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dataCan: Robust Approach for Genome Cancer data Analysis 3rd

DataCan: Robust Approach for Genome Cancer Data Analysis

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international conference on data Management, analytics and Innovation (ICDMAI)

作者： Goel, Varun Jangir, Vishal Shankar, Venkatesh Gauri Manipal Univ Jaipur Dept Informat Technol Jaipur Rajasthan India

ISBN: (纸本)9789811393648;9789811393631

While we glance in the past twenty years, it can be evidently noticed that biological sciences have brought about an active analytical research in high-dimensional data. Recently, many new approaches in data Science and Machine Learning fields have emerged to handle the ultrahigh-dimensional genome data. Several cancer data types together with the availability of pertinent studies going on similar types of cancers adds to the complexity of the data. It is of commentative biological and clinical interest to understand what subtypes a cancer has, how a patient's genomic profiles and survival rates vary among subtypes, whether a survival of a patient can be predicted from his or her genomic profile, and the correlation between different genomic profiles. It is of utmost importance to identify types of cancer mutations as they play a very significant role in divulging useful observations into disease pathogenesis and advancing therapy varying from person to person. In this paper we focus on finding the cancer-causing genes and their specific mutations and classifying the genes on the 9 classes of cancer. This will help in predicting which genetic mutation causes which type of cancer. We have used Sci-kit Learn and NLTK for this project to analyze what each class means by classifying all genetic mutations into 17 major mutation types (according to dataset). dataset is in two formats: CSV and Text, where csv containing the genes and their mutations and text file containing the description of these mutations. Our approach merged the two datasets and used Random Forest, with GridSearchCv and ten-fold Cross-Validation, to perform a supervised classification analysis and has provided with an accuracy score of 68.36%. This is not much accurate as the genes & their variations don't follow the HGVS Nomenclature of genes because of which conversion of text to numerical format resulted in loss of some important features. Our findings suggest that classes 1, 4 and 7 contribute the

关键词： Cancer Genes Random-Forest SVM Variations data analytics

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Western culture MOOC teaching in the age of big data

Western culture MOOC teaching in the age of big data

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1st international conference on Big data analytics for Cyber-Physical System in smart City, BDCPS 2019

作者： Yao, Wei Huang, Yanping School of Foreign Language Wuhan University of Technology Wuhan China International College of Chinese Studies Fujian Normal University Fuzhou China

ISBN: (纸本)9789811525674

In this era of information technology, big data has had a huge impact on education. As a new online product of big data, MOOC offers a good platform for students to learn efficiently, effectively and individually. Western Culture course is a selective English course for college students in many universities of China. For a long time, Western Culture courses in China’s universities have been taught by the traditional teaching mode: teachers are the instructors in teaching activities;students are the recipients of knowledge. In terms of teaching materials, textbooks in the traditional Western Culture courses emphasize western cultural history, containing many cultural concepts, which are difficult for students to learn and memorize. It is not conducive to stimulate students to learn. Students are easily fed up with the teaching and learning. This study researches the application of MOOC in the Western Culture course in a key university of China. It analyzes the advantages of applying MOOC in the Western Culture course, and proposes the corresponding curriculum design. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Big data

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A Neuro-Fuzzy Based Approach for Energy Consumption and Profit Operation Forecasting 5th

A Neuro-Fuzzy Based Approach for Energy Consumption and Prof...

引用

5th international conference on Advanced intelligent Systems and Informatics (AISI)

作者： Shalaby, Mohamed A. Wahby Ortiz, Nicolas Ramirez Ammar, Hossam Hassan Cairo Univ Fac Comp & Artificial Intelligence Giza Egypt Nile Univ Smart Engn Syst Res Ctr SESC Giza Egypt Nile Univ Sch Engn & Appl Sci Giza Egypt

ISBN: (纸本)9783030311292;9783030311285

In recent years, the massive growth in the scale of data is being a key factor in the needed data processing approaches. The efficiency of the algorithms of knowledge extraction depends significantly on the quality of the raw data, which can be improved by employing preprocessing techniques. In the field of energy consumption, the forecasting of power cost needed plays a vital role in determining the expected profit. To achieve a forecasting with higher accuracy, it is needed to deal with the large amount of data associated with power plants. It is shown in the literature that the use of artificial neural networks for the forecast electric power consumption and show short term profit operation is capable of achieving forecasting decisions with higher accuracy. In this research work, a neuro-fuzzy based approach for energy consumption and profit operation forecasting is proposed. First, the main influential variables in the consumption of electrical energy are determined. Then, the raw data is pre-processed using the proposed fuzzy-based technique. Finally, an artificial neural network is employed for the forecasting phase. A comparative study is conducted to compare between the proposed approach and the traditional neural networks. It is shown that the achieved forecasting accuracy of the proposed technique is better than what achieved by employing only the neural network.

