Journal articles on the topic 'User’s journey modeling'

A direct way of reducing the number of cars on the road is to dissuade individuals from exclusively using their car and instead integrate public transport into their daily routine. Planning multi-modal journeys is a complex task for which individuals often rely on decision support tools. However, offering individuals different journey options represents a significant algorithmic challenge. The failure to provide users with a set of journey options that differ considerably from one another in terms of the modes of transport employed is currently preventing the widespread uptake of multi-modal journey planning among the general public. In this paper, we introduce a dynamic programming algorithm that remedies this situation by modeling different transport networks as a graph that is then pruned by various graph-reduction pre-processing techniques. This approach enables us to offer a diverse set of efficient multi-modal solutions to users almost instantaneously. A computational study on three datasets corresponding to various real-world mobility networks with up to 30,000 vertices and 596,000 arcs demonstrates the effectiveness of the proposed algorithm.

Online resources of engineering design information are a critical resource for practicing engineers. These online resources often contain references and content associated with technical memos, journal articles and “white papers” of prior engineering projects. However, filtering this stream of information to find the right information appropriate to an engineering issue and the engineer is a time-consuming task. The focus of this research lies in ascertaining tacit knowledge to model the information needs of the users of an engineering information system. It is proposed that the combination of reading time and the semantics of documents accessed by users reflect their tacit knowledge. By combining the computational text analysis tool of Latent Semantic Analysis with analyses of on-line user transaction logs, we introduce the technique of Latent Interest Analysis (LIA) to model information needs based on tacit knowledge. Information needs are modeled by a vector equation consisting of a linear combination of the user’s queries and prior documents downloaded, scaled by the reading time of each document to measure the degree of relevance. A validation study of the LIA model revealed a higher correlation between predicted and actual information needs for our model in comparison to models lacking scaling by reading time and a representation of the semantics of prior accessed documents. The technique was incorporated into a digital library to recommend engineering education materials to users.

The CoVid-19 pandemic has demanded society to social distance, which significantly affected not only people's routine but also and their mental health. The way each person is facing this period of confinement is shaped according to their principles, culture, health, and financial stability, thus leading individuals to react emotionally in different ways. Through Design, it is possible to map these experiences and represent them through User Journeys, allowing clear representations of how the experience took place when facing the fear of contagion, the sudden change of routine, and isolation. This study focuses on discussing the effectiveness of unifying different experiences in a single representation, mainly to outline emotional aspects. Trying to balance all emotional variations in a single User Journey prevents the researcher from seeing important details of the users' experience. In this study, the need to use individual User Journeys was evidenced when it is intended to analyse the emotional aspects of users when dealing with products or services, as individuality can shed light on aspects not observable in a consolidated analysis.

Abstrak: Open Journal Systems (OJS) adalah aplikasi perangkat lunak open source untuk mengelola dan menerbitkan jurnal ilmiah, untuk mendukung fungsinya tersebut Open Journal Systems (OJS) secara umum memiliki fitur yang dalam perkembangan setiap versinya mengalami perbaikan dan penyesuaian dengan kebutuhan. Proses penerbitan jurnal sangat berdampak pada proses akreditasi jurnal, oleh karena itu perlu dipahami proses bisnis alur pengiriman artikel dari author menggunakan Open Journal Systems (OJS) hingga artikel di publish. Dalam sistem diperlukan pemodelan perencanaan, desain dan penggunaan interface antara pengguna dan komputer, interaksi ini dikenal sebagai interaksi antara manusia dengan komputer (Human Computer Interaction). Framework digunakan untuk memahami interaksi sistem komputer memberikan fasilitas bahasa antara bahasa user dan bahasa sistem. Pengguna (user) dan sistem komputer (system) dapat saling berinteraksi menggunakan beberapa cara interaksi yaitu style kombinasi form fill-in dan direct manipulation. Open Journal Systems (OJS) 3.x. memiliki tampilan yang lebih ringkas, mudah dan flexible karena dibangun dengan prinsip Interaction Framework melibatkan user, input, system, output. Kata kunci: framework, HCI, jurnal, OJS, PKP Abstract: Open Journal Systems (OJS) is an open source software application to manage and publish scientific journals, to support this function Open Journal Systems (OJS) generally has features that in each version's development experience improvements and adjustments to the needs. The process of publishing a journal greatly affects the accreditation process of the journal, therefore it is necessary to understand the business process of sending articles from the author using Open Journal Systems (OJS) until the article is published. In the system required modeling planning, design and use of interfaces between users and computers, this interaction is known as the interaction between humans and computers (Human Computer Interaction). Framework is used to understand the interaction of computer systems to provide language facilities between the user's language and system language. Users (users) and computer systems (systems) can interact with each other using several modes of interaction, namely the combination style form fill-in and direct manipulation. Open Journal Systems (OJS) 3.x. has a more concise, easy and flexible appearance because it is built on the principle of Interaction Framework involving users, input, system, output. Keywords: framework, HCI, journals, OJS, PKP

CASPUR allows many academic Italian institutions located in the Centre-South of Italy to access more than 7 million articles through a digital library platform. The behaviour of its users were analyzed by considering their “traces”, which are stored in the web server log file. Using several web mining and data mining techniques the author discovered a gradual and dynamic change in the way articles are accessed. In particular there is evidence of a journal browsing increase in comparison to the searching mode. Such phenomenon were interpreted using the idea that browsing better meets the needs of users when they want to keep abreast about the latest advances in their scientific field, in comparison to a more generic searching inside the digital library.

This study provides a deeper understanding of the inner-mechanism which users engage in their acceptance of social media (in this case, Facebook event pages) via extending the TAM model by adding three factors: emotion, perceived enjoyment and perceived relevance. This work applied structural equation modelling (SEM) to test 13 hypotheses, with collected data from 323 Facebook users who have been members of the event page “Traveling Talent 2017”. Empirical results showed that the model fits well with the sample. The results of empirical tests using a structural equation model confirm all the research hypotheses. Implications and insights are given for event practitioners and are discussed accordingly.

The disruptive offline mobilization of participants in online conspiracy theory (CT) discussions has highlighted the importance of understanding how online users may form radicalized conspiracy beliefs. While prior work researched the factors leading up to joining online CT discussions and provided theories of how conspiracy beliefs form, we have little understanding of how conspiracy radicalization evolves after users join CT discussion communities. In this paper, we provide the empirical modeling of various radicalization phases in online CT discussion participants. To unpack how conspiracy engagement is related to radicalization, we first characterize the users' journey through CT discussions via conspiracy engagement pathways. Specifically, by studying 36K Reddit users through their 169M contributions, we uncover four distinct pathways of conspiracy engagement: steady high, increasing, decreasing, and steady low. We further model three successive stages of radicalization guided by prior theoretical works. Specific sub-populations of users, namely those on steady high and increasing conspiracy engagement pathways, progress successively through various radicalization stages. In contrast, users on the decreasing engagement pathway show distinct behavior: they limit their CT discussions to specialized topics, participate in diverse discussion groups, and show reduced conformity with conspiracy subreddits. By examining users who disengage from online CT discussions, this paper provides promising insights about conspiracy recovery process.

Because new learning technologies are enabling students to build and explore probability models, we believe that there is a need to determine the big enduring ideas that underpin probabilistic thinking and modeling. By uncovering the elements of the thinking modes of expert users of probability models we aim to provide a base for the setting of new and more relevant goals for probability education in the 21st century. We interviewed seven practitioners, whose professional lives are centered on probability modeling over a diverse range of fields including the development of probability theory. A thematic analysis approach produced four frameworks: (1) probability modeling approaches; (2) probabilistic thinking approaches to a problem; (3) a probability modeling cycle; and (4) core building blocks for probabilistic thinking and modeling. The main finding was that seeing structure and applying structure were important aspects of probability modeling. The implications of our findings for probability education are discussed. First published November 2016 at Statistics Education Research Journal Archives

Abstrak - Penelitian ini bertujuan untuk mengembangkan Jurnal Pariwisata Darussalam berbasis jurnal elektronik di Politeknik Darussalam Palembang dengan menggunakan Open Journal System (OJS) yang dapat digunakan untuk publikasi artikel penelitian dosen-dosen di Politeknik Darussalam dan para peneliti di Bidang Pariwisata. Metode pengumpulan data menggunakan metode wawancara dengan pihak pengelola Jurnal Pariwisata Darussalam. Selain menggunakan metode wawancara, pengumpulan data juga dilakukan dengan melakukan observasi dengan cara mengamati OJS-OJS sejenis serta pengumpulan data dengan menggunakan studi pustaka. Metode pengembangan sistem yang digunakan untuk mengembangkan Jurnal Pariwisata Darussalam adalah metode rekayasa web yang merupakan gabungan dari aktifitas rekayasa perangkat lunak dan web publishing yang terdiri dari lima tahapan, yaitu Customer communication , planning, modeling, Construction, delivery dan feedback. Proses Construction meliputi pengaturan pada journal, website, workflow, distribution, users dan roles. Setelah melalui uji coba dari internal pengembang dan pihak Politeknik Darussalam yang terdiri dari dosen dan pihak pengelola jurnal, maka Jurnal Pariwisata resmi digunakan dan dapat di akses di https://ojs.politeknikdarussalam.ac.id/index.php/jpd yang dapat digunakan untuk publikasi artikel oleh dosen Politeknik Darussalam dan para peneliti pada bidang pariwisata

In this article, we introduce dynamac, a suite of commands designed to assist users in modeling and visualizing the effects of autoregressive distributed lag models and in testing for cointegration. We discuss the bounds cointegration test proposed by Pesaran, Shin, and Smith (2001, Journal of Applied Econometrics 16: 289–326), which we have adapted into a command. Because the resulting models can be dynamically complex, we follow the advice of Philips (2018, American Journal of Political Science 62: 230–244) by introducing a flexible command designed to dynamically simulate and plot a variety of types of autoregressive distributed lag models, including error-correction models.

