The Effectiveness of Using Subtitled Video to Teach Grammar

This study explored the effect of subtitled videos on grammar learning in an intermediate level ESL grammar classroom at a large state university in the U.S. Midwest. This classroom-based research makes use of the noticing hypothesis (Schmidt, 1990) to investigate the effect of using enhanced subtitles and input flooding of a specific grammatical structure, the past perfect form, on learning. The study also looked at nine participants\u27 attitudes and their opinions on using videos to learn grammar. An immediate noticing activity was used to reveal if students noticed the enhanced past perfect forms from the video subtitles while a pretest and post-test was used to examine if students demonstrated a gain in knowledge of the usage of the form. Results show that the first time the noticing activity was administered only 3 out of 9 students noticed fewer than 3 words out of the 7 subtitled words. In the second time the same activity was administered 5 students were able to notice some of the words with an average of 3 words being noticed. Pre-test and post-test results show that there was a gain in grammatical knowledge with an average of 58.3 % hence the subtitled video helped learners learn the target structure. However, the students were not just exposed to implicit instruction by watching the subtitled video during the two class periods. They also received explicit instruction on when and how to use the form through using an animated cartoon before watching the subtitled video. Overall, students interacted together as they worked within their groups to complete tasks with minimal student-teacher interaction. Findings of the questionnaire and debriefing session showed that the students had a positive attitude towards this grammar teaching approach while some students expressed some concerns. Overall, explicit instruction and implicit instruction through watching the enhanced subtitled video helped students better understand the context that a specific grammatical structure was used

Prosodic and discourse function variations in lexical bundles in university lectures

Multiword sequences are important components of language because they are building blocks that can be used to create long stretches of discourse. They are word combinations that have particular importance because of their co-occurrence and function in discourse that suggest that they are stored and retrieved from memory as a whole rather than as separate word units. The functions that they perform in discourse can vary according to register. In spoken academic discourse, one of the essential functions of multi-word sequences is a discourse organizing function that include introducing a topic and elaborating on an existing topic These varied discourse functions have two main roles in the information structure of discourse: as a major rhetorical organizer or a minor rhetorical organizer (Chaudron & Richards, 1986). However, studies that have examined the discourse-organizing role of spoken linguistic devices, including multi-word sequences, either have examined limited data or have analyzed them from written transcripts only, overlooking an important aspect of speech, i.e., prosody, that has an important communicative role. This study focuses on one type of multi-word sequence, lexical bundles, which are frequently used recurrent word combinations that are identified computationally in a corpus to understand how their prosodic variations are linked to their discourse function(s). Lexical bundles in spoken academic discourse have been found to have a discourse-organizing function through analyzing spoken text from orthographic transcription. However, what remains to be explored is their prosodic features that have the potential to specify specific discourse-organizing functions more precisely. Therefore, this study focuses on understanding the relationship between the prosodic variation(s) and discourse function(s) of frequently occurring lexical bundles in a corpus. This study used a corpus-driven framework to analyze the prosodic and discourse function variations of lexical bundles in a spoken academic corpus compiled from YALE open courses. The discourse function of the lexical bundles was analyzed using transcripts and audio files to find emerging patterns in their rhetorical function in information structure. In other words, lexical bundles were classified according to the relationship to preceding and following discourse, i.e., whether it introduced a new topic or expanded, contrasted, or emphasized specific details related to the main topic. Prosodic analysis involved examining pitch movement and prominence within the lexical bundle. Then, the emerging prosodic patterns and their corresponding discourse functions were cross-tabulated to understand the relationship between them. Findings indicate that some lexical bundles had multiple prosodic variations related to discourse function variations while others had minimal prosodic variation related to one discourse function. The discourse functions were categorized as having a major rhetorical organization role (introducing the main topic for discussion, connecting topics, major contrast) or a minor rhetorical organization role (expanding on a topic through specific details, providing background information, exemplification, or rephrasing, contrasting ideas, emphasizing important information). The variation in discourse function and prosody of lexical bundles in university lectures may indicate that some lexical bundles are more formulaic than others

Evaluation of Machine Learning Models for Breast Cancer Diagnosis Via Histogram of Oriented Gradients Method and Histopathology Images

Breast cancer is the main death rate from malignant growth worldwide and the most frequently diagnosed type of cancer in females. Machine learning systems have been developed to assist in the accurate detection of cancer. There are numerous methods for cancer detection. But histopathological images are thought to be more precise. In this study, we used the HOG features extractor to extract statistical features from histopathology images of invasive ductal carcinoma. We chose the following images at random from the histopathology images: 100, 200, 400, 1000, and 2000. These statistical features were then used to train several algorithms, including the decision tree, quadratic discriminant analysis, extra randomized trees, gradient boosting, gaussian process classifier, naive bayes, nearest centroid, multilayer perceptron, and support vector machine, to identify whether or not the images depict cancerous or noncancerous growth. The algorithms' performance was evaluated depending on the specificity, accuracy, sensitivity, precision, F1_score, and AUC. The algorithms used worked best when the number of images was set to 100. As the number of images went up, their effectiveness went down

Physical Activity and Sport Participation Among Adolescents from MENA

Physical activity is positively associated with short- and long-term mental and physical health effects. Adolescence represents a sensitive period of development and habit formation, during which the adoption of healthy behaviors such as physical activity is critical. A low level of physical activity is a key risk factor for the development of chronic diseases throughout the life course. Physical activity levels decline among adolescents with age, especially among girls. Encouraging physical activity early during childhood development and into adolescence may increase perceived self-efficacy and may enhance levels of physical activity later in life. Countries in the Middle East and North Africa (MENA) have experienced many changes over the past two decades, including significant economic, sociodemographic, industrial, and political transformations, such as high levels of urbanization, loss of green space, and heavy reliance on vehicles for transportation. These changes along with other country-specific factors may present distinct constraints to physical activity among adolescents. This chapter focuses on the prevalence of physical activity and sport participation and their related constraints that adolescents experience in the MENA region. It presents a literature review on physical activity among adolescents in the MENA, followed by results of a brief study on the prevalence of sport participation among adolescents from the United Arab Emirates (UAE). Results suggest that culturally appropriate community- and school-based interventions are required to improve overall physical activity levels of adolescents in MENA countries. Regionally, examinations and assessments of specific constraints are key to identify patterns of physical activity and sport participation and to formulate interventions that have the capacity to increase these sport participation levels. General recommendations that have the potential to increase adolescent physical activity and sport participation include increasing awareness and knowledge on the related benefits, providing adequate support and encouragement for adolescents from MENA in relation to physical activity and sport participation, as well as ensuring related opportunities are available within school programs

