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Artykuły w czasopismach na temat "Personalized Translation Tools"
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Karamysheva, Iryna, Roksolyana Nazarchuk i Kateryna Lishnievska. "PECULIARITIES OF TRANSLATION OF ENGLISH LANGUAGE INSTRUCTIONS WITH THE USE OF ADDITIONAL TOOLS IN SDL TRADOS STUDIO AND MEMOQ TRANSLATOR PRO ENVIRONMENTS". Research Bulletin Series Philological Sciences 1, nr 193 (kwiecień 2021): 376–82. http://dx.doi.org/10.36550/2522-4077-2021-1-193-376-382.
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The presented research focuses upon the analysis of additional specific tools (namely translation memory (TM) technologies) of SDL Trados Studio 2017 and MemoQ Translator Pro 2017 automated translation systems and their application for translation of English-language instructions into Ukrainian. With the help of the above-mentioned software tools 60 English-language operating instructions for household appliances have been translated into Ukrainian (three projects were created in both systems, each containing 10 instructions). TM is a database consisting of segments of source text (sentences, paragraphs, headings, etc.) and translations of each of these segments. TM, used in both SDL Trados Studio and MemoQ Translator Pro systems, significantly improves the quality, speed, consistency and efficiency of each translation task. SDL Trados Studio 2017 and MemoQ Translator Pro 2017 compare content of the current segment of the source file with segments of the same language already contained in the TM. If the system finds a similar segment that is currently stored in the TM, it prompts the translator to use a ready-made translation. The degree of equivalence between the segment of the source document and the segment contained in the TM is expressed as a percentage. Thus, both software tools capture the cases of «Exact match», «Perfect match» and «Fuzzy match». SDL Trados Studio 2017 andMemoQ Translator Pro 2017 slightly differ in segment statuses and colour segment marking. Both systems do not make adjustments automatically, but their identification and navigation capabilities allow one to quickly correct such errors by hand. Unfortunately, the initial focus on the Russian-language market (and, consequently, on the Russian language system) has led to another peculiarity of automated translation into Ukrainian in SDL Trados Studio and MemoQ Translator Pro systems, namely a large number of stylistic errors that require quality personalized correction.
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Zhang, Ping. "Design and Implementation of English-Chinese Translation Teaching Platform Based on Deep Learning". Journal of Electrical Systems 20, nr 3s (31.03.2024): 1746–55. http://dx.doi.org/10.52783/jes.1714.
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The Translation Teaching Platform based on Deep Learning represents a groundbreaking advancement in language education, offering students immersive and personalized learning experiences. By leveraging deep learning algorithms, this platform facilitates real-time translation practice, allowing students to engage with authentic language materials and receive immediate feedback on their performance. Through interactive exercises, multimedia resources, and adaptive learning modules, students can enhance their language proficiency in a dynamic and engaging environment. Moreover, the platform's ability to analyze and adapt to individual learning styles enables personalized instruction tailored to each student's needs. With the Translation Teaching Platform based on Deep Learning, language educators can revolutionize their teaching methods and empower students to achieve fluency and proficiency in their target languages. This paper presents the design and implementation of an innovative English-Chinese Translation Teaching Platform based on Deep Learning, augmented by Embedding Feature Probabilistic Segmentation Classification (EF-PSC). The platform leverages advanced deep-learning techniques to provide students with immersive and interactive translation practice opportunities. Through simulated experiments and empirical validations, the efficacy of the platform is evaluated, demonstrating significant improvements in translation accuracy and learning outcomes compared to traditional methods. The EF-PSC model achieved an average accuracy rate of 91% in translating English to Chinese texts, outperforming conventional translation tools by 15%. Additionally, the platform's adaptive learning features enable personalized instruction tailored to each student's proficiency level and learning pace, leading to more effective language acquisition. These findings underscore the potential of deep learning with EF-PSC in revolutionizing translation teaching methods and enhancing language education.
