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The purpose of this paper is to introduce types of hijackings in the academic world. Some of these hijacking are already known as hijacked journals, but some other type of hijacking are potential and unknown to most researchers. The author detected these hijacks by experimental study on journals, conferences and invitation emails and classifying them into groups which will be introduced in this paper.

The author can see other types of hijacks in the academic world that will introduce in this short paper with possible examples and general detection guideline for them. These were detected by experimental study on journals, conferences and invitation emails followed by classifying them into groups which will be introduced in the next section.

There are types of hijackings in the academic world that are introduced in this paper.

The author’s observation shows that hijacked journals and predatory publishers are only part of the problem.

Scientific publishing has recently faced challenges in dealing with questionable (predatory and hijacked) journals. The presence of questionable journals in any field, including management science, will yield junk science. Although there are studies about questionable journals in other fields, these journals have not yet been examined in the field of business and management. This study aims to identify facilitators and barriers to dealing with questionable journals in management science.

A Delphi research method consisting of three rounds was used in this study. Data were collected from 12 experts in the first two rounds, and ten experts in the final round.

The present study shows that management science is vulnerable to questionable journals. A total of 18 barriers and eight facilitators to dealing with questionable journals in management science were found. The present study also identifies some new barriers and facilitators for avoiding questionable journals, which are specific to management science and have not been identified in previous research. Most of these barriers and facilitators were identified as “important” or “very important”. Publishers and scientific databases, government, the research community and universities and research centers were identified as critical players in overcoming challenges posed by questionable journals.

The number of articles that investigate predatory journals in management science is limited, and there is no research focused specifically on hijacked journals in this field. This study identifies facilitators and obstacles to dealing with predatory and hijacked journals in the field of management, by gathering opinions from experts. Thus it is the first study to examine hijacked journals in the field of management science. It is also one of the few studies that examine predatory and hijacked journals by conducting exploratory research rather than with a descriptive/conceptual approach.

This paper aims to present a hybrid approach based on classification algorithms that was capable of identifying different types of phishing pages. In this approach, after eliminating features that do not play an important role in identifying phishing attacks and also after adding the technique of searching page title in the search engine, the capability of identifying journal phishing and phishing pages embedded in legal sites was added to the presented approach in this paper.

The hybrid approach of this paper for identifying phishing web sites is presented. This approach consists of four basic sections. The action of identifying phishing web sites and journal phishing attacks is performed via selecting two classification algorithms separately. To identify phishing attacks embedded in legal web sites also the method of page title searching is used and then the result is returned. To facilitate identifying phishing pages the black list approach is used along with the proposed approach so that the operation of identifying phishing web sites can be performed more accurately, and, finally, by using a decision table, it is judged that the intended web site is phishing or legal.

In this paper, a hybrid approach based on classification algorithms to identify phishing web sites is presented that has the ability to identify a new type of phishing attack known as journal phishing. The presented approach considers the most used features and adds new features to identify these attacks and to eliminate unused features in the identifying process of these attacks, does not have the problems of previous techniques and can identify journal phishing too.

The major advantage of this technique was considering all of the possible and effective features in identifying phishing attacks and eliminating unused features of previous techniques; also, this technique in comparison with other similar techniques has the ability of identifying journal phishing attacks and phishing pages embedded in legal sites.

At the moment, business intelligence (BI) is known as the way for analyzing data in an organization. Simple search in the literature shows that there are many papers which discuss about BI applications and related matters. In addition, there are different approaches and tools that support using BI in organizations. This paper aims to focus on the use of BI tools for academic applications, and it describes how the academic area will benefit from using BI.

This paper is based on using BI tools and other library studies.

A process for using BI tools in academic applications has been presented. Also, two cases are stated about activities of e-learning participants and literature analysis, for which BI tools are used to analyze data and simplify difficult tasks.

This paper shows how BI tools can be used for research and academic applications.

Internet of things (IoT) promises advantages in different sectors, especially the health-care sector. Due to its capabilities for chronic disease management, IoT has attracted the attention of researchers. Nowadays, there is research that focuses on the use of IoT for chronic disease management. However, the use of IoT in various contexts faces different barriers. This paper aims to explore Iranian experts’ conceptions of the barriers to using IoT in Iran regarding its application for chronic disease management.

This study follows a phenomenographic method to investigate Iranian experts’ conceptions of the barriers to using IoT in Iran regarding its application for chronic disease management.

The results show that there are four categories of description (governance, technical, economic and social barriers) that vary among experts’ conceptions.

The findings of the present work could provide valuable insights for managers and policymakers who want to address IoT barriers.

The purpose of this study is to empirically evaluate the potential of the blockchain technology in tourism. The blockchain technology (BCT) holds potential to contribute significantly to tourism policy and practice. Academic interest in the BCT is rapidly growing with studies looking at the opportunities and challenges of its application. The shortcoming of research on the BCT in tourism has however been in its conceptual nature. The lack of empirical investigations hinders an understanding of how the BCT can be more broadly adopted in tourism, especially from the viewpoint of minimizing its risks.

The initial screening of the opportunities, challenges and risks is undertaken via a systematic literature review. The Delphi study is subsequently applied to empirically confirm what opportunities, challenges and risks can be attributed to the BCT use in tourism. Twelve industry and academic experts have contributed to the Delphi study.

The risks identified have been categorized as societal, technical, financial and legal. Propositions have been made on how these risks can, at least partially, be overcome.

