International Islamic University, Chittagong

About: International Islamic University, Chittagong is a education organization based out in Chittagong, Bangladesh. It is known for research contribution in the topics: Debye model & Density functional theory. The organization has 1111 authors who have published 1089 publications receiving 7918 citations. The organization is also known as: IIUC.

Toxicodynamics of Lead, Cadmium, Mercury and Arsenic- induced kidney toxicity and treatment strategy: A mini review.

Abstract: Environmental pollution has become a concerning matter to human beings. Flint water crisis in the USA pointed out that pollution by heavy metal is getting worse day by day, predominantly by Lead, Cadmium, Mercury and Arsenic. Despite of not having any biological role in flora and fauna, they exhibit detrimental effect following exposure (acute or chronic). Even at low dose, they affect brain, kidney and heart. Oxidative stress has been termed as cause and effect in heavy metal-induced kidney toxicity. In treatment strategy, different chelating agent, vitamins and minerals are included, though chelating agents has been showed different fatal drawbacks. Interestingly, plants and plants derived compounds had shown possible effectiveness against heavy metals induced kidney toxicity. This review will provide detail information on toxicodynamics of Pb, Cd, Hg and As, treatment strategy along with the possible beneficiary role of plant derived compound to protect kidney.

Programming challenges of chatbot: Current and future prospective

Abstract: In the modern Era of technology, Chatbots is the next big thing in the era of conversational services Chatbots is a virtual person who can effectively talk to any human being using interactive textual skills Currently, there are many cloud base Chatbots services which are available for the development and improvement of the chatbot sector such as IBM Watson, Microsoft bot, AWS Lambda, Heroku and many others A virtual person is based on machine learning and Artificial Intelligence (AI) concepts and due to dynamic nature, there is a drawback in the design and development of these chatbots as they have built-in AI, NLP, programming and conversion services This paper gives an overview of cloud-based chatbots technologies along with programming of chatbots and challenges of programming in current and future Era of chatbot

A Comprehensive Review of the Load Forecasting Techniques Using Single and Hybrid Predictive Models

Abstract: Load forecasting is a pivotal part of the power utility companies. To provide load-shedding free and uninterrupted power to the consumer, decision-makers in the utility sector must forecast the future demand for electricity with a minimum error percentage. Load prediction with less percentage of error can save millions of dollars to the utility companies. There are numerous Machine Learning (ML) techniques to amicably forecast electricity demand, among which the hybrid models show the best result. Two or more than two predictive models are amalgamated to design a hybrid model, each of which provides improved performances by the merit of individual algorithms. This paper reviews the current state-of-the-art of electric load forecasting technologies and presents recent works pertaining to the combination of different ML algorithms into two or more methods for the construction of hybrid models. A comprehensive study of each single and multiple load forecasting model is performed with an in-depth analysis of their advantages, disadvantages, and functions. A comparison between their performance in terms of Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE) values are developed with pertinent literature of several models to aid the researchers with the selection of suitable models for load prediction.