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Luo, Jing. "Integration and Practice of Computer-Assisted Translation Technology in Modern Translation Teaching". International Education Forum 2, nr 5 (11.07.2024): 8–14. http://dx.doi.org/10.26689/ief.v2i5.7065.
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With the advancement of globalization and the rapid development of information technology, the demand for the translation industry is increasing, posing new challenges and opportunities for translation teaching. The introduction of Computer-Assisted Translation (CAT) technology provides rich resources and innovative methods for translation teaching. This paper explores the integration and practice of CAT technology in modern translation teaching, including translation memory, terminology management, machine translation, translation project management, quality assessment and proofreading tools, collaborative translation platforms, and personalized learning and feedback, analyzing their roles in improving teaching effectiveness and student translation abilities.
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Yefymenko, Tetiana, Tamara Bilous, Anna Zhukovska, Iryna Sieriakova i Iryna Moyseyenko. "Technologies for using interactive artificial intelligence tools in the teaching of foreign languages and translation". Revista Amazonia Investiga 13, nr 74 (29.02.2024): 299–307. http://dx.doi.org/10.34069/ai/2024.74.02.25.
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The article explores the potential of artificial intelligence technologies in teaching foreign languages and translation. It explores the advantages and possible challenges of using such technologies in language education and provides practical examples. The article also discusses perspectives on the future development and use of interactive artificial intelligence tools in the field of language teaching and translation. The integration of artificial intelligence into higher education has ushered in a new era of transformation in educational processes, reforming various aspects of the educational experience. The advantages of introducing artificial intelligence into higher education are numerous, ranging from personalized learning paths to intelligent assessment tools. The tools are classified into categories for students, teachers, and the education system. It identifies key results of such processes and examines various technologies, including Linguatech Learning Assistant, Linguatech Translation Tool, and Linguatech Language Lab, which help students improve their language and translation skills. The research examines the effectiveness of interactive tools in education, comparing their use in classroom and distance learning formats. The article’s conclusions are significant for the development and improvement of language and translation education programs that use innovative artificial intelligence technologies.
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Adishesh i Hapangama. "Enriching Personalized Endometrial Cancer Research with the Harmonization of Biobanking Standards". Cancers 11, nr 11 (5.11.2019): 1734. http://dx.doi.org/10.3390/cancers11111734.
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Endometrial cancer is the commonest gynecological cancer, with an incidence predicted to escalate by a further 50–100% before 2025, due to the rapid rise in risk factors such as obesity and increased life expectancy. Endometrial cancer associated mortality is also rising, depicting the need for translatable research to improve our understanding of the disease. Rapid translation of scientific discoveries will facilitate the development of new diagnostic, prognostic and therapeutic strategies. Biobanks play a vital role in providing biospecimens with accompanying clinical data for personalized translational research. Wide variation in collection, and pre-analytic variations in processing and storage of bio-specimens result in divergent and irreproducible data from multiple studies that are unsuitable for collation to formulate robust conclusions. Harmonization of biobanking standards is thus vital, in facilitating international multi-center collaborative studies with valuable outcomes to improve personalized treatments. This review will detail the pitfalls in the biobanking of biosamples from women with cancer in general, and describe the recent international harmonization project that developed standardized research tools to overcome these challenges and to enhance endometrial cancer research, which will facilitate future development of personalized novel diagnostic strategies and treatments.
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Lightbody, Gaye, Valeriia Haberland, Fiona Browne, Laura Taggart, Huiru Zheng, Eileen Parkes i Jaine K. Blayney. "Review of applications of high-throughput sequencing in personalized medicine: barriers and facilitators of future progress in research and clinical application". Briefings in Bioinformatics 20, nr 5 (14.06.2019): 1795–811. http://dx.doi.org/10.1093/bib/bby051.
