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Lampung Province is located on the island of Sumatera. For the immigrants in Lampung, they have difficulty in communicating with the indigenous people of Lampung. As an alternative, both immigrants and the indigenous people of Lampung speak Indonesian. This research aims to build a language model from Indonesian language and a translation model from the Lampung language dialect of nyo, both models will be combined in a Moses decoder. This research focuses on observing the effect of adding mono corpus to the experimental statistical machine translation of Indonesian - Lampung dialect of nyo. This research uses 3000 pair parallel corpus in Indonesia language and Lampung language dialect of nyo as source language and uses 3000 mono corpus sentences in Lampung language dialect of nyo as target language. The results showed that the accuracy value in bilingual evalution under-study score when using 1000 sentences, 2000 sentences, 3000 sentences mono corpus show the accuracy value of the bilingual evaluation under-study, respectively, namely 40.97 %, 41.80 % and 45.26 %.

A radiology report plays a crucial role in guiding patient treatment, but writing these reports is a time-consuming task that demands a radiologist’s expertise. In response to this challenge, researchers in the subfields of artificial intelligence for healthcare have explored techniques for automatically interpreting radiographic images and generating free-text reports, while much of the research on medical report creation has focused on image captioning methods without adequately addressing particular report aspects. This study introduces a Conditional Self Attention Memory-Driven Transformer model for generating radiological reports. The model operates in two phases: initially, a multi-label classification model, utilizing ResNet152 v2 as an encoder, is employed for feature extraction and multiple disease diagnosis. In the second phase, the Conditional Self Attention Memory-Driven Transformer serves as a decoder, utilizing self-attention memory-driven transformers to generate text reports. Comprehensive experimentation was conducted to compare existing and proposed techniques based on Bilingual Evaluation Understudy (BLEU) scores ranging from 1 to 4. The model outperforms the other state-of-the-art techniques by increasing the BLEU 1 (0.475), BLEU 2 (0.358), BLEU 3 (0.229), and BLEU 4 (0.165) respectively. This study’s findings can alleviate radiologists’ workloads and enhance clinical workflows by introducing an autonomous radiological report generation system.

There is a lack of effective, comprehensive understudy training programs in the Roads Authority (RA) of Namibia, compounded by a lack of monitoring and evaluation mechanisms of such programs. Minimal research has been done on the topic of understudy programs and knowledge transfer in Namibia. The objectives of this study were to investigate the implementation of the RA’s understudy programs and their management and determine the extent to which expatriates comply with the understudy policies. This study adopted a mixed research approach. Data for the study were obtained through face-to-face interviews and self-administered questionnaires. The motive behind this choice was the need to communicate only with those with experience as mentors or who have been appointed as understudies in the Roads Authority (RA). The overall findings established that the effectiveness of the understudy program was hampered by a lack of commitment, awareness and communication, and a lack of personal growth and development opportunities. In addition, the study revealed conflicting roles in work situations due to incompatible work programs, and scheduling of the program. It is recommended that RA devise formal training programs for understudies appointed to understudy expatriates and ensure that those are strictly enforced. The program should include tacit on-the-job knowledge transfer which is monitored by management on a regular basis. The program should be tailored to suit the employees’ training needs. In addition, regular information sessions should be conducted in order to sensitize all parties involved concerning the understudy policy and Affirmative Action Act, No.28 of 1998.

This study is a quantitative analysis that investigates and compares the quality level of Computer Assisted Translation (CAT) tools, Neural Machine Translation (NMT) systems, and Large Language Models (LLMs) against each other and how well they can perform on translation tasks from English into Arabic and vice versa, in comparison to human translator. By utilizing a Bilingual Evaluation Understudy (BLEU) and comparing seven translation platforms, the study revealed that AI models outperform both CAT tools and NMT systems when translating in both directions. In addition, Gemini scores the highest BLEU score in both directions, surpassing all the other six platforms, while Google Translate scores are the lowest. The study also reveals that these platforms struggle more with English-to-Arabic translation due to the complexity of the Arabic language. Since CAT tools generally have the lowest scores, they assist the human translator rather than replacing them, providing a partially automated translation. Accordingly, AI models can be more helpful and preferable due to their high BLEU score. However, despite often producing accurate translations and conveying the core meaning, MT may still struggle to imitate the stylistic choices and conciseness that characterize a professional human translator at work.

