Ubiquitous Computing Application and Wireless Sensor

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Lecture Notes in Electrical Engineering 331

James J. (Jong Hyuk) Park

Yi Pan

Han-Chieh Chao

Gangman Yi

Editors

Ubiquitous

Computing

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Lecture Notes in Electrical Engineering

Volume 331

Board of Series editors

Leopoldo Angrisani, Napoli, Italy Marco Arteaga, Coyoacá_{n, M}é_xico Samarjit Chakraborty, Mü_{nchen, Germany} Jiming Chen, Hangzhou, P.R. China Tan Kay Chen, Singapore, Singapore Rü_{diger Dillmann, Karlsruhe, Germany} Haibin Duan, Beijing, China

Gianluigi Ferrari, Parma, Italy Manuel Ferre, Madrid, Spain Sandra Hirche, Mü_{nchen, Germany} Faryar Jabbari, Irvine, USA Janusz Kacprzyk, Warsaw, Poland Alaa Khamis, New Cairo City, Egypt Torsten Kroeger, Stanford, USA Tan Cher Ming, Singapore, Singapore Wolfgang Minker, Ulm, Germany Pradeep Misra, Dayton, USA Sebastian Mö_{ller, Berlin, Germany}

Subhas Mukhopadyay, Palmerston, New Zealand Cun-Zheng Ning, Tempe, USA

Toyoaki Nishida, Sakyo-ku, Japan Bijaya Ketan Panigrahi, New Delhi, India Federica Pascucci, Roma, Italy

Tariq Samad, Minneapolis, USA

Gan Woon Seng, Nanyang Avenue, Singapore Germano Veiga, Porto, Portugal

Haitao Wu, Beijing, China

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About this Series

“Lecture Notes in Electrical Engineering (LNEE)”is a book series which reports the latest research and developments in Electrical Engineering, namely:

• Communication, Networks, and Information Theory • Computer Engineering

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More information about this series at http://www.springer.com/series/7818

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James J. (Jong Hyuk) Park

Yi Pan

•

Han-Chieh Chao

•

Gangman Yi

Editors

Ubiquitous Computing

Application and Wireless

Sensor

UCAWSN-14

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Editors

Library of Congress Control Number: 2014955621 Springer Dordrecht Heidelberg New York London

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Message from the UCAWSN 2014 General

Chairs

The 2nd FTRA International Conference on Ubiquitous Computing Application and Wireless Sensor Network (UCAWSN-14) is an event of the series of interna-tional scientiﬁc conferences. This conference took place in Jeju, Korea, during July 7–10, 2014. UCAWSN-14 was the most comprehensive conference focused on various aspects of Ubiquitous Computing Application and Wireless Sensor Net-work (UCA-WSN). The UCAWSN-14 will provided an opportunity for academic and industry professionals to discuss the latest issues and progress in the area of UCAWSN. In addition, the conference published high-quality papers that are closely related to various theories and practical applications. Furthermore, we expect that the conference and its publications will be a trigger for further related research and technology improvements in this important subject.

The papers included in the proceedings cover two tracks: Track 1–Ubiquitous Computing and Track 2–Wireless Sensor Network. Accepted and presented papers highlight new trends and challenges of Ubiquitous Computing Application and Wireless Sensor Network. The presenters showed how new research could lead to novel and innovative applications. We hope you willﬁnd these results useful and inspiring for your future research.

We would like to express our sincere thanks to the Program Chairs: Gangman Yi (Gangneung-Wonju National University, Korea), Yuh-Shyan Chen (National Taipei University, Taiwan), Xiaohong Peng (Aston University, UK), Ali Abedi (Maine University, US), Neil Y. Yen (the University of Aizu, Japan), Jen Juan Li (North Dakota State University, USA), Hongxue (Harris) Wang (Athabasca Uni-versity, Canada), Lijun Zhu (ISTIC, China), and all Program Committee members and additional reviewers for their valuable efforts in the review process, which helped us to guarantee the highest quality of the selected papers for the conference. Our special thanks go to the invited speakers who kindly accepted our invitation, and helped to meet the objectives of the conference: Prof. Young-Sik Jeong (Dongguk University, Korea) and Mohammad S. Obaidat (Monmouth University,

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USA), and another special thank you goes to Hak Hyun Choi (Seoul Women’s University) for his efforts to make the conference successful.

