Big Data is changing how organizations conduct operations. Data are assembled from multiple points of view through online quests, investigation of purchaser purchasing conduct, and then some, and industries utilize it to improve their net revenue and give an overall better experience to clients. Each of these organizations must figure out how to improve the general client experience and meet every client’s novel necessities, and big data helps with this cycle. Through the utilization and reviews of Big Data, travel industry organizations can study the inclinations of more modest portions of their intended interest group or even about people in some cases. In this paper, a Crow Search Optimization-based Hybrid Recommendation Model is proposed to get accurate suggestions based on clients’ preferences. The hybrid recommendation is performed by combining collaborative filtering and content-based filtering. As a result, the advantages of collaborative filtering and content-based filtering are utilized. Moreover, the intelligent behavior of Crows’ assists the proper selection of neighbors, rating prediction, and in-depth analysis of the contents. Accordingly, an optimized recommendation is always provided to the target users. Finally, performance of the proposed model is tested using the TripAdvisor dataset. The experimental results reveal that the model provides 58%, 58.5%, 27%, 24.5%, and 25.5% better Mean Absolute Error, Root Mean Square Error, Precision, Recall, and F-Measure, respectively, compared to similar algorithms.

The pollution due to minerals and anions in surface water and their settlement tendency on sediment of the Turag river has been studied. Higher concentration of potassium and phosphate ion in surface water and similar deposition on sediment has been recorded. The observed average concentration of Na, K, Cl-, PO4 3- in surface water and in surface sediment was 22.10, 13.20, 108.50, 17.80 mg/L and 1359.07, 2526.10, 37.50, 31.76 mg/kg, respectively. This high concentration of minerals and anions in surface water and sediments indicates that hidro-environment of the Turag river is badly affected.The minerals and ions are strongly correlated (r = 0.99) which implies that they come from similar sources and forcefully added to the river in a regular basis. Principal component analysis reveals that only one principal component is covering more than 99 % of cumulative variance. There are very few variations of parameters in the principal component to indicate that all parameters exert similar effect on hydro-environment and are contributing to deteriorate the ecological balance.These are supported by dendrogram analysis.Bangladesh J. Sci. Ind. Res.53(3), 161-168, 2018

In this era, feature clustering is a prominent technique in data mining. Feature clustering has also huge applications in biomedical research for multiple purposes including grouping, feature reduction, and many more. The Internet of Medical Things (IoMT) is a promising and emerging field of research that is having a major impact on knowledge retrieval and networking. IoMT also has significant application in biomedical research regarding remote monitoring and remote healthcare services. In this COVID-19 pandemic situation, psychological effects and human reactions have become a major concern of further research. A dataset can be reduced in size by using feature selection techniques. To facilitate subsequent processing, this will make the data easier to manage. Feature selection is also used to clean, reduce, and reduce dimensions of data. The clustering method has proven to be a powerful tool for finding patterns and structures in both labeled and unlabeled datasets. Our study basically provides various state-of-the-art methods regarding medical IoMT for remote healthcare, feature clustering for information retrieval regarding biomedical science. In this study, we have studied five different types of feature selection algorithms such as minimum redundancy maximum relevance (mRMR), random forest, normalized mutual information feature selection (NMIFS), F-test, and chi-square and five different types of clustering algorithms like hierarchical clustering, density-based spatial clustering of applications with noise (DBSCAN) clustering, K-means clustering, shrinkage clustering, and fuzzy C-means clustering. Finally, this study is very useful to understand and apply the appropriate IoMT, feature clustering, and catharsis on the various biomedical applications for the benevolence of society. Received: 31 March 2023 | Revised: 22 June 2023 | Accepted: 30 June 2023 Conflicts of Interest The authors declare that they have no conflicts of interest to this work. Data Availability Statement The data that support the findings of this study are openly available in UCSC Xena at https://xenabrowser.net/datapages. The data that support the findings of this study are openly available in National Cancer Institute at https://www.cancer.gov/ccg/access-data. The data that support the findings of this study are openly available in NCBI at https://www.ncbi.nlm.nih.gov/geo/. Author Contribution Statement Atikul Islam: Conceptualization, Methodology, Software, Validation, Formal analysis, Resources, Data curation, Writing - original draft, Writing - review & editing, Visualization, Supervision, Project administration. Soumita Seth: Methodology, Software, Validation, Formal analysis, Data curation, Writing - original draft, Writing - review & editing, Visualization, Supervision, Project administration. Tapas Bhadra: Methodology, Software, Validation, Formal analysis, Resources, Data curation, Writing - review & editing, Visualization, Supervision. Saurav Mallik: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing - original draft, Writing - review & editing, Visualization, Supervision, Project administration. Arup Roy: Software, Validation, Formal analysis, Investigation, Resources, Data curation. Aimin Li: Resources, Data curation. Manash Sarkar: Formal analysis, Investigation, Resources, Data curation.

Social network is an exciting online community for sharing the moments, opinion and comments. This tendency of having a unanimous person as a friend or as an acquaintance could be a serious threat to the security aspects of social network and the pri