Papers by Rahimullah Ramish
International journal of english, literature and social science, 2024
The main and basic purpose of this research is to investigate and analyze the function of literat... more The main and basic purpose of this research is to investigate and analyze the function of literature in contemporary times, when the mirror of truth is broken into a thousand pieces and human society is more involved than ever. They create new difficulties and fight over them, and in the meantime, people are the victims. Therefore, with its systematic activities, literature overcomes these fences drawn in front of human society with artistic language. The fact that today's human society is falling into misery with each passing day, without a doubt, one of the reasons is that human society is far from literature. This is because in most societies, especially in the third world societies, reductionist positions have been adopted towards literature, and these positions are another step towards damage and nigritude. The method used in this research is descriptive-analytical and based on library studies. In this research, while philosophically examining the place of literature in modern times, we will also briefly mention some writers who have turned the unsaid of today's people into words through poetry and literature. The findings showed that, in the epoch of the collapse of meaning and fencing between people in human society, literature is the only one that gives us the possibility of considering ourselves as members of each other everywhere in this world. It is through literature that today's people understand and recognize one another, despite their differences based on faith, religion, geography, gender, etc. Therefore, literature in our time is the real defender of the common phenomena among humans.
International Journal of Language and Literary Studies
This mixed-methods case study explores how Rahim Shah learned to speak English and Persian much m... more This mixed-methods case study explores how Rahim Shah learned to speak English and Persian much more fluently than his native language (Pashto). In this study, different aspects of the subject- including his personality, language learning style, language learning history, oral and written language skills- are analyzed to seek patterns and causes of behavior. Accordingly, attempts have been made in this paper to enlighten his exposure to three languages, Pashto (native), Persian (second) and English (foreign). The results drew that he speaks Persian much more confident than his native language mainly because his parents moved to a Persian-speaking community when he was a child of three years old. This makes it clear that non-native speakers use their knowledge of the new language through interaction with others. The results also recovered that he learned how to speak English better than his native language mainly because he was intrinsically motivated, knowing the positive consequenc...
Crop models are tools used for predicting year to year crop development on field to regional scal... more Crop models are tools used for predicting year to year crop development on field to regional scales. However, robust predictions are hampered by factors such as uncertainty in crop model parameters and in the data used for calibration. Bayesian calibration allows for the estimation of model parameters and quantification of uncertainties, with the consideration of prior information. In this study, we used a Bayesian sequential updating (BSU) approach to progressively incorporate additional data at a yearly time-step to calibrate a phenology model (SPASS) while analysing changes in parameter uncertainty and prediction quality. We used field measurements of silage maize grown between 2010 and 2016 in the regions of Kraichgau and Swabian Alb in southwestern Germany. Parameter uncertainty and model prediction errors were expected to progressively reduce to a final, irreducible value. Parameter uncertainty reduced as expected with the sequential updates. For two sequences using synthetic data, one in which the model was able to accurately simulate the observations, and the other in which a single cultivar was grown under the same environmental conditions, prediction error mostly reduced. However, in the true sequences that followed the actual chronological order of cultivation by the farmers in the two regions, prediction error increased when the calibration data was not representative of the validation data. This could be explained by differences in ripening group and temperature conditions during vegetative growth. With implications for manual and automatic data streams and model updating, our study highlights that the success of Bayesian methods for predictions depends on a comprehensive understanding of inherent structure in the observation data and model limitations.
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Papers by Rahimullah Ramish