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Abstract There has been an exponential growth in the performance and output of sequencing technologies (omics data) with full genome sequencing now producing gigabases of reads on a daily basis. These data may hold the promise of personalized medicine, leading to routinely available sequencing tests that can guide patient treatment decisions. In the era of high-throughput sequencing (HTS), computational considerations, data governance and clinical translation are the greatest rate-limiting steps. To ensure that the analysis, management and interpretation of such extensive omics data is exploited to its full potential, key factors, including sample sourcing, technology selection and computational expertise and resources, need to be considered, leading to an integrated set of high-performance tools and systems. This article provides an up-to-date overview of the evolution of HTS and the accompanying tools, infrastructure and data management approaches that are emerging in this space, which, if used within in a multidisciplinary context, may ultimately facilitate the development of personalized medicine.
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Alghamdi, Maha Ali, Antonino N. Fallica, Nicola Virzì, Prashant Kesharwani, Valeria Pittalà i Khaled Greish. "The Promise of Nanotechnology in Personalized Medicine". Journal of Personalized Medicine 12, nr 5 (22.04.2022): 673. http://dx.doi.org/10.3390/jpm12050673.
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Both personalized medicine and nanomedicine are new to medical practice. Nanomedicine is an application of the advances of nanotechnology in medicine and is being integrated into diagnostic and therapeutic tools to manage an array of medical conditions. On the other hand, personalized medicine, which is also referred to as precision medicine, is a novel concept that aims to individualize/customize therapeutic management based on the personal attributes of the patient to overcome blanket treatment that is only efficient in a subset of patients, leaving others with either ineffective treatment or treatment that results in significant toxicity. Novel nanomedicines have been employed in the treatment of several diseases, which can be adapted to each patient-specific case according to their genetic profiles. In this review, we discuss both areas and the intersection between the two emerging scientific domains. The review focuses on the current situation in personalized medicine, the advantages that can be offered by nanomedicine to personalized medicine, and the application of nanoconstructs in the diagnosis of genetic variability that can identify the right drug for the right patient. Finally, we touch upon the challenges in both fields towards the translation of nano-personalized medicine.
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Raballo, A. "Diagnostic Procedures for Prediction of Psychosis - Achievements and Challenges". European Psychiatry 41, S1 (kwiecień 2017): S27. http://dx.doi.org/10.1016/j.eurpsy.2017.01.139.
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Individualized prognostic predictions in people at clinical high risk are crucial to tailor suitable interventions and personalized prevention. Furthermore, in recent years, the synergy between fast-pace technical sophistication in neuroscience (e.g. neuroimaging and neurophysiological) and novel bio-statistical tools (e.g. machine learning algorithms) has accelerated the development of more inclusive predictive models and magnified the potential for such individualized risk stratification enriching classical psychopathological tools. However, the clinical translation of such research insights is still circumscribed and, despite incremental optimization of assessment tools, increasingly accepted criteria to characterize at risk mental states and tumultuous advance in the field, the prediction of psychosis at such individual level remains a not fully accomplished target.Disclosure of interestThe author has not supplied his declaration of competing interest.
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Antunes, Nina, Banani Kundu, Subhas C. Kundu, Rui L. Reis i Vítor Correlo. "In Vitro Cancer Models: A Closer Look at Limitations on Translation". Bioengineering 9, nr 4 (7.04.2022): 166. http://dx.doi.org/10.3390/bioengineering9040166.
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In vitro cancer models are envisioned as high-throughput screening platforms for potential new therapeutic discovery and/or validation. They also serve as tools to achieve personalized treatment strategies or real-time monitoring of disease propagation, providing effective treatments to patients. To battle the fatality of metastatic cancers, the development and commercialization of predictive and robust preclinical in vitro cancer models are of urgent need. In the past decades, the translation of cancer research from 2D to 3D platforms and the development of diverse in vitro cancer models have been well elaborated in an enormous number of reviews. However, the meagre clinical success rate of cancer therapeutics urges the critical introspection of currently available preclinical platforms, including patents, to hasten the development of precision medicine and commercialization of in vitro cancer models. Hence, the present article critically reflects the difficulty of translating cancer therapeutics from discovery to adoption and commercialization in the light of in vitro cancer models as predictive tools. The state of the art of in vitro cancer models is discussed first, followed by identifying the limitations of bench-to-bedside transition. This review tries to establish compatibility between the current findings and obstacles and indicates future directions to accelerate the market penetration, considering the niche market.
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Chen, Xiaoxian. "Research on the Application of Artificial Intelligence in Translation Courses". International Journal of Education and Humanities 12, nr 1 (15.01.2024): 41–44. http://dx.doi.org/10.54097/3c1b8w36.
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With the rapid development of artificial intelligence technology, its application in the field of education is more and more extensive. This paper aims to deeply explore the application of artificial intelligence in translation courses, analyze its advantages, application models, problems and solutions, and forecast the future research direction and development trend. First of all, this paper gives a comprehensive overview of artificial intelligence technology, and elaborates its definition, classification and development history in depth. Then, in light of the problems and challenges of traditional translation courses, this paper focuses on the advantages of AI application in translation courses, including improving the accuracy and efficiency of translation and providing personalized learning support. At the same time, this paper also introduces the application mode and practice of artificial intelligence in translation courses in detail, including the principle and function of intelligent translation tools, case analysis of translation course design based on artificial intelligence technology. When discussing the problems faced in the application and solving strategies, this paper deeply analyzes the technical limitations and defects, the change of teacher's role and students' learning mode, and puts forward a series of feasible solving strategies. Finally, the practical value of artificial intelligence in translation courses is summarized, and the future research direction and development trend are prospected.
Rozprawy doktorskie na temat "Personalized Translation Tools"
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Hansen, Damien. "Évaluation experte d'un prototype d'aide à la traduction créative : la traduction littéraire automatique individualisée au regard de ses enjeux traductologiques, éthiques et sociétaux". Electronic Thesis or Diss., Université Grenoble Alpes, 2024. http://www.theses.fr/2024GRALM002.
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Si la traduction automatique a traditionnellement été perçue en littérature comme une technologie avant-gardiste digne des créations oulipiennes, l'arrivée plus récente des outils de traduction neuronaux a ouvert un débat nouveau, bien plus polarisé qu'auparavant. Pour poser un regard critique et objectif sur cette question, nous avons donc entrepris de mettre au point un système spécifiquement entraîné sur des textes littéraires. Si nous voyons qu'il est bien possible d'adapter de tels systèmes à ce domaine particulier, malgré les limites évidentes dont ces modèles font encore preuve, notre expérience sur la prose de fiction montre qu'il est aussi possible de les adapter au style individuel d'un traducteur ou d'une traductrice. Ces conclusions soulèvent évidemment de nombreuses questions liées à l’ergonomie des technologies de la traduction, ainsi qu'aux questions éthiques et aux enjeux sociétaux qui les entourent, mais elles indiquent surtout qu'il est possible de réimaginer ces outils et de les repenser d'une manière qui serve plus directement l'interaction humain-machine, le processus créatif et la qualité des textes traduitsAlthough machine translation has traditionally been perceived in the literary domain as a sort of avant-garde technology on a par with Oulipian techniques, the recent arrival of neural translation tools seems to have given rise to an entirely new and deeply polarized debate. In order to take a critical and objective look on the matter, we therefore attempt to build a system specifically trained on literature. While our results show that it is indeed possible to train such a system for this particular domain, despite the still evident limitations of these models, our experience on prose fiction also demonstrates that they can be tailored to the individual style of a translator. Our conclusions obviously raise newfound questions regarding the ergonomic aspects of translation technology, the ethical concerns that it raises or the societal issues that have to be addressed. But, more importantly, they indicate that it is possible to reimagine such tools and rethink their use in a way that better serves the human-machine interaction, the creative process and the quality of translated texts
Części książek na temat "Personalized Translation Tools"
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Garbani-Nerini, Elide, Elena Marchiori, Rossella Reale i Lorenzo Cantoni. "Understanding Preferences in Tourism Email Marketing". W Information and Communication Technologies in Tourism 2022, 382–94. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-94751-4_34.