This research investigates the way consumer repurchase intention in social commerce is shaped by electronic word-of-mouth at global scale. Building our argument by drawing on data collected from Deloitte, eMarketer, MarketingCharts, Marketing Insider Group, McKinsey, Mediakix, Nielsen, Smart Insights, and Statista, we performed analyses and made estimates regarding trusted information sources according to consumers, products/services that Internet users have personally recommended to others, channels through which Internet users would like to receive recommendations from others, leading social media marketing tactics among marketers/media agency professionals, sources that have influenced a recent purchase decision, what are retail digital buyers most concerned about when choosing a social e-commerce platform, important information in online reviews that influence purchase decisions according to Internet users, % of respondents who made a purchase influenced by electronic word-of-mouth channels, leading social media trends that will have the biggest effect on their advertising and marketing strategies, Internet users who agree that online reviews have an important influence on purchase decisions (by age), effective content formats for influencer marketing, and factors that influence whether a product is considered at each stage of the consumer decision journey. The data for this research were collected through an online survey questionnaire and were analyzed via structural equation modeling on a sample of 4,200 respondents.

Autonomous vehicles (AVs) can generate major changes in urban systems due to their ability to use road infrastructures more efficiently and shorten trip times. However, there is great uncertainty about these effects and about whether the use of these vehicles will continue to be private, in continuity with the current paradigm, or whether they will become shared (carsharing/ridesharing). In order to try to shed light on these matters, the use of a scenario-based methodology and the evaluation of the scenarios using a land use–transport interaction model (LUTI model TRANSPACE) is proposed. This model allows simulating the impacts that changes in the transport system can generate on the location of households and companies oriented to local demand and accessibility conditions. The obtained results allow us to state that, if AVs would generate a significant increase in the capacity of urban and interurban road infrastructures, the impacts on mobility and on the location of activities could be positive, with a decrease in the distances traveled, trip times, and no evidence of significant urban sprawl processes. However, if these increases in capacity are accompanied by a large augment in the demand for shared journeys by new users (young, elderly) or empty journeys, the positive effects could disappear. Thus, this scenario would imply an increase in trip times, reduced accessibilities, and longer average distances traveled, all of which could cause the unwanted effect of expelling activities from the consolidated urban center.

Abstract. Application of digital terrain analysis (DTA), which is typically a modeling process involving workflow building, relies heavily on DTA domain knowledge of the match between the algorithm (and its parameter settings) and the application context (including the target task, the terrain in the study area, the DEM resolution, etc.), which is referred to as application-context knowledge. However, existing DTA-assisted tools often cannot use application-context knowledge because this type of DTA knowledge has not been formalized to be available for inference in these tools. This situation makes the DTA workflow-building process difficult for users, especially non-expert users. This paper proposes a case-based formalization for DTA application-context knowledge and a corresponding case-based reasoning method. A case in this context consists of a series of indices that formalize the DTA application-context knowledge and the corresponding similarity calculation methods for case-based reasoning. A preliminary experiment to determine the catchment area threshold for extracting drainage networks has been conducted to evaluate the performance of the proposed method. In the experiment, 124 cases of drainage network extraction (50 for evaluation and 74 for reasoning) were prepared from peer-reviewed journal articles. Preliminary evaluation shows that the proposed case-based method is a suitable way to use DTA application-context knowledge to achieve a marked reduction in the modeling burden for users.

Background Maintaining a healthy weight can reduce the risk of developing many diseases, including type 2 diabetes, hypertension, and certain types of cancers. Online social media platforms are popular among people seeking social support regarding weight loss and sharing their weight loss experiences, which provides opportunities for learning about weight loss behaviors. Objective This study aimed to investigate the extent to which the content posted by users in the r/loseit subreddit, an online community for discussing weight loss, and online interactions were associated with their weight loss in terms of the number of replies and votes that these users received. Methods All posts that were published before January 2018 in r/loseit were collected. We focused on users who revealed their start weight, current weight, and goal weight and were active in this online community for at least 30 days. A topic modeling technique and a hierarchical clustering algorithm were used to obtain both global topics and local word semantic clusters. Finally, we used a regression model to learn the association between weight loss and topics, word semantic clusters, and online interactions. Results Our data comprised 477,904 posts that were published by 7660 users within a span of 7 years. We identified 25 topics, including food and drinks, calories, exercises, family members and friends, and communication. Our results showed that the start weight (β=.823; P<.001), active days (β=.017; P=.009), and median number of votes (β=.263; P=.02), mentions of exercises (β=.145; P<.001), and nutrition (β=.120; P<.001) were associated with higher weight loss. Users who lost more weight might be motivated by the negative emotions (β=−.098; P<.001) that they experienced before starting the journey of weight loss. In contrast, users who mentioned vacations (β=−.108; P=.005) and payments (β=−.112; P=.001) tended to experience relatively less weight loss. Mentions of family members (β=−.031; P=.03) and employment status (β=−.041; P=.03) were associated with less weight loss as well. Conclusions Our study showed that both online interactions and offline activities were associated with weight loss, suggesting that future interventions based on existing online platforms should focus on both aspects. Our findings suggest that online personal health data can be used to learn about health-related behaviors effectively.

In recent years, it has become conventional wisdom that artificial intelligence (AI) will be a game-changer in business. However, it remains challenging to adopt enterprise AI, i.e., enterprise software that incorporates AI techniques, into firms’ core and overall data strategies. In this study, we investigate the path to AI maturity and enterprise-wide adoption from a service provider perspective. Wecollect secondary data from 66white papers published by leading AI service providers in the past five years anduse topic modeling to understand the current themes in AI implementation. Thereafter, we analyze pertinent challengesthrough the lens of the classi-cal technology-organization-environment (TOE) framework. Our results demonstrate that, even though AI service providers have successfully addressed—at least in part—major questions faced by clients, there still exists a gap between the features demanded by end-users and the skills possessed and focused on by the AI service providers. For example, a vendor thinks his user does not have a clear vision on AI adoption, whereas the user finds it difficult to align the provided AI solution with the firm’s vision. We then argue that a holistic review of all TOE contexts is critical for closing the gap on the journey to AI maturity.

Purpose The purpose of this paper is to understand the similarities and differences between the Twitter users who tweeted on journal articles in psychology and political science disciplines. Design/methodology/approach The data were collected from Web of Science, Altmetric.com, and Twitter. A total of 91,826 tweets with 22,541 distinct Twitter user profiles for psychology discipline and 29,958 tweets with 10,478 distinct Twitter user profiles for political science discipline were used for analysis. The demographics analysis includes gender, geographic location, individual or organization user, academic or non-academic background, and psychology/political science domain knowledge background. A machine learning approach using support vector machine (SVM) was used for user classification based on the Twitter user profile information. Latent Dirichlet allocation (LDA) topic modeling was used to discover the topics that the users discussed from the tweets. Findings Results showed that the demographics of Twitter users who tweeted on psychology and political science are significantly different. Tweets on journal articles in psychology reflected more the impact of scientific research finding on the general public and attracted more attention from the general public than the ones in political science. Disciplinary difference in term of user demographics exists, and thus it is important to take the discipline into consideration for future altmetrics studies. Originality/value From this study, researchers or research organizations may have a better idea on who their audiences are, and hence more effective strategies can be taken by researchers or organizations to reach a wider audience and enhance their influence.

Research background: This paper analyzes the outcomes of an exploratory review of the current research on the relationship between the global adoption of mobile payment technologies, social interactive consumer-oriented applications, and online purchasers’ decision-making process. Purpose of the article: The data used for this study was obtained and replicated from previous research conducted by Econsultancy and Statista. We performed analyses and made estimates regarding mobile e-commerce sales worldwide, frequency of mobile retail app usage according to U.S. smartphone shoppers, how well organizations understand the customer journey for certain audiences, share of Internet users who are likely to use mobile payments on their smartphone in the next year (by country), and time spent per mobile app category. Methods: Data collected from 6,200 respondents are tested against the research model by using structural equation modeling. Findings & Value added: The advent of smartphones redesigns the routine of shopping, thus altering the agency of users. Retailers have instant access to data on the geographical position of users that can be employed in addition to other information to regulate the decision-making process. Perceived effortlessness in utilization of the smartphone is somewhat similar for various mobile shopping application settings. The degree to which mobile purchasing applications are time critical and location sensitive may differ substantially. Mobile retailers can make public the personal, collaborative, and instantaneous buying experience that mobile shopping can offer to customers.

Increasing urbanisation has inevitably led to the continuous construction of buildings. Urban expansion and densification processes reshape cities and, in particular, the third dimension (3D), thus calling for a technical shift from 2D to 3D for property valuation. However, most property valuation studies employ 2D geoinformation in hedonic price models, while the benefits of 3D modelling potentially brought for property valuation and the general context of digital twin (DT) creation are not sufficiently explored. Therefore, this review aims to identify appropriate urban 3D modelling method(s) for city DT, which can be used for 3D property valuation (3DPV) in the future (both short-term and long-term). We focused on 3D modelling studies investigating buildings and urban elements directly linked with residential properties. In total, 180 peer-reviewed journal papers were selected between 2016 and 2020 with a narrative review approach. Analytical criteria for 3D modelling methods were explicitly defined and covered four aspects: metadata, technical characteristics, users’ requirements, and ethical considerations. From this, we derived short-term and long-term prospects for 3DPV. The results provide references for integrating 3D modelling and DT in property valuation and call for interdisciplinary collaboration including researchers and stakeholders in the real estate sector, such as real estate companies, house buyers and local governments.

Recent studies have highlighted the existence of a gap between actual and perceived safety and have shown that feelings of insecurity can affect individuals’ travel behavior before and during the journey. In this paper, a methodology is proposed for assessing determinants of travelers’ perception of safety and security in railway stations. The methodological approach includes focus groups, stated preference (SP) surveys, and the estimation of behavioral models with fixed parameters (Binomial Logit) and random parameters (Mixed Logit). The estimation results for a medium-sized railway station (Frosinone, Italy) confirmed that safety and security measures are not equally perceived by individuals and the use of random-parameters models leads to more robust estimates. The proposed modeling approach allows the identification of the interventions that should be prioritized to increase travelers’ perceived levels of safety, highlighting those factors, such as, for the considered case study, the presence of security personnel and the level of decorum and maintenance, which are perceived by users as more important than others (e.g., surveillance cameras).