We cordially thank all the authors for their valuable contributions and the other participants of this conference. The conference would not have been possible without their support. Thanks are also due to the many experts who contributed to making the event a success.

July 2014 Hwa-Young Jeong

Kyung Hee University, Korea

Han-Chieh Chao National Ilan University, Taiwan

Yi Pan Georgia State University, USA

Qun Jin Waseda University, Japan

vi Message from the UCAWSN 2014 General Chairs

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Message from the UCAWSN 2014 Program

Chairs

Welcome to the 2nd FTRA International Conference on Ubiquitous Computing Application and Wireless Sensor Network (UCAWSN-14), held in Jeju during July 7–10, 2014. UCAWSN 2014 is the most comprehensive conference focused on various aspects of information technology. UCAWSN 2014 provides an opportu-nity for academic and industry professionals to discuss the latest issues and progress in the area of UCAWSN such as Ubiquitous and aware computing, context-awareness reasoning and representation, locations context-awareness services, architectures, protocols and algorithms of WSN, energy, management and control of WSN, etc. In addition, the conference will publish high-quality papers that are closely related to the various theories and practical applications in UCA-WSN. Furthermore, we expect that the conference and its publications will be a trigger for further related research and technology improvements in this important subject.

For UCAWSN 2014, we received many paper submissions after a rigorous peer-review process; we accepted articles of high quality for the UCAWSN 2014 pro-ceedings, published by Springer. All submitted papers underwent blind reviews by at least three reviewers from the Technical Program Committee, which consisted of leading researchers around the globe. Without their hard work, achieving such a high-quality proceeding would not have been possible. We take this opportunity to thank them for their great support and cooperation. We would like to sincerely thank the following invited speakers who kindly accepted our invitation, and, in this way, helped to meet the objectives of the conference: Prof. Young-Sik Jeong (Dongguk University, Korea) and Mohammad S. Obaidat (Monmouth University,

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USA). Finally, we would like to thank all of you for your participation in our conference, and we also thank all the authors, reviewers, and organizing committee members. Thank you and enjoy the conference!

July 2014 Gangman Yi

Gangneung-Wonju National University, Korea

Yuh-Shyan Chen National Taipei University, Taiwan

Xiaohong Peng Aston University, UK

Ali Abedi Maine University, US

Neil Y. Yen The University of Aizu, Japan

Jen Juan Li North Dakota State University, USA

Hongxue (Harris) Wang Athabasca University, Canada

Lijun Zhu, ISTIC, China UCAWSN 2014 Program Chairs

viii Message from the UCAWSN 2014 Program Chairs

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Organization

Steering Chairs

James J. Park, SeoulTech, Korea

Hamid R. Arabnia, The University of Georgia, USA

General Chairs

Hwa-Young Jeong, Kyung Hee University, Korea Han-Chieh Chao, National Ilan University, Taiwan Yi Pan, Georgia State University, USA

Qun Jin, Waseda University, Japan

General Vice-Chairs

Young-Sik Jeong, Dongguk University, Korea Jason C. Hung, Overseas Chinese University, Taiwan Hanmin Jung, KISTI, Korea

Yang Xiao, University of Alabama, USA

Program Chairs

Gangman Yi, Gangneung-Wonju National University, Korea Yuh-Shyan Chen, National Taipei University, Taiwan Xiaohong Peng, Aston University, UK

Ali Abedi, Maine University, US

Neil Y. Yen, the University of Aizu, Japan Jen Juan Li, North Dakota State University, USA Hongxue (Harris) Wang, Athabasca University, Canada Lijun Zhu, ISTIC, China

International Advisory

Sherali Zeadally, University of the District of Columbia, USA Naveen Chilamkurti, La Trobe University, Australia

Luis Javier Garcia Villalba, Universidad Complutense de Madrid (UCM), Spain Mohammad S. Obaidat, Monmouth University, USA

Jianhua Ma, Hosei University, Japan

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Laurence T. Yang, St. Francis Xavier University, Canada Hai Jin, HUST, China

Weijia Jia, City U. of Hong Kong, Hong Kong Albert Zomaya, University of Sydney, Australia Bin Hu, Lanzhou University, China