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AbstractNowadays, advanced tools allow the personalization of email communication with tourism clients or prospects based on explicit (e.g. name, age, language, country) and implicit indicators (e.g. ranking of activity in the opening rate of the newsletter, browsing preferences, online preferences provided by cookies, etc.). However, knowing how audiences react to emails allows Destination Marketing Organizations (DMOs) to create content clusters for personalized communication. The purpose of this study is to empirically investigate the preferences on tourism email marketing of different audiences based on a specific explicit indicator, namely the language chosen by users to receive communications by a DMO. A content analysis on a longitudinal dataset based on 131 newsletter messages sent between 2018 and 2021 to more than 50′000 contacts by a DMO in Switzerland was performed. Results show that content should be adapted to different audiences speaking different languages instead of providing just a translation. Specifically, the German-speaking audience seems to be more inclined to messages that focus on winter sports and hiking, the Italian-speaking audience to news about hiking and information on COVID-19, the French-speaking audience to news about promotions, while the English-speaking audience to contents on discounts and COVID-19-related. These results provide an important contribution to studies on tourism personalization of communication in the context of email marketing, suggesting the role of content adaptation according to the language and cultural background of the audience. DMO managers can also benefit from this research in understanding how to address a similar study on their datasets and compare the emerged content clusters.
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Kaemmerer, Daniel. "Nuclear Medicine and Surgery on the Way to Personalized Medicine. Ten Years of Clinical and Translational Oncology and Research". W Beyond Becquerel and Biology to Precision Radiomolecular Oncology: Festschrift in Honor of Richard P. Baum, 177–80. Cham: Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-33533-4_17.
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AbstractSurgery with a complete tumor removal is the only therapeutic option with a curative approach in a neuroendocrine tumor disease. Recurrent abdominal surgery is associated with inflammation, altered anatomy, and scar tissue and can be challenging [1]. Additionally, tumor lesions can be really small, invisible, or not palpable by the surgeon’s fingers. For that reason, an intraoperative diagnostic tool is necessary because the prior imaging (scintigraphy, PET/CT) has a reduced sensitivity with lower tumor size. Sufficient, preoperative, and intraoperative imaging can provide the surgeon with valuable assistance and also significantly simplify the surgical procedure. Depending on the intraoperative findings, the surgical intervention can be expanded or even significantly reduced.
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J. Jayamani, Mr, Mrs U. Gokul Priya i Dr C. P. Sangeetha. "ENHANCING TOURIST EXPERIENCES THROUGH IMMERSIVE VIRTUAL REALITY, AUGMENTED REALITY AND ARTIFICIAL INTELLIGENCE TECHNOLOGIES". W Futuristic Trends in Management Volume 3 Book 10, 126–32. Iterative International Publisher, Selfypage Developers Pvt Ltd, 2024. http://dx.doi.org/10.58532/v3bhma10p1ch8.
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As the tourism industry continually seeks innovative ways to engage and captivate travelers, immersive technologies such as Virtual Reality (VR), Augmented Reality (AR), and Artificial Intelligence (AI) are emerging as transformative tools. This research explores the potential of these technologies to enhance tourist experiences. Through an in-depth analysis of current applications and case studies, this study investigates how VR, AR, and AI contribute to personalized and immersive tourism encounters. Key findings highlight the ability of VR and AR to provide virtual travel previews, historical context, and interactive storytelling, while AI enhances tourists' journeys through personalized recommendations, real-time language translation, and adaptive travel planning. This research underscores the immense potential of these technologies to reshape the tourism landscape, making it more accessible, interactive, and memorable.
