solution for detecting malicious PE files by circumventing the earlier-mentioned shortcomings. Our proposed framework, which is based on automated feature engineering through autoencoders, trains the model over a fairly large dataset. It focuses on the visual patterns of malware samples to automatically extract the meaningful part of the visual pattern. Our experiment has successfully produced a state-of-the-art accuracy of 99.54 % over test data.

Keywords: malware, auto encoders, automated feature engineering, classification

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Authors: Ki-Yeo Kim

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Trends in genetics are transforming in order to identify differential coexpressions of correlated gene expression rather than the significant individual gene. Moreover, it is known that a combined biomarker pattern improves the discrimination of a specific cancer. The identification of the combined biomarker is also necessary for the early detection of invasive oral squamous cell carcinoma (OSCC). To identify the combined biomarker that could improve the discrimination of OSCC, we explored an appropriate number of genes in a combined gene set in order to attain the highest level of accuracy. After detecting a significant gene set, including the pre-defined number of genes, a combined expression was identified using the weights of genes in a gene set. We used the Principal Component Analysis (PCA) for the weight calculation. In this process, we used three public microarray datasets. One dataset was used for identifying the combined biomarker, and the other two datasets were used for validation. The discrimination accuracy was measured by the out-of-bag (OOB) error. There was no relation between the significance and the discrimination accuracy in each individual gene. The identified gene set included both significant and insignificant genes. One of the most significant gene sets in the classification of normal and OSCC included MMP1, SOCS3 and ACOX1. Furthermore, in the case of oral dysplasia and OSCC discrimination, two combined biomarkers were identified. The combined genomic expression achieved better performance in the discrimination of different conditions than in a single significant gene. Therefore, it could be expected that accurate diagnosis for cancer could be possible with a combined biomarker.

Keywords: oral squamous cell carcinoma, combined biomarker, microarray dataset, correlated genes

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Authors: Lakshmi Chebolu

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'War’, the word itself, is so vibrant and handcuffs the entire society. Since the beginning of manhood, the world has been evident in constant struggles. However, along with the growth of communities, relations, on the one hand, and disputes, on the other hand, infinitely increased. When states cannot or will not settle their disputes or differences by means of peaceful agreements, weapons are suddenly made to speak. It does not mean states can engage in war whenever they desire. At an international level, there has been a vast development of the law of war in the 20th century. War, it may be internal or international, in all situations, belligerent actors should follow the principles of warfare. With the advent of technology, the shape of war has changed, and it violates fundamental principles without observing basic norms. Conversely, states' attitudes towards international relationships are also undermined to some extent as state parties are not prioritized the communal interest rather than political or individual interest. In spite of the persistent development of communities, still many people are innocent victims of modern wars. It costs a toll on many lives, liberties, and properties and remains a major obstacle to nations' development. Recent incidents in Afghan are a live example to World Nations. We know that the principles of international law cannot be implemented very strictly on perpetrators due to the lacuna in the international legal system. However, the rules of war are universal in nature. The Geneva Convention, 1949 which are the core element of IHL, has been ratified by all 196 States. In fact, very few international treaties received this much of big support from nations. State’s approach towards Modern International Law, places a heavy burden on States practice towards in implementation of law. Although United Nations Security Council possesses certain powers under ‘Pacific Settlement of Disputes’, (Chapter VI) of the United Nations Charter to prevent disputes in a peaceful manner, conversely, this practice has been overlooked for many years due to political interests, favor, etc. Despite international consensus on the prohibition of war and protection of fundamental freedoms and human dignity, still, often, law has been misused by states’. The recent tendencies trigger questions about states’ willingness towards the implementation of the law. In view of the existing practices of nations, this paper aims to elevate the legal obligations of the international community to save the succeeding generations from the scourge of modern war practices.

Keywords: modern wars, weapons, prohibition and suspension of war activities, states’ obligations

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Authors: Maggie Hui

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Risk management is not a new concept; however, it is an uncharted area as applied to the translation process and translator training. Risk managers are responsible for managing risk, i.e. adopting strategies with the intention to minimize loss and maximize gains in spite of uncertainty. Which risk strategy to use often depends on the frequency of an event (i.e. probability) and the severity of its outcomes (i.e. impact). This is basically the way translation/localization project managers handle risk management. Although risk management could involve both positive and negative impacts, impact seems to be always negative in professional translators’ management models, e.g. how many days of project time are lost or how many clients are lost. However, for analysis of translation performance, the impact should be possibly positive (e.g. increased readability of the translation) or negative (e.g. loss of source-text information). In other words, the straight business model of risk management is not directly applicable to the study of risk management in the rendition process. This research aims to explore trainee translators’ risk managing while translating in a simulated setting that involves translator-client relations. A two-cycle experiment involving two roles, the translator and the simulated client, was carried out with a class of translation students to test the effects of the main variable of peer-group interaction. The researcher made use of a user-friendly screen-voice recording freeware to record subjects’ screen activities, including every word the translator typed and every change they made to the rendition, the websites they browsed and the reference tools they used, in addition to the verbalization of their thoughts throughout the process. The research observes the translation procedures subjects considered and finally adopted, and looks into the justifications for their procedures, in order to interpret their risk management. The qualitative and quantitative results of this study have some implications for translator training: (a) the experience of being a client seems to reinforce the translator’s risk aversion; (b) there is a wide gap between the translator’s internal risk management and their external presentation of risk; and (c) the use of role-playing simulation can empower students’ learning by enhancing their attitudinal or psycho-physiological competence, interpersonal competence and strategic competence.