This paper proposes the use of threshold heteroskedastic models which integrate threshold nonlinearity [Tong, H (1978). On a Threshold Model, pp. 575–586. Netherlands: Sijthoff & Noordhoff; Tong, H and KS Lim (1980). Threshold autoregression, limit cycles and cyclical data. Journal of the Royal Statistical Society. Series B (Methodological), 3, 245–292.] and GARCH-type conditional variance for modeling Bitcoin returns to provide an understanding on the huge volatility that Bitcoin has been famous for. Specifically, the model attempts to identify different regimes throughout the history of Bitcoin using the different available Bitcoin network characteristics, such as cost per transaction, number of transactions per block, number of active addresses and number of transactions. Estimation and diagnostic checks are performed using Markov chain Monte Carlo methods. In the empirical analysis, we show that our model is able to identify periods of crashes as one of these regimes, which is also a period of declining returns and declining number of active users. We also find that the number of users and the number of transactions determine the magnitude or persistence of a crash period.

Dengan melihat kecanggihan teknologi terkini, sehingga informasi tidak lagi dalam bentuk konvensional namun sekarang sudah diterapkan elektronik yang disajikan. Di dalam pengelolaan karya ilmiah di STISIP YUPPENTEK ini masih manual sehingga memiliki permasalahan-permaslahan seperti penerbitan jurnal yang begitu susah dan data terpisah-pisah karena membutuhkan waktu cukup lama dan biaya cukup besar. Arikel ilmiah pada STISIP YUPPENTEK belum memenuhi syarat ketentuan dikti perihal akreditasi jurnal yang mengharuskan jurnal dikelola dengan cara online dalam pengelolaan yang dilakukan lebih dengan mudah dan cepat. Setelah peneliti menganalisa permasalahan dengan menggunakan suatu metode pengumpulan data berupa observasi, wawancara dan studi pustaka serta menggunakan UML (Unified Modeling Language). Untuk mengatasi permasalahan tersebut peneliti memberikan usulan sistem yang memudakan pengguna sehingga proses pengelolaan jurnal dapat lebih memudahkan pengguna. Kata Kunci: Jurnal Ilmiah, E-Journal, Open Journal System, Indeksasi By looking at the sophistication of the latest technology, so the information is no longer in the conventional form but now it is applied electronics are presented. In the management of scientific work in STISIP YUPPENTEK is still manual so it has problems such as publishing journals that are so difficult and data separated because it takes quite a long time and cost is quite large. The scientific article on STISIP YUPPENTEK has not fulfilled the requirement of dictation about journaling accreditation which requires the journal to be managed by online in the management which done more easily and quickly. After the researchers analyze the problem by using a method of collecting data in the form of observation, interview and literature study and using Flowchart. To overcome these problems the researchers provide a system proposal that allows users so that the process of managing the journal can further facilitate the user. Keywords: Scientific Journal, E-Journal, Open Journal System, Indexation

Today, Online Social Networks becomes the first choice for businesses to broadcast their campaigns for branding, publicity, strategies, advertising, marketing, social influence and so many other areas. Social Network is a platform for communicating with social actors and Social Media is used by companies for broadcasting information. Online Social Network used by businesses for number of purposes but the primary concern is build new social connections that helps to target most audiences for successful campaign purposes. In OSNs sites the social objects are represented by nodes and the term edge used for connection between nodes under the graph theory. Today Social Network sites have becomes most exploded as compared to traditional sites because of impact of so many influence models over traditional models.Some of popular websites of OSN such as MySpace, Facebook, Flickr, YouTube, Google Video, Orkut, LinkedIn, Live Journal and BlogSpot have great impact on customer when targeting the sales marketing funnel for businesses. Adjacent users sometimes called engaged users tend to have more trust level as compared to random pairs users on the social media sites. Already have so much research that helps to calculate the trust factor using influence modeling. So influence models play a vital role to predict the behavior of the customer that helps to fulfill the goal of the business. The key contribution of this work is study of online social networking models.

Purpose This study aims to address the following research questions: Do the two types of service firms (individual or aggregator) have similar competitiveness on online search ads? How should the two types of service firms select optimal branded keywords to improve search performance? In addition, how do consumers’ search queries influence the service search performance of the two types of service firms? Design/methodology/approach In this study, the authors conduct an empirical analysis by building a two-stage choice modeling on the process of search engine ranking and consumer click-through decisions. The authors estimate the parameter coefficients and test the hypotheses using maximum likelihood estimation in the logistic regression model. Findings The empirical findings suggest that consumer response rates are highly dependent upon three aspects (service types, branded keyword strategy and consumer search query). First, the authors found that service aggregators receive greater consumer responses than individual service providers. Second, depending upon the various branded keyword strategies (e.g. generic vs branded, “within-type” vs “cross-type”) implemented by service aggregators or individual firms, the expected consumer responses could be quite different. Finally, customer’s search query, being either generic or branded, also has direct effect and interactive effect with service type on how consumers would response to the sponsored ads in the service search process. Research limitations/implications The limitation of the research is twofold. First, conversion rate is not considered in the model estimation due to the nature of the data set. Second, the discussion about the keywords selection strategies is focusing on the hospitality industry. Future research shall further validate the generalizability into other industries. Practical implications First, given this competitive advantage, service aggregators should take an aggressive approach to adopting paid search strategy in acquiring new users and enhance its brand salience in the service ecosystem. Second, when considering other competitor’s brand names to include, if a firm is a service provider (e.g. hotel), a strategy that can help it receive higher consumer response would be to use “within-type” rather than “cross-type” branded keyword strategy. If a firm is a service aggregator, a better branded keyword strategy would be to use “across-type” instead of “within-type” approach. In addition, given that consumer’s brand awareness can influence the effectiveness of branded keyword strategy, online service search should target consumers in earlier stages of a decision journey. Social implications The authors believe their theoretical framework can provide actionable solutions to service firms to ease customer’s search process, increase customer’s stickiness using search engines and add value to the customer relationships with all services entities within the digital ecosystem. Originality/value This study is the first to expand online search marketing into granule examinations (main and interactive effects of three key factors) in the service search domain. First, the authors differentiate service firms into two categories – online travel aggregators and individual hotels in the model. Second, the authors introduce two sets of new classifications of branded keywords for online service search research (i.e. own versus other brand and “cross-type” versus “within-type” branded keywords). Third, this study integrates service consumers’ search word specificity into the conceptual framework which is often missing in previous online search research.

The work focused on the examining the use of virtual reality (VR) technologies in the reduction of depression in Europe. More than 70 issues of the journals “Cyberpsychology, Behavior, and Social Networking”, “European Psychologist” were analyzed. We used the bibliometric analysis, the "keyword method" to analyze the text, which is understood as a search for typical terms, content analysis of the content of articles that used VR and depression. In the journal "European Psychologist" the term VR has not been mentioned for the last 2 years, which indicates the secondary importance of this issue for general psychology. In cyberpsychology, on the contrary, since 2019 in Europe, the interest of researchers in the use of VR technologies in clinical psychology has increased. By the content of the journal articles. "Cyberpsychology, Behavior, and Social Networking" VR technologies are used primarily for the correction of anxiety disorders, and secondly, for the correction of depression. These technologies are used in various ways. The first option is to create VR programs with a direct impact on depression reduction. Here, VR is used as a symptom awareness tool, to create an avatar environment for client dialogue in a non- judgmental environment. Research has shown that such VR programs are rated by users as a useful tool for informing and emotionally responding to depressive states. The second option is an indirect effect on reducing the level of depression through the reduction of fears, phobias; increased activation, tone, euphoria in mental states; the development of a positive mood, cognitive motivation; an increase in indicators of field independence (cognitive style). A study based on the methods of psychosemantics is presented, which has demonstrated the effect of a specially created VR program with an avatar on changing the unconscious attitudes of the personality, reducing phobia of darkness. The effectiveness of using of VR technologies in reducing depression is determined by modeling of mental experiences and actions in VR, creating a virtual ontology, the influence of VR on conscious and unconscious attitudes, the possibility of responding to unconscious experiences through the user's identification with an avatar.

MapBio is a project initiated by the Chinese Academy of Sciences, which aims at integrating species distribution data from different sources and mapping the biodiversity of China to support biodiversity research and biodiversity conservation decisions. Species distribution data may be found in journal articles, books and different databases in various formats, and most species distributions are described in free text. MapBio is trying to build up a workflow for collecting this free text, parsing it into standardized data and projecting distributions onto a map for each species in China. A map module of MapBio is designed and implemented based on Web GIS to visualize species distributions on a map at different levels, e.g., occurrence points, county, province, distribution range, protected area, waterbody, biogeographic realm. Since the completeness of distribution data is very important for assessing biodiversity, we developed a tool in MapBio for analysis of the gaps in distribution data. Based on the species distribution data, especially the occurrence data, MapBio provides an integrated modeling tool for helping users to build species niche models. MapBio is an open access project. Users can get data and services from it easily for biodiversity research and conservation, and also can contribute their own biodiversity data to MapBio.

Snapchat, and Instagram are two social networks which recently gain their users after adopting such a feature called "Story" which allows a certain post to be disappeared after a certain time. This research takes up this technology trends analyzing the factors that probably affect the behavioral intention to use Snapchat and Instagram stories among generation Z. Factors are analyzed using Structural Equation Modeling, with basis model and variables from Technology Acceptance Model. Data collection was targeted to finished within 1 week using online questionnaire with respondent from Jakarta and Tangerang for 100 respondent that are using both Snapchat stories and Instagram Stories. There are two tools researcher usually use to analyze Structural Equation Modeling: SPSS AMOS and LISREL. In this research, researchers choose AMOS. From six hypothesis proposed for Snapchat analysis, four hypothesis is accepted, while the other two are rejected. Meanwhile, on Instagram Stories analysis, five hypothesis is accepted and one hypothesis is rejected. This study finds out the Social Presence is an exogenous variable which has a major role in affecting other variables. While Perceived Enjoyment influenced the behavioral intention to use Snapchat and Instagram Stories the most. Index Terms—Structural Equation Modeling, Technology Acceptance Model, influence, generation Z, Snapchat, Instagram REFERENCES [1] L. Chin and Z. Ahmad, "Perceived Enjoyment and Malaysian Consumers’ Intention to Use a Single Platform EPayment", SHS Web of Conferences, vol. 18, 2015. [2] M. Ariff, T. Shan, N. Zakuan, N. Ishak and M. Wahi, "Examining Users' E-Satisfaction in the Usage of Social Networking Sites; Contribution from Utilitarian and Hedonic Information Systems", IOP Conference Series: Materials Science and Engineering, vol. 58, 2014. [3] K. Hassanein and M. Head, "Manipulating perceived social presence through the web interface and its impact on attitude towards online shopping", International Journal of HumanComputer Studies, vol. 65, no. 8, pp. 689-708, 2007. [4] P. Surendran, "Technology Acceptance Model: A Survey of Literature", 2012. [5] F. Davis, "Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology", MIS Quarterly, vol. 13, no. 3, p. 319, 1989

Business developments that occur today cannot be separated from the role of technology and information systems. The system that will be discussed in this journal is a Web-based Restaurant System that uses a QR code. This system will handle at least 5 types of users, namely admin, waiter, chef, cleaning service, and customers where the five kind of users have different access rights. Restaurant information systems using this QR Code can speed up performance in ordering menus, serving ordered dishes, paying bills to customers and cleaning tables after use. The use of the QR code itself is very suitable in the restaurant business and marketing practices because of its advantages, namely being mobile fried and easy to get information. This will improve the quality of the restaurant in terms of service and time. This Web-Based Restaurant Menu Ordering Application is designed using web programming languages, namely PHP. For the database, it will use MySQL and the system development method will use the Agile Kanban method which can help an organization produce software that has been tested and is ready to use. The results of the system design will be in the form of a comparison table for the old and new systems depicted by the PIECES table, then UML for system modeling, and website interface. The system created will help in reducing the amount of paper used for order receipts. In addition, users can also order menus during the COVID-19 pandemic with restaurants that use this system.

