Soft Computing, Artificial Intelligence and Applications

Gradient Omissive Descentis A Minimization Algorithm Gustavo A. Lado and Enrique C. Segura Universidad de Buenos Aires Cyprus ABSTRACT This article presents a promising new gradient-based backpropagation algorithm for multi-layer feedforward networks. The method requires no manual selection of global hyperparameters and is capable of dynamic local adaptations using only first-order information at a low computational cost. Its semi-stochastic nature makes it fit for mini-batch training and robust to different architecture choices and data distributions. Experimental evidence shows that the proposed algorithm improves training in terms of both convergence rate and speed as compared with other well known techniques. KEYWORDS Neural Networks, Backpropagation, Cost Function Minimization Original Source URL: http://aircconline.com/ijscai/V8N1/8119ijscai03.pdf http://airccse.org/journal/ijscai/current2019.html

Innovative Bi Approaches and Methodologies Implementing A Multilevel Analytics Platform Based on Data Mining and Analytical Models: A Case of Study in Roadside Assistance Services Alessandro Massaro, Angelo Leogrande, Palo Lisco, Angelo Galiano and Nicola Savino Dyrecta Lab, IT Research Laboratory, Italy. ABSTRACT The paper proposes an advanced Multilevel Analytics Model –MAM-, applied on a specific case of study referring to a research project involving an industry mainly working in roadside assistance service (ACI Global S.p.A.). In the first part of the paper are described the initial specifications of the research project by addressing the study on information system architectures explaining knowledge gain, decision making and data flow automatism applied on the specific case of study. In the second part of the paper is described in details the MAM acting on different analytics levels, by describing the first analyzer module and the second one involving data mining ...

Deep Learning Sentiment Analysis of Amazon.Com Reviews and Ratings Nishit Shrestha and Fatma Nasoz University of Nevada Las Vegas, USA ABSTRACT Our study employs sentiment analysis to evaluate the compatibility of Amazon.com reviews with their corresponding ratings. Sentiment analysis is the task of identifying and classifying the sentiment expressed in a piece of text as being positive or negative. On e-commerce websites such as Amazon.com, consumers can submit their reviews along with a specific polarity rating. In some instances, there is a mismatch between the review and the rating. To identify the reviews with mismatched ratings we performed sentiment analysis using deep learning on Amazon.com product review data. Product reviews were converted to vectors using paragraph vector, which then was used to train a recurrent neural network with gated recurrent unit. Our model incorporated both semantic relationship of review text and product information. We also developed a w...

Bacteria Identification From Microscopic Morphology: A Survey Noor Amaleena Mohamad, Noorain Awang Jusoh, Zaw Zaw Htike and Shoon Lei Win International Islamic University Malaysia, Malaysia ABSTRACT Great knowledge and experience on microbiology are required for accurate bacteria identification. Automation of bacteria identification is required because there might be a shortage of skilled microbiologists and clinicians at a time of great need. There have been several attempts to perform automatic background identification. This paper reviews state-of-the-art automatic bacteria identification techniques. This paper also provides discussion on limitations of state-of-the-art automatic bacteria identification systems and recommends future direction of automatic bacteria identification. KEYWORDS Bacteria Identification, Cocci,Bacilli, Vibrio, Naïve Bayes, Machine Learning Original Source URL: http://airccse.org/journal/ijscai/papers/3214ijscai01.pdf http://airccse.org/journal...

Cancer Prognosis Prediction Using Balanced Stratified Sampling J.S.Saleema1, N.Bhagawathi2, S.Monica2, P.Deepa Shenoy2, K.R.Venugopal2 and L.M.Patnaik3 1Christ University, India 2University Visvesvaraya College of Engineering, India 3Indian Institute of Science, India ABSTRACT High accuracy in cancer prediction is important to improve the quality of the treatment and to improve the rate of survivability of patients. As the data volume is increasing rapidly in the healthcare research, the analytical challenge exists in double. The use of effective sampling technique in classification algorithms always yields good prediction accuracy. The SEER public use cancer database provides various prominent class labels for prognosis prediction. The main objective of this paper is to find the effect of sampling techniques in classifying the prognosis variable and propose an ideal sampling method based on the outcome of the experimentation. In the first phase of this work the traditio...

Artificial Intelligence Handling Through Teaching and Learning Process and It�s Effect on Science-Based Economy Mohammad Ziaaddini and Aref Tahmasb shahidBahonar University, Iran ABSTRACT According to this fact that educational system is the base of constant development in every country and this system educates human-forces and this forces,are accelerators and a factor, of achieving the goals of development,the educational system can play, Major role in the context economic behavior, in this context some concepts are regarded as behavioral targets and performance.In educational system, handling artificial intelligence, in teaching and learning process, had a surprising evolution through educational advantages, making job, respecting customers rights and customer relationship management, to assist priority and citizenship, correct investment through formal markets. Science-Based economy, resistible economy and a positive view to job and Iran capital,including concepts which...

