Gotowa bibliografia na temat „Dragonfly and DraMS”

Face recognition is one of the best applications of computer recognition and recent smart house applications. Therefore, it draws considerable attention from researchers. Several face recognition algorithms have been proposed in the last decade, but these methods did not give the efficient outcome. Therefore, this work introduces a novel constructive training algorithm for smart face recognition in door locking applications. The proposed Framed Recurrent Neural Network with Mutated Dragonfly Search Optimization (FRNN-MDSO) Strategy is applied to face recognition application. The steady preparing system has been utilized where the training designs are adapted steadily and are divided into completely different modules. The facial feature process works on global and local features. After the feature extraction and selection process, employ the improved classifier followed by the Framed Recurrent Neural Network classification technique. Finally, the face image based on the feature library can be identified. The proposed Framed Recurrent Neural Network with Mutated Dragonfly Search Optimization starts with a single training pattern using Bidirectional Encoder Representations from Transformers (BERT) model. During network training, the Training Data (TD) decrease the Mean Square Error (MSE) while the matching process increases the algorithms generated which are trapped at the local minimum. The training data have been trained to increase the number of input forms (one after the other) until all the forms are selected and trained. An FRNN-MDSO based face recognition system is built, and face recognition is tested using hyperspectral Database parameters. The simulation results indicate that the proposed method acquires the associate grade optimum design of FRNN with MDSO methodology using the present constructive algorithm and prove the proposed FRNN-MDSO method’s effectiveness compared to the conventional architecture methods.

Social media can advocate for social causes and catalyse audience support. To better understand the role of social media in advocacy communication, this article explores how advocates utilised Facebook to advocate for the ‘Taa Marbuta’ women empowerment campaign in Egypt. Our research draws on the dragonfly effect model and muted group theory as theoretical and analytical frameworks. In-depth interviews are conducted with advocates from all campaign partners who were directly involved in planning and managing the campaign. Following the dragonfly effect model, findings show that the campaign has a clear goal and uses various message strategies and pop culture for grabbing audience attention and generating audience engagement; however, there is no clear call for action. Thematic analysis also reveals two emerging themes: customisation of women empowerment communication and a supportive community of women empowerment that can stimulate societal debates necessary for social change. This study contends that including men can mitigate the muted effect on women in a male-dominant society and paves the way towards women’s empowerment. Overall, this study shows how social media helps make the ‘Taa Marbuta’ campaign an icon of women empowerment.

AbstractPredicting the drill penetration rate is a fundamental requirement in mining operations, profoundly impacting both the cost-effectiveness of mining activities and strategic mine planning. Given the intricate web of factors influencing rotary drilling performance, the necessity for advanced modeling techniques becomes evident. To this end, the hybrid extreme gradient boosting (XGBoost) was utilized to gauge the penetration rate of rotary drilling machines, utilizing random search, grid search, Harris Hawk optimization (HHO), and the dragonfly algorithm (DA) as metaheuristic algorithms. Our research draws from extensive data collected in copper mine case studies, encompassing both field and investigational data. This dataset incorporates critical material properties, such as tensile strength (TS), uniaxial compressive strength (UCS), as well as vital rock-mass characteristics including joint direction (JD), joint spacing (JS), and bit diameter (D). Our investigation evaluates the reliability of these prediction methods using various performance indicators, including mean absolute error (MAE), root mean square error (RMSE), average absolute relative error (AARE), and coefficient of determination (R2). The multivariate analysis reveals that the HHO-XGB model stands out, demonstrating superior prediction accuracy (MAE: 0.457; RMSE: 2.19; AARE: 2.29; R2: 0.993) compared to alternative models. Furthermore, our sensitivity analysis emphasizes the substantial impact of uniaxial compressive strength and tensile strength on the drill penetration rate. This underlines the importance of considering these material properties in mining operations. In conclusion, our research offers robust models for forecasting the penetration rate of similar rock formations, providing invaluable insights that can significantly enhance mining operations and planning processes.

Au cours de cette thèse, nous avons fourni des éléments de réponse pour les problématiques d'exploration spatiale : i) Quelles signatures recherchons-nous pour des traces de vie et/ou une chimie prébiotique sur les surfaces planétaires de notre système solaire ? et ii) Comment pouvons-nous les détecter ? Quelle méthode de préparation des échantillons est la plus adéquate pour une analyse GC-MS spatiale ? ainsi que pour les problématiques fondamentales : i) Comment s'est déroulé la transition entre une chimie prébiotique abiotique et une chimie biotique ? Y a-t-il une limite nette ou un état de transition que l'on pourrait défnir comme « biochimie primitive » ? et ii) Quel est l'influence de chaque paramètre environnemental sur la dégradation/transformation de cette matière organique abiotique ou biotique ?L'application d'une approche transdisciplinaire a permis non seulement de préparer les instruments GC-MS spatiaux avec des analogues définit par des caractéristiques communes aux surfaces planétaires extraterrestres explorées mais aussi d'identifier des précurseurs, bioindicteurs et bisoignatures que l'on a sous catégorisé comme agnostique d'une vie quelconque ou gnostique assimilé à la vie terrestre connue.Les protocoles d'extraction de matière organique optimisés dans cette thèse ont permis l'application de protocole spatial pour une approche de métabolomique environnementale non ciblée et ainsi identifier des populations au sein des environnements analogues investigués et des molécules essentielles à l'adaptation au milieu et préservation face aux sels, irradiations et biodisponibilité de l'eau et de nutriments
During this thesis, we provided elements of answers for space exploration issues: i) What signatures are we looking for traces of life and/or prebiotic chemistry on the planetary surfaces of our solar system? and ii) How can we detect them? Which sample preparation method is most suitable for spatial GC-MS analysis? as well as for fundamental issues: i) How did the transition take place between abiotic prebiotic chemistry and biotic chemistry? Is there a clear boundary or transition state that could be defined as “primitive biochemistry”? and ii) What is the influence of each environmental parameter on the degradation/transformation of this abiotic or biotic organic matter?The application of a transdisciplinary approach has made it possible not only to prepare space GC-MS instruments with analogues defined by characteristics common to the extraterrestrial planetary surfaces explored but also to identify precursors, bioindicators and bisignatures that we have under categorized as agnostic of any life or gnostic assimilated to known earthly life.The organic matter extraction protocols optimized in this thesis allowed the application of spatial protocols for a non-targeted environmental metabolomics approach and thus identify populations within the analogous environments investigated and molecules essential for adaptation to the environment and preservation against salts, irradiation and bioavailability of water and nutrients