Interpretation Ability Research Articles

The use of paradigmatic research: The model of a perfect world according to Targum Qohelet

The purpose of this study is to identify and explain a religious paradigm in Targum Qohelet (TgQoh). Targum Qohelet is dated to a period between 500 CE and 1101 CE. This study concludes that the most probable setting for this Targum was the beit midrash (the house of study). A paradigmatic research approach is used to identify the range of translation components to explain the translation method employed in TgQoh and the rationale behind it. This research approach reveals how the translator(s) used their interpretative ability to create a completely different thought-world when compared with the original Hebrew Text. Various subparadigms emerge as a network of connected religious beliefs to form a cogent systematic rabbinic theology of a perfect world order to replace the pessimism of the Hebrew base text. The Aramaic version reflects a complete solution to the existential problems raised by Biblical Qohelet. It seeks to provide humankind with guidelines for creating a ‘perfect world’ both on earth and in the afterlife. The use of a paradigmatic analysis based on the concept of a ‘perfect world’ provides an ideal model for analysing the translation strategy of TgQoh and understanding its method of rendering. Contribution: The application of paradigmatic methodology bridges the gap between the relatively secular nature of the Hebrew version of Qohelet (Ecclesiastes) and the overwhelmingly and inescapable theological forms of the Aramaic targum. The paradigms in the Aramaic translation identify how the targum applied rabbinic ideology to explain the meanings that lies behind the original Hebrew text of Qohelet. The paradigms, when taken together reveal how the cynical nature of Hebrew Qohelet was changed into a rabbinical guide for righteous living, here described as ‘perfect world’.

منهج الإمام الداني في أسباب النزول من خلال کتابه المکتفى

وصية الله تبارک وتعالى لهذه الأمة ووصية نبينا صلى الله عليه وسلم لأمته بتدبر القرآن الکريم والتمسک به والعمل بما فيه، فالخير کله والسعادة والبرکة التي ينشدها الناس مضمونة لهم إن تسمکوا بکتاب ربهم، وقد تمسک بهذه الوصية علماؤنا فاعتنوا بکتاب الله تبارک وتعالى غاية الاعتناء حفظا وفهما وتعلما وتدبرا وتفسيرا، وألفوا فيه المؤلفات النافعة وحرصوا عليها غاية الحرص، ومن هؤلاء الأئمة الإمام الحافظ الفذ العالم القارئ المفسر عثمان بن سعيد بن عثمان بن سعيد، المشهور بأبي عمرو الداني إن سبب اختياري البحثإبراز جهد الإمام الداني في علوم القرآن عموما. مشکلة البحث:شهرة الداني في القراءات وتحريراتها دون باقي أبواب علوم القرآن. وإن أهم نتائج البحث:عناية الداني بعلوم القرآن.،تمکنه في التفسير وعلوم القرآن وعلوم اللغة.،اعتناء العلماء بدراسة شخصيته ودراسة مؤلفاته. Abstract: The will of God bless and exalt to this nation and the will of our Prophet ' to his nation by managing the Holy Quran and sticking to it and working with it, because all the goodness, happiness and blessing sought by people are guaranteed to them if you are used to the Book of their Lord, and this commandment has been adhered to by our scholars, so take care of the Book of God. They wrote useful works and took care of them very carefully, including these imams Imam Al-Hafiz al-Faim, the interpreter, Othman bin Saeed bin Othman bin Saeed, known as Abu Amr al-Dani. The reason I chose to research is to highlight imam Al-Dani's efforts in the sciences of the Qur'an in general. The problem of research: Al-Dani's fame in readings and edits without the rest of the qur'an sciences. The most important results of the research: al-Dani's care of the sciences of the Qur'an, his ability in interpretation, the sciences of the Qur'an and the sciences of language, the study of his personality and the study of his writings. Keywords: Method - Danny - Reasons to Go Down - The Enough

Positive Evaluations Expressed Through Original Stories: An Intervention to Promote Resilience in Japan1

AbstractThis study aimed to design a program incorporating a narrative perspective that promotes resilience. A program was implemented that conveys an appreciation for the internal qualities of a familiar other person through the creation of a story about them. The experiment was conducted with 36 pairs of women; each pair had a “giver” and a “recipient.” The giver created a story that praised the “good points” of the recipient. There were significant increases in recipients' scores on measures of resilience, self‐esteem, and sense of acceptance of the giver. Additionally, the use of a story can help expand the interpretative ability of receiving and expressing praise.

