EAI Endorsed Transactions on Scalable Information Systems

Visit the new journal website to submit and consult our contents: https://publications.eai.eu/index.php/sis/index

Editor(s)-in-Chief: Hua Wang and Xiaohua Jia

Aims & Scope
Indexing
Editorial Board
Special Issues

EAI Endorsed Transactions on Scalable Information Systems is open access, a peer-reviewed scholarly journal focused on scalable distributed information systems, scalable, data mining, grid information systems, and more. The journal publishes research articles, review articles, commentaries, editorials, technical articles, and short communications. From 2024, the journal started to publish twelve issues per year. Authors are not charged for article submission and processing.

INDEXING: ESCI-WoS (IF: 1.3), Scopus (CiteScore 2022: 2.6), Compendex, DOAJ, ProQuest, EBSCO

The scope of the journal includes:

Scalable distributed information systems
Scalable grid information systems
Parallel information processing and systems
Web information searching and retrieval
Data mining
Content delivery networks (CDN)
VLDB
P2P systems
Scalable mobile and wireless database systems
Large scale sensor network systems
Index compression methods
Architectures for scalability
Scalable information system applications
Evaluation metrics for scalability
Information security

Call for Papers: Special issue on: Real-time image information processing with deep neural networks and data mining technologies (Manuscript submission deadline: 2022-02-28; Notification of acceptance: 2022-04-15; Submission of final revised paper: 2022-05-15; Publication of special issue (tentative): 2022-06-15)

Guest Editor: Dr. Prof. Hang Li (Northeastern University, China) Guest Editor: Dr. Prof. Jochen Schiewe (HafenCity Universität Hamburg, Germany)

Editors-in-Chief
Hua Wang, Victoria University, Australia
Xiaohua Jia, City University of Hong Kong
Editorial board
Manik Sharma, DAV University, India
Ajay Kattepur (Tata Consultancy Services)
Aniello Castiglione (University of Salerno)
Chang Choi (Chosun University)
Cho-Li Wang (University of Hong Kong)
Daniel S. Katz (University of Chicago)
Fabrizio Silvestri (ISTI – CNR, Italy)
Hamed Taherdoost (Hamta Business Solution Snd)
Heng Tao Shen (University of Queensland)
Houbing Song (Embry-Riddle Aeronautical University)
José Manuel Machado (University of Minho, Portugal)
Jose Merseguer (Universidad de Zaragoza)
Jie Li (University of Tsukuba)
Lin Yun (Harbin Engineering University)
Phan Cong Vinh (Nguyen Tat Thanh University)
Raj Gururajan (University of Southern Queensland)
Sherman Chow (Chinese University of Hong Kong)
Silva Fábio (University of Minho, Portugal)
Steve Beitzel (Telcordia)
Tzung-Pei Hong (National University of Kaohsiung, Kaohsing City, Taiwan)
Wang-Chien Lee (The Pennsylvania State University)
Weili Wu (The University of Texas at Dallas)
Xueyan Tang (Nanyang Technological University)
Vijayakumar Ponnusamy (SRM University, India)
J Amudhavel (KL University, India)
Yingshu Li (Georgia State University)
Jerry Chun-Wei Lin (Western Norway University of Applied Sciences, Norway)
Karolj Skala (Ruđer Bošković Institute, Croatia)
Xiao-Zhi Gao (University of Eastern Finland, Finland)
Thaier Hayajneh (Fordham University, USA)
Chin-Ling Chen (Chaoyang University of Technology, Taiwan)
Nuno M. Garcia (Faculty of Sciences, University of Lisbon, Portugal)
Arianna D'Ulizia (Consiglio Nazionale delle Ricerche (CNR), Italy)
Robertas Damaševičius (Kaunas University of Technology (KTU), Lithuania)
Hiep Xuan Huynh (Can Tho University, VietNam)
Vincent A. Cicirello (Stockton University, USA)
Ji Zhang (University of Southern Queensland, Australia)
Xiaohui Tao (University of Southern Queensland, Australia)
Ye Wang (National University of Defense Technology, China)
Nageswara Rao Moparthi (KL University, India)
Shuai Liu (Hunan Normal University, China)
Prof Xiaoming Fu (Georg-August-University of Goettingen, Germany)
Prof Zhisheng Huang (Vrije University of Amsterdam)
Prof Rose Quan (Northumbria University, UK)
Prof Shi Dong (Zhoukou Normal University, China)
Dr Limei Peng (Kyungpook National University, South Korea)
Prof Hui Ma( Victoria University of Wellington, New Zealand)
Dr. Venkatesan Subramanian (Indian Institute of Information Technology – Allahabad, India)
Dr Pon Harshavardhanan (VIT Bhopal University, India)
Dr. Manish Kumar (The Indian Institute of Information Technology, Allahabad, India)

Recently Published
Most Popular

Design and Application of Evaluation Method for Civics Classroom Based on CRITIC Fuzzy Algorithm
Appears in:
sis 23(1):

Author:
Zhanyu Chang

Published:
24th Oct 2024

Abstract:
INTRODUCTION: Through in-depth study of Civics classroom evaluation, it can provide teachers with scientific evaluation indexes and methods, improve teaching quality and effect, promote the overall development of students, and also promote the professional growth of teachers. OBJECTIVES: Based on …INTRODUCTION: Through in-depth study of Civics classroom evaluation, it can provide teachers with scientific evaluation indexes and methods, improve teaching quality and effect, promote the overall development of students, and also promote the professional growth of teachers.
OBJECTIVES: Based on critical and fuzzy comprehensive evaluation methods, this study aims to study the effectiveness and accuracy of the evaluation methods in Civics and Politics classrooms. Based on the CRITIC method, the fuzzy comprehensive evaluation method was introduced to solve the problem of subjectivity and uncertainty in the evaluation process.
METHODS: Various research methods were used, including observation, interviews, and questionnaires. By comprehensively analyzing the students' performance, feedback, and assessment, and the teachers' pre-course preparation, the advantages and improvement directions of Civics classroom teaching can be accurately evaluated using the CRITIC and fuzzy comprehensive evaluation methods.
RESULTS: The study results show that the CRITIC and fuzzy comprehensive evaluation methods can provide a more comprehensive, accurate, and objective evaluation of the Civics classroom. The undefined complete evaluation method plays an essential role in dealing with ambiguity and uncertainty in the evaluation process, making the evaluation results more objective and reliable.
CONCLUSION: The Civics classroom evaluation method based on the CRITIC and fuzzy comprehensive evaluation methods is adequate and accurate. These findings strongly support improving the quality of Civics classroom teaching and enhancing students' learning outcomes.
more »
Utilizing Blockchain Technology in Global Supply Chain Management: An Exploration of Scalable Information Systems
Appears in:
sis 23(1):

Authors:
Syamsuddin , Saharuddin , Yusrizal , Tuti Dharmawati, Endang Fatmawati

Published:
14th Nov 2023

Abstract:
INTRODUCTION: Global supply chain management is a critical component in the increasingly complex and connected world of modern business. In the era of globalization, companies face pressure to increase efficiency, transparency, and security in their supply chains. Blockchain technology has emerged …INTRODUCTION: Global supply chain management is a critical component in the increasingly complex and connected world of modern business. In the era of globalization, companies face pressure to increase efficiency, transparency, and security in their supply chains. Blockchain technology has emerged as a potential solution to address some of these challenges by enabling more decentralized, transparent, and efficient supply chain management. However, the use of this technology in global supply chain management also raises several issues related to regulation, law, and collaboration with third parties.
OBJECTIVE: This research then aims to explore the potential of blockchain technology in global supply chain management and understand the regulatory framework needed to support the implementation of this technology.
METHOD: This research was carried out using a qualitative approach. The data used in this research comes from various research results and previous studies that are relevant to the discussion.
RESULTS: The results of this research then found that the use of blockchain technology in global supply chain management promises to increase transparency, efficiency, and security. Smart contracts enable the automation of business processes, reducing costs and increasing visibility of operations. Collaboration with third parties is an important strategy in increasing supply chain efficiency. Regulation, data security, and international harmonization remain challenges.
CONCLUSION: Defining the legal status of smart contracts and protecting data is key. Effective collaboration with third parties requires good communication and a mature strategy. With a deep understanding of blockchain technology and proper regulation, companies can maximize their benefits to create an efficient, transparent, and reliable supply chain.
more »
Adoption of Quantum Computing in Economic Analysis: Potential and Challenges in Distributed Information Systems
Appears in:
sis 23(1):

Authors:
Tuti Dharmawati, Loso Judijanto, Endang Fatmawati, Abdul Rokhim, Faria Ruhana, Moh Erkamim

Published:
14th Nov 2023

Abstract:
INTRODUCTION: Quantum computing technology has become a center of attention in various scientific disciplines, including economic analysis. The adoption of quantum computing in economic analysis offers tremendous potential to improve the processing of complex economic data and provide deep insights…INTRODUCTION: Quantum computing technology has become a center of attention in various scientific disciplines, including economic analysis. The adoption of quantum computing in economic analysis offers tremendous potential to improve the processing of complex economic data and provide deep insights. However, the use of quantum technology in the context of distributed information systems also raises several challenges, including data security and the limitations of quantum technology.
OBJECTIVE: This research aims to investigate the implications of adopting quantum computing in economic analysis, with a focus on distributed information systems.
METHODS: This research was carried out using a descriptive qualitative approach, with data derived from the results of relevant research and previous studies. The collected data will be processed and analyzed to gain a deeper understanding of the adoption of quantum computing in economic analysis in distributed information systems.
RESULTS: This research then finds that the adoption of quantum computing in economic analysis has the potential to increase efficiency, accuracy, and depth of economic insight. However, limitations of current quantum technologies, including quantum errors, limited scale of operations, and data security issues, limit their applications. In the long term, research and development will be key to overcoming these obstacles and maximizing the potential of this technology in economic analysis.
CONCLUSION: The long-term implications include increased economic competitiveness and significant changes in the way economic decision-making is carried out, assuming that ethical and regulatory issues are also carefully considered.
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Optimizing Electronic Voting System in Village Head Elections: Evaluation and Recommendations from Sleman Regency, Indonesia
Appears in:
sis 23(1):

Authors:
Teguh Ilham, Eko Budi Santoso, Hasna Azmi Fadhilah

Published:
14th Nov 2023

Abstract:
INTRODUCTION: The rapid technological advancements of Industry 4.0 have influenced government politics, extending to the adoption of electronic voting in village head elections. In Sleman, e-voting was introduced in 2020, aiming for voting system efficiency and synchronization of population data, p…INTRODUCTION: The rapid technological advancements of Industry 4.0 have influenced government politics, extending to the adoption of electronic voting in village head elections. In Sleman, e-voting was introduced in 2020, aiming for voting system efficiency and synchronization of population data, positioning the region as an e-voting pioneer in Indonesia. While e-voting offers efficiency and cost savings, it faces some problems.
OBJECTIVES: This study endeavors to comprehensively assess the implementation of the e-voting system in village head elections and provide recommendations for its optimization, with a specific focus on the context of Sleman Regency.
METHODS: This qualitative research encompasses data from 17 villages spread across 35 sub-districts within Sleman Regency. The study utilizes a comprehensive approach that includes secondary data analysis, incorporating literature, internet-based resources, scientific journals, books, regulations, and official documents. It further involves interviews with government officials at Sleman offices, officials at polling stations, and voters. Additionally, observational data is gathered to shed light on the intricate dynamics of e-voting.
RESULTS: The evaluation focused on four pivotal aspects of the e-voting system's success: public trust, public participation, technology, and adherence to election principles. The findings reveal improved dynamics in 2021 when compared to 2020. Public trust in the e-voting system has notably increased, aligning with the relatively successful implementation in the previous year. While community participation has reached a satisfactory level, it has yet to attain full community control, with interesting nuances observed, particularly in less ‘advanced’ villages where participation tends to be lower. In the realm of technology, the e-voting system excels in terms of security, hardware reliability, the comprehensiveness of application features, and user-friendliness.
CONCLUSION: The study underscores that the enhancement of e-voting systems presents an avenue to fortify democratic practices and electoral processes in Indonesia. Acknowledging imperfections in data collection systems and addressing participation disparities among villages should be prioritised. Furthermore, the study suggests that comprehensive future research is needed to evaluate the feasibility of extending e-voting systems to higher levels of government elections. This examination offers valuable insights into the evolution of e-voting in Indonesia and the prospects for its expansion in democratisation efforts.
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Internet of Things and Cloud Computing Integration of Opera Elements into Vocal Singing Teaching Practice Exploration
Appears in:
sis 23(1):

Author:
Gang Li

Published:
14th Nov 2023

Abstract:
INTRODUCTION: With the rapid development of computer technology, the application of the Internet of Things and cloud computing technology is becoming more and more common. However, there is no more computer technology integration in integrating opera elements into vocal singing teaching. Therefore,…INTRODUCTION: With the rapid development of computer technology, the application of the Internet of Things and cloud computing technology is becoming more and more common. However, there is no more computer technology integration in integrating opera elements into vocal singing teaching. Therefore, compared with other industries, the development of verbal singing teaching could be faster and adapt to the current era of the Internet of Things and cloud computing. Thus studies the exploration of the practice of integrating opera elements into vocal singing teaching based on the Internet of Things and cloud computing.
OBJECTIVES: To improve the level of China's Internet of Things and cloud computing technology-based opera elements into vocal singing teaching practice; to solve the current problem of China's traditional culture not being integrated into verbal singing teaching; to promote the development of China's opera industry, the modernization of oral singing teaching, and to enhance the relevance of the Internet and economic development.
METHODS: In the study, firstly, the Internet of Things (IoT) and cloud computing technology are used for the establishment of the evaluation model; secondly, the feasibility of integrating opera elements into vocal singing teaching is analyzed through theoretical discussions; lastly, through the analysis of the model of the Internet of Things (IoT) and cloud computing, the feasibility of integrating opera elements into vocal singing teaching is illustrated by the analysis of the model of the Internet of Things (IoT) and cloud computing, and how the Internet of Things and cloud computing can assist opera elements to be integrated into vocal singing teaching.
RESULTS: Using the Internet of Things and cloud computing technology to enrich the vocal singing teaching model from multiple perspectives can better enhance the integration of opera elements into verbal singing teaching. Internet of Things and cloud computing technology play an auxiliary role in the integration of opera elements into vocal singing teaching; the study of the additional mechanism reveals that the effect of the integration of opera elements into verbal singing teaching can be improved through the improvement of the means of the auxiliary function.
CONCLUSION: As a representative of Chinese culture, the integration of opera elements into vocal singing teaching practice is of great significance, and the Internet of Things and cloud computing technology play an essential role in helping the integration of opera elements into vocal singing teaching practice.
more »
Edge Computing in E-commerce Business: Economic Impacts and Advantages of Scalable Information Systems
Appears in:
sis 23(1):

Authors:
Dikson Silitonga, Siti Alfia Ayu Rohmayanti, Zaenal Aripin, Dadi Kuswandi, Arif Budi Sulistyo, Juhari

Published:
10th Nov 2023

Abstract:
INTRODUCTION: Edge Computing brings better responsiveness and faster customer experiences, while Scalable Information Systems enable efficient business growth management. OBJECTIVE: This research analyzes the economic impact of using Edge Computing in E-Commerce businesses and reveals the advantag…INTRODUCTION: Edge Computing brings better responsiveness and faster customer experiences, while Scalable Information Systems enable efficient business growth management.
OBJECTIVE: This research analyzes the economic impact of using Edge Computing in E-Commerce businesses and reveals the advantages of Scalable Information Systems.
METHOD: The research approach used is a mixed-method, which includes quantitative data analysis and interviews with key stakeholders in five E-Commerce companies.
RESULTS: The research results show increased responsiveness, operational efficiency, cost savings, enhanced data security, and better customer retention due to the implementation of Edge Computing. Scalable Information Systems also help E-Commerce companies manage rapid business growth flexibly.
CONCLUSION: This technology provides significant and relevant advantages in improving company performance and competitiveness in a competitive E-Commerce context.
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Application EIMT Algorithm on Evaluation Method of English Multimedia Classroom Teaching Quality
Appears in:
sis 23(1):

Authors:
Bin Xie, Lili Ma, Fengjun Liu

Published:
24th Oct 2023

Abstract:
INTRODUCTION: Multimedia teaching at this stage requires teachers to have specific technical and pedagogical skills when using multimedia teaching and be able to flexibly utilize multimedia tools for education. OBJECTIVES: The evaluation aims to provide a reference for teachers to improve their te…INTRODUCTION: Multimedia teaching at this stage requires teachers to have specific technical and pedagogical skills when using multimedia teaching and be able to flexibly utilize multimedia tools for education.
OBJECTIVES: The evaluation aims to provide a reference for teachers to improve their teaching and provide feedback on the quality of instruction for schools and educational management.
METHODS: Based on the EIMT method, a method for evaluating the quality of English multimedia classroom teaching is proposed. The technique considers three factors, namely, teachers' teaching ability, students' learning, and course content, to comprehensively evaluate the quality of teaching.
RESULTS: The final example verification of the selected cases shows that the evaluation system is reasonably constructed and the evaluation model is well applicable.
CONCLUSION: Multimedia classroom teaching can improve students' participation and enthusiasm. Multimedia teaching can stimulate students' interest and curiosity through various forms, such as image, sound, and video, so they can actively participate in learning.
more »
Information Security Construction of SPOC: Path Selection for Japanese Information Acquisition
Appears in:
sis 23(1):

Author:
Lei Chen

Published:
24th Oct 2023

Abstract:
INTRODUCTION: In the traditional oral Japanese teaching model, Japanese courses emphasize theoretical knowledge of vocabulary and grammar, with few practical functions, low student interest in learning, and low attendance in class. They have made breakthroughs in information technology, e-commerce,…INTRODUCTION: In the traditional oral Japanese teaching model, Japanese courses emphasize theoretical knowledge of vocabulary and grammar, with few practical functions, low student interest in learning, and low attendance in class. They have made breakthroughs in information technology, e-commerce, and other professional fields.
METHODS: A traditional teaching format is used, with the mains taught by teachers, without using learning platforms or offline teaching. Each lesson contains three elements: preschool, instructional practices, and external extensions. A cloud-based classroom learning platform is part of Cyber Chemistry's preschool and out-of-school learning. Classroom instruction consisted primarily of discussions and exchanges between teachers and students, competitive exercises, and visualization of the results of conversations. To test the effectiveness of the SPOC-based model, the authors administered two speaking tests, as well as related questionnaires and interviews, during and at the end of the test.
RESULTS: Improvements in the intermediate pretest and post-test speaking tests compared to the control group suggest that the Japanese hybrid speaking test model, SPOC, is positively compelling.
CONCLUSION: The class stimulates students' interest and motivation. It plays an active role in developing good learning practices and improving the learning of spoken Japanese.
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Application Entropy Weight and TOPSIS Method in English Teaching Quality Evaluation of "Smart Classroom"
Appears in:
sis 23(1):

Author:
Qingqing Chen

Published:
20th Oct 2023

Abstract:
INTRODUCTION: Based on TOPSIS (Technological Ordering of Superiority and Inferiority) and entropy weight method, it aims to evaluate the quality of intelligent classroom English teaching. The brilliant classroom teaching model has attracted much attention for its highly interactive, personalized, a…INTRODUCTION: Based on TOPSIS (Technological Ordering of Superiority and Inferiority) and entropy weight method, it aims to evaluate the quality of intelligent classroom English teaching. The brilliant classroom teaching model has attracted much attention for its highly interactive, personalized, and real-time feedback features; however, how to accurately evaluate the quality of intelligent classroom teaching remains a challenge.
OBJECTIVES: To combine the TOPSIS and entropy weight methods in practical application and consider the index ordering and weight calculation comprehensively to arrive at the quality evaluation results of each brilliant classroom teaching.
METHODS: The TOPSIS method is first used to rank multiple indicators of teaching quality to determine the optimal teaching quality. The TOPSIS method can consider the interrelationships between the hands and find the solution closest to the positive ideal solution and farthest away from the negative perfect solution by calculating each indicator's positive and negative perfect solutions. Then, the weight of each hand is calculated by combining the entropy weight method. The entropy weight method can consider the indicators' information and differences and measure the degree of their contribution to the evaluation results by calculating the entropy value of the hands.
RESULTS: The results show that the method can comprehensively consider the correlation and weight of multiple indicators, provide teachers and educational administrators with accurate teaching quality evaluation and improvement suggestions, and thus promote the optimization and enhancement of innovative classroom teaching.
CONCLUSION: By analyzing the actual smart classroom teaching data, the Author found that the method can effectively evaluate the quality of intelligent classroom teaching and provide valuable guidance for English teaching improvement.
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A Hybrid Named Entity Recognition System for Aviation Text
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sis 23(1):

Authors:
Bharathi A, Robin Ramdin, Preeja Babu, Vijay Krishna Menon, Chandrasekhar Jayaramakrishnan, Sudarasan Lakshmikumar

Published:
20th Oct 2023

Abstract:
Named Entity Recognition (NER) is a crucial task in Natural Language Processing (NLP) that aims to identify and categorize named entities in text. While NER has been well-studied in various domains, it remains a challenging task in new domains where annotated data is limited. In this paper, we prop…Named Entity Recognition (NER) is a crucial task in Natural Language Processing (NLP) that aims to identify and categorize named entities in text. While NER has been well-studied in various domains, it remains a challenging task in new domains where annotated data is limited. In this paper, we propose an NER system for the aviation domain that addresses this challenge. Our system combines rule-based and supervised methods to develop a model with little to no manual annotation work.We evaluate our system on a benchmark dataset and it outperforms baseline scores and achieves competitive results. To the best of our knowledge, this is the first study to develop an NER system that specifically targets aviation entities. Our findings highlight the potential of our proposed system for NER in aviation and pave the way for future research in this area.
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Topic Modeling: A Comprehensive Review
Appears in:
sis 20(24): e2

Authors:
Pooja Kherwa, Poonam Bansal

Downloads:
9856

Abstract:
Topic modelling is the new revolution in text mining. It is a statistical technique for revealing the underlying semantic structure in large collection of documents. After analysing approximately 300 research articles on topic modeling, a comprehensive survey on topic modelling has been presented i…Topic modelling is the new revolution in text mining. It is a statistical technique for revealing the underlying semantic structure in large collection of documents. After analysing approximately 300 research articles on topic modeling, a comprehensive survey on topic modelling has been presented in this paper. It includes classification hierarchy, Topic modelling methods, Posterior Inference techniques, different evolution models of latent Dirichlet allocation (LDA) and its
applications in different areas of technology including Scientific Literature, Bioinformatics, Software Engineering and analysing social network is presented. Quantitative evaluation of topic modeling techniques is also presented in detail for better understanding the concept of topic modeling. At the end paper is concluded with detailed discussion on challenges
of topic modelling, which will definitely give researchers an insight for good research.
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The impact of using social media and internet on academic performance case study Bahrain Universities
Appears in:
sis 17(13): e2

Author:
Abdulla Jaafar Desmal

Downloads:
8990

Abstract:
The internet and social media provide students with a range of academic benefits and opportunities to enhance their learning process. The main goal of this research is to examine the impact of using the social media on the academic performance. The new social networks, such as Instagram, Facebook, …The internet and social media provide students with a range of academic benefits and opportunities to enhance their learning process. The main goal of this research is to examine the impact of using the social media on the academic performance. The new social networks, such as Instagram, Facebook, Twitter, etc., can affect the behavior and academic performance of the universities' students; therefore the selected universities were Ahlia University, Applied Science University and University of Bahrain. The sample was (150) students distributed equally among the three universities. The research questions will answer (1) what is the evolution of ICTs and the Internet in the World; (2) what is the impact caused by ICT in education; (3) what are the effects of social media on the academic performance of students at Bahrain Universities; (4) what are the social networking sites that are more popular among students at Bahrain Universities. The results show that the social media has a positive impact on academic performance and 57% of students prefer the mobile application WhatsApp as a social media for their academic purpose.
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Preventing DDoS using Bloom Filter: A Survey
Appears in:
sis 18(19): e3

Authors:
Ripon Patgiri, Sabuzima Nayak, Samir Kumar Borgohain

Downloads:
5607

Abstract:
Distributed Denial-of-Service (DDoS) is a menace for service provider and prominent issue in network security. Defeating or defending the DDoS is a prime challenge. DDoS make a service unavailable for a certain time. This phenomenon harms the service providers, and hence, causes loss of business re…Distributed Denial-of-Service (DDoS) is a menace for service provider and prominent issue in network security. Defeating or defending the DDoS is a prime challenge. DDoS make a service unavailable for a certain time. This phenomenon harms the service providers, and hence, causes loss of business revenue. Therefore, DDoS is a grand challenge to defeat. There are numerous mechanism to defend DDoS, however, this paper surveys the deployment of Bloom Filter in defending the DDoS attack. The Bloom Filter is a probabilistic data structure for membership query that returns either true or false. Bloom Filter uses tiny memory to store information of large data. Therefore, packet information is stored in Bloom Filter to defend and defeat DDoS. This paper presents a survey on DDoS defending technique using Bloom Filter.
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A Parking Management System based on Background Difference Detecting Algorithm
Appears in:
sis 15(7): e3

Authors:
Xiaoling Wu, Yanwen Wang, Hainan Chen, Kangkang Liang, Lei Shu

Downloads:
5308

Abstract:
The number of vehicles in cities has increased dramatically due to rapid economic development. However, the infrastructure for accommodating these vehicles has grown relatively slow. Alleviating the pressure on the urban transport system and solving the ‘parking difficulty’ problem have thus becom…The number of vehicles in cities has increased dramatically due to rapid economic development. However, the infrastructure for accommodating these vehicles has grown
relatively slow. Alleviating the pressure on the urban transport system and solving the ‘parking difficulty’ problem have thus become hot topics recently. In this paper, an intelligent parking system based on geomagnetic field variations is presented to solve
this problem. An algorithm which detects the presence of vehicles in parking spaces in a parking lot is designed and field test results are presented. Our results show that this system has an acceptably high accuracy with low cost, high feasibility, high efficiency and hence is recommended for wide use.
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A Narrative Literature Review and E-Commerce Website Research
Appears in:
sis 18(17): e1

Author:
K.M. Rahman

Downloads:
4953

Abstract:
In this study, a narrative literature review regarding culture and e-commerce website design has been introduced. Cultural aspect and e-commerce website design will play a significant role for successful global e-commerce sites in the future. Future success of businesses will rely on e-commerce. To…In this study, a narrative literature review regarding culture and e-commerce website design has been introduced. Cultural aspect and e-commerce website design will play a significant role for successful global e-commerce sites in the future. Future success of businesses will rely on e-commerce. To compete in the global e-commerce marketplace, local businesses need to focus on designing culturally friendly e-commerce websites. To the best of my knowledge, there has been insignificant research conducted on correlations between culture and e-commerce website design. The research shows that there are correlations between e-commerce, culture, and website design. The result of the study indicates that cultural aspects influence e-commerce website design. This study aims to deliver a reference source for information systems and information technology researchers interested in culture and e-commerce website design, and will show less-focused research areas in addition to future directions.
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A Hybrid Approach for Breast Cancer Classification and Diagnosis
Appears in:
sis 19(20): e2

Authors:
Bibhuprasad Sahu, Sachi Nandan Mohanty, Saroj Kumar Rout

Downloads:
4837

Abstract:
Feature selection in breast cancer disease important and risky task for further analysis. Breast cancer is the second leading reason for death among the women. Cancer starts from breast and spread to other part of the body. People are unable to identify their disease before it become dangerous. It …Feature selection in breast cancer disease important and risky task for further analysis. Breast cancer is the second leading reason for death among the women. Cancer starts from breast and spread to other part of the body. People are unable to identify their disease before it become dangerous. It can be cured if the disease identified at early stage. Accurate classification of benign tumours can avoid patients undergoing unnecessary treatments. Data Analytics and machine learning methods provides framework for prognostic studies by errorless classification of data instances into relevant based on the cancer severity. In this study we have purposed a prediction model by combining artificial intelligent based learning technique with multivariate statistical method. For automation of the diagnosis process data mining plays an significant role. The data sets available in different repositories are noisy in nature. This study suggests a hybrid feature selection method to be used with PCA (Principal Component Analysis) and Artificial Neural Network (ANN). Preprocessing of data and extracting the most relevant features done by PCA. The proposed algorithm is tested by applying it on Wisconsin Breast Cancer Dataset from UCI Repository of Machine Learning Databases. In classification phase 10 fold cross validation was used. The suggested algorithm was measured against different classifier algorithms on the same database. The evaluation results of the algorithm proposed have achieved better accuracy with sensitivity and F measure comparison with others and by enhancing this concept we can provide a future scope to produce sophisticated learning models for diagnosis.
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An Advanced Conceptual Diagnostic Healthcare Framework for Diabetes and Cardiovascular Disorders
Appears in:
sis 18(18): e5

Authors:
M. Sharma, G. Singh, R. Singh

Downloads:
4456

Abstract:
The data mining along with emerging computing techniques have astonishingly influenced the healthcare industry. Researchers have used different Data Mining and Internet of Things (IoT) for enrooting a programmed solution for diabetes and heart patients. However, still, more advanced and united solu…The data mining along with emerging computing techniques have astonishingly influenced the healthcare industry. Researchers have used different Data Mining and Internet of Things (IoT) for enrooting a programmed solution for diabetes and heart patients. However, still, more advanced and united solution is needed that can offer a therapeutic opinion to individual diabetic and cardio patients. Therefore, here, a smart data mining and IoT (SMDIoT) based advanced healthcare system for proficient diabetes and cardiovascular diseases have been proposed. The hybridization of data mining and IoT with other emerging computing techniques is supposed to give an effective and economical solution to diabetes and cardio patients. SMDIoT hybridized the ideas of data mining, Internet of Things, chatbots, contextual entity search (CES), bio-sensors, semantic analysis and granular computing (GC). The bio-sensors of the proposed system assist in getting the current and precise status of the concerned patients so that in case of an emergency, the needful medical assistance can be provided. The novelty lies in the hybrid framework and the adequate support of chatbots, granular computing, context entity search and semantic analysis. The practical implementation of this system is very challenging and costly. However, it appears to be more operative and economical solution for diabetes and cardio patients.
more »
Comparative Analysis of Wind Speed Forecasting Using LSTM and SVM
Appears in:
sis 20(25): e1

Authors:
Satyam Gangwar, Vikram Bali, Ajay Kumar

Downloads:
4396

Abstract:
The objective of this work is to present a comprehensive exploration of deep learning based wind forecasting model. The forecasting of speed of wind is called as the wind speed forecasting/prediction. It is basically done to achieve the better sustainability for power generation and production. The…The objective of this work is to present a comprehensive exploration of deep learning based wind forecasting model. The forecasting of speed of wind is called as the wind speed forecasting/prediction. It is basically done to achieve the better sustainability for power generation and production. The availability of wind energy in ample amount makes it quite
comfortable to be utilized for various functionalities. In this research work the main aim is to forecast speed using LSTM including certain parameters and then comparative analysis is done using SVM. Both are machine learning approaches but have different functionalities in comparison to each other. This comparison is done to obtain the better technique which can be further applied on larger datasets to design a better, accurate, efficient forecasting model for speed of wind. The survey and implementation of both the techniques gave a clear idea about the utilisation of long short term memory for the better and enhanced wind speed forecasting. The forecasting is based on various atmospheric variables, and the data set is
taken from the kaggle datsets which have numerous attributes but we have considered few of them only for the prediction purpose.
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Stock Price Prediction using Artificial Neural Model: An Application of Big Data
Appears in:
sis 19(20): e1

Authors:
Malav Shastri, Sudipta Roy, Mamta Mittal

Downloads:
4370

Abstract:
In recent time, stock price prediction is an area of profound interest in the realm of fiscal market. To predict the stock prices, authors have proposed a technique by first calculating the sentiment scores through Naïve Bayes classifier and after that neural network is applied on both sentiment sc…In recent time, stock price prediction is an area of profound interest in the realm of fiscal market. To predict the stock prices, authors have proposed a technique by first calculating the sentiment scores through Naïve Bayes classifier and after that neural network is applied on both sentiment scores and historical stock dataset. They have also addressed the issue of data cleaning using a Hive ecosystem. This ecosystem is being used for pre-processing part and a neural network model with inputs from sentiment analysis and historic data is used to predict the prices. It has been observed from the experiments that the accuracy level reaches above 90% in maximum cases, as well as it also provides the solid base that model will be more accurate if it trained with recent data. The intended combination of sentiment analysis and Neural networks is used to establish a statistical relationship between historic numerical data records of a particular stock and other sentimental factors which can affects the stock prices.
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Machine Learning and Predictive Analysis of Fossil Fuels Consumption in Mid-Term
Appears in:
sis 17(15): e4

Authors:
Mahmood Amerion, Mohammadmehdi Hosseini, Abdorreza Alavi Gharahbagh, Mohsen Amerion

Downloads:
3980

Abstract:
In economies that are dependent on fossil fuel revenues, Realization of long-term plans, mid-term and annual budgeting requires a fairly accurate estimation of the amount of consumption and its price fluctuations. Accordingly, the present study is using machine learning techniques to predict the us…In economies that are dependent on fossil fuel revenues, Realization of long-term plans, mid-term and annual budgeting requires a fairly accurate estimation of the amount of consumption and its price fluctuations. Accordingly, the present study is using machine learning techniques to predict the usage of fossil fuels (Diesel, Black oil, Heating oil, and Petrol) in mid-term. Exponential Smoothing, a model of time series and the Neural Network model have been applied on the actual usage data obtained from Shahroud area from 2010 to 2015. For estimation of predictive value by Neural Network method, the training and testing samples, the highest and lowest errors with a range of 41% -0.89% and 88% -3% for the Mean Absolute Percent Deviation are the most appropriate predictions for Petrol consumption. And in the Single Exponential Smoothing, the forecast rate for each product is estimated on a
quarterly as well as monthly basis.
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Publisher: EAI
ISSN: 2032-9407
Number of Volumes: 11

Last Published: 2023-11-13