Doo-soon Park, SoonChunHyang University, Korea

Publicity Chair

Deok-Gyu Lee, ETRI, Korea

Hak Hyun Choi, Seoul Women’s University, Korea Weiwei Fang, Beijing Jiaotong University, China Cain Evans, Birmingham City University, UK

Chun-Cheng Lin, National Chiao Tung University, Taiwan Antonio Coronato, ICAR, Italy

Rung-Shiang Cheng, Kunshan University, Taiwan Haixia Zhang, Shandong University, China Rafael Falcon, Larus Technologies, Canada

Xu Shao, Institute for Infocomm Research, Singapore Bong-Hwa Hong, Kyunghee Cyber University, Korea

Local Arrangement Chairs

Namje Park, Jeju National University, Korea Cheonshik Kim, Sejong University, Korea Min Choi, Chungbuk National University, Korea Aziz Nasridinov, Dongguk University, Korea

x Organization

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Chapter 59 Perceived Risk of Anti-corruption

e-Learning, Email Phishing Literacy,

and Anomia

Juneman Abraham and Sharron

Abstract In order to prevent corruption in Indonesia, the use of anti-corruption e-learning needs to be optimized and to reach young generation whose life now-adays mostly inseparable from the internet connections. The aim of this research is to identify predictor variables of perceived risk of anti-corruption e-learning. When risk perception is low, attitude toward e-learning is expected to be more positive. This psychotechnological research employs predictive correlational design, with the predictors (1) email phishing literacy and (2) anomia. The participants of this research were 71 students of faculty of psychology at a private university in Jakarta, Indonesia (20 males, 51 females; Mean of age = 19.93 years old; Standard Devi-ation of age = 1.397 years old). The data were analyzed by using simple linear regression analyses. Results of this research show that both variables are able to predict perceived risk of anti-corruption e-learning, consecutively in negative and positive ways.

Keywords Psychology of e-Learning

Anti-corruption

Phishing literacy

Anomia

59.1 Introduction

Andersen et al., through their empirical research, indicated their support for a proposition stating that the internet is a powerful anti-corruption technology [1]. It is driven by the characteristic of the internet which emphasizes at disseminating transparent information, facilitating the public to identify or to detect corrupt behavior (and hence it can generate‘_{deterrent effect}’_{to do corruption), and cutting} the bureaucracy between government and public. Zinnbauer, however, stated carefully that the effectiveness of the internet toﬁght corruption is not conclusive

J. Abraham (&)Sharron

Psychology Department, Bina Nusantara University, Jakarta, Indonesia e-mail: juneman@binus.edu

©Springer Science+Business Media Dordrecht 2015

J.J. (Jong Hyuk) Park et al. (eds.),Ubiquitous Computing Application and Wireless Sensor, Lecture Notes in Electrical Engineering 331, DOI 10.1007/978-94-017-9618-7_59

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yet, and it needs further researches [2]. In addition, he also mentioned the importance of accompanying factor which is society empowerment. This factor will enhance civil engagement to guard the implementation of technology, so that technology will not only be a‘_{make up}’_{without actual substances of accountability and integrity} enforcement. Finnegan speciﬁcally highlighted the role of online collaborative learning networks–either utilized by activists or organizations which are the stake-holders of government–in enhancing governance accountability and preventing corruption [3]. One of the manifestations of online collaborative learning networks is Anti-corruption e-Learning (ACL, for instance: http://theﬁghtagainstcorruption.

unodc.org).

With the growing expectations for ACL, it is beneﬁcial to identify models of relationship between variables which explain the attitude of actual or potential ACL users. No matter how sophisticated the ACL system is, it will be‘_useless’_{(in terms} of expected competence and learning outcomes are not achieved) if the attitude of its users is less positive which has an implication to less optimal utilization. In this research, negative attitude toward ACL is operationalized as perceived risk of ACL, based on the understanding that it has a contribution to the negative attitude [4].

