Affective meanings of 1,469 Bengali concepts.

This article provides semantic differential ratings of 1,469 concepts in Bengali, a language spoken by about 250 million individuals in eastern India and Bangladesh. These data were collected from 20 male and 20 female Calcutta respondents who rated stimuli on three culturally universal affective dimensions: evaluation-potency-activity (EPA). This study employs pan-respondent component analyses as a means of examining the respondents' usage of the standard EPA scales. The pan-respondent component analyses indicate that some respondents used the rating scales in unexpected ways, recording their feelings about one component of concepts' EPA with ratings on a scale intended to measure a different dimension. When scores were based only on respondents who used the scales appropriately, several interesting patterns were found. For respondents of both genders, potency scores have a curvilinear relation with evaluation, such that very good and very bad concepts are mostly seen as very potent, whereas evaluatively neutral concepts are seen as somewhat impotent or just slightly potent. A moderate linear correlation exists between activity and evaluation, and a modest positive relation exists between potency and activity. Gender correlations are high on evaluation, .93, but much lower for potency scores, with a correlation of .55, and even lower for activity, .30. In this article we examine several explanations for why scales denoting potency and activity were reinterpreted as indicating goodness by certain respondents, and consider the matter of including data collected from respondents who used scales in this way.

Validation of Bengali version of EORTC QLQ-SWB32: A standalone measure of spiritual wellbeing for advanced cancer patients receiving palliative care.

Background: Spiritual wellbeing (SWB) is one of the crucial components of holistic care for patients with terminal illnesses. The use of a validated instrument can help health professionals approach this difficult and subjective topic. There is no validated Bengali tool to measure this domain. Our study aimed to translate the EORTC QLQ SWB32 tool into Bengali, validate it among advanced cancer patients in Bangladesh, and compare the study's findings to international validation studies to determine its suitability as a measurement and intervention tool for these patients. Methods: The original English version of the tool was translated in Bengali and back-translated by four independent translators with good command in both languages. After approval from the EORTC translation team and linguistic validation, the tool was further validated among 163 advanced cancer patients from palliative care units of four tertiary-level hospitals in Bangladesh. Reliability was tested with Cronbach's alpha, and construct validity was determined by exploratory factor analysis. Known group comparisons were performed by the Kruskal-Wallis H test and the Mann-Whitney U test. Result: Ten adult cancer patients (two female and eight male, three Hindu and seven Muslim) participated in the linguistic validation. Six out of ten participants found the measure understandable and acceptable. A total of 163 advanced cancer patients participated in the psychometric validation phase. The majority of those participants were Muslims (94 %), with a slight male predominance. The internal consistency of each scale was satisfactory (0.7). Exploratory factor analysis also showed similarity to the original scale except item 12 (able to forgive others), which was loaded in both the EX and RO components (0.813 and 0.544, respectively). Older patients had a better relationship with themselves and a lower level of existential fulfilment than the younger group. Patients who tried to find comfort in their religion or spiritual faith, actively performed religious rituals, and had affiliations with religious or spiritual communities showed significantly higher global SWB. Conclusion: The Bengali version of the EORTC QLQ-SWB32 is a reliable and valid tool for measuring the spiritual wellbeing of advanced cancer patients receiving palliative care.

Generation of simulated data for Bengali text localization in natural images.

In the domain of vision-based applications, the importance of text cannot be underestimated due to its natural capacity to provide accurate and comprehensive information. The application of scene text editing systems enables the modification and enhancement of textual material included in natural images while maintaining the integrity of the overall visual layout. The complexity of keeping the original background context and font styles when altering, however, is an extremely difficult challenge considering the changed image must perfectly blend with the original without being altered. This article contains significant simulated data on the dynamic features of digital image editing, advertising, content development, and related fields. The system comprises key components such as 2D simulated text on the styled image (is), text image (it), masking of text (maskt), real background image (tb), real sample image (tf), text skeleton (tsk), and text styled image (tt). The source dataset contains diverse components such as background images, color variations, fonts, and text content, while the synthetic dataset consists of 49,000 randomly generated images. The dataset provides both researchers and practitioners with a rich resource for identifying and evaluating these dynamic features. The dataset is publicly accessible via the link: https://data.mendeley.com/datasets/h9kry9y46s/3.

BEmoC: A Corpus for Identifying Emotion in Bengali Texts.

Emotion classification in text has growing interest among NLP experts due to the enormous availability of people's emotions and its emergence on various Web 2.0 applications/services. Emotion classification in the Bengali texts is also gradually being considered as an important task for sports, e-commerce, entertainments, and security applications. However, It is a very critical task to develop an automatic emotion classification system for low-resource languages such as, Bengali. Scarcity of resources and deficiency of benchmark corpora make the task more complicated. Thus, the development of a benchmark corpus is the prerequisite to develop an emotion classifier for Bengali texts. This paper describes the development of an emotional corpus (hereafter called 'BEmoC') for classifying six emotions in Bengali texts. The corpus development process consists of four key steps: data crawling, pre-processing, labelling, and verification. A total of 7000 texts are labelled into six basic emotion categories such as anger, fear, surprise, sadness, joy, and disgust, respectively. Dataset evaluation with 0.969 Cohen's κ score indicates the close agreement between the corpus annotators and the expert. The analysis of evaluation also represents that the distribution of emotion words obeys Zipf's law. Moreover, the results of BEmoC analysis shown in terms of coding reliability, emotion density, and most frequent emotion words, respectively.

Validity of vision screening program conducted by preschool teachers: An interventional study.

Background: Clear vision is crucial for effective learning among preschool children. Hence, early detection of vision impairment and prompt treatment are required to improve prognosis. Currently, limited information is available, and no program exists to screen for vision impairment among preschoolers in Bangladesh. This study aimed to validate the KieVision™ Preschool Vision Screening Kit, translated into the Bengali language, to improve vision impairment detection among preschool children. Methods: In this prospective case-control study, 60 preschool teachers from Chittagong were randomly selected. The study group was trained to conduct vision screening among preschool children using the translated kit, whereas the control group was trained using the Chittagong Eye Infirmary and Training Complex (CEITC) School Teachers' Training Module. Fifteen preschool children aged 4-6 years were screened by each preschool teacher and again by the optometrist. Results: Sixty preschool teachers screened 900 children. The results showed a higher validity of vision screening findings by the preschool teachers in the study group (sensitivity, 68.00%; specificity, 92.75%) than in the control group (sensitivity 47.37%, specificity 70.39%). The level of agreement between the preschool teachers and optometrists was high for all tests (first-order agreement coefficient [AC1] ≥ 0.80 in the study group). The sensitivity and specificity of the visual acuity test for the study group were 59.65% and 94.15%, respectively, while in the control group it was 13.33% and 62.54%, respectively. A similar trend was noted in the general observation component and Hirschberg's test. Conclusions: The Bengali Language KieVision™ Preschool Vision Screening Kit can be used effectively by preschool teachers in vision screening programs to improve the identification of vision impairment among preschool children in Bangladesh.