The park and ride (P&R) parking type is usually located near peripheral public transport stops. These parking places are dedicated to people who, after leaving their vehicle in the parking, continue their journey to the city center using some form of public transport such as bus, metro, rail or tram systems. This article aims to examine the features associated with P&R parking locations in use in Cracow (Poland). The analysis included the number of entries and exits to and from parking during particular periods of the day, week and year, parking time of vehicles, and parking space use. A parking peak hour factor was also calculated, which expresses the crowding degree of vehicle entries/exits in/out parking during a particular period. In addition, the paper presents an analysis of factors determining users to P&R parking use. In the modeling process, logit models were used, which, as stated after analyzing the literature on the subject, were already used in various countries around the world to describe the behavior of P&R parking users. However, so far, such research relating to Polish conditions has been not published in the available literature. The obtained results allowed to state that the most important factors determining the likelihood of using P&R parking in Cracow are age, number of years having a driving license, monthly income (gross), and an average number of trips made during a day. Other variables, which not included in the study, can influence the P&R parking use. However, the presented results are the basis for conducting furtherer, more in-depth analyses based on a larger number of independent variables that may determine the P&R parking use.

Creating a transportation network that reduces the cost of urban freight is highly challenging. Freight route is determined by the amount of congestion generated by the vehicle type. Furthermore, it must compete with other users to locate the optimal path for their traffic on the city's restricted road network infrastructure system. Freight network routing begins with identifying and determining the optimum route. The freight network is optimized by introducing a heavy traffic restriction mechanism in metropolitan areas, and an attempt is made to propose a set of routes as a set of freight traffic modes. The primary goal of freight routing in this research is making a freight network model optimization to find a set of freight routing by optimizing (efficiency) trip prices due to limited road infrastructure and the difficulties of constructing road infrastructure in metropolitan areas. Therefore, selecting a group of routes as the journey of the commodities is a realistic alternative to minimizing costs. The problem of route selection is one of combinatorial optimization. The challenge is to narrow the pool of action options to a set of recommended actions. Due to vehicle characteristics and traffic flow, route selection carefully considers vehicle behavior. A two-level mathematical model that was created by formulating route options served as the framework for the research. The combination of chosen routes is maximized using a genetic algorithm such as a Genetic Local Search. The model is examined via its application to a fictitious network. The result converges to the target value of 246,311.9 IDR. It shows that the model satisfies the convergence condition of producing in 0.76 seconds. As a result, a model with a genetic local search technique that can search more effectively in the city's freight network's ideal path is created. The GLS combinatorial optimization model shows us it could find the best set of urban freight networks with the best performance. This is consistent with Yamada et al. GLS methods perform well in solving combinatorial problems.

Introduction. The development of power semiconductor devices and technology served the basis for fundamentally new types of frequency-controlled electric drives with traction asynchronous motors on the rolling stock of electrified railways. Therefore, problems of theoretical and experimental study of the operating modes of the mentioned drives become actual. This article is a theme continuation of the asynchronous machines control on the AC locomotive, which was presented in no. 5 of Russian Railway Scientific Journal in 2021.Materials and methods. For analysing the frequency converter operation, the authors used mathematical modeling methods, which allowed evaluating the motor operation in various modes without resorting to time-consuming full-scale tests. Recently, software packages for visual programming have been developed, aimed mainly at domestic users, which are not inferior in their capabilities to leading foreign counterparts. Among such software products is SimInTech software for modeling technical systems, developed by 3V Service. The software focuses on solving various applied problems, particularly, on modeling a vector control system for an asynchronous drive.Results. The authors developed a mathematical model of an asynchronous drive of auxiliary machines of an electric locomotive in a rotating coordinate system d – q by the SimInTech application package and concerning the cross-impact influence of d and q control channels.Discussion and conclusion. The developed complex of an asynchronous motor and a vector control system enable to work out various algorithms for improving the energy efficiency of the operation of asynchronous auxiliary machines of an electric locomotive by applying the proposed algorithm for choosing the optimal value of the rotor flux linkage. The presented vector control structure also enables to implement it on the basis of modern microcontrollers, helping to reduce programming time.

This paper focuses on a particular form of high mobility, namely the long journeys to work generated by cross-border job market. More precisely, it studies the impact of such behaviors on well-being by analyzing the relationships between mode choice, transport-related attitudes, socio-demographic and spatial attributes, and the level of satisfaction in the context of cross-border long commutes to Luxembourg. The statistical modelling is rooted to a conceptual framework that emphasizes the mutual dependencies between attitudes, mode choice, and satisfaction. Based on a survey among long-distance commuters (N = 3093) held in 2010 and 2011, two ordered logistic regressions, one of which including latent constructs of transport-related attitudes derived from a structural equation modelling, are developed to explain satisfaction in commuting. Main findings are: (1) Travel-related attitudes influence satisfaction with travel more than socio-demographic attributes; (2) public transport users are globally more satisfied in commuting than car drivers; (3) the socio-economic model of satisfaction is plagued by omitted variables issues; (4) the attitude model of satisfaction drops all but one socio-economic attributes (education remains) while improving adjustment (Pseudo-R-squared = 0.57 versus 0.09; BIC = 2953 versus 6059) and avoiding omitted variables bias. The effect of attitudes and other latent constructs is of paramount importance, even concealing most socio-demographic attributes to assess satisfaction. The conclusion is devoted to a discussion on the sustainability of these cross-border long commutes from the individual, social, and environmental points of view.

PurposeThis paper aims to examine the current technology acceptance model (TAM) in the field of mixed reality and digital twin (MRDT) and identify key factors affecting users' intentions to use MRDT. The factors are used as a set of key metrics for proposing a predictive model for virtual, augmented and mixed reality (MR) acceptance by users. This model is called the extended TAM for MRDT adoption in the architecture, engineering, construction and operations (AECO) industry.Design/methodology/approachAn interpretivist philosophical lens was adopted to conduct an inductive systematic and bibliographical analysis of secondary data contained within published journal articles that focused upon MRDT acceptance modelling. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) approach to meta-analysis were adopted to ensure all key investigations were included in the final database set. Quantity indicators such as path coefficients, factor ranking, Cronbach’s alpha (a) and chi-square (b) test, coupled with content analysis, were used for examining the database constructed. The database included journal papers from 2010 to 2020.FindingsThe extant literature revealed that the most commonly used constructs of the MRDT–TAM included: subjective norm; social influence; perceived ease of use (PEOU); perceived security; perceived enjoyment; satisfaction; perceived usefulness (PU); attitude; and behavioural intention (BI). Using these identified constructs, the general extended TAM for MRDT in the AECO industry is developed. Other important factors such as “perceived immersion” could be added to the obtained model.Research limitations/implicationsThe decision to utilise a new technology is difficult and high risk in the construction project context, due to the complexity of MRDT technologies and dynamic construction environment. The outcome of the decision may affect employee performance, project productivity and on-site safety. The extended acceptance model offers a set of factors that assist managers or practitioners in making effective decisions for utilising any type of MRDT technology.Practical implicationsSeveral constraints are apparent due to the limited investigation of MRDT evaluation matrices and empirical studies. For example, the research only covers technologies which have been reported in the literature, relating to virtual reality (VR), augmented reality (AR), MR, DT and sensors, so newer technologies may not be included. Moreover, the review process could span a longer time period and thus embrace a fuller spectrum of technology development in these different areas.Originality/valueThe research provides a theoretical model for measuring and evaluating MRDT acceptance at the individual level in the AECO context and signposts future research related to MRDT adoption in the AECO industry, as well as providing managerial guidance for progressive AECO professionals who seek to expand their use of MRDT in the Fourth Industrial Revolution (4IR). A set of key factors affecting MRDT acceptance is identified which will help innovators to improve their technology to achieve a wider acceptance.

A park and ride (P&R) system is a set of facilities where private vehicle users can transfer to public transport to complete their journey. The main advantage of the system is reducing the congestions problem in the central business district (CBD). Thus, the notion of symmetry is particularly important in multi-criteria decision aid (MCDA) because they are basic characteristics of the binary relationships used in modelling the preferences of decision-makers. The focal point of this study is evaluating the P&R facility system location problem from the experts’ point of view. For this aim, an integrated multicriteria decision-making (MCDM) methodology is proposed to evaluate the location of the facilities of the P&R system. The questionnaire survey was designed and estimated by 10 transport experts in the related field. The famous analytic hierarchy process (AHP) was adopted in a fuzzy environment, where the fuzzy sets have an efficient ability to manage the vague concepts in a specific way; moreover, it can mitigate the evaluator reasoning during decision-making. The hierarchical structure of the problem was established to evaluate a real-life problem in Cuenca city, Ecuador. The outcomes highlighted the “accessibility of public transport” as the most significant issue in the P&R facility location problem. The obtained results provide more flexible facilities than the pure AHP method.

