Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date. A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM scheme for categorizing employees. In 1st stage, analytic hierarchy process (AHP) has been utilized for assigning relative weights for employee accomplishment factors. In second stage, TOPSIS has been used for expressing significance of employees for performing employee categorization. A simple 20-30-50 rule in DE PARETO principle has been applied to categorize employees into three major groups namely enthusiastic, behavioral and distressed employees. Random forest algorithm is then applied as baseline algorithm to the proposed employee churn framework to predict class-wise employee churn which is tested on standard dataset of the (HRIS), the obtained results are evaluated with other ML methods. The Random Forest ML algorithm in SNEC scheme has similar or slightly better overall accuracy and MCC with significant less time complexity compared with that of ECPR scheme using CATBOOST algorithm.
The ability of the human brain to communicate with its environment has become a reality through the use of a Brain-Computer Interface (BCI)-based mechanism. Electroencephalography (EEG) has gained popularity as a non-invasive way of brain connection. Traditionally, the devices were used in clinical settings to detect various brain diseases. However, as technology advances, companies such as Emotiv and NeuroSky are developing low-cost, easily portable EEG-based consumer-grade devices that can be used in various application domains such as gaming, education. This article discusses the parts in which the EEG has been applied and how it has proven beneficial for those with severe motor disorders, rehabilitation, and as a form of communi
... Show MoreThe hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s
... Show MoreMotifs template is the input for many bioinformatics systems such codons finding, transcription, transaction, sequential pattern miner, and bioinformatics databases analysis. The size of motifs arranged from one base up to several Mega bases, therefore, the typing errors increase according to the size of motifs. In addition, when the structures motifs are submitted to bioinformatics systems, the specifications of motifs components are required, i.e. the simple motifs, gaps, and the lower bound and upper bound of each gap. The motifs can be of DNA, RNA, or Protein. In this research, a motif parser and visualization module is designed depending on a proposed a context free grammar, CFG, and colors human recognition system. GFC describes the m
... Show MoreIn this paper, preliminary test Shrinkage estimator have been considered for estimating the shape parameter α of pareto distribution when the scale parameter equal to the smallest loss and when a prior estimate α0 of α is available as initial value from the past experiences or from quaintance cases. The proposed estimator is shown to have a smaller mean squared error in a region around α0 when comparison with usual and existing estimators.
Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D
... Show MoreThere are great figures in our nation, who are famous for their encyclopedia in their sciences, and their fame spreads across the horizons for what they presented to their religion and nation.
So they became torches of guidance, advocates of goodness, and treasuries of knowledge until God inherits the earth and those on it.
Among these imams is Imam al-Qurtubi, who died in the year (671 AH), after whom he left a great legacy of valuable books, including this one, which is the subject of my research, his valuable interpretation (Al-Jami’ Li Ahkam Al-Qur’an). Taking from him and his approach in interpreting the verses of judgment, following the method of extrapolation, investigation and deduction to know his style, which he used
The aim of the current research is to study a topic from the Qur’anic topics, few have researched it and realized its content, so people knew it in one name in the Qur’an in another name, and due to the ancientity of the topic and its contemporaneity, I wanted to write about it. The research has an introduction, three demands, and a conclusion with the most important results of the research:
As for the introduction: It was to indicate the importance of the topic and an optional reason for it.
As for the first requirement: it included the definition of reasoning, its divisions, and its characteristics.
As for the second requirement, it was to indicate the meaning, types, and methods of labeling it.
As for the third require