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Saba Farheen, N. S., Chethan S. Badiger, Lalith Kishore, V. Dheeraj i Sindhu R. Rajendran. "A Future Look at Artificial Intelligence in the World of Tourism". W Marketing and Big Data Analytics in Tourism and Events, 1–16. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-3310-5.ch001.
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In the realm of travel, a silent revolution is unfolding, driven by artificial intelligence (AI). Tailored experiences powered by AI are tangible, with data analytics crafting bespoke itineraries and recommendations fueled by natural language processing and simplifying planning and navigation. AI optimizes transportation, refining traffic control and route planning for convenience. Augmented reality adds immersive layers to traveler experiences. AI plays a pivotal role in sustainability, regulating visitor flows and energy usage. Real-time data analysis aids crisis management, ensuring safety and industry resilience. AI systems, standalone or integrated, encompass recommendation engines, personalization algorithms, conversational interfaces, predictive tools, language translation software, and intelligent destination mapping. Smart destinations integrate these technologies with social and organizational elements. AI empowers travelers with personalized options and enables companies to tailor experiences.
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Valencia Quiroz, Israel. "Exploring the Intersection of Omics Technologies and Biotechnology in Drug Interaction Studies". W Biotechnology and Drug Development for Targeting Human Diseases, 188–203. BENTHAM SCIENCE PUBLISHERS, 2024. http://dx.doi.org/10.2174/9789815223163124090011.
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The integration of omics tools with biotechnology has led to a paradigm shift in our comprehension of drug interactions, providing profound insights into the molecular mechanisms underlying these interactions. We explore the crucial functions of genomes, transcriptomics, proteomics, and metabolomics in this chapter to decode pharmacological interactions at various molecular levels. Notably, significant emphasis is placed on the application of omics tools in areas such as high-throughput screening for unveiling novel drug targets, personalized medicine, pharmacogenomics, understanding drug-drug and drug-metabolite interactions, drug repurposing, polypharmacology, and systems biology. Furthermore, the paper explores the potential of integrating omics data with computational approaches to study complex biological networks, highlighting the instrumental role of microbial biotechnology in drug interactions. Importantly, alongside these advancements, there is also an in-depth discussion of the ethical, legal, and societal ramifications of the use of omics technologies in biotechnology. Moreover, the text presents an in-depth examination of the emerging trends, challenges, and prospective developments in the realm of omics research. As the field continues to evolve, overcoming challenges related to data integration, reproducibility, and standardization are underscored as crucial for the translation of these pioneering discoveries into improved patient care and the development of more effective, personalized therapeutic strategies. It is crucial to remember that the combination of omics tools and biotechnology will have significant effects on how medicine and healthcare are delivered in the future. As a result, it is essential to maintain research and development in this field to ensure that all future healthcare-related exigencies can be met with the most advanced and innovative solutions possible.
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Bansal, Shruti, Punjika Rathi, Rachit Agarwal i Ramneek Ahluwalia. "Leveraging AI to Enhance the Global Mobility Experience". W Transforming the Financial Landscape With ICTs, 108–33. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-1503-3.ch006.
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The study investigates how AI-driven solutions are revolutionizing student interactions, admissions processes, academic support, and cross-cultural adaptation. Through intelligent chatbots, personalized recommendations, and predictive analytics, universities are catering to individual needs and streamlining administrative procedures. Furthermore, AI-powered language translation tools are aiding international students in overcoming language barriers, fostering better communication, and enriching their learning experiences. In the Indian higher education landscape, this trend holds particular significance due to the nation's burgeoning student population and aspirations for global recognition. The chapter underscores the importance of continuous innovation, collaboration, and adaptability in integrating AI solutions effectively. By embracing these advancements, Indian universities can position themselves as attractive destinations for international students, fostering diversity and cross-border learning. This study provides valuable insights into the symbiotic relationship between AI and global education mobility, accentuating the need for a dynamic approach to reshape the future of higher education on a global scale and helpful for policymakers to enhance the AI in higher education system.