Digitalization is one of the important keys in increasing productivity, namely by building digital technology that improves process efficiency, product and service quality, and optimizes resource allocation, so as to reduce processing time for faster, streamlined operations, and greater customer satisfaction. as good as Power Apps. Power Apps is a service for building and deploying custom business applications that connect to your data and work across the web and mobile - without the time and expense of specialized software development. Power Apps are a number of applications, services, and connectors, as well as a data platform, that provide a fast development environment for building custom applications for business needs. Using Power Apps, users can quickly create custom business applications that connect to data stored on the base data platform (Microsoft Dataverse) or across various online and on-premises data sources (such as SharePoint, Microsoft 365, Dynamics 365, SQL Server, and so on). The purpose of this study is to implement and analyze the use of Power Apps in modeling drug retrieval at the Melia Clinic PT POMI, Paiton with the aim of improving the quality of Melia clinic services through acceleration and ease of drug taking. The output of this research is an accredited national journal.

Purpose – The purpose of this paper is to investigate the factors that affect how people maintain their friendships by using information on Plurk. Design/methodology/approach – This study extended the Theory of Planned Behavior model to include both interpersonal curiosity and reciprocity. Data were collected via an online survey with 220 valid samples. The respondents answered the survey questionnaire based on their past experiences using Plurk. The proposed research model was assessed using structural equation modeling as performed in the LISREL program. Findings – The attitude toward using Plurk for maintaining friendships is the strongest predictor of intention to use, followed by perceived behavioral control. The findings indicate that reciprocity has the strongest effect on attitude toward using Plurk for maintaining friendship, followed by subjective norms and interpersonal curiosity. An analysis of the research explained 61 percent of the variance in attitude toward using Plurk for maintaining friendship, and 73 percent of the variance in intention to use Plurk for maintaining friendship. Research limitations/implications – This study only focussed on a limited number of factors, and as a result, the effects of some variables, such as personal characteristics, may have been overlooked. In the future, researchers can extend this model by incorporating more variables into the analysis of maintaining friendships via Plurk. Practical implications – As microblogging firms compete for online customers, it would be useful to gain some understanding of the possible effects of reciprocity and interpersonal curiosity on users’ intention to use Plurk for maintaining friendships. As firms compete for internet marketing, managers should know the potential use of Plurk as an effective channel to promote their products and services to whoever needs them. Originality/value – From the literature available in the public journal databases, no existing research model was found to explain the behavior of Plurk users on microblogs. The paper fulfills this objective.

Purpose The practice of facility management (FM) has been evolving with the rapid development of pervasive sensing technologies (PSTs) such as sensors, automatic identification (auto-ID), laser scanning and photogrammetry. Despite the proliferation of research on the use of PSTs for FM, a comprehensive review of such research is missing from the literature. This study aims to cover the knowledge void by examining the status quo and challenges of the selected PSTs with a focus on FM. Design/methodology/approach This paper reviewed 204 journal papers recounting cases of using PSTs for FM. The reviewed papers were extracted from Elsevier Scopus database using the advanced search. Findings Findings of this study revealed that PSTs and FM applications form a many-to-many mapping, i.e. one PST could facilitate many FM applications, and one application can also be supported by various PSTs. It is also found that energy modeling and management is the most referred purpose in FM to adopt PSTs, while space management, albeit important, received the least attention. Five challenges are identified, which include high investment on PSTs, data storage problem, absence of proper data exchange protocols for data interoperability, a lack of mature data processing methods for data utilization and privacy of users. Originality/value This paper paints a full picture of PSTs adoption for FM. It pinpoints the promising explorations for tackling the key challenges to future development.

BackgroundExisting research identified substantial gaps between NHS mental health services and the criminal justice system for individuals with enduring moderate to severe mental health needs (EMHN). A pilot study in Cornwall echoed these findings, identifying deficiencies in provision at the interface of police and mental health services.AimTo explore the interagency management of individuals with EMHN as they come into contact with the police.DesignA mixed-methods approach within a community psychology framework to enhance the implementation of findings. Stage 1: policy review and clinical audit to identify a sample of mental health service users who were in contact with the police. Stage 2: case-linkage study of 80 service user journeys through services at the time of three types of police contact (Section 136 detention; arrest for criminal offence and contact that did not result in detention); and a health economics component including analysis of the actual cost of 55 service user journeys and enhanced service scenarios. Stage 3: local stakeholder consultation to validate and contextualise case-linkage findings, including a national event.SettingThe research site was the county of Cornwall within the organisational contexts of Cornwall Partnership NHS Foundation Trust and Devon & Cornwall Police.SampleProportionate stratified random sampling identified a sample of 80 cases examined in the case-linkage study from the 538 linked cases identified by the clinical audit.Data sourcesCase-linkage and health economics data involved individuals’ police and mental health records; stakeholder consultation data involved focus groups and interviews.ResultsOf the sample of 80 cases examined, 23 individuals had been detained under Section 136 of the Mental Health Act (1983: Great Britain.Mental Health Act 1983.Chapter 20. London: The Stationery Office; 1983) (accounting for 32 detentions), 52 had been detained in custody on suspicion of an offence (accounting for 126 arrests) and 15 had non-detention contact with the police. Findings showed that where police were aware of mental health needs and individuals were on caseload of a Mental Health Team, there was increased interaction and enhanced outcomes for service users and organisations. The health economics scenario modelling suggests that enhancing services has minimal effects on individual level costs compared with current practice.ConclusionsThe research revealed discrepancy in police and mental health professionals’ assessment of risk and interpretation of protocol and highlighted the need for joint interagency protocols and training to improve information sharing between agencies to enhance the management of individuals with enduring moderate to severe mental health needs.FundingThe National Institute for Health Research Health Services and Delivery Research programme.

The National Pollutant Release Inventory (NPRI), which has been collecting and disseminating pollutant data since 1994, is Canada’s legislated, publicly accessible inventory of pollutant releases (to air, water, and land), disposals, and transfers (for treatment, recycling, or energy recovery). The public availability of NPRI data is a key program output, initially driven by the community-right-to-know movement and now also compelled by the need to support a myriad of environmental science and policy efforts at various scales. Twenty-five years after the inception of the NPRI, this scoping review of peer-reviewed literature (up to 2019) was undertaken to better understand the nature and extent of uptake of NPRI information by researchers, namely, who are using it and how. The findings show that NPRI use in peer-reviewed research has increased steadily since 1997. NPRI information is implicated in 225 scholarly journal articles between 1994 and 2019. The main users are from the Government of Canada and Canadian universities, though many users from diverse backgrounds beyond these categories and beyond Canada were also noted. Researchers were primarily leveraging NPRI data on pollutants released to air, the focus of which was most often on the criteria air contaminants and metals (mercury). Less popular were data on water releases, land releases, and disposal data, while there were no examples of researchers using data on transfers. Seven prominent themes arose pertaining to the area(s) of interest of studies that use NPRI information, including geospatial analyses, environmental monitoring, predictive modelling, industrial sectors, other pollutant inventories, human health outcomes, and policy or program analysis. Several other study themes were also noted relating to socioeconomic issues, waste treatment and remediation, climate change, indigenous groups, and biomonitoring. Future opportunities to increase NPRI use in research in general, and in understudied areas in particular, as well as to increase the use of underutilized NPRI variables, remain.

Abstract. Data on global agricultural production are usually available as statistics at administrative units, which does not give any diversity and spatial patterns; thus they are less informative for subsequent spatially explicit agricultural and environmental analyses. In the second part of the two-paper series, we introduce SPAM2010 – the latest global spatially explicit datasets on agricultural production circa 2010 – and elaborate on the improvement of the SPAM (Spatial Production Allocation Model) dataset family since 2000. SPAM2010 adds further methodological and data enhancements to the available crop downscaling modeling, which mainly include the update of base year, the extension of crop list, and the expansion of subnational administrative-unit coverage. Specifically, it not only applies the latest global synergy cropland layer (see Lu et al., submitted to the current journal) and other relevant data but also expands the estimates of crop area, yield, and production from 20 to 42 major crops under four farming systems across a global 5 arcmin grid. All the SPAM maps are freely available at the MapSPAM website (http://mapspam.info/, last access: 11 December 2020), which not only acts as a tool for validating and improving the performance of the SPAM maps by collecting feedback from users but is also a platform providing archived global agricultural-production maps for better targeting the Sustainable Development Goals. In particular, SPAM2010 can be downloaded via an open-data repository (DOI: https://doi.org/10.7910/DVN/PRFF8V; IFPRI, 2019).

Abstract. Numerical simulation, and in particular simulation of the earth system, relies on contributions from diverse communities, from those who develop models to those involved in devising, executing, and analysing numerical experiments. Often these people work in different institutions and may be working with significant separation in time (particularly analysts, who may be working on data produced years earlier), and they typically communicate via published information (whether journal papers, technical notes, or websites). The complexity of the models, experiments, and methodologies, along with the diversity (and sometimes inexact nature) of information sources, can easily lead to misinterpretation of what was actually intended or done. In this paper we introduce a taxonomy of terms for more clearly defining numerical experiments, put it in the context of previous work on experimental ontologies, and describe how we have used it to document the experiments of the sixth phase for the Coupled Model Intercomparison Project (CMIP6). We describe how, through iteration with a range of CMIP6 stakeholders, we rationalized multiple sources of information and improved the clarity of experimental definitions. We demonstrate how this process has added value to CMIP6 itself by (a) helping those devising experiments to be clear about their goals and their implementation, (b) making it easier for those executing experiments to know what is intended, (c) exposing interrelationships between experiments, and (d) making it clearer for third parties (data users) to understand the CMIP6 experiments. We conclude with some lessons learnt and how these may be applied to future CMIP phases as well as other modelling campaigns.

