Search

The complex process of online information search has been of great interest to academics and practitioners, regarding its motivation, triggers, phases, and various aspects of user search behaviour. Web search spanning multiple sessions has been studied, including users switching between devices. The study presented in this paper aims to critically analyse two decades (2000 – 2020) of research on cross-session and cross-device search. A systematic literature review of 29 journal papers and peer reviewed academic conference proceedings was conducted. The main results were extracted, synthesised, and presented. Topical (focus and terminology), methodological (data collection, sample size, sample type, and countries studied) and bibliometric (publication outlet and citations) aspects of online information search were evaluated and described. The paper identifies keywords for effective literature searches and adds new insights about effective research methods and sampling, the most cited publications and most influential authors in this field and the possibility of conducting interdisciplinary research. Both scholars and practitioners can use this study to gain a deeper understanding of the cross-session and cross-device search research agenda. Future research suggestions inform researchers about issues that warrant further attention. Refereed/Peer-reviewed

Infections encompass a set of medical conditions of very diverse kinds that can pose a significant risk to health, and even death. As with many other diseases, early diagnosis can help to provide patients with proper care to minimize the damage produced by the disease, or to isolate them to avoid the risk of spread. In this context, computational intelligence can be useful to predict the risk of infection in patients, raising early alarms that can aid medical teams to respond as quick as possible. In this paper, we survey the state of the art on infection prediction using computer science by means of a systematic literature review. The objective is to find papers where computational intelligence is used to predict infections in patients using physiological data as features. We have posed one major research question along with nine specific subquestions. The whole review process is thoroughly described, and eight databases are considered which index most of the literature published in different scholarly formats. A total of 101 relevant documents have been found in the period comprised between 2003 and 2019, and a detailed study of these documents is carried out to classify the works and answer the research questions posed, resulting to our best knowledge in the most comprehensive study of its kind. We conclude that the most widely addressed infection is by far sepsis, followed by Clostridium difficile infection and surgical site infections. Most works use machine learning techniques, from which logistic regression, support vector machines, random forest and naive Bayes are the most common. Some machine learning works provide some ideas on the problems of small data and class imbalance, which can be of interest. The current systematic literature review shows that automatic diagnosis of infectious diseases using computational intelligence is well documented in the medical literature.

In order to adopt specific agile methods and to accommodate lean principles, many organizations need to tailor their processes. Different frameworks supporting and guiding the agile transition and adoption process exist in the literature. However, there is a demand for specific guidelines on the different circumstances influencing agile adoption. This paper provides a Systematic mapping of the available frameworks, issues and factors affecting a successful agile transition and adoption process. Twenty-eight primary studies have been considered. The results are presented according to the three research questions. Firstly, nine systematic approaches and frameworks for agile transition and adoption are analyzed. Secondly, different issues related to the agile transition and adoption process are gathered, compared and synthesized in the following five categories: pre-transformation activities, obstacles and results, stages and activities, agile practices and situational factors. Finally, a list of 154 situational factors affecting the agile transition and adoption process is proposed.

A simulation model based on parallel systems is established, aiming to explore the relation between the number of submissions and the overall standard of academic journals within a similar discipline under peer review. The model can effectively simulate the submission, review, and acceptance behaviors of academic journals in a distributed manner. According to the simulation experiments, it could possibly happen that the overall standard of academic journals deteriorates due to excessive submissions., Comment: This paper is already published in the journal IEEE Access and its copyright is fully open. The title was adjusted according to the review comments

Healthcare systems are transformed digitally with the help of medical technology, information systems, electronic medical records, wearable and smart devices, and handheld devices. The advancement in the medical big data, along with the availability of new computational models in the field of healthcare, has enabled the caretakers and researchers to extract relevant information and visualize the healthcare big data in a new spectrum. The role of medical big data becomes a challenging task in the form of storage, required information retrieval within a limited time, cost efficient solutions in terms care, and many others. Early decision making based healthcare system has massive potential for dropping the cost of care, refining quality of care, and reducing waste and error. Scientific programming play a significant role to overcome the existing issues and future problems involved in the management of large scale data in healthcare, such as by assisting in the processing of huge data volumes, complex system modelling, and sourcing derivations from healthcare data and simulations. Therefore, to address this problem efficiently a detailed study and analysis of the available literature work is required to facilitate the doctors and practitioners for making the decisions in identifying the disease and suggest treatment accordingly. The peer reviewed reputed journals are selected for the accumulated of published research work during the period ranges from 2015 – 2019 (a portion of 2020 is also included). A total of 127 relevant articles (conference papers, journal papers, book section, and survey papers) are selected for the assessment and analysis purposes. The proposed research work organizes and summarizes the existing published research work based on the research questions defined and keywords identified for the search process. This analysis on the existence research work will help the doctors and practitioners to make more authentic decisions, which ultimately will help to use the study as evidence for treating patients and suggest medicines accordingly.