El lenguaje se ve afectado, no solo por las reglas gramaticales, sino también por el contexto y las diversidades socioculturales, por lo cual, el resumen automático de textos (un área de interés en el procesamiento de lenguaje natural - PLN), enfrenta desafíos como la identificación de fragmentos importantes según el contexto y el tipo de texto analizado. Trabajos anteriores describen diferentes métodos de resúmenes automáticos, sin embargo, no existen estudios sobre su efectividad en contextos específicos y tampoco en textos en español. En este artículo se presenta la comparación de tres algoritmos de resumen automático usando noticias y editoriales en español. Los tres algoritmos son métodos extractivos que buscan estimar la importancia de una frase o palabra a partir de métricas de similitud o frecuencia de palabras. Para esto se construyó una base de datos de documentos donde se incluyeron 33 editoriales y 27 noticias, obteniéndose un resumen manual para cada texto. La comparación de los algoritmos se realizó cuantitativamente, empleando la métrica Recall-Oriented Understudy for Gisting Evaluation. Asimismo, se analizó el potencial de los algoritmos seleccionados para identificar los componentes principales del texto. En el caso de las editoriales, el resumen automático debía incluir un problema y la opinión del autor, mientras que, en las noticias, el resumen debía describir las características temporales y espaciales de un suceso. En términos de porcentaje de reducción de palabras y precisión, el método que permite obtener los mejores resultados, tanto para noticias como para editoriales, es el basado en la matriz de similitud. Este método permite reducir en un 70 % los textos, tanto editoriales como noticiosos. No obstante, es necesario incluir la semántica y el contexto en los algoritmos para mejorar su desempeño en cuanto a precisión y sensibilidad.  

There is a lack of effective, comprehensive understudy training programs in the Roads Authority (RA) of Namibia, compounded by a lack of monitoring and evaluation mechanisms of such programs. Minimal research has been done on the topic of understudy programs and knowledge transfer in Namibia. The objectives of this study were to investigate the implementation of the RA’s understudy programs and their management and determine the extent to which expatriates comply with the understudy policies. This study adopted a mixed research approach. Data for the study were obtained through face-to-face interviews and self-administered questionnaires. The motive behind this choice was the need to communicate only with those with experience as mentors or who have been appointed as understudies in the Roads Authority (RA). The overall findings established that the effectiveness of the understudy program was hampered by a lack of commitment, awareness and communication, and a lack of personal growth and development opportunities. In addition, the study revealed conflicting roles in work situations due to incompatible work programs, and scheduling of the program. It is recommended that RA devise formal training programs for understudies appointed to understudy expatriates and ensure that those are strictly enforced. The program should include tacit on-the-job knowledge transfer which is monitored by management on a regular basis. The program should be tailored to suit the employees’ training needs. In addition, regular information sessions should be conducted in order to sensitize all parties involved concerning the understudy policy and Affirmative Action Act, No.28 of 1998.

In Rehearsal is a clear and accessible how-to approach to the rehearsal process. Author Gary Sloan brings more than thirty years' worth of acting experience to bear on the question of how to rehearse both as an individual actor and as part of the team of professionals that underpins any successful production. Interviews with acclaimed actors, directors, playwrights, and designers share a wealth of knowledge on dynamic collaboration. The book is divided in to three main stages, helping the reader to refine their craft in as straightforward and accessible manner as possible: In the world: A flexible rehearsal program that can be employed daily, as well as over a typical four week production rehearsal. In the room: Advice on working independently and productively with other members of a company, such as directors, playwrights, designers and technical crew; how your personal creative process varies depending on the role, be it Shakespeare, musicals, film, television or understudying. On your own: Creating your own rehearsal process, exploring original and famous rehearsal techniques, breaking through actor's block and how to practice every day. In Rehearsal breaks down the rehearsal process from the actor's perspective and equips its reader with the tools to become a generous and resourceful performer both inside and outside the studio. Its independent, creative and daily rehearsal techniques are essential for any modern actor.

Rebeck starts by imagining that a newly discovered lost masterpiece by Kafka, a two-man play full of paranoia, existential absurdity, and faceless oppression, has been brought to Broadway - with, naturally enough in the current climate, two big movie-star action heroes playing the roles.

Coen brings to \"Understudy\" a keen eye for the vagaries, absurdities, and serial humiliations of an actor's life - from which, we will see as \"Understudy\" unfolds, even movie stars are not exempt.