The Joint Conference of the 2nd International Conference on Soft Computing and Intelligent Systems and the 5th International Symposium on Advanced Intelligent Systems (SCIS & ISIS 2004) held at Keio University in Yokohama, Japan, on September 21-24, 2004, attracted over 300 papers in fields such as mathematics, urban and transport planning, entertainment, intelligent control, learning, image processing, clustering, neural networks applications, evolutionary computation, system modeling, fuzzy measures, and robotics. The Program Committee requested reviewers in SCIS & ISIS 2004 to select papers for a special issue of the Journal of Advanced Computational Intelligence & Intelligent Informatics (JACIII), with 27 papers accepted for publication in a two-part SCIS & ISIS 2004 special – Vol.9, No.2, containing 13 and the second part containing 14. Paper 1 details tap-changer control using neural networks. Papers 2-5 deal with image processing and recognition – Paper 2 proposing a model of saliency-driven scene learning and recognition and applying its model to robotics, paper 3 discussing breast cancer recognition using evolutionary algorithms, paper 4 covering a revised GMDH-typed neural network model applied to medical image recognition, paper 5 presenting how to compensate for missing information in the acquisition of visual information applied to autonomous soccer robot control. Paper 6 details gene expressions networks for 4 fruit fly development stages. Paper 7 proposes an α-constrained particle swarm optimized for solving constrained optimization problem. Paper 8 develops a fuzzy-neuro multilayer perceptron using genetic algorithms for recognizing odor mixtures. Paper 9 discusses how to integrate symbols into neural networks for the fusion of computational and symbolic processing and its effectiveness demonstrated through simulations. Paper 10 proposes an electric dictionary using a set of nodes and links whose usefulness is verified in experiments. Paper 11 presents a multi-agent algorithm for a class scheduling problem, showing its feasibility through computer simulation. Paper 12 proposes inductive temporal formula specification in system verification, reducing memory and time in the task of system verification. Paper 13 applies an agent-based approach to modeling transport using inductive learning by travelers and an evolutionary approach. The last paper analyzes architectural floor plans using a proposed index classifying floor plans from the user's point of view. We thank reviewers for their time and effort in making these special issues available so quickly, and thank the JACIII editorial board, especially Editor-in-Chief Profs. Hirota and Fukuda and Managing Editor Kenta Uchino, for their invaluable aid and advice in putting these special issues together.

Abstract Hartman, S. E., Lampitt, R. S., Larkin, K. E., Pagnani, M., Campbell, J., Gkritzalis, T., Jiang, Z.-P., Pebody, C. A., Ruhl, H. A., Gooday, A. J., Bett, B. J., Billett, D. S. M., Provost, P., McLachlan, R., Turton, J. D., and Lankester, S. 2012. The Porcupine Abyssal Plain fixed-point sustained observatory (PAP-SO): variations and trends from the Northeast Atlantic fixed-point time-series. – ICES Journal of Marine Science, 69: 776–783. The Porcupine Abyssal Plain sustained observatory (PAP-SO) in the Northeast Atlantic (49°N 16.5°W; 4800 m) is the longest running open-ocean multidisciplinary observatory in the oceans around Europe. The site has produced high-resolution datasets integrating environmental and ecologically relevant variables from the surface to the seabed for >20 years. Since 2002, a full-depth mooring has been in place with autonomous sensors measuring temperature, salinity, chlorophyll-a fluorescence, nitrate, and pCO2. These complement ongoing mesopelagic and seabed observations on downward particle flux and benthic ecosystem structure and function. With national and European funding, the observatory infrastructure has been advanced steadily, with the latest development in 2010 involving collaboration between the UK's Meteorological Office and Natural Environment Research Council. This resulted in the first simultaneous atmospheric and ocean datasets at the site. All PAP-SO datasets are open access in near real time through websites and as quality-controlled datasets for a range of remote users using ftp sites and uploaded daily to MyOcean and the global telecommunications system for use in modelling activities. The combined datasets capture short-term variation (daily–seasonal), longer term trends (climate-driven), and episodic events (e.g. spring-bloom events), and the data contribute to the Europe-wide move towards good environmental status of our seas, driven by the EU's Marine Strategy Framework Directive (http://ec.europa.eu/environment/water/marine).

A coordinated set of global coupled climate model [atmosphere–ocean general circulation model (AOGCM)] experiments for twentieth- and twenty-first-century climate, as well as several climate change commitment and other experiments, was run by 16 modeling groups from 11 countries with 23 models for assessment in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). Since the assessment was completed, output from another model has been added to the dataset, so the participation is now 17 groups from 12 countries with 24 models. This effort, as well as the subsequent analysis phase, was organized by the World Climate Research Programme (WCRP) Climate Variability and Predictability (CLIVAR) Working Group on Coupled Models (WGCM) Climate Simulation Panel, and constitutes the third phase of the Coupled Model Intercomparison Project (CMIP3). The dataset is called the WCRP CMIP3 multimodel dataset, and represents the largest and most comprehensive international global coupled climate model experiment and multimodel analysis effort ever attempted. As of March 2007, the Program for Climate Model Diagnostics and Intercomparison (PCMDI) has collected, archived, and served roughly 32 TB of model data. With oversight from the panel, the multimodel data were made openly available from PCMDI for analysis and academic applications. Over 171 TB of data had been downloaded among the more than 1000 registered users to date. Over 200 journal articles, based in part on the dataset, have been published AMERICAN METEOROLOGICAL SOCIETY so far. Though initially aimed at the IPCC AR4, this unique and valuable resource will continue to be maintained for at least the next several years. Never before has such an extensive set of climate model simulations been made available to the international climate science community for study. The ready access to the multimodel dataset opens up these types of model analyses to researchers, including students, who previously could not obtain state-of-the-art climate model output, and thus represents a new era in climate change research. As a direct consequence, these ongoing studies are increasing the body of knowledge regarding our understanding of how the climate system currently works, and how it may change in the future.

1554 Background: There is strong interest by researchers, the pharmaceutical industry, medical journal editors, funders of research, and regulators in sharing clinical trial data. Reusing data extracts the most utility possible from patient contributions. The majority of patients do want to share their data for secondary research purposes. However, data access for secondary analysis remains a challenge. A key reason why individual-level data is not made directly available to data users by authors and data custodians is concern over breaches of patient privacy. Synthetic data generation (SDG) is an effective way to address privacy concerns that can enable the broader sharing of clinical trial datasets. However, a key question is whether the reproducibility of the generated data is adequate to draw reliable conclusions. Methods: We synthesized datasets from five pragmatic breast cancer clinical trials performed by the REaCT group (https://react.ohri.ca/). A sequential synthesis method, a type of machine learning was performed. The published analysis of each trial was repeated on each synthetic dataset to evaluate reproducibility. We evaluated reproducibility on three criteria: (a) decision agreement: the direction and statistical significance of the primary endpoint effect estimates are the same as the real data, (b) estimate agreement: the parameter estimates from the synthetic data are within the 95% confidence interval of the real data, and (c) the confidence interval overlap between real and synthetic parameters is above 50%. In addition, we evaluated privacy using a membership disclosure metric. This evaluates the ability of an adversary to determine that a target individual was in the original dataset using the synthetic data, computed as an F1 classification accuracy score. Results: Our results show that decision and estimate agreements held true across all five trials, and the confidence interval overlap was high. The risks of membership disclosure are all below the established 0.2 threshold. Conclusions: In this study, we were able to successfully generate synthetic datasets that accurately replicated original data from 5 oncology trials and yielded the same results as in the original published studies, with a very low risk of membership disclosure. With proper modeling techniques, synthetic datasets can play a key role in data democratization and the reuse of oncology clinical trials.[Table: see text]

Introduction Shoulder problems like pain or pathology are highly prevalent in manual wheelchair users (MWU) with spinal cord injury, lead to limitations in participation, a reduced quality of life and are often associated with “shoulder overload” (Mercer et al., 2006). Laboratory based experiments have examined shoulder load for a variety of wheelchair related activities (WRA; van Drongelen et al., 2005), but no research has been conducted that investigates the actual shoulder load profile of MWU’s in daily conditions. Such a profile would help in understanding the relation of shoulder overload and shoulder problems and could thereby support clinical decision making in the prevention of shoulder problems. Inspired by recent work on machine learning (ML) prediction of joint load from wearable sensors, the current project's ultimate aim is to develop a generalizable ML algorithm that can predict shoulder load for a variety of WRA. Methods 10 able bodied participants were trained before the actual measurement of the WRA of interest: wheelchair propulsion (WCP) at 0.56 and 1.1 m/s at 0%, 0.56 m/s at 6%, WCP in restricted space, short ramp 12% up and down, weight relieve lift, manual material handling with 2 kg and desk work. Participants were equipped with five Shimmer3 sensors on wheelchair, wheel, thorax, upper arm and forearm; EMG was collected from the biceps and medial deltoid muscles. An 8 camera Qualisys system was used to obtain kinematics conform ISB recommendations (Wu et al., 2005). A SmartWheel (Out-Front) for collecting propulsion kinetics replaced the original wheel of a standard Kuschal wheelchair. From laboratory kinematics and kinetics 3D shoulder joint reaction forces (JRF) were estimated with an OpenSim based musculoskeletal model (Wu et al., 2016) (MSM), which consequently served as target for the training of a variety of ML algorithms, using sensor data (acceleration, angular velocity, EMG) as input. Results & Discussion Starting with simple input (upper arm sensors only) and a linear neural network (NN, one input, one hidden, one output layer for total JRF; iteratively trained following a Leave One Subject Out approach, a R2 of around 60% was obtained between predicted JRF (NN) and target (MSM output), but results varied considerably over participants. In a next phase the complexity of the ML models was increased to deep learning models (recurrent NN) and more signals (e.g. forearm and thorax sensors) were added to the input, which, however, did not improve the overall performance considerably. Currently, it is explored whether using training the algorithms on individual datasets, for single tasks, can improve the performance. The explorative process will be presented and discussed in the light of the relevant results. References Mercer, J. L., Boninger, M., Koontz, A., Ren, D., Dyson-Hudson, T., & Cooper, R. (2006). Shoulder joint kinetics and pathology in manual wheelchair users. Clincal Biomechanics, 21(8), 781-789. https://doi.org/10.1016/j.clinbiomech.2006.04.010 van Drongelen, S., van der Woude, L. H., Janssen, T. W., Angenot, E. L., Chadwick, E. K., & Veeger, D. H. (2005). Glenohumeral contact forces and muscle forces evaluated in wheelchair-related activities of daily living in able-bodied subjects versus subjects with paraplegia and tetraplegia. Archives of Physical Medicine and Rehabilitation, 86(7), 1434-1440. https://doi.org/10.1016/j.apmr.2005.03.014 Wu, W., Lee, P. V. S., Bryant, A. L., Galea, M., & Ackland, D. C. (2016). Subject-specific musculoskeletal modeling in the evaluation of shoulder muscle and joint function. Journal of Biomechanics, 49(15), 3626-3634. https://doi.org/10.1016/j.jbiomech.2016.09.025 Wu, G., van der Helm, F. C., Veeger, H. E., Makhsous, M., Van Roy, P., Anglin, C., Nagels, J., Karduna, A. R., McQuade, K., Wang, X., Werner, F. W., Buchholz, B., & International Society of, B. (2005). ISB recommendation on definitions of joint coordinate systems of various joints for the reporting of human joint motion-Part II: Shoulder, elbow, wrist and hand. Journal of Biomechanics, 38(5), 981-992. https://doi.org/10.1016/j.jbiomech.2004.05.042