Keywords: risk management, role-playing simulation, translation pedagogy, translator-client relations

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Authors: Kun Xu, Yuan Xu, Jia Qiao

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The document detection plays an important role in optical character recognition and text analysis. Because the traditional detection methods have weak generalization ability, and deep neural network has complex structure and large number of parameters, which cannot be well applied in mobile devices, this paper proposes a lightweight Document Corner Detection Network (DCDNet). DCDNet is a two-stage architecture. The first stage with Encoder-Decoder structure adopts depthwise separable convolution to greatly reduce the network parameters. After introducing the Feature Attention Union (FAU) module, the second stage enhances the feature information of spatial and channel dim and adaptively adjusts the size of receptive field to enhance the feature expression ability of the model. Aiming at solving the problem of the large difference in the number of pixel distribution between corner and non-corner, Weighted Binary Cross Entropy Loss (WBCE Loss) is proposed to define corner detection problem as a classification problem to make the training process more efficient. In order to make up for the lack of Dataset of document corner detection, a Dataset containing 6620 images named Document Corner Detection Dataset (DCDD) is made. Experimental results show that the proposed method can obtain fast, stable and accurate detection results on DCDD.

Keywords: document detection, corner detection, attention mechanism, lightweight

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Authors: Deepthy Ann Joy, N. Sreedevi

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Hearing impairment (HI) at an early age, identified before the onset of language development can reduce the negative effect on speech and language development of children. Early rehabilitation is very important in the improvement of speech production in children with HI. Other than conventional hearing aids, Cochlear Implants are being used in the rehabilitation of children with HI. However, delay in acquisition of speech and language milestones persist in children with Cochlear Implant (CI). Delay in speech milestones are reflected through speech sound errors. These errors reflect the temporal and spectral characteristics of speech. Hence, acoustical analysis of the speech sounds will provide a better representation of speech production skills in children with CI. The present study aimed at investigating the acoustic characteristics of vowels in Malayalam speaking children with a cochlear implant. The participants of the study consisted of 20 Malayalam speaking children in the age range of four and seven years. The experimental group consisted of 10 children with CI, and the control group consisted of 10 typically developing children. Acoustic analysis was carried out for 5 short (/a/, /i/, /u/, /e/, /o/) and 5 long vowels (/a:/, /i:/, /u:/, /e:/, /o:/) in word-initial position. The responses were recorded and analyzed for acoustic parameters such as Vowel duration, Ratio of the duration of a short and long vowel, Formant frequencies (F₁ and F₂) and Formant Centralization Ratio (FCR) computed using the formula (F₂u+F₂a+F₁i+F₁u)/(F₂i+F₁a). Findings of the present study indicated that the values for vowel duration were higher in experimental group compared to the control group for all the vowels except for /u/. Ratio of duration of short and long vowel was also found to be higher in experimental group compared to control group except for /i/. Further F₁ for all vowels was found to be higher in experimental group with variability noticed in F₂ values. FCR was found be higher in experimental group, indicating vowel centralization. Further, the results of independent t-test revealed no significant difference across the parameters in both the groups. It was found that the spectral and temporal measures in children with CI moved towards normal range. The result emphasizes the significance of early rehabilitation in children with hearing impairment. The role of rehabilitation related aspects are also discussed in detail which can be clinically incorporated for the betterment of speech therapeutic services in children with CI.

Keywords: acoustics, cochlear implant, Malayalam, vowels

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Authors: A. Bouzekri, H. Benmassaud

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Aurès region is one of the arid and semi-arid areas that have suffered climate crises and overexploitation of natural resources they have led to significant land degradation. The use of remote sensing data allowed us to analyze the land and its spatiotemporal changes in the Aurès between 1987 and 2013, for this work, we adopted a method of analysis based on the exploitation of the images satellite Landsat TM 1987 and Landsat OLI 2013, from the supervised classification likelihood coupled with field surveys of the mission of May and September of 2013. Using ENVI EX software by the superposition of the ground cover maps from 1987 and 2013, one can extract a spatial map change of different land cover units. The results show that between 1987 and 2013 vegetation has suffered negative changes are the significant degradation of forests and steppe rangelands, and sandy soils and bare land recorded a considerable increase. The spatial change map land cover units between 1987 and 2013 allows us to understand the extensive or regressive orientation of vegetation and soil, this map shows that dense forests give his place to clear forests and steppe vegetation develops from a degraded forest vegetation and bare, sandy soils earn big steppe surfaces that explain its remarkable extension. The analysis of remote sensing data highlights the profound changes in our environment over time and quantitative monitoring of the risk of desertification.