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Singhal, Priyanshi, i Ms Natasha. "HARNESSING THE POWER OF PERSONALIZED MEDICINES: STEPS AND INNOVATIONS". W Futuristic Trends in Biotechnology Volume 3 Book 5, 171–81. Iterative International Publishers, Selfypage Developers Pvt Ltd, 2024. http://dx.doi.org/10.58532/v3bjbt5p5ch3.
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Personalized medicine, precision medicine, and precision health as approaches to healthcare that emphasize tailoring treatments to an individual's unique biological, behavioral, and environmental factors. These terms are sometimes used interchangeably, but personalized medicine is considered broader than precision medicine, encompassing a wide range of health factors. Precision medicine specifically focuses on genomic and physiological biomarkers. These approaches aim to prevent, diagnose, and treat diseases within the healthcare system. Precision health represents a broader framework that includes public health and consumer health management. The chapter highlights the principles and advancements of personalized and precision medicine, the shift from a "one size fits all" paradigm to individualized patient identification, diagnosis, and treatment, leveraging genomics and molecular diagnosis. The goal is to maximize therapeutic efficacy while reducing the risk of drug toxicity. The study emphasizes the potential of personalized medicine to improve target selectivity of drugs, enhance clinical trial success, and develop personalized treatment strategies. Additionally, the chapter mentions the application of personalized medicine and challenges faced during data collection, medicine development, and clinical trials. Overall, personalized medicine offers a promising approach for better healthcare, focusing on prevention, prediction, and treatment tailored to individual needs based on their genomic makeup and other factors. The emergence of genomics and translational genetics has provided powerful tools for clinical diagnosis, disease prediction, high throughput screening, and the development of personalized therapies and vaccines.
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Jayapriya, J., M. Vinay, Blessy Louis i S. Deepa. "Securing Her Digital Footprint". W Wearable Devices, Surveillance Systems, and AI for Women's Wellbeing, 206–37. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-3406-5.ch013.
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This chapter emphasizes the importance of artificial intelligence (AI) tools, analysis about the existing AI tools, and recommendations for future AI tools for women's safety. AI is experiencing significant growth and influence in the current era. Several key trends and developments highlight the role of AI in various domains: AI is being used for medical diagnosis, drug discovery, and patient care. Machine learning models are helping doctors analyse medical images, predict disease outcomes, and personalize treatment plans. Self-driving cars and drones are utilizing AI algorithms for navigation, obstacle detection, and decision-making. These technologies are advancing transportation and logistics. Natural language processing models like GPT-3 are transforming language-related tasks, from chatbots and virtual assistants to content generation, translation, and sentiment analysis. This chapter highlights the AI tools that exist for women's safety in the digital world and future apps needs for the same.
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Lee, Sangmin-Michelle. "L2 learners’ strategies for using machine translation as a personalized writing assisting tool". W Smart CALL: Personalization, Contextualization, & Socialization, 184–206. Castledown Publishers, 2022. http://dx.doi.org/10.29140/9781914291012-9.
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In recent years, MT has shown a marked increase in popularity among L2 students, both inside and outside the classroom. While MT is a smart tool to assist L2 learners’ writing, ‘smart’ strategies are also crucial for learners to effectively use MT for their language learning. Studies have confirmed that learners’ attitudes and strategies for utilizing and adopting options from resources during their writing and revising vary. In the similar vein, it is assumed that students utilize different strategies when using MT, which will influence their writing outcomes. Despite the growing number of students using MT, learner strategies for using MT have not been reported. Therefore, the current study investigated L2 learners’ strategies for using MT during the writing and revising process. The present study employed a mixed method with quantitative content analysis of the 32 Korean college students’ essays and screen recordings of their writing processes and qualitative analysis of post-interviews. The result showed that the students were not merely dependent on MT during writing, but they effectively and strategically used MT for their needs based on their linguistic knowledge and other resources. However, the study also showed that depending on language proficiencies, the students perceived using MT differently and used it in different ways. While more proficient students perceived MT as a smart CALL tool, using MT was too challenging for low-level students. Based on the results, the study suggested pedagogical implications regarding using MT in language classrooms.