To the best of the authors’ knowledge, it is the first known attempt to study the BCT from the perspective of academic and industry experts. This research is also one of the first to evaluate the risks of the BCT use in tourism. Most risks are identified as not critical and can be addressed as the BCT develops.

区块链技术（BCT）具有为旅游政策和实践做出重大贡献的潜力。随着研究着眼于其应用的机遇和挑战, 对 BCT 的学术兴趣正在迅速增长。然而, 旅游业中 BCT 研究的不足之处在于其概念性。缺乏实证研究阻碍了对如何在旅游业中更广泛地采用 BCT 的理解, 特别是从最小化其风险的角度来看。这项研究代表了第一次从学术和行业专家的角度实证评估 BCT 在旅游业中的潜力的已知尝试。

机会、挑战和风险的初步筛选是通过系统的文献回顾进行的。德尔菲研究法随后被应用于实证确认哪些机会、挑战和风险可归因于 BCT 在旅游业中的使用。 12 位行业和学术专家是德尔菲研究法的主要贡献人员。

已识别的风险分为社会、技术、财务和法律。研究就如何至少部分地克服这些风险提出了建议。

从学术和行业专家的角度研究BCT是已知的第一次尝试。该研究也是最早评估 BCT 在旅游中使用风险的研究之一。大多数风险被确定为不重要的, 可以随着 BCT 的发展而得到解决。

In this paper, experimental and numerical results of a lambda wing have been compared. The purpose of this paper is to study the behaviour of lambda wings using a CFD tool and to consider different numerical models to obtain the most accurate results. As far as the consideration of numerical methods is concerned, the main focus is on the evaluation of computational methods for an accurate prediction of contingent leading edge vortices’ path and the flow separation occurring because of the burst of these vortices on the wing.

Experimental tests are performed in a closed-circuit wind tunnel at the Reynolds number of 6 × 105 and angles of attack (AOA) ranging from 0 to 10 degrees. Investigated turbulence models in this study are Reynolds Averaged Navior–Stokes (RANS) models in a steady state. To compare the accuracy of the turbulence models with respect to experimental results, sensitivity study of these models has been plotted in bar charts.

The results illustrate that the leading edge vortex on this lambda wing is unstable and disappears soon. The effect of this disappearance is obvious by an increase in local drag coefficient in the junction of inner and outer wings. Streamlines on the upper surface of the wing show that at AOA higher than 8 degrees, the absence of an intense leading edge vortex leads to a local flow separation on the outer wing and a reverse in the flow.

Results obtained from the behaviour study of transition (TSS) turbulence model are more compatible with experimental findings. This model predicts the drag coefficient of the wing with the highest accuracy. Of all considered turbulence models, the Spalart model was not able to accurately predict the non-linearity of drag and pitching moment coefficients. Except for the TSS turbulence model, all other models are unable to predict the aerodynamic coefficients corresponding to AOA higher than 10 degrees.

The presented results in this paper include lift, drag and pitching moment coefficients in various AOA and also the distribution of aerodynamic coefficients along the span.

The presented results include lift, drag and pitching moment coefficients in various AOA and also aerodynamic coefficients distribution along the span.

Internet of Things (IoT) as the new technological paradigm has found many applications in different domains. Nowadays, more than 30,000 records related to IoT research can be accessed in Scopus (Scopus.com). Health care is the one of domains which benefits from IoT. However, observations indicate that most active researchers in this area are technical people not health professionals. The purpose of this paper is to understand how health professionals can contribute to the IoT body of knowledge.

IoT professionals are asked to provide their views regarding research concerns, and the collected data are analyzed by phenomenography research methodology.

Findings indicate that health professionals can contribute through providing information, requirement or standards for developing IoT systems or devices. They can also introduce new applications or domains for which IoT is fit.

This paper tries to fill the gap concerning the lack of attention to undertaking IoT-related research from health professionals’ side and highlights ways that health professionals can contribute IoT body of knowledge.

The purpose of this paper is to propose an extensiveness intelligent hybrid model to short-term load electricity forecast that can simultaneously model the seasonal complicated nonlinear uncertain patterns in the data. For this purpose, a fuzzy seasonal version of the multilayer perceptrons (MLP) is developed.

In this paper, an extended fuzzy seasonal version of classic MLP is proposed using basic concepts of seasonal modeling and fuzzy logic. The fundamental goal behind the proposed model is to improve the modeling comprehensiveness of traditional MLP in such a way that they can simultaneously model seasonal and fuzzy patterns and structures, in addition to the regular nonseasonal and crisp patterns and structures.

Eventually, the effectiveness and predictive capability of the proposed model are examined and compared with its components and some other models. Empirical results of the electricity load forecasting indicate that the proposed model can achieve more accurate and also lower risk rather than classic MLP and some other fuzzy/nonfuzzy, seasonal nonseasonal, statistical/intelligent models.

One of the most appropriate modeling tools and widely used techniques for electricity load forecasting is artificial neural networks (ANNs). The popularity of such models comes from their unique advantages such as nonlinearity, universally, generality, self-adaptively and so on. However, despite all benefits of these methods, owing to the specific features of electricity markets and also simultaneously existing different patterns and structures in the electrical data sets, they are insufficient to achieve decided forecasts, lonely. The major weaknesses of ANNs for achieving more accurate, low-risk results are seasonality and uncertainty. In this paper, the ability of the modeling seasonal and uncertain patterns has been added to other unique capabilities of traditional MLP in complex nonlinear patterns modeling.