Frequency: Quarterly E- ISSN: 2278-6295 P- ISSN: Abstracted/ Indexed in: Ulrich's International Periodical Directory, Google Scholar, SCIRUS, Genamics JournalSeek, EBSCO Information Services
Quarterly published in print and online "Inventi Rapid: Artificial Intelligence" publishes high quality unpublished as well as high impact pre-published research and reviews catering to the needs of researchers and professionals. It focuses on multidimensional aspects of artificial intelligence, particularly - artificial intelligence and philosophy, automated reasoning and inference, cognitive aspects of AI, commonsense reasoning, intelligent robotics, etc.
Recent approaches in web log data representation aim to capture the user navigational patterns with respect to the overall structure of the web site. One such representation is tree-structured log files which is the focus of this work. Most existing methods for analyzing such data are based on the use of frequent sub tree mining techniques to extract frequent user activity and navigational paths. In this paper we evaluate the use of other standard data mining techniques enabled by a recently proposed structure preserving flat data representation for tree-structured data. The initially proposed framework was adjusted to better suit the web log mining task. Experimental evaluation is performed on two real world web log datasets and comparisons are made with an existing state-of-the art classifier for tree-structured data. The results obtain the great potential of the method in enabling the application of a wider range of data mining/analysis techniques to tree-structured web log data....
Artificial intelligence (AI) is rapidly emerging as a transformative technology in the pharmaceutical and biomedical fields. This narrative review article focuses on the emerging role of artificial intelligence (AI) in the paradigm shift of pharmaceutical and biomedical sciences. The current article discusses the potential of AI to revolutionise the pharmaceutical industry by increasing the efficiency and effectiveness of drug development and discovery, lowering drug development costs and providing personalised medicine. Furthermore, the article emphasises the potential of AI in disease prevention and outbreak prediction by analysing large data sets and identifying patterns and trends that can aid in the development of targeted interventions. Furthermore, the article discusses the importance of AI in biomedical research, particularly in genomics, proteomics and metabolomics. Finally, the article discusses the potential of AI in transforming the patient-physician interface by improving diagnosis and treatment accuracy and efficiency. Overall, this review article provides an overview of the current state of the art in artificial intelligence (AI) in pharmaceutical and biomedical sciences, highlighting the potential for future development and impact on patient care....
For better cost effective risk management plans, the accuracy of the electricity load forecast in the is crucial in providing, this paper proposes a Short Term Electricity Load Forecast (STLF) model with a high forecasting accuracy. A cascaded forward BPN neuro-wavelet forecast model is adopted to perform the STLF. The model is composed of several neural networks whose data are processed using a wavelet technique. The data to be used in the model is electricity load historical data. The historical electricity load data is decomposed into several wavelet coefficient using the Discrete wavelet transform (DWT). The wavelet coefficients are used to train the neural networks (NNs) and later, used as the inputs to the NNs for electricity load prediction. The Levenberg-Marquardt (LM) algorithm is selected as the training algorithm for the NNs. To obtain the final forecast, the outputs from the NNs are recombined using the same wavelet technique....
Globally, heart diseases are the number one cause of death. About 80% of deaths occurred in low- and middle-income countries. WHO estimated by 2030, almost 23.6 million people will die due to heart disease. The healthcare industry generally clinical diagnosis is done mostly by the doctorâ??s expertise and experience. Computer-aided decision support system plays a major role in the medical field. The healthcare industry gathers enormous amounts of heart disease data which, unfortunately, are not â??minedâ? to discover hidden information for effective decision making. With the growing research on heart disease predicting system, it has become important to categories the research outcomes and provides readers with an overview of the existing heart disease prediction techniques in each category. Data mining provides the methodology and technology to transform these mounds of data into useful information for decision making. By using data mining techniques it takes less time for the prediction of the disease with more accuracy. Neural Networks are one of many data mining analytical tools that can be utilized to make predictions for medical data....
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