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Remya, E. "Therapeutic Potential of Ayurvedic Practices for the Mental Health of the Geriatric Population". W Advances in Psychology, Mental Health, and Behavioral Studies, 263–79. IGI Global, 2023. http://dx.doi.org/10.4018/978-1-6684-9778-4.ch015.
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Drastic population ageing points to increased prevalence of physical and mental disorders in the elderly. Mental illnesses of the elderly are often related to biological and psychosocial risk elements which can be predicted and prevented using Ayurvedic diagnostic tools such as Dosha and Prakriti. This chapter presents a hypothetical personalised model to preserve the mental health of geriatric population w.s.r to dietary and lifestyle modifications. This section also explores the translational research outlook and evidence-based perspectives of Rasayana drugs, and Panchakarma procedures in most prevalent and distressing psychological disorders such as anxiety, post-traumatic stress disorders, insomnia, psychological imbalances inherent to mood disorders, psychotic diseases, neuro-degenerative disorders, etc.
Streszczenia konferencji na temat "Personalized Translation Tools"
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Zech, Henrike, Adriana Perugachi Heinsohn, Katharina Stölzel, Arne Böttcher, Nikolaus Möckelmann, Thorsten Rieckmann i Christian Betz. "Tumor tissue slice cultivation – A translational tool to personalize (radio-)therapy in sinunasal squamous cell carcinoma (SNSCC)?" W 95th Annual Meeting German Society of Oto-Rhino-Laryngology, Head and Neck Surgery e. V., Bonn. Georg Thieme Verlag KG, 2024. http://dx.doi.org/10.1055/s-0044-1784785.
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Sanatkhani, Soroosh, i Prahlad G. Menon. "Three-Dimensional Cephalometric Analysis Using Computed Tomographic Imaging". W ASME 2018 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/imece2018-88259.
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Successful outcomes from the use of orthodontic devices are underpinned on their effective anchorage and the loading that they apply to the underlying facial structures. Anchorage plays an important role in determining the point of application of the corrective forces and subsequently the orientation of the resultant of these forces, which in-turn governs the outcome of treatment. Therefore, patient-specific design of anchors and their placement may benefit significantly from personalization using patient-specific and three-dimensional (3D) cephalometry. 3D cephalometry is therefore a first step to personalization of orthodontic treatment. In this feasibility study, we demonstrate the viability a novel image processing and surface analysis pipeline to quantify facial symmetry about the mid-sagittal facial plane, which may offer insight into optimal placement and orientation for implantation of orthodontic anchors, starting with patient-specific cone beam computed tomography (CBCT) images. Typical assessments of geometrical features/attributes of face include size, position, orientation, shape, and symmetry. Using 3D CBCT images in the DICOM image format, skull images were first segmented using a basic iso-contouring approach. To quantify symmetry, we split the skull along the mid-sagittal plane and used an iterative closest point (ICP) approach in order to rigidly co-register the left and right sides of the skull, optimizing for rotation, translation and scaling, after reflection of one half across the mid-sagittal plane. This was accomplished using an in-house plugin is developed for the open-source visualization toolkit (VTK) based 3D visualization tool, Paraview (Kitware Inc.). Finally, using a signed regional distance mapping plugin we were able to assess the regional asymmetry of regions of the skull (e.g. upper and lower jaw – specific targets for therapy) using colormaps of regional asymmetry (in terms of left-v/s-right side surface distance) and visualized the same as vector glyphs. The direction of these vectors is synonymous with anticipated regional forces required in order to achieve left-right symmetry, which in-turn may have value in surgical planning for orthodontic implantation. In sum, we demonstrate a workflow for computer-aided cephalometry to assess the symmetry of the skull, which shows promise for personalized orthodontic anchor design.