ABSTRAKTujuan dari Penelitian ini adalah menguji pengaruh kepercayaan dan citra website yang diintegrasikan dengan persepsi kemudahan penggunaan dan persepsi kebermanfaatan pada niatan seorang mahasiswa dalam membayar wakaf secara online, yang menjadikan penelitian ini berbeda dengan penelitian sebelumnya adalah penggunaan citra website sebagai determinan niatan mahasiswa dalam menggunakan layanan wakaf online ini. Penelitian ini menggunakan pendekatan kuantitatif dengan metode SEM-PLS serta melibatkan responden sebesar 100 responden dengan menggunakan Purposive Sampling dengan kriteria seorang muslim usia 18-35 dan seorang mahasiswa. Software analisis untuk mengolah data dalam penelitian ini menggunakan Smartpls 3.3, untuk data diperoleh dengan menggunakan kuesioner online menggunakan skala likert 1 sampai 5, dengan keterangan sangat setuju hingga tidak setuju. Hasil dari penelitian ini menunjukkan bahwa kepercayaan, citra website, kebermanfaatan aplikasi, dan kemudahan penggunaan berhubungan signifikan terhadap niat penggunaan wakaf online. Implikasi hasil penelitian ini diharapkan dapat memberikan tambahan pengetahuan terutama dalam ilmu pemasaran Islam terkait penggunaan behavioral intention dalam penggunaan layanan wakaf online, serta diharapkan penelitian ini dapat memberikan masukan bagi manajemen lembaga donasi terutama nazir untuk lebih memperhatikan kemudahan penggunaan konsumen, manfaat yang dirasakan, kepercayaan lembaga, citra perusahaan serta niat dalam menggunakan layanan wakaf secara online.Kata kunci: Wakaf online, technology acceptance model, trust, image. ABSTRACTThe purpose of this study was to examine the effect of trust and website image, which is integrated with perceived ease of use and perceived usefulness, on a student's intention to pay waqf online. What makes this research different from previous research is using website images to determine student intention in using this online waqf service. This study uses a quantitative approach with the SEM-PLS method and involves 100 respondents using purposive sampling with the criteria of a Muslim aged 18-35 and a student. The analysis software to process data in this study used Smartpls 3.3 for data obtained using an online questionnaire using a Likert scale of 1 to 5, with statements strongly agreeing to disagree. This study indicates that trust, website image, application usefulness, and ease of use are significantly related to the intention to use online waqf. The implications of the results of this study are expected to provide additional knowledge, especially in Islamic marketing related to the use of behavioral intention in the use of online waqf services. It is hoped that this research can provide input for the management of donation institutions, especially Nazir, to pay more attention to consumers' ease of use, perceived benefits, and institutional trust., corporate image and intention to use online waqf services.Keywords: online waqf, technology acceptance model, trust, image. DAFTAR PUSTAKAAbdul Shukor, S., Johari, F., Abd Wahab, K., Kefeli Zulkefli, Z., Ahmad, N., Haji Alias, M., Abdul Rahman, A., Mohd Orip, N. M., Ibrahim, P., & Abu-Hussin, M. F. (2019). Trust on awqaf institutions: evidence from Malaysia. Journal of Islamic Marketing, 10(2), 511–524. https://doi.org/10.1108/JIMA-05-2017-0054Ahn, J. chang, Sura, S., & An, J. C. (2018). Intention to donate via social network sites (SNSs): A comparison study between Malaysian and South Korean users. Information Technology and People, 31(4), 910–926. https://doi.org/10.1108/ITP-12-2015-0307Aldeen, K. N., Ratih, I. S., & Herianingrum, S. (2020). Contemporary issues on cash waqf: A thematic literature review. International Journal of Islamic Economics and Finance (IJIEF), 3(3), 119–144. https://doi.org/10.18196/ijief.3236Alrubaiee, L. S., Aladwan, S., Abu Joma, M. H., Idris, W. M., & Khater, S. (2017). Relationship between corporate social responsibility and marketing performance: The mediating effect of customer value and corporate image. International Business Research, 10(2), 104. https://doi.org/10.5539/ibr.v10n2p104Bailey, A. A., Pentina, I., Mishra, A. S., & Ben Mimoun, M. S. (2017). Mobile payments adoption by US consumers: An extended TAM. International Journal of Retail and Distribution Management, 45(6), 626–640. https://doi.org/10.1108/IJRDM-08-2016-0144Berakon, I., Aji, H. M., & Hafizi, M. R. (2021). Impact of digital sharia banking systems on cash-waqf among Indonesian Muslim youth. Journal of Islamic Marketing. https://doi.org/10.1108/JIMA-11-2020-0337Blagoeva, K. T., & Mijoska, M. (2017). Applying TAM to study online shopping adoption among youth in the republic of Macedonia. Genetika, 46(3), 27–32.Eneizan, B., Alsaad, A., Alkhawaldeh, A., Rawash, H. N., & Enaizan, O. (2020). E-WOM, trust, usefulness, ease of use, and online shopping via websites: The moderating role of online shopping experience. Journal of Theoretical and Applied Information Technology, 98(13), 2554–2565.Faisal, M., Yusof, M., Alam, S., Faiz, M., Yusof, M., Alam, S., Hasarudin, M. H., Alam, S., Romli, N., Lumpur, K., Terms, G., & Statement, P. (2014). Cash waqf and infaq: A proposed e-philanthropy in Malaysia. Jurnal Kemanusiaan, 12(1), 1–10.Hair Jr., J. F., Gabriel, M. L. D. da S., & Patel, V. K. (2014). Modelagem de equações estruturais baseada em covariância (CB-SEM) com o AMOS: Orientações sobre a sua aplicação como uma Ferramenta de Pesquisa de Marketing. Revista Brasileira de Marketing, 13(2), 44–55. https://doi.org/10.5585/remark.v13i2.2718Indahsari, K., Burhan, M. U., Ashar, K., & Multifiah. (2014). Determinants of individual Muslim behaviour in accomplishing zakah, infaq, shadaqah and waqf through amil institution. International Journal of Economic Policy in Emerging Economies, 7(4), 346–365. https://doi.org/10.1504/IJEPEE.2014.066627Iskandar, M., Hartoyo, H., & Hermadi, I. (2020). Analysis of factors affecting behavioral intention and use of behavioral of mobile banking using unified theory of acceptance and use of technology 2 model approach. International Review of Management and Marketing, 10(2), 41–49. https://doi.org/10.32479/irmm.9292Joseph, S. (2014). Waqf in historical perspective: Online fatāwā and contemporary discourses by muslim scholars. Journal of Muslim Minority Affairs, 34(4), 425–437. https://doi.org/10.1080/13602004.2014.965974Kasri, R. A., & Chaerunnisa, S. R. (2021). The role of knowledge, trust, and religiosity in explaining the online cash waqf amongst Muslim millennials. Journal of Islamic Marketing. https://doi.org/10.1108/JIMA-04-2020-0101Klopping, I. M., & Mckinney, E. (2004). Extending the technology acceptance model and the task-technology fit model to consumer e-commerce. Information Technology, Learning, and Performance Journal, 22(1), 35–48.Lubis, H. (2020). Potensi dan strategi pengembangan wakaf uang di indonesia. IBF: Islamic Business and Finance, 1(1), 43–59.Masrikhan, M. (2019). Optimalisasi potensi wakaf di era digital melalui platform online wakafin.com dengan konsep crowdfunding sebagai penggerak ekonomi masyarakat. Jurnal Ekonomi Syariah, 1, 1–12.Mohd Thas Thaker, M. A. Bin. (2018). Factors influencing the adoption of the crowdfunding-waqf model (CWM) in the waqf land development. Journal of Islamic Marketing, 9(3), 578–597. https://doi.org/10.1108/JIMA-05-2016-0043Mohd Thas Thaker, M. A., Mohd Thas Thaker, H., A.Pitchay, A., & Khaliq, A. (2019). A proposed integrated zakat-crowdfunding model (IZCM) for effective collection and distribution of zakat fund in Malaysia. International Journal of Zakat and Islamic Philanthropy, 1(2), 1–12.Niswah, F. M., Mutmainah, L., & Legowati, D. A. (2019). Muslim millennial’s intention of donating for charity using fintech platform. Journal of Islamic Monetary Economics and Finance, 5(3), 623–644. https://doi.org/10.21098/jimf.v5i3.1080Nour Aldeen, K., Ratih, I. S., & Sari Pertiwi, R. (2021). Cash waqf from the millennials’ perspective: a case of Indonesia. ISRA International Journal of Islamic Finance, ahead-of-p(ahead-of-print). https://doi.org/10.1108/ijif-10-2020-0223Phatthana, W., & Mat, N. K. N. (2011). The application of technology acceptance model (TAM) on health tourism e-purchase intention predictors in Thailand. 2010 International Conference on Business and Economics Research, 1, 196–199. http://www.ipedr.com/vol1/43-B10046.pdfRaza, S. A., Shah, N., & Ali, M. (2019). Acceptance of mobile banking in Islamic banks: Evidence from modified UTAUT model. Journal of Islamic Marketing, 10(1), 357–376. https://doi.org/10.1108/JIMA-04-2017-0038Rybaczewska, M., Sparks, L., & Sułkowski, Ł. (2020). Consumers’ purchase decisions and employer image. Journal of Retailing and Consumer Services, 55(October 2019), 0–7. https://doi.org/10.1016/j.jretconser.2020.102123Sabri, F. A. (2014). Wakaf uang (Sebuah alternatif dalam upaya menyejahterakan masyarakat). AL-IHKAM: Jurnal Hukum & Pranata Sosial, 8(1), 40–54. https://doi.org/10.19105/al-lhkam.v8i1.339Shaikh, I. M., Qureshi, M. A., Noordin, K., Shaikh, J. M., Khan, A., & Shahbaz, M. S. (2020). Acceptance of Islamic financial technology (FinTech) banking services by Malaysian users: An extension of technology acceptance model. Foresight, 22(3), 367–383. https://doi.org/10.1108/FS-12-2019-0105Singh, S., Sahni, M. M., & Kovid, R. K. (2020). What drives fintech adoption? 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Introduction This statement revises our earlier “WAME Recommendations on ChatGPT and Chatbots in Relation to Scholarly Publications” (January 20, 2023). The revision reflects the proliferation of chatbots and their expanding use in scholarly publishing over the last few months, as well as emerging concerns regarding lack of authenticity of content when using chatbots. These Recommendations are intended to inform editors and help them develop policies for the use of chatbots in papers published in their journals. They aim to help authors and reviewers understand how best to attribute the use of chatbots in their work, and to address the need for all journal editors to have access to manuscript screening tools. In this rapidly evolving field, we will continue to modify these recommendations as the software and its applications develop. A chatbot is a tool “[d]riven by [artificial intelligence], automated rules, natural-language processing (NLP), and machine learning (ML)…[to] process data to deliver responses to requests of all kinds.”1 Artificial intelligence (AI) is “the ability of a digital computer or computer-controlled robot to perform tasks commonly associated with intelligent beings.”2 “Generative modeling is an artificial intelligence technique that generates synthetic artifacts by analyzing training examples; learning their patterns and distribution; and then creating realistic facsimiles. Generative AI (GAI) uses generative modeling and advances in deep learning (DL) to produce diverse content at scale by utilizing existing media such as text, graphics, audio, and video.”3, 4 Chatbots are activated by a plain-language instruction, or “prompt,” provided by the user. They generate responses using statistical and probability-based language models.5 This output has some characteristic properties. It is usually linguistically accurate and fluent but, to date, it is often compromised in various ways. For example, chatbot output currently carries the risk of including biases, distortions, irrelevancies, misrepresentations, and plagiarism many of which are caused by the algorithms governing its generation and heavily dependent on the contents of the materials used in its training. Consequently, there are concerns about the effects of chatbots on knowledge creation and dissemination – including their potential to spread and amplify mis- and disinformation6 – and their broader impact on jobs and the economy, as well as the health of individuals and populations. New legal issues have also arisen in connection with chatbots and generative AI.7 Chatbots retain the information supplied to them, including content and prompts, and may use this information in future responses. Therefore, scholarly content that is generated or edited using AI would be retained and as a result, could potentially appear in future responses, further increasing the risk of inadvertent plagiarism on the part of the user and any future users of the technology. Anyone who needs to maintain confidentiality of a document, including authors, editors, and reviewers, should be aware of this issue before considering using chatbots to edit or generate work.9 Chatbots and their applications illustrate the powerful possibilities of generative AI, as well as the risks. These Recommendations seek to suggest a workable approach to valid concerns about the use of chatbots in scholarly publishing.