Design and Implementation of Smart Cooking Based on Amazon Echo Lin Xiaoguang1,2,3, Yang Yong3 and Zhang Ju1,3 1University of Chinese Academy of Sciences, China 2Chinese Academy of Sciences - Chengdu, China 3Chinese Academy of Sciences - Chongqing, China ABSTRACT Smart cooking based on Amazon Echo uses the internet of things and cloud computing to assist in cooking food. People may speak to Amazon Echo during the cooking in order to get the information and situation of the cooking. Amazon Echo recognizes what people say, then transfers the information to the cloud services, and speaks to people the results that cloud services make by querying the embedded cooking knowledge and achieving the information of intelligent kitchen devices online. An intelligent food thermometer and its mobile application are well-designed and implemented to monitor the temperature of cooking food. KEYWORDS Smart Cooking, Things of Internet, Cloud Services, Smart Home. Original Source URL: ht...

Forecasting Macroeconomical Indices with Machine Learning : Impartial Analysis of the Relation Between Economic Freedom and Quality of Life Jonathan Staufer and Patricia Brockmann Technische Hochschule Nurnberg, Germany ABSTRACT The importance of economic freedom has often been stressed by supporters of liberalism, but can its actu-al effect be observed in a data driven, objective way? To analyze this relation the Economic Freedom of the World (EFW) index and the Human Development Index (HDI) were examined with modern machine learning algorithms and a wide-ranging approach. Considering the EFW index’s preference of a liberal-istic oriented economic policy, an objective recommendation for creating an economic policy that im-proves people’s everyday lives might be derived by the analysis results. It was found that these more ad-vanced algorithms achieve a considerably stronger correlation between both indices than pure statistical means yet leave a small room for interpretati...

Intelligent Electrical Multi Outlets Controlled and Activated by a Data Mining Engine Oriented to Building Electrical Management Alessandro Massaro, Valeria Vitti, Angelo Galiano Dyrecta Lab, Italy ABSTRACT In the proposed paper are discussed results of an industry project concerning energy management in building. Specifically the work analyses the improvement of electrical outlets controlled and activated by a logic unit and a data mining engine. The engine executes a Long Short-Terms Memory (LSTM) neural network algorithm able to control, to activate and to disable electrical loads connected to multiple outlets placed into a building and having defined priorities. The priority rules are grouped into two level: the first level is related to the outlet, the second one concerns the loads connected to a single outlet. This algorithm, together with the prediction processing of the logic unit connected to all the outlets, is suitable for alerting management for cases of thresh...

5th International Conference on Artificial Intelligence and Applications (AIFU 2019) July 13~14, 2019, Toronto, Canada https://ccsea2019.org/aifu/index.html

7 th International Conference on Soft Computing, Artificial Intelligence and Applications (SCAI 2018) December 22~ 23, 2018, Sydney, Australia http://iccsea2018.org/scai/index.html Scope & Topics 7 th  International Conference on Soft Computing, Artificial Intelligence and Applications ( SCAI 2018)  Will Provide An Excellent International Forum For Sharing Knowledge And Results In Theory, Methodology And Applications Of Artificial Intelligence, Soft Computing. The Conference Looks For Significant Contributions To All Major Fields Of The Artificial Intelligence, Soft Computing In Theoretical And Practical Aspects. The Aim Of The Conference Is To Provide A Platform To The Researchers And Practitioners From Both Academia As Well As Industry To Meet And Share Cutting-Edge Development In The Field. Authors Are Solicited To Contribute To The Conference By Submitting Articles That Illustrate Research Results, Projects, Surveying Works And Industr...

6th International Conference on Artificial Intelligence and Applications (AIAP-2019) May 25~26, 2019, Vancouver, Canada https://ccseit2019.org/aiap/index.html Contact Us Here's where you can reach us : aiap_conf@yahoo.com or aiap@ccseit2019.org Paper Submission : https://ccseit2019.org/submission/index.php

MODEL OF MULTIPLE ARTIFICIAL NEURAL NETWORKS ORIENTED ON SALES PREDICTION AND PRODUCT SHELF DESIGN Alessandro Massaro, Valeria Vitti, Angelo Galiano Dyrecta Lab, Italy ABSTRACT In this paper the authors proposed different Multilayer Perceptron Models (MLP) of artificial neural networks (ANN) suitable for visual merchandising in Global Distribution (GDO) applications involving supermarket product facing. The models are related to the prediction of different attributes concerning mainly shelf product allocation applying times series forecasting approach. The study highlights the range validity of the sales prediction by analysing different products allocated on a testing shelf. The paper shows the correct procedures able to analyse most guaranteed results, by describing how test and train datasets can be processed. The prediction results are useful in order to design monthly a planogram by taking into account the shelf allocations, the general sales trend, and the promotion ...

6 th  International Conference on Artificial Intelligence and Applications (AIAP-2019)  May 25~26, 2019, Vancouver, Canada https://ccseit2019.org/aiap/index.html Scope 6 th  International Conference on Artificial Intelligence and Applications (AIAP-2019)  will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence and its applications. The Conference looks for significant contributions to all major fields of the Artificial Intelligence, Soft Computing in theoretical and practical aspects. The aim of the Conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field. Authors are solicited to contribute to the Conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances...