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About this book

This book constitutes the refereed proceedings of the 16th World Congress on Services, SERVICES 2020, held as part of the Services Conference Federation, SCF 2020, in Honolulu, HI, USA, in September 2020. The conference was held virtually due to the COVID-19 pandemic.The 5 full papers and 4 short papers presented were carefully reviewed and selected from 10 submissions. The papers cover topics in the field of software engineering foundations and applications with a focus on novel approaches for engineering requirements, design and architectures, testing, maintenance and evolution, model-driven development, software processes, metrics, quality assurance and new software economics models, search-based software engineering, benefiting day-to-day services sectors and derived through experiences, with appreciation to scale, pragmatism, transparency, compliance and/or dependability.

Table of Contents

Frontmatter

Case Study on Key Influencing Factors of Modern Service Industry Development

Abstract
In the process of industrial structure adjustment and economic development model innovation, the role and status of modern service industry are becoming increasingly important. Shenzhen Municipal People’s Government had paid great attention on the development of modern service industry. On one hand, modern service industry has been quite large and mature, and on the other hand, there are problems of insufficient in total volume, relatively narrow industry field and somehow inadequate industry structure. Based on rational choosing and building an influencing indicator system, this paper tries to analysis the development of modern service industry in Shenzhen. Through using methods such as cointegration analysis, Granger causality test and multiple linear regression, combined with the relevant data collected, we found that the foreign direct investment and the investment level of modern service industry are the key factors. Therefore, this paper suggested that the development of modern service industry in Shenzhen might improve on expanding foreign investment, strengthening the investment level of modern service industry, and upgrading professional talents.
Zhu Xiangbo, Ou Guoliang, Li Yi, Zhou Zhigang

Blockchain Driven Three Domain Secure 2.x in Digital Payment Services Architecture

Abstract
Due to the recent advancements in digital commerce, consumers expect real-time digital payment convenient and available across channels as more connected devices become payment devices. It offers consumers to pay in-store or online purchases in many diversified ways. The three domains secure protocol evolved to version 2.x (3DS2) supporting the development in digital payment domain and its rapid adaptation. The specification includes the provisioning of the application-based purchases enabling risk-based decisions to authenticate the consumer transactions. 3DS2 enhances consumers’ checkout experiences through out-of-band authentication. It eliminates the need for enrollment process and static password supporting non-payment activities and native mobile. The primary challenges to implement 3DS2 are dimensioning the risks, real-time variability in the risk factors, and precision to compute the accumulative risk associated with the individuals. Financial services, merchants, and consumers are enabled to connect into the blockchain network using application programming interfaces (APIs). It alleviates participants of Blockchain network from having to build out their own distributed transactions’ server nodes. This paper proposes a blockchain-driven 3DS2 service architecture framework that integrates the risk-based decisions and provides a secure communication platform in digital commerce. We illustrate the increased level of authenticity, maintainability, extendibility, and flexibility in the digital payment ecosystem with the industry case study of membership-based in-store or online charitable contribution campaigns during point-of-sale.
Vikas S. Shah

Educational Application of Big Data Research: A Comparison of China and US

Abstract
Huge amount of data is generated each day, and big data research can be applied in various fields to analyze and extract new knowledge from this big amount of data, with education being one of the most important applications. However, few researchers are focused on comparative analysis of big data application in education between China and the US. In this paper, we analyze the differences between these two countries in their applications of big data theory to the education field. In addition, we also discuss the ethical challenges of these applications, such as how China and US protect privacy in the educational field when applying big data research. Finally, this paper also discusses the lessons learned from the development of big data applications to the education field. This includes privacy protection, which could be used to help policy makers of countries around the world regulate the application of big data theory in the education field.
Ting Zhang, Clara Elizabeth, Renzhi Cao

DLchain: Blockchain with Deep Learning as Proof-of-Useful-Work

Abstract
Blockchains based on Proof-of-Work can maintain a distributed ledger with a high security guarantee but also lead to severe energy waste due to the useless hash calculation. Proof-of-Useful-Work (PoUW) mechanisms are alternatives, but finding hard puzzles with easy verification and useful results is challenging. Recent popular deep learning algorithms require large amount of computation resources due to the large-scale training datasets and the complexity of the models. The work of deep learning training is useful, and the model verification process is much shorter than its training process. Therefore, in this paper, we propose DLchain, a PoUW-based blockchain using deep learning training as the hard puzzle. Theoretical analysis shows that DLchain can achieve a security level comparable to existing PoW-based cryptocurrency when the miners’ best interest is to maximize their revenue. Notably, this is achieved without relying on common assumptions made in existing PoUW-based blockchain such as globally synchronized timestamps. Simulated experiments also show that the extra network delay caused by data transfer and the full nodes’ validation is acceptable.
Changhao Chenli, Boyang Li, Taeho Jung

