Early identification of skin cancer is mandatory to minimize the worldwide death rate as this disease is covering more than 30% of mortality rates in young and adults. Researchers are in the move of proposing advanced...
详细信息
As Virtual Reality (VR) is on the rise in popularity in learning contexts, the corresponding ethical challenges of its use increase in complexity and importance. This theoretical paper discusses the ethical consequenc...
详细信息
This paper introduces a novel multimedia learning environment designed to support holistic learning of web development. ANNs and the WSM model have been adopted to implement the framework of the VARK learning style mo...
详细信息
Due to the exponential increase in data volume, the widespread use of intelligent information systems has created significant obstacles and issues. High dimensionality and the existence of noisy and extraneous data ar...
详细信息
Due to the exponential increase in data volume, the widespread use of intelligent information systems has created significant obstacles and issues. High dimensionality and the existence of noisy and extraneous data are a few of the difficulties. These difficulties incur high computing costs and have a considerable effect on the accuracy and efficiency of machine learning (ML) methods. A key idea used to increase classification accuracy and lower computational costs is feature selection (FS). Finding the ideal collection of features that can accurately determine class labels by removing unnecessary data is the fundamental goal of FS. However, finding an effective FS strategy is a difficult task that has given rise to a number of algorithms built using biological systems based soft computing approaches. In order to solve the difficulties faced during the FS process;this work provides a novel hybrid optimization approach that combines statistical and soft-computing intelligence. On the first dataset of diabetes disease, the suggested approach was initially tested. The approach was later tested on the Wisconsin Diagnostic Breast Cancer (WDBC) dataset after yielding encouraging results on diabetes dataset. While finding the solution, typically, data cleaning happens at the pre-processing stage. Later on, in a series of trials, different FS methods were used separately and in hybridized fashion, such as fine-tuned statistical methods like lasso (L1 regularization) and chi-square, as well as binary Harmony search algorithm (HSA) which is based on soft computing algorithmic approach. The most efficient strategy was chosen based on the performance metric data. These FS methods pick informative features, which are then used as input for a variety of traditional ML classifiers. The chosen technique is shown along with the determined influential features and associated metric values. The success of the classifiers is then evaluated using performance metrics like accuracy, preci
Network updates have become increasingly prevalent since the broad adoption of software-defined networks(SDNs)in data *** TCP designs,including cutting-edge TCP variants DCTCP,CUBIC,and BBR,however,are not resilient t...
详细信息
Network updates have become increasingly prevalent since the broad adoption of software-defined networks(SDNs)in data *** TCP designs,including cutting-edge TCP variants DCTCP,CUBIC,and BBR,however,are not resilient to network updates that provoke flow *** this paper,we first demonstrate that popular TCP implementations perform inadequately in the presence of frequent and inconsistent network updates,because inconsistent and frequent network updates result in out-of-order packets and packet drops induced via transitory congestion and lead to serious performance *** look into the causes and propose a network update-friendly TCP(NUFTCP),which is an extension of the DCTCP variant,as a *** are used to assess the proposed *** findings reveal that NUFTCP can more effectively manage the problems of out-of-order packets and packet drops triggered in network updates,and it outperforms DCTCP considerably.
Digital revolution has transformed education, allowing students to interact, communicate, and collaborate beyond traditional classroom settings. computer-Supported Collaborative Learning (CSCL) provides opportunities ...
详细信息
Plant diseases significantly threaten global food security and economic stability by reducing crop yields, increasing production costs, and exacerbating food shortages. Early and precise detection of plant diseases is...
详细信息
With increasing embedding of artificial intelligence (AI) in web information systems (WIS), the maximum assurance on the reliability of such AI systems is solicited. Although this aspect is gaining importance, no comp...
详细信息
The pervasive impact of digital technologies has permeated all facets of our society. As technology continues to evolve rapidly, it is imperative for educators to adapt and integrate these advancements into their teac...
详细信息
Process mining allows the extraction of useful information from the event logs and historical data of business processes. Predictive business process monitoring is a sub-field of process mining and deals with runtime ...
详细信息
暂无评论