关键词： Energy consumption Neural networks Fuzzy sets Adaptive neuro-fuzzy

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Holistic Productivity Management Using Digitalization

Holistic Productivity Management Using Digitalization

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10th international conference on Applied Human Factors and Ergonomics (AHFE) / international conference on Human Factors and Systems Interaction

作者： Jeske, Tim Weber, Marc-Andre Lennings, Frank Stowasser, Sascha Ifaa Inst Appl Ind Engn & Ergon Uerdinger Str 56 D-40474 Dusseldorf Germany Kiel Univ Appl Sci Inst Supply Chain & Operat Management Dept Management Studies Sokratespl 2 D-24149 Kiel Germany

ISBN: (纸本)9783030200404;9783030200398

Holistic approaches for designing and developing enterprises and production systems are well-proven for years. They are still crucial when digitalization is introduced. Digitalization brings new opportunities regarding the collection, transfer, processing, providing and usage of data. An integrated application of these new opportunities for handling data can support holistic approaches and leads to what is defined as Industry 4.0, Industrial Internet of Things or smart/Advanced Manufacturing. This contribution emphasizes on describing three basic elements of holistic approaches for managing productivity in production companies: Deriving goals for all management levels, designing work for reaching defined goals and continuous improvement for considering further potentials. The opportunities of digitalization for supporting each of these elements are elaborated in detail. Finally, a holistic implementation of digitalization by the help of a stepwise approach is described which can be supported by a detailed checklist.

关键词： Holistic management Productivity Digitalization Industry 4.0 Industrial Internet of Things smart manufacturing

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Missing data Imputation Techniques for Software Effort Estimation: A Study of Recent Issues and Challenges 4th

Missing Data Imputation Techniques for Software Effort Estim...

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4th international conference of Reliable Information and Communication Technology (IRICT)

作者： Almutlaq, Ayman Jalal Hassan Jawawi, Dayang N. A. Univ Teknol Malaysia UTM Fac Engn Sch Comp Skudai Johor Malaysia

ISBN: (纸本)9783030335823;9783030335816

Software effort estimation is one the critical aspects of software engineering. It revolves around predicting the required efforts needed to complete a software task. However, any estimation technique or model relies on an input data in which it defines and predicts future values. Missing data and values within such data is a common occurrence in the software development industry and thus it leads to inaccurate predictions or misleading results. Thus, Missing data is an important aspect of effort estimation models that is required to be addressed. However, Missing data is not without its gaps and issues. This review aims at elaborating the recent issues and gaps that exist within the missing data and software effort estimation field. This may allow future researchers to get a better grasp and understanding of the inner workings of Missing data and the methods through which these challenges can be addressed.

关键词： Missing data Software Effort Estimation Imputation methods Literature review

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smart energy management for fog-enabled iot network 20

Smart energy management for fog-enabled iot network

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13th international conference on intelligent Systems: Theories and Applications, SITA 2020

作者： Essalhi, Salah Eddine El Fenni, Mohammed Raiss Chafnaji, Houda Rabat Morocco

ISBN: (纸本)9781450377331

The Internet of Things (IoT) is a paradigm that continues to stir the curiosity of the scientific community which has been the subject of several research studies in recent years. Formed by a very large number of connected devices IoT applications generate a huge amount of data to be processed and analyzed taking into account the constraints of latency and energy. Fog computing has proven to be an efficient way to provide computing management and storage resources through small distributed data centers located at the edge of the network as close as possible to end-users and connected devices offering accordingly reduced latency and energy saving. In this context energy efficiency is one of the parameters that must be emphasized in order to cope with the increased consumption of energy associated with this gigantic volume of data. The proposed work presents a new approach based on a Fog-IoT architecture with the objective of ensuring smart energy management during communication and processing of offloaded tasks in IoT applications while respecting the latency constraint. Experimental results attests the effectiveness of the proposed approach in terms of energy efficiency. © 2020 ACM.

关键词： Energy efficiency

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Enterprise Internal Audit data Network Security System in the Information Age

Enterprise Internal Audit Data Network Security System in th...