Local Phase Coherence Measurement for Image Analysis and Processing

The ability of humans to perceive significant pattern and structure of an image is something which humans take for granted. We can recognize objects and patterns independent of changes in image contrast and illumination. In the past decades, it has been widely recognized in both biology and computer vision that phase contains critical information in characterizing the structures in images. Despite the importance of local phase information and its significant success in many computer vision and image processing applications, the coherence behavior of local phases at scale-space is not well understood. This thesis concentrates on developing an invariant image representation method based on local phase information. In particular, considerable effort is devoted to study the coherence relationship between local phases at different scales in the vicinity of image features and to develop robust methods to measure the strength of this relationship. A computational framework that computes local phase coherence (LPC) intensity with arbitrary selections in the number of coefficients, scales, as well as the scale ratios between them has been developed. Particularly, we formulate local phase prediction as an optimization problem, where the objective function computes the closeness between true local phase and the predicted phase by LPC. The proposed framework not only facilitates flexible and reliable computation of LPC, but also broadens the potentials of LPC in many applications. We demonstrate the potentials of LPC in a number of image processing applications. Firstly, we have developed a novel sharpness assessment algorithm, identified as LPC-Sharpness Index (LPC-SI), without referencing the original image. LPC-SI is tested using four subject-rated publicly-available image databases, which demonstrates competitive performance when compared with state-of-the-art algorithms. Secondly, a new fusion quality assessment algorithm has been developed to objectively assess the performance of existing fusion algorithms. Validations over our subject-rated multi-exposure multi-focus image database show good correlations between subjective ranking score and the proposed image fusion quality index. Thirdly, the invariant properties of LPC measure have been employed to solve image registration problem where inconsistency in intensity or contrast patterns are the major challenges. LPC map has been utilized to estimate image plane transformation by maximizing weighted mutual information objective function over a range of possible transformations. Finally, the disruption of phase coherence due to blurring process is employed in a multi-focus image fusion algorithm. The algorithm utilizes two activity measures, LPC as sharpness activity measure along with local energy as contrast activity measure. We show that combining these two activity measures result in notable performance improvement in achieving both maximal contrast and maximal sharpness simultaneously at each spatial location

Parameters estimation of BLDC motor based on physical approach and weighted recursive least square algorithm

Brushless DC motors (BLDCM) are widely used when high precision converters are required. Model based torque control schemes rely on a precise representation of their dynamics, which in turn expect reliable system parameters estimation. In this paper, we propose two procedures for BLDCM parameters identification used in an agriculture mobile robot’s wheel. The first one is based on the physical approach or equations using experimentation data to find the electrical and mechanical parameters of the BLDCM. The parameters are then used to elaborate the model of the motor established in Park’s reference frame. The second procedure is an online identification based on recursive least square algorithm. The procedure is implemented in a closed-loop scheme to guarantee the stability of the system, and it provide parameter matrices obtained by transforming electrical equations, established in Parks reference frame, and mechanical equation to discrete-time domain. From these matrices, and using well formulated intermediate variables, all desired parameters are deduced simultaneously. The identification procedures are being verified using simulation under Matlab-Simulink software

The suffering of refugees in Ghassan Kanafani’s “The Child Goes to the Camp”: a critical appraisal

Purpose – This paper aims to present a critical appraisal of Ghassan Kanafani’s short story “The Child Goes to the Camp” using the Appraisal Theory proposed by Martin and Rose (2007) in an attempt to investigate the predicament of the Palestinians who were forced to flee their country and live in refugee camps as well as the various effects refugee life had on them. Design/methodology/approach – Using the Appraisal Theory, and with a special focus on the categories of Attitude and Graduation, the paper aims to shed light on the plight of refugees through revealing the narrator’s suffering in a refugee camp where the most important virtue becomes remaining alive. Findings – Analysing the story using the Appraisal Theory reveals the impact refugee life has left on the narrator and his family. This story serves as a warning for the world of the suffering refugees have to endure when they are forced to flee their war-torn countries. Originality/value – Although Kanafani’ resistance literature has been studied extensively, his short stories have not received much scholarly attention. In addition, his works have not been subject to linguistic analysis. This study presents an appraisal analysis of Kanafani’s “The Child Goes to the Camp” in an attempt to investigate how the author’s linguistic choices are key to highlighting the suffering of the Palestinians, especially children, in refugee camps

A Numerical Confirmation of a Fractional SEITR for Influenza Model Efficiency

The main idea of this study is to reduce the number of susceptible to infections so that ill patients can receive prompt hospitalization. Fractional SEITR was introduced for this purpose. Both endemic and disease-free equilibrium’s’ durability was examined. The fundamental reproduction number of the fractional SEITR model was determined using the next-generation matrix method. Our analytical results were supported by numerical models. Here, a graphical representation of the fractional order model is presented to validate the conclusion through numerical simulation. We have come to the conclusion that the fractional order model is more precise and provides more information about the true data of disease dynamics