Blockchain Federation Enabled Trustable Internet of Things

Abstract
The Internet of Things (IoT) provides an infrastructure enabling advanced functions based on interoperable information and communication technologies by interconnecting physical and virtual things. IoT has gained more and more attention from both academy and industry. However, the design, maintenance, and governance of IoT are facing challenges because of an enormous amount of heterogeneous devices involved. IoT requires strengthening its trustable features. The blockchains are immutable distributed ledger systems supporting trustable features including security, scalability, privacy, safety, and connectivity usually without a central authority. Due to the complexity of IoT system any current blockchain cannot satisfy all demands of heterogeneous devices, networks, and higher level functionalities. This paper proposes a novel reference architecture combines Blockchain Federation with IoT to make IoT capable of being trusted. The architecture enables trustable features by integrating blockchains with different IoT tiers and layers. Proof of concept system is implemented to demonstrate the correctness and feasibility of the architecture. Furthermore, the future directions of Blockchain Federation and IoT evolution are discussed.
Zhitao Wan, Minqiang Cai, Xiuping Hua, Jinqing Yang, Xianghua Lin

Decision Support for Patient Discharge in Hospitals – Analyzing the Relationship Between Length of Stay and Readmission Risk, Cost, and Profit

Abstract
Determining the optimal time for patient discharge is a challenging and complex task that involves multiple opposing decision perspectives. On the one hand, patient safety and the quality of healthcare service delivery and on the other hand, economic factors and resource availability need to be considered by hospital personnel. By using state-of-the-art machine learning methods, this paper presents a novel approach to determine the optimal time of patient discharge from different viewpoints, including a cost-centered, an outcome-centered, and a balanced perspective. The proposed approach has been developed and tested as part of a case study in an Australian private hospital group. For this purpose, unplanned readmissions and associated costs for episodes of admitted patient care are analyzed with regards to the respective time of discharge. The results of the analyses show that increasing the length of stay for certain procedure groups can lead to reduced costs. The developed approach can aid physicians and hospital management to make more evidence-based decisions to ensure both sufficient healthcare quality and cost-effective resource allocation in hospitals.
Isabella Eigner, Freimut Bodendorf

AIServiceX: A Knowledge Graph-Based Intelligent Question-Answering System for Personal Services

Abstract
Knowledge graph-based question-answering systems are widely used in e-commerce enterprises. They can reduce the costs of customer services and improve service capabilities. The description of questions is often ambiguous, and the knowledge graph’s update in online personal services always has a high overhead. To address the above issues, by augmenting domain semantics, this paper proposes a knowledge graph-based intelligent question-answering system called as AIServiceX. It employs a gate recurrent unit model to identify entities and assertions, and then gets the most related semantic augmentation contents from existing external domain knowledge via topic comparison. Then, it ranks all the candidates to get optimal answers by discovering several heuristic rules. Periodically, it augments the global knowledge graph with minimized updating costs with an Integer linear programming resolving model. This mechanism can recognize question entities precisely, and map domain knowledge to the KG automatically, which achieves a high answering precision with a low overhead. Experiments with a production e-commerce data show that AIServiceX can improve the precision.
Yao Sun, Wenming Gui, Cheng Han, Yan Zhang, Shudong Zhang

Review for Influence of 5G on Industry Internet

Abstract
In recent year, the downward pressure on the global economy is increasing, and the market is gradually changing. The urgent problem for entrepreneurs is how to keep their companies growing continuously. Industry Internet is a new direction that can help them by promoting business growth of enterprises. And the growth should be realized by exploring innovative business scenarios. The core of industry internet is not the internet, but the traditional industry. It forms the industry value chain through the mutual connection of traditional industries. The enterprises in each link of the value chain will become more powerful because of their value-added data. This paper solves several key problems in the development of enterprises: what economic era are they in? What is industry internet? How does industry Internet empower enterprises? How can 5G related technologies help traditional industries transform into industry internet?
Yang Liu, Liang-Jie Zhang, Chunxiao Xing

A Fuzzy AHP and TOPSIS Approach for Web Service Selection

Abstract
Multi criteria decision making (MCDM) model is proposed for determining the most suitable web service from a collection of functionally-equivalent web services with different non-functional properties. This paper presents an evaluation approach that combines fuzzy analytic hierarchy process (AHP) and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) to solve the MCDM selection problems with conflicting criteria. Fuzzy AHP method determines subjective weights by dealing with vagueness and uncertainty in subjective user’s judgment while, TOPSIS algorithm ranks the different alternatives. A numerical example is based on a real-world dataset is presented to illustrate the procedural matters of the web service selection model. The numerical results show that the proposed approach can effectively select an appropriate web service based on user preference. WeatherStationService performed better than other web services under the selected QoS requirements.
Sandile T. Mhlanga, Manoj Lall, Sunday O. Ojo

Backmatter

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