Some researchers have identiﬁed that attitude toward e-learning is contributed by the following variables: (1) privacy concern, (2) perception on e-learning quality (including the instructor), (3) perception on cheating level of e-learning participants in online assessment for the sake of obtaining certiﬁcate, (4) level of the need of ‘_blended’ _{learning sessions (e-learning combined with classroom learning}

facili-tated by subject matter expert), (5) level of client involvement in e-learning pro-duction and evaluations phases, (6) level of accommodation for varied learning styles, as well as (7) aspects of aesthetics, error prevention, redundancy reduction, memorability, and clearly deﬁned learning outcomes and paths [5–7]. Nevertheless, there is a crucial factor that has not been much studied in terms of attitude toward e-learning, i.e. email phishing literacy. The deﬁnition of phishing is as follows: “_{A phishing attack occurs when a user receives a fraudulent or} ‘_spoofed’ _email

representing a trusted source (e.g., bank, retailer or credit card company). This e-mail leads them to an equally fraudulent web site that maliciously collects per-sonal information, including account information, passwords and PINs”_[₈_].

Tembe et al., through his empirical research, found that the consequences of being phished experience can be personal, technological, economical, social, and psychological [9]. They identified seven experiences coming afterward, i.e. (1) Providing private information to an unauthorized person, (2) Experiencing identity theft as a result of stolen personal information, (3) Lost money or property as a result of stolen personal information, (4) Loss of use of a service, such as an email account, (5) Unwillingness to use a service in the future, (6) Reduced trust in technology, and (7) Reduced trust in people. Thefifth to the seventh consequences, in our opinion, can further predict positive or negative individual attitude toward ACL. Thus this hypothesis needs empirical testing. It is in line with the‘_stimulus generalization’_{concept of behavioristic psychology. Conceptual de}_fi_{nition of the} terminology is as follows [10]:“_{The generalization of the conditioned response to} stimuli that is similar to the initial stimulus causing the response. For example,

578 J. Abraham and Sharron

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Pavlov’_{s infamous dog may have started to salivate on hearing a sound similar to} the original sound that was used to elicit the conditioned response. Other examples include‘_{Little Albert}’_{, who was conditioned to fear rats. A few days later, the child} not only feared rats but also a rabbit, a dog, and even a Santa Claus mask. As not many stimuli in real life are exactly the same, stimulus generalization serves an adaptive purpose. As a general rule, the closer the stimulus is to the initial stimulus causing the response, the greater the likelihood ofstimulus generalization”_{(p. 493).} We assume that there is a similar characteristic between email phishing and e-learning participation invitation or offering. Both of them appear as authoritative and trustworthy parties. They also employ persuasion for their prospective users participating further to enter and to involve in the system and the material offered. In addition, Chien found that lack of computer knowledge contributes on computer anxiety and further decreasing the effectiveness of e-learning [11]. This research is different from Chien’_{s since predictor used in this research is more speci}_ﬁ_{c and} directly related to the online world, that is, email phishing literacy, not computer knowledge in general. Thus,the_ﬁrst hypothesisof this research is:“_{The lower} an individual’_{s email phishing literacy, the higher his/her risk perception of ACL} will be”_.

Furthermore, in relation to anti-corruption materials, the fundamental question arising is:“_{Why should one believe on ACL?}”_{This is a sociopsychotechnological} question which is related to field of psychology of trust. Cheshire specifically investigated factors contributing on online trust [12]. She stated that there is an urgency to differentiate trust in human and trust in the system, although it is also necessary not to get trapped in oversimplification and pedantic distinction since equalization between interpersonal trust and trust in the computer/internet system on several facets indeed has an analogical likeness. Meanwhile, if they have to be differentiated, the assumption would be as follows [12]:“_{When a human betrays a} friend’_{s trust, the friend knows who is culpable, and the consequences are often} clear for both parties. When a system‘_betrays’_{a human}’_{s trust, assigning blame can} have enormous repercussions”_{(p. 56).}

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59.2 Methods

This research employs quantitative, predictive correlational design. As shown in Fig.59.1, the independent variables of this research are email phishing literacy and anomia while the dependent variable of this research is perceived risk of anti-corruption e-learning (ACL). The statistical analyses used in testing the prediction of independent variables toward dependent variable are simple linear regression analyses.

Participants of this research were 71 students of faculty of psychology at a private university in Jakarta, the capital city of Indonesia, who were taken by using convenience sampling technique. Here are the descriptions of the participants: mean of age 19.93 years old, standard deviation of age 1.397 years old; gender: 20 males, 51 females; majority of the participants are Javanese (30 %) and Chinese (25 %). In Indonesia, Psychology is indeed a study program dominated by female students.