Adopting deep learning methods for airborne RGB fluvial scene classification

Rivers are among the world's most threatened ecosystems. Enabled by the rapid development of drone technology, hyperspatial resolution (<10 cm) images of fluvial environments are now a common data source used to better understand these sensitive habitats. However, the task of image classification remains challenging for this type of imagery and the application of traditional classification algorithms such as maximum likelihood, still in common use among the river remote sensing community, yields unsatisfactory results. We explore the possibility that a classifier of river imagery based on deep learning methods can provide a significant improvement in our ability to classify fluvial scenes. We assemble a dataset composed of RGB images from 11 rivers in Canada, Italy, Japan, the United Kingdom, and Costa Rica. The images were labelled into 5 land-cover classes: water, dry exposed sediment, green vegetation, senescent vegetation and roads. In total, >5 billion pixels were labelled and partitioned for the tasks of training (1 billion pixels) and validation (4 billion pixels). We develop a novel supervised learning workflow based on the NASNet convolutional neural network (CNN) called ‘CNN-Supervised Classification’ (CSC). First, we compare the classification performance of maximum likelihood, a multilayer perceptron, a random forest, and CSC. Results show median F1 scores (a commonly used quality metric in machine learning) of 71%, 78%, 72% and 95%, respectively. Second, we train our classifier using data for 5 of 11 rivers. We then predict the validation data for all 11 rivers. For the 5 rivers that were used in model training, median F1 scores reach 98%. For the 6 rivers not used in model training, median F1 scores are 90%. We reach two conclusions. First, in the traditional workflow where images are classified one at a time, CSC delivers an unprecedented mix of labour savings and classification F1 scores above 95%. Second, deep learning can predict land-cover classifications (F1 = 90%) for rivers not used in training. This demonstrates the potential to train a generalised open-source deep learning model for airborne river surveys suitable for most rivers ‘out of the box’. Research efforts should now focus on further development of a new generation of deep learning classification tools that will encode human image interpretation abilities and allow for fully automated, potentially real-time, interpretation of riverine landscape images.

THE BLACK ATLANTIC TRADITION AND THE AFRICAN-AMERICAN NOVEL: SIGNIFYIN(G) AND THE FIGURE OF ESU ELEGBARA IN RALPH W. ELLISON’S INVISIBLE MAN

By exploring the black Atlantic tradition, the present article aims to demonstrate that the narrator’s grandfather in Ralph Ellison’s novel Invisible Man is not only an emblem of the black vernacular, but a correlative of the West African god and trickster Esu Elegbara. Likewise, the black characters, Tarp, Clifton, and Rinehart, function as interpreters of the grandfather’s ‘double-voiced’ text viewed as metaphoric of the black vernacular and evocative of Ifa, the ‘ambiguous’ West African religious texts. The first part of this article presents the main tenets of the black Atlantic tradition constituting the approach to be deployed. This is an integrative model comprising West African mythology and the African-American model of “Signifyin(g).” The second part examines the ways whereby the protagonist is guided into establishing linkage with the black vernacular. After examining those linguistic and functional aspects demonstrating the correlation between the grandfather and Esu, I will consider Tarp’s and Clifton’s Signifyin(g) strategies meant to enhance the protagonist’s interpretive ability. I will subsequently investigate Rinehart’s masquerading tricks inspiring both the protagonist’s subversion of fix identities and his positive reception of the ambivalence of his grandfather’s ‘Signification.’ Such interpretive enterprise ultimately brings about the protagonist’s emancipation from the alienating discourse of “Progress” and his realization of self-identification and self-expression through the black vernacular.&#x0D; &lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt; Article visualizations:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;img src="/-counters-/edu_01/0620/a.php" alt="Hit counter" /&gt;&lt;/p&gt;

Self-Evolving Fuzzy Controller Composed of Univariate Fuzzy Control Rules

The paper proposes a methodology to online self-evolve direct fuzzy logic controllers (FLCs), to deal with unknown and time-varying dynamics. The proposed methodology self-designs the controller, where fuzzy control rules can be added or removed considering a predefined criterion. The proposed methodology aims to reach a control structure easily interpretable by human operators. The FLC is defined by univariate fuzzy control rules, where each input variable is represented by a set of fuzzy control rules, improving the interpretability ability of the learned controller. The proposed self-evolving methodology, when the process is under control (online stage), adds fuzzy control rules on the current FLC using a criterion based on the incremental estimated control error obtained using the system’s inverse function and deletes fuzzy control rules using a criterion that defines “less active” and “less informative” control rules. From the results on a nonlinear continuously stirred tank reactor (CSTR) plant, the proposed methodology shows the capability to online self-design the FLC by adding and removing fuzzy control rules in order to successfully control the CSTR plant.

