In recent years, reinforcement learning (RL) has achieved a remarkable achievement and it attracted researchers' attention in modeling real-life scenarios by expanding its research beyond conventional complex games. Prediction of optimal treatment regimens from observational real clinical data is being popularized, more advanced versions RL algorithms are implemented the literature. However, RL-generated medications still need careful supervision expertise parties or doctors healthcare....

In identifying objects, understanding the world, analyzing time series and predicting future sequences, recent developments in Artificial Intelligence (AI) have made human beings more inclined towards novel research goals. There is a growing interest Recurrent Neural Networks (RNN) by AI researchers today, which includes major applications fields of speech recognition, language modeling, video processing analysis. Recognition Human Behavior or Activity (HAR) one difficult issues this...

SplitFed Learning, a combination of Federated and Split Learning (FL SL), is one the most recent developments in decentralized machine learning domain. In learning, model trained by clients server collaboratively. For image segmentation, labels are created at each client independently and, therefore, subject to clients' bias, inaccuracies, inconsistencies. this paper, we propose data quality-based adaptive averaging strategy for called QA-SplitFed, cope with variation annotated ground truth...

Text summarization helps in reducing the size of a text while preserving its information content. Summarization can be derived as shortening source to version that it's content and overall meaning is preserved. It very difficult for human beings manually summarize large documents text. These methods classified into two broader such extractive abstractive summarization. The prior method consists selecting important sentences; paragraphs etc. from document make brief it by combining them....

Text summarization is the task of condensing a text segment into shorter version, reducing size original context while also preserving informational elements and meaning content. Manual will involve significant amount time thus become expensive generally laborious task. Aiming to reduce these pitfalls in manual summarization, automatic has been evolving now bearing strong motivation for academic research. Summarization carried out by two main approaches, namely Extraction Abstraction. This...

Tourism in Sri Lanka is an evolving field which significantly influencing on the development of country. With rapid advancement Affective computing and its' diverse paths where applications are being implemented by facilitating user needs emotions, tourism has become one prominent fields to provide a comprehensive analysis useful inclination specific travel spots based interests emotions. Traditional methodologies guide guides tourists' journey nowadays old fashion tourist himself innovative...

Recent advancements in decentralized learning, such as Federated Learning (FL), Split (SL), and (SplitFed), have expanded the potentials of machine learning. SplitFed aims to minimize computational burden on individual clients FL parallelize SL while maintaining privacy. This study investigates resilience packet loss at model split points. It explores various parameter aggregation strategies by examining impact splitting different points-either shallow or deep split-on final global...

Federated Learning (FL) enables multiple clients to train a collaborative model without sharing their local data. Split (SL) allows be trained in split manner across different locations. Split-Federated (SplitFed) learning is more recent approach that combines the strengths of FL and SL. SplitFed minimizes computational burden by balancing computation servers, while still preserving data privacy. This makes it an ideal framework various domains, especially healthcare, where privacy utmost...

Blessing with fresh air to breathe is one of the primary living requirements Human being. Nowadays, majority countries in world are suffering from problem Air pollution. This getting worse day by because rapid economic growth, industrialization, urbanization and resulting rise energy demand. pollution has been become concern Sri Lanka. In most Lankan cities, cause for lack prevalence proper environmental regulations. Although scientific evaluation such technologies systems generally...

SplitFed Learning, a combination of Federated and Split Learning (FL SL), is one the most recent developments in decentralized machine learning domain. In learning, model trained by clients server collaboratively. For image segmentation, labels are created at each client independently and, therefore, subject to clients' bias, inaccuracies, inconsistencies. this paper, we propose data quality-based adaptive averaging strategy for called QA-SplitFed, cope with variation annotated ground truth...

Decentralized machine learning has broadened its scope recently with the invention of Federated Learning (FL), Split (SL), and their hybrids like (SplitFed or SFL). The goal SFL is to reduce computational power required by each client in FL parallelize SL while maintaining privacy. This paper investigates robustness against packet loss on communication links. performance various aggregation strategies examined splitting model at two points -- shallow split deep testing whether point makes a...