ABSTRAK Penurunan profit bisnis kecil akibat implikasi ekonomi pasca pandemi COVID-19. Persoalan struktur permodalan menjadi kendala dalam mempertahankan dan meningkatkan usahanya secara terus menerus seiring kerubahan zaman. Koperasi Syariah sebagai salah satu lembaga keuangan Islam yang keislaman lebih dekat secara eksistensi maupun teritorial dengan masyarakat tingkat bawah sehingga menjadi alternatif pengembangan usaha masyarakat secara syariah sesuai persyaratan yang diberikan. Studi ini bertujuan untuk untuk menganalisis pengaruh literasi keuangan syariah dalam sikap, pengaruh sosial dan self-efficacy terhadap perilaku pemanfaatan produk koperasi syariah di Indonesia. Studi kuantitatif survey online dengan melibatkan 280 calon anggota koperasi syariah yang membutuhkan pembiayaan dan merupakan pemilik UMKM dijalankan dengan teknik analisis SEM PLS. Hasil studi menunjukkan pengaruh literasi keuangan terhadap sikap, pengaruh sosial dan self-efficacy lalu dilanjutkan arah jalur dukungan hipotesis terhadap niat untuk memilih Koperasi Syariah sebagai solusi kebutuhan finansial UMKM ditemukan. Strategi manajerial khususnya pemasaran dikembangkan dengan mempertimbangkan efek sikap positif, pengaruh sosial dan efikasi diri calon anggota sebagai pemilik bisnis atau produk keuangan syariah yang akan mereka tawarkan kepada pelanggan mereka akan berkontribusi pada pertumbuhan sektor UMKM khususnya UMKM Generasi Millenial dan UMKM Hijau di Indonesia melalui upaya promosi dan kerjasama. Kata Kunci: ASE Model, Ekonomi Islam, Koperasi Syariah, Pemberdayaan, UMKM. ABSTRACT The decline in small business profits due to the post-COVID-19 pandemic economy. The issue of capital structure is an obstacle in maintaining and increasing development continuously in line with the changing times. Sharia cooperatives as one of the Islamic financial institutions are closer in existence and territorially to the lower level of society so that they become an alternative for community business development in accordance with the requirements given. This study aims to analyze the effect of Islamic financial literacy on attitudes, social influence and self-efficacy on the application of Islamic cooperative products in Indonesia. Quantitative study of online surveys involving 280 prospective members of Islamic cooperatives who need financing and are MSME owners carried out with the PLS SEM analysis technique. The results of the study show the effect of financial literacy on attitudes, social influence and self-efficacy, then choosing the direction of hypothesis support for the intention to find Islamic Cooperatives as a solution to the financial needs of MSMEs. Managerial strategies especially marketing that are developed taking into account the effects of positive attitudes, social influence and self-efficacy of prospective members as owners or Islamic financial products that they will offer to their customers will increase the growth of the MSME sector, especially Millennial Generation MSMEs and Green MSMEs in Indonesia through promotional efforts and cooperation. Keywords: ASE Model, Islamic Economics, Sharia Cooperatives, Empowerment, MSMEs. REFERENCES Abourrig, A. (2021). Social influence in predicting Islamic banking acceptance: Evidence from Morocco. International Journal of Accounting, Finance, Auditing, 2(2), 42–56. https://doi.org/10.5281/zenodo.4641472 Ajzen, I. (1991a). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T Ajzen, I. (1991b). The theory of planned behavior. 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Background Cancer patients transitioning to survivorship after completing cancer treatments need psychosocial interventions to manage stressors such as anxiety, depression, and fear of cancer recurrence. Mindfulness-based interventions (MBIs) are effective for treating these symptoms; however, cancer survivors are often unable to participate in face-to-face interventions because of difficulties such as work and family commitments, treatment-related side-effects, scheduling conflicts, and geography. Smartphone app–based MBIs are an innovative way to deliver psychosocial cancer care and can overcome several such difficulties, since patients can participate at their own convenience. Objective The SEAMLESS (Smartphone App–Based Mindfulness Intervention for Cancer Survivors) study aims to evaluate the efficacy of a tailored app-based mindfulness intervention for cancer survivors (the Am Mindfulness-Based Cancer Survivorship—MBCS—Journey) for treating (1) symptoms of stress (primary outcome), as well as (2) fear of cancer recurrence, anxiety, depression, fatigue, and overall physical functioning (secondary outcomes). This is the first Canadian efficacy trial of a tailored mindfulness app intervention in cancer survivors. Methods This is a randomized waitlist-controlled trial, which will evaluate the effectiveness of Am MBCS for impacting the primary and secondary outcomes in cancer survivors who have completed all their cancer treatments. Outcomes will be assessed using web-based surveys with validated psychometric instruments at (1) baseline, (2) mid-intervention (2 weeks later), (3) immediately postintervention (4 weeks), (4) 3 months postbaseline, (5) 6 months postbaseline, and (6) 12 months postbaseline. The waitlist group will complete all assessments and will cross over to the intervention condition after the 3-month assessment. In addition, data will be obtained by the smartphone app itself, which includes users’ engagement with the app-based intervention, their emotional state (eg, angry and elated) from a user-inputted digital emotion-mapping board, and psychobiometric data using photoplethysmography technology. Results The study received ethics approval in September 2018 and recruitment commenced in January 2019. Participants are being recruited through a provincial cancer registry, and the majority of participants currently enrolled are breast (44/83, 53%) or colorectal (17/83, 20%) cancer survivors, although some survivors of other cancer are also present. Data collection for analysis of the primary outcome time-point will be complete by September 2019, and the follow-up data will be collected and analyzed by September 2020. Data will be analyzed to determine group differences using linear mixed modelling statistical techniques. Conclusions Cancer care providers are uncertain about the efficacy of app-based mindfulness interventions for patients, which are available in great supply in today’s digital world. This study will provide rigorously evaluated efficacy data for an app-based mindfulness intervention for cancer survivors, which if helpful, could be made available for psychosocial care at cancer centers worldwide. Trial Registration ClinicalTrials.gov NCT03484000; https://clinicaltrials.gov/ct2/show/NCT03484000 International Registered Report Identifier (IRRID) DERR1-10.2196/15178

Underwater acoustic signature identification has been employed as a technique for detecting underwater vehicles, such as in anti-submarine warfare or harbour security systems. The underwater sound channel, however, has interference due to spatial variations in topography or sea state conditions and temporal variations in water column properties, which cause multipath and scattering in acoustic propagation. Thus, acoustic data quality control can be very challenging. One of challenges for an identification system is how to recognise the same target signature from measurements under different temporal and spatial settings. This paper deals with the above challenges by establishing an identification system composed of feature extraction, classification algorithms, and feature selection with two approaches to recognise the target signature of underwater radiated noise from a research vessel, Ocean Researcher III, with a bottom mounted hydrophone in five cruises in 2016 and 2017. The fundamental frequency and its power spectral density are known as significant features for classification. In feature extraction, we extract the features before deciding which is more significant from the two aforementioned features. The first approach utilises Polynomial Regression (PR) classifiers and feature selection by Taguchi method and analysis of variance under a different combination of factors and levels. The second approach utilises Radial Basis Function Neural Network (RBFNN) selecting the optimised parameters of classifier via genetic algorithm. The real-time classifier of PR model is robust and superior to the RBFNN model in this paper. This suggests that the Automatic Identification System for Vehicles using Acoustic Signature developed here can be carried out by utilising harmonic frequency features extracted from unmasking the frequency bandwidth for ship noises and proves that feature extraction is appropriate for our targets. 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