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international conference on Cyber Security Intelligence and analytics, CSIA 2020

作者： Lin, Renzao Huang, Yeping Fuzhou University of International Studies and Trade Fuzhou350202 China Fujian Agriculture and Forestry University Fuzhou350002 China

ISBN: (纸本)9783030433055

With the development of the times, the big data has been widely applied in the management of modern enterprises, and the Internet, cloud computing, block chain, artificial intelligence, and material networking, thus bringing great challenges to the enterprise management [1]. Network security has become one of the most important risk management faced by enterprises. Internal audit cannot fully meet the requirements of the big data era. There are problems in the network security system of big data of enterprise internal audit. Enterprises need to make long-term planning, improve internal management and monitoring system, construct internal audit information platform, improve quality of personnel information. It is an urgent task for internal audit to adapt to data network security in the information age and how to identify and adjust its own role to deal with the current network risks. © Springer Nature Switzerland AG 2020.

关键词： Network security

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Characteristics of international trade benefits based on the cluster analysis of compatibility relation

Characteristics of international trade benefits based on the...

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1st international conference on Big data analytics for Cyber-Physical System in smart City, BDCPS 2019

作者： Dai, Ting Jiangxi College of Foreign Studies Nanchang China

ISBN: (纸本)9789811525674

The sustainable development of international trade is related to the success or failure of reform and opening up. This paper constructs a set of evaluation system of sustainable development of international trade based on c-means clustering algorithm. Clustering analysis is an important research content in data mining, the traditional clustering algorithm can be divided into two kinds of hard clustering and fuzzy clustering, puts forward a method based on object set on the compatible relationship of clustering algorithm, this algorithm through great compatible clusters to classifying the data object sets, making the same object can belong to different clusters, and each cluster has its own unique member object, and is different from both hard clustering is different from fuzzy clustering effect of clustering. First through a summary of existing research results, and gives out the evaluation index system of sustainable development of international trade, then the argument is based on c-means clustering analysis of the scientific nature and necessity of the evaluation of the sustainable development of foreign trade, and gives the corresponding evaluation method, through the evaluation of the sustainable development of foreign trade in the 15 region in empirical analysis, the feasibility and practicability of this method was verified. Finally, according to the characteristics of the sustainable development of foreign trade, the paper puts forward some countermeasures and Suggestions to strengthen the sustainable development of foreign trade. © Springer Nature Singapore Pte Ltd. 2020.

关键词： data mining

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smart Protective Protection Equipment for an accessible work environment and occupational hazard prevention 10

Smart Protective Protection Equipment for an accessible work...

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10th international conference on Cloud computing, data Science and Engineering (Confluence)

作者： Marquez Sanchez, Sergio Corchado Rodriguez, Juan Manuel Grp Invest Bioinformat Sistemas Informat Intelige Edificio Multiusos I D I Calle Espejo S-N Salamanca 37007 Spain

ISBN: (纸本)9781728127910

Wearable technologies have begun to play an important role in the workplace. This paper presents a smart PPE (Personal Protective Equipment) solution which employs a sensor network located on a helmet and a belt to monitor the state of the worker and the environment. Most of the accidents that occur in the workplace are caused by the lack of prevention measures, poor safety training and obsolete safety systems which do no adapt technologically to the needs of today's work environments. The solutions provided by Industry 4.0 for hazard prevention and propose a wireless PPE model that incorporates intelligent tools and fabrics capable of reacting in real time to a risk situation. This novel model implements continuous risk monitoring biometrics of the worker, detects the external impact, shock, luminosity, gases, temperature of the environment and provides real-time recommendations to workers. The motivation behind this work is to improve health and safety in work sectors with high accident risk.

关键词： e-Health Context Modelling Condition monitoring

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A Personal Assistant Supporting Agriculture Operators 10

A Personal Assistant Supporting Agriculture Operators

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10th IEEE international conference on intelligent Systems, IS 2020

作者： Stoyanov, Ivan Stoyanova-Doycheva, Asya Krasteva, Irina Uhr, Zlatina Plovdiv University "paisii Hilendarski" Faculty of Mathematics and Informatics Plovdiv Bulgaria Institute of Plant Genetic Resources "k. Malkov" Information and Documentation Center Sadovo Plovdiv district Bulgaria

ISBN: (纸本)9781728154565

This paper introduces a infrastructure for smart agriculture. The basic components of the infrastructure are also presented. The kernel component is the Operative Center consisting of personal assistants. The purpose of this center is to be the institution for operational management of the whole infrastructure. Furthermore, the development of a personal assistant as a BDI intelligent agent is presented in more details. Some implementation issues of the personal assistant are also discussed in this paper. © 2020 IEEE.

关键词： intelligent agents

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