A Spectral-Aware Convolutional Neural Network for Pansharpening

Pansharpening aims at fusing a low-resolution multiband optical (MBO) image, such as a multispectral or a hyperspectral image, with the associated high-resolution panchromatic (PAN) image to yield a high spatial resolution MBO image. Though having achieved superior performances to traditional methods, existing convolutional neural network (CNN)-based pansharpening approaches are still faced with two challenges: alleviating the phenomenon of spectral distortion and improving the interpretation abilities of pansharpening CNNs. In this work, we develop a novel spectral-aware pansharpening neural network (SA-PNN). On the one hand, SA-PNN employs a network structure composed of a detail branch and an approximation branch, which is consistent with the detail injection framework; on the other hand, SA-PNN strengthens processing along the spectral dimension by using a spectral-aware strategy, which involves spatial feature transforms (SFTs) coupling the approximation branch with the detail branch as well as 3D convolution operations in the approximation branch. Our method is evaluated with experiments on real-world multispectral and hyperspectral datasets, verifying its excellent pansharpening performance.

A Hierarchical Mentoring Program Increases Confidence and Effectiveness in Data Analysis and Interpretation for Undergraduate Biology Students.

Science instructors are increasingly incorporating teaching techniques that help students develop core competencies such as critical-thinking and communication skills. These core competencies are pillars of career readiness that prepare undergraduate students to successfully transition to continuing education or the workplace, whatever the field. Course-based undergraduate research experiences that culminate in written research papers can be effective at developing critical-thinking and communication skills but are challenging to implement as class size (and student-to-instructor ratio) grows. We developed a hierarchical mentoring program in which graduate student mentors guided groups of four to five undergraduate students through the scientific process in an upper-level ecology course. Program effectiveness was evaluated by grading final research papers (including previous year papers, before the program was implemented) and surveys (comparing to a course that did not implement the program). Results indicated that primary benefits of hierarchical mentoring were improvements in perceived and demonstrated ability in data analysis and interpretation, leading to a median increase in paper score of ∼10% on a 100-point scale. Future directions indicated by our study were a need to incorporate more approaches (e.g., low-stakes writing exercises) and resources into a revised program to improve outcomes for students whose primary language is not English.

Pathway-Guided Deep Neural Network toward Interpretable and Predictive Modeling of Drug Sensitivity.

To efficiently save cost and reduce risk in drug research and development, there is a pressing demand to develop in silico methods to predict drug sensitivity to cancer cells. With the exponentially increasing number of multi-omics data derived from high-throughput techniques, machine learning-based methods have been applied to the prediction of drug sensitivities. However, these methods have drawbacks either in the interpretability of the mechanism of drug action or limited performance in modeling drug sensitivity. In this paper, we presented a pathway-guided deep neural network (DNN) model to predict the drug sensitivity in cancer cells. Biological pathways describe a group of molecules in a cell that collaborates to control various biological functions like cell proliferation and death, thereby abnormal function of pathways can result in disease. To take advantage of the excellent predictive ability of DNN and the biological knowledge of pathways, we reshaped the canonical DNN structure by incorporating a layer of pathway nodes and their connections to input gene nodes, which makes the DNN model more interpretable and predictive compared to canonical DNN. We have conducted extensive performance evaluations on multiple independent drug sensitivity data sets and demonstrated that our model significantly outperformed the canonical DNN model and eight other classical regression models. Most importantly, we observed a remarkable activity decrease in disease-related pathway nodes during forward propagation upon inputs of drug targets, which implicitly corresponds to the inhibition effect of disease-related pathways induced by drug treatment on cancer cells. Our empirical experiments showed that our method achieves pharmacological interpretability and predictive ability in modeling drug sensitivity in cancer cells. The web server, the processed data sets, and source codes for reproducing our work are available at http://pathdnn.denglab.org.

The Cruciality of Using Literature to Enhance Reading Comprehension Skills

This paper attempted to shade the light upon “The cruciality of teaching Literature to enhance reading comprehension skills”, is conducted to find out the role and importance of teaching literature in developing comprehension skills in tertiary level. The researcher adopted descriptive analysis method, the population of this study of (30) English language teachers from different Sudanese universities. Date was gathered by questionnaire. The researcher used a statistical package for social studies (SPSS package). The study comes up with followings: Teaching literature in language courses helps students to develop Reading Comprehension skills, teaching literature in reading lessons helps students to develop skimming and scanning techniques, literature presents valuable material to teach reading comprehension lesson, literature is a good way to practice acquiring quick information from the texts, and teaching literature develops students’ interpretative abilities.

Utilizing Correlative Imaging Approaches with ToF-SIMS Expands Our Biochemical Interpretation Abilities Across Biological Kingdoms

Utilizing Correlative Imaging Approaches with ToF-SIMS Expands Our Biochemical Interpretation Abilities Across Biological Kingdoms

Remote sensing image fine-processing method based on the adaptive hyper-Laplacian prior

High-quality remote sensing images have wide application prospects in agroforestry investigation, target monitoring, disaster prevention, urban planning and military defense. However, remote sensing imaging links such as atmosphere, platform and optical system seriously affect the ability of image interpretation and analysis. The traditional regularized processing methods have a strong ability to improve the definition, but most of them may sacrifice texture details or introduce artifacts, because their fixed prior parameters cannot fully adapt to various kinds of scenes. To address this problem, we propose a novel fine-processing method based on the adaptive hyper-Laplacian prior for remote sensing imaging systems. The method is developed by automatically updating and optimizing the prior parameters and objective function in the iterative process based on the prior characteristics of different regions of remote sensing images. Experimentally, the proposed method can realize the fine-processing of remote sensing images, including the edge enhancement, texture detail preservation, and artifact suppression.

Research on Teaching Methods to Improve College Students' English Interpretation Ability

With the development of China's foreign economy and trade, the integration model of national economy and world economy is becoming more and more obvious, and there is a gap in the demand for English interpreting talents. As an important carrier of cross-cultural and cross-national communication, English interpretation has been paid more and more attention by colleges and universities, and higher and higher requirements have been put forward for the teaching of English interpretation. Based on this, this paper starts from the current situation of English interpretation teaching in colleges and universities, and analyzes the teaching methods to improve the English interpretation ability of college students.

Sports Nutrition and Health and English Interpretation Ability

Sports Nutrition and Health and English Interpretation Ability

The Application of Seismic Three Dimensional Coherence Analysis Techniques in the Fine Structure Study of Oilfield

In recent years, with the emergence, wide application and continuous improvement of high-precision (high resolution) seismic acquisition technology, coherent data volume interpretation technology, 3d visualization technology and spectral decomposition technology, the identification ability and interpretation accuracy of seismic data interpretation have been greatly improved. Especially in the process of rolling edge expansion and development adjustment in the old oilfield, the small faults and microstructures in the oilfield have become one of the key contents of fine structure interpretation.

On-Sight and Red-Point Climbing: Changes in Performance and Route-Finding Ability in Male Advanced Climbers.

AimIn lead climbing, the ascent of the route can be defined as on-sight or red-point. On-sight is the more challenging style since it demands greater physiological and psychological commitment. The differences between the two modes in advanced climbers have not been studied much. Two essential skills needed to optimize performance, in both on-sight and in red-point climbing, are route interpretation (RI) ability and movements sequence recall. Therefore, this study aimed to compare performance between on-sight and red-point ascent in advanced climbers and evaluate how a climber’s RI ability and movement sequences recall might change before and after on-sight and red-point climbing.MethodsEighteen advanced male climbers (age 29.2 ± 4.7 years, body mass 67.8 ± 3.6 kg, stature 175.2 ± 2.4 cm, best red-point and on-sight grades 7b+/8a and 7a+/7b+, respectively) were video-recorded during the route ascent in on-sight and red-point modes to evaluate performance and to measure static and dynamic action times. RI ability and movement sequence recall were assessed before and after each climb. Level of anxiety was evaluated via a self-report questionnaire. Heart rate (fH), lactate concentration, ([La–]), and rating of perceived exertion (RPE) were detected during and after each climb.ResultsCompared to on-sight, an improvement in performance was observed in a red-point climb: the ascent was faster (148.7 ± 13.6 s and 179.5 ± 12.5 s, respectively, P < 0.05), smoother (significant reduction in exploratory moves and in stops times, P < 0.05), less demanding physiologically (lower fHpeak and [La–]peak, P < 0.05), and psychologically (lower RPE, cognitive and somatic anxiety and higher self-confidence, P < 0.05). The RI ability was improved in red-point versus on-sight and, in the same mode, between pre and post ascent.ConclusionRed-point climbing was found to be less demanding than on-sight, both physiologically and psychologically, under the conditions investigated by this study. Our findings suggest that RI is a trainable skill and underscore the importance of including specific techniques in training programs designed to improve interaction between perceptual, psychological, and physiological factors.

Analysis of students’ critical thinking skills on chapter of motion of objects and living things

This study aimed to analyze the ability of students to think in critically analytical and evaluative ways on chapter of motion of objects and living things. The object of the study was 280 students of 8th grade of MTs Negeri 1 Wonogiri in the academic year 2019/2020. This study used descriptive qualitative method to describe students’ critical thinking skills. Data was collected using reasoned multiple choice test which was developed based on skills of critical thinking according to Facione’s theory. As a result, it can be concluded that the criteria of the analysis and inference ability of the students were lack. While the ability of interpretation, evaluation, explanation, and self-regulation were in the very lack criteria.

Simile and Metaphor Interpretation in Children

Metaphors and similes have been treated as the same comparable types of figurative speech since Aristotle. In early theories, metaphors are interpreted as corresponding similes by paraphrasing. Based on this theoretical framework, some experimental studies interpret simile understanding as evidence for metaphor understanding. However, according to Relevance Theory, similes are interpreted as comparisons, whereas metaphors are interpreted as categorization statements. Therefore, only metaphor reveals metaphor interpretation. In other words, studies cannot use simile interpretation as evidence for metaphor interpretation ability in children. Simile should be easier to understand for children since they exclude an “ad hoc concept” construction as in metaphor understanding. This study seeks evidence showing children’s better performance in simile interpretation than that in metaphor interpretation, thus supporting Relevance Theory. For the Relevance Theory account, whether the experiments use similes or metaphors as testing materials is of considerable significance, whereas for comparison account, it is not. By review and re-interpretation of the empirical studies, we find that few early studies expose “real metaphor” understanding in children. Most experimental results indicate that simile interpretation is easier than metaphor interpretation for children. We consider comparison theory and the Relevance Theory as complementary strategies in metaphor interpretation.

Profile of the Interpreting Ability of Students on Static Fluid

&lt;em&gt;The purpose of this study was to get a description of the students' ability to interpret the static fluid material. This research was a quantitative descriptive study and the sample was taken by purposive sampling technique with a total sample of 26 students at one of the Madrasah Aliyah in the city of Singkawang. To achieve this goal, students had filled in questions about static fluids in a multiple-choice test. The results of this study were a quantitative description of the student's ability to interpret the static fluid material. The interpretive ability category was adapted from the n-gain category. The results showed that the category of students' ability to interpret the concept of hydrostatic pressure and Archimedes principle was in the high category with a percentage of 88% and on the Pascal principle it was categorized as low with a percentage of 19%. The results of this study can be a reference for future researchers to improve aspects of understanding interpreting categories in students.&lt;/em&gt;

Vocal Component of Characters of the Comedy by Lope De Vega «Dance Teacher» in the Performance Interpretation of Drama Actors

The purpose of this article is to find out and analyze the characteristic features of the vocal component of the characters of classical Spanish comedy in the performance interpretation of the drama theatre actors (evidence from the famous production of the CTA play Lope De Vega «Dance Teacher», film 1952).Research methodology. The study is based on the general scientific methods: cognitive, analytical, and comparative; and, in particular, music and theoretical methods: interpretation, the analysis of musical forms, vocal-performing.Results. In drama theatre, music is often an artistic and compositional component of a production. The overall musical component of the performance refers to its frequency and vocal performance of actors, which is not the dominant side of the interpretation of the role image, but significantly the complements of the artistic image of the character, bringing into it the inherent emotional and sensual concept of music art. The significant role of the vocal component on the drama stage is clearly represented in the production of the comedy by Lope De Vega «Dance Teacher» (CTA, director V. Kancell, composer A. Crane, film 1952). Singing is included in various scenes of the performance and, in general, is present as a significant artistic component in five of the twelve actors of the comedy: Aldemaro (Vladimir Zeldin), Feliciana (Lyubov Dobrzhanskaya), Vandalino (Mikhail Mayorov), Belardo (Mark Pertsovsky), Lisena (Henrietta Ostrovskaya). Having analyzed the performance interpretation of the drama actors of the main vocal lyrics, the manners of singing used by artists (variety, academic) have been determined, and a specific connection of elements of different manners of sound formation in one vocal lyric has been revealed; it has been noted that a worthy vocal-performing interpretation substantially complements and enriching the artistic image of the role in the dramatic performance. Novelty. The article covers the specific features of the performance interpretation of vocal lyrics by the actors of the drama theatre (evidence from the CTA production of the play Lope De Vega «Dance Teacher», film 1952).The practical significance. The article contains the information that is useful for professional representatives of the theatre art field and students-actors in terms of improving their performance interpretation, developing vocal and stage abilities and skills.