Keywords: remote sensing, spatiotemporal, land use, Aurès

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Authors: Tianqiao Zhang, Ye Tian, Yanliang Yin, Yichao Tian, Suzhai Tian, Weige Sun, Shuhui Gong, Limei Tang, Ruoliang Tang

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Introduction: Healthcare workers, especially the nurses all over the world, are highly vulnerable to work-related musculoskeletal disorders (WMSDs), experiencing high rates of neck, shoulder, and low back injuries, due to the unfavorable working conditions. To reduce WMSDs among nursing personnel, many workplace interventions have been developed and implemented. Unfortunately, the ongoing Covid-19 (SARS-CoV-2) pandemic has posed great challenges to the ergonomic practices and interventions in healthcare facilities, particularly the hospitals, since current Covid-19 mitigation measures, such as social distancing and working remotely, has substantially minimized in-person gatherings and trainings. On the other hand, hospitals throughout the world have been short-staffed, resulting in disturbance of shift scheduling and more importantly, the increased job demand among the available caregivers, particularly the doctors and nurses. With the latest development in communication technology, remote intervention measures have been developed as an alternative, without the necessity of in-person meetings. The Omaha System (OS) is a standardized classification system for nursing practices, including a problem classification system, an intervention system, and an outcome evaluation system. This paper describes the development of an OS-based ergonomic intervention program. Methods: First, a comprehensive literature search was performed among worldwide electronic databases, including PubMed, Web of Science, Cochrane Library, China National Knowledge Infrastructure (CNKI), between journal inception to May 2020, resulting in a total of 1,418 scientific articles. After two independent screening processes, the final knowledge pool included eleven randomized controlled trial studies to develop the draft of the intervention program with Omaha intervention subsystem as the framework. After the determination of sample size needed for statistical power and the potential loss to follow-up, a total of 94 nurses from eight clinical departments agreed to provide written, informed consent to participate in the study, which were subsequently assigned into two random groups (i.e., intervention vs. control). A subgroup of twelve nurses were randomly selected to participate in a semi-structured interview, during which their general understanding and awareness of musculoskeletal disorders and potential interventions was assessed. Then, the first draft was modified to reflect the findings from these interviews. Meanwhile, the tentative program schedule was also assessed. Next, two rounds of consultation were conducted among experts in nursing management, occupational health, psychology, and rehabilitation, to further adjust and finalize the intervention program. The control group had access to all the information and exercise modules at baseline, while an interdisciplinary research team was formed and supervised the implementation of the on-line intervention program through multiple social media groups. Outcome measures of this comparative study included biomechanical load assessed by the Quick Exposure Check and stresses due to awkward body postures. Results and Discussion: Modification to the draft included (1) supplementing traditional Chinese medicine practices, (2) adding the use of assistive patient handling equipment, and (3) revising the on-line training method. Information module should be once a week, lasting about 20 to 30 minutes, for a total of 6 weeks, while the exercise module should be 5 times a week, each lasting about 15 to 20 minutes, for a total of 6 weeks.

Keywords: ergonomic interventions, musculoskeletal disorders (MSDs), omaha system, nurses, Covid-19

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Authors: Raúl Jiménez Vilches

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Native (L1) speakers can mark prosodically one part of an utterance and make it more relevant as opposed to the rest of the constituents. Conversely, non-native (L2) speakers encounter problems when it comes to marking prosodically information structure in English. In fact, the L2 speaker’s choice for the prosodic realization of focus is not so clear and often obscures the intended pragmatic meaning and the communicative value in general. This paper reports some of the findings obtained in an L2 prosodic training course for Spanish learners of English within the context of public speaking. More specifically, it analyses the effects of the course experiment in relation to the non-native production of the tonic syllable to mark focus and compares it with the public speeches delivered by native English speakers. The whole experimental training was executed throughout eighteen input sessions (1,440 minutes total time) and all the sessions took place in the classroom. In particular, the first part of the course provided explicit instruction on the recognition and production of the tonic syllable and how the tonic syllable is used to express focus. The non-native and native oral presentations were acoustically analyzed using Praat software for speech analysis (7,356 words in total). The investigation adopted mixed and embedded methodologies. Quantitative information is needed when measuring acoustically the phonetic realization of focus. Qualitative data such as questionnaires, interviews, and observations were also used to interpret the quantitative data. The embedded experiment design was implemented through the analysis of the public speeches before and after the intervention. Results indicate that, even after the L2 prosodic training course, Spanish learners of English still show some major inconsistencies in marking focus effectively. Although there was occasional improvement regarding the choice for location and word classes, Spanish learners were, in general, far from achieving similar results to the ones obtained by the English native speakers in the two types of focus. The prosodic realization of focus seems to be one of the hardest areas of the English prosodic system to be mastered by Spanish learners. A funded research project is in the process of moving the present classroom-based experiment to an online environment (mobile app) and determining whether there is a more effective focus usage through CAPT (Computer-Assisted Pronunciation) tools.

Keywords: focus, prosody, public speaking, Spanish learners of English

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