Measurement instrument for Risk Perception of ACL variable is adapted from Perceived Risk in Online Education Questionnaire [15]. This questionnaire is adapted by employing the ACL as the object of risk perception. The dimensions of this instrument are perceived performance risk, perceived time-demand risk, per-ceived social risk, perper-ceived psychological risk, and perper-ceived source risk. The response scale of this questionnaire ranged fromStrongly Disagree(score of 1) to Strongly Agree (score of 6). It begins by the following instruction: “_Nowadays, Indonesia is active in preventing corruption, including through anticorruption e-learning. Below is the display taken from the example of the e-learning site[the picture is taken from http://e-integrity.net/elearning/; this website was established by a collaboration of TIRI-Integrity Action Indonesia, United States Agency for International Development (USAID), the Royal Kingdom of Netherlands, and Partnership for Governance Reform.]. You are kindly requested to carefully read the home page display. To give response to statements in scales, please imagine that you are offered to attend online classes of this e-learning”_.

Sample items of perceived performance risk:“_{I doubt the instructor will be able to} make this type of class work for all of the students”_,“_{I do not believe the instructor} will be highly accessible by e-mail”_{. Sample items of perceived time-demand risk:}

Email Phishing

Fig. 59.1 Hypothetical model. Note(+) positive predictive correlation. (−) Negative predictive

correlation

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“_I’_{m not sure I}’_{ll have the time needed to successfully complete online courses}”_,“_{If I}

take an online course, I’_{ll have less free time}”_{. Sample items of perceived social risk:} “_{In general, people who earn their degrees through online programs are held in} higher esteem than are traditional students” ₍unfavorable item, reversed score). Sample items of perceived psychological risk:“_{Just thinking about taking an online} class makes me feel stressed”_{. Sample items of perceived source risk:}“_{It is dif}_ﬁ_cult to determine the credibility of some universities offering anti-corruption e-learning”_. The result of validity and reliability testing shows that the instrument containing the risk perceptions dimensions of ACL is reliable (Cronbach’_{s Alpha index of internal} consistency = 0.762) after aborting 17 items, with corrected item-total correlations ranging from 0.252 to 0.507.

Measurement instrument for Email Phishing Literacy variable is adapted from Ability to Identify Phishing Emails Questionnaire [16]. This questionnaire consists of 8 items and is preceded by the following question: “_{Which of the following} generally indicates that an email may be phishing or fraudulent?”_{The example of} the items is as follows: “_{Asking you to enter information about your account}”_, “_{Conveying sense of urgency and surprise}”_,“_{Containing attachment, notifying you} that it might contain viruses that could harm your computer”_,“_{Directing you to the} web site with URL starting with https”_{. The options to response this questionnaire} are“_Phishing”₍“_Penipuan”_{in Indonesian) and}“_Legitimate”₍“_{Bukan Penipuan}”_in Indonesian). The answer of the participants will be valued by score 1 (True) or 0 (False) based on the answer keys from Al-Hamar et al. [16]. The maximum score of the participants for this sale is 8, and the minimum is 0. This questionnaire has been tested to 2,000 respondents consisting of 1,000 Qatari citizens and 1,000 United Kingdom citizens, by a margin of error of 3.1 % with a confidence level of 95 %. Measurement instrument for anomia variable is adapted from Multidimensional Scale of Feeling of Anomie [17]. This questionnaire consists of three dimensions, i.e. (1) meaninglessness and distrust, (2) powerlessness, and (3) fetishism of money. Sample items of meaningless and distrust:“_{Everything is relative, and there just are} not any definite rules to live by”_; “_{There is little use writing to public of}_fi_cials because often they are not genuinely interested in the problems of the average man”_{. Sample items of powerlessness:}“_{The world is changing so fast that it is hard} for me to understand what is going on”_;“_{I lead a trapped or frustrated life}”_{. Sample} items of fetishism of money:“_{A person is justi}_fi_{ed in doing almost anything if the} reward is high enough”_{. The response scale of this questionnaire ranged from} Strongly Disagree(score of 1) toStrongly Agree(score of 6). The result of validity and reliability instrument testing shows that the instrument is reliable (Cronbach’_s Alpha = 0.836) after aborting 6 items, with corrected item-total correlations ranging from 0.272 to 0.717. It means the instrument is reliable (α> 0.6) and valid

(cor-rected rit> 0.250).

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59.3 Results and Discussion

Data analysis with SPSS 21 for Windows gives results as shown in Table 63.1. Email phishing literacy is able to predict risk perception of ACL in a negative way while anomia is able to predict it in a positive way. They show that both hypotheses are supported by the data. This research brings out the new insight related to individual perspective toward e-learning, especially anti-corruption e-learning.

Perceived risk of ACL can be predicted by email phishing literacy. This is understandable since there is parallelism between them. For instance, phishing email can waste an individual’_{s time to restore the infected computer condition to} its condition before being exposed to phishing. ACL can also be perceived as time-consuming, lowering efﬁcacy in utilizing it. For example, the users will feel the loss of leisure time since they should complete a series of online courses which may also be complicated with potential conflicts [18]. Perceived performance risk also can be felt in email phishing and e-learning system. Email phishing usually has a good “_{face validity}” _{as it involves complex social engineering. Actually, however,}

behind surface appearance, there is a trap or a trick which harm the users either economically or psychosocially. Generally, e-learning system does not trap, although it does have technical and security risks [19] similar to that of phishing (integrity and conﬁdentiality attack, unauthorized use, etc.). Nevertheless, the potential discrepancies between credible display (e.g. with the inclusion of nationally or internationally-wide instructors’_{names and reputations, the inclusion} of educational institution and authoritative government or NGO logos) and the actual quality of its contents and instructors can make users feel deceived, have a sense of risk for“_consuming”_{or being involved in the e-learning system and give} negative attitude to the e-learning system. All of this explanation can be bridged by the stimulus generalization concept in psychological science as described in the Introduction.

This research alsoﬁnds that anomia can predict perceived risk of ACL. Anomie effect on the learning process has actually been studied by Hibbert et al. [20]. They stated:“_Anomie.._{. It is also possible for}_{learning to be limited} _{because of} discon-nection, a lack of a sense of collective purpose, or even uncertainty about the nature or reality of the collective and a resultant lack of effective social norms”_{(p. 462).}

Table 63.1 Simple linear regression analyses predicting perceived risk of anti-corruption e-learning (n= 71)

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One of the characteristics of anomia is feeling of normless, meaningless, isolated, helpless, powerless, and materialistic. Such individuals tend to avoid their ethical obligation because of disabled moral thinking and moral disengagement as the effect of anomic situation, and to behave less positive toward social changes. In fact, anti-corruption education requires simultaneously sustainable effort and collective work which are supported by the state as well as stakeholders having creativity and obvious stance against corruption [21,22]. Based on that argument, it is clear that anomie becomes a barrier for e-learning participants to coordinate in collective learning and action of which, in this research, is shown by high perceived risk of ACL when anomia is high.

59.4 Conclusion

This research concludes that email phishing literacy is able to predict perceived risk of ACL in a negative way, and anomia is able to predict it in a positive way.

In the context of enhancing effective participation of the young generation in anti-corruption e-learning environment, the result of this research implicate that personal and socio-contextual factors are necessary to be seriously managed. Per-sonal factor in this research is email phishing literacy while contextual factor is anomia. Anti-corruption e-learning providers and organizers need to do networking with other parties to overcome the barrier either in a personal level or socio-contextual level in order to make the users’_{involvement in the e-learning system} optimal.

This research has added the body of knowledge in psychotechnologyﬁeld by successfully extending the Yamakami’_{s propositions that:}“_{Human beings are social} beings. Therefore, the hook, retention… _{phases have direct links to social} con-texts”_[₂₃_{] (p. 114).}

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Ubiquitous Computing Application and Wireless Sensor

Lecture Notes in Electrical Engineering 331

James J. (Jong Hyuk) Park

Yi Pan

Han-Chieh Chao

Gangman Yi

Editors

Ubiquitous

Computing

Lecture Notes in Electrical Engineering

Volume 331

James J. (Jong Hyuk) Park

Yi Pan

Han-Chieh Chao

Gangman Yi

Editors

Ubiquitous Computing

Application and Wireless

Sensor

UCAWSN-14

Message from the UCAWSN 2014 General

Chairs

Message from the UCAWSN 2014 Program

Chairs

Organization

Contents

Chapter 59

Perceived Risk of Anti-corruption

e-Learning, Email Phishing Literacy,

and Anomia

59.1 Introduction

59.2 Methods

59.3 Results and Discussion

59.4 Conclusion

References