Primary Research Areas Research Articles

Investigating research in human resource analytics through the lens of systematic literature review

BACKGROUND: In today’s data-driven society, most organizations use data to streamline their processes and achieve greater efficiencies. Human resource management is also affected by this new management style. Human Resource Analytics (HRA) is a novel and emerging method for enhancing human resource management. Due to the novelty of this field, few studies have been published in HRA. OBJECTIVE: The purpose of this paper is to investigate the primary research area of Human Resources Analytics (HRA) and to identify the research gaps. METHODS: This paper employs a systematic literature review methodology and bibliometric approach to analyze 91 pieces of academic literature published between 2008 and 2022. The exclusion and inclusion criteria of the PRISMA framework were used to select the publications. Descriptive analysis, citation analysis, three field plot analysis, and level of study analysis were some of the analysis techniques used. RESULTS: The findings showed that there has been an increase in interest in HRA recently, with most of the research coming from India. Additionally, it was found that most research are carried out at the organisational level. The main areas of research are awareness and comprehension of HRA, HRA software, HRA applications, and barriers to HRA adoption in companies. The primary study needs were determined to include post-implementation effects, an examination of industry acceptance of HRA, and factors influencing the adoption of HRA successfully. CONCLUSION: This paper makes distinctive contribution to the body of knowledge on human resource analytics while also opening up fresh directions for in-depth investigation into the use of human resource analytics in businesses.

79 Role of Neurocritical Care Physicians in Traumatic Brain Injury Systems of Care and Research: Perspectives from Provider Surveys

OBJECTIVES/GOALS: The purpose of this small survey-based study was to characterize the current role of neurocritical care physicians in traumatic brain injury (TBI) systems of care and research. In doing so, we aim to highlight potential roles of neurology providers in the medical management and enhancement of translational science in the field of TBI. METHODS/STUDY POPULATION: Between April and June 2021, a web-based survey was disseminated by email to members of the Neurocritical Care Society. The survey was open to all physician providers. A total of 36 surveys were completed. The survey consisted of 18 questions with pre-defined answer choices. Survey questions aimed to determine areas of practice, primary clinical specialty, hospital practice setting, provider involvement in TBI care, provider involvement in TBI research, and current research roles. RESULTS/ANTICIPATED RESULTS: 92% of survey respondents were in the United States (n=33), representing all national regions. 75% of the physicians were neurocritical care trained (n=27). 69% of providers were practicing in academic institutions while 78% were at sites designated as Level I trauma centers. All respondents managed acute TBI, but 50% served as consultants rather than being the primary service provider. At their sites of practice, 31% of patients were on non-neuroscience services, especially those with non-neurologic traumatic injury. Only 36% reported that TBI protocols were written and adhered to at their site. Only 44% reported that TBI research was performed at their site, while 50% had interest in participating in TBI research. TBI was the primary area of research for 17% of physicians. DISCUSSION/SIGNIFICANCE: This small physician survey highlights heterogeneity in TBI systems-based practice and research roles. Areas of potential improvement include greater involvement of neurocritical care physicians in TBI management, protocol-building and implementation, and TBI research. Reasons for current barriers are multifactorial and will be discussed.

Considerations for AI-EO for agriculture in Sub-Saharan Africa

Abstract With the ever-growing urgency of food insecurity and the threat of climate change, there is increasing interest in using artificial intelligence for Earth observations (AI-EO) for agriculture, particularly in Sub-Saharan Africa (SSA). This paper provides an overview of the primary research areas within AI-EO for agriculture in SSA. %(cropland and crop type classification, field boundary delineation, yield estimation, and pest/disease monitoring). We discuss examples and limitations of current research and opportunities for future work. In addition, we identify ten key considerations for future efforts involving AI-EO for agriculture in SSA.

Radiation-induced acoustic imaging

We explore new ways to generate ultrasound for medical diagnosis and treatment monitoring. Specifically, we use varies radiations (X-ray, proton, and electrical field) to treat diseases, simultaneously it will produce ultrasound waves for image-guided interventions. This talk will cover three primary research areas: (1) x-ray-induced acoustic computed tomography (XACT) for precision radiotherapy and radiology; (2) proton-induced acoustic imaging for proton therapy guidance; and (3) electroacoustic tomography (EAT) for irreversible electroporation (IRE) monitoring. Prospects and challenges for the clinical implementation of these techniques will be discussed. The successful development of these technologies will expand the current clinical paradigm towards precision medicine.

Characterization of Global Research Trends and Prospects on Moyamoya Disease: Bibliometric Analysis

Moyamoya disease (MMD) is a rare cerebrovascular disease in neurology. This study investigates the literature related to MMD from its discovery to the present and identifies research levels, achievements, and trends. All publications on MMD from its discovery to present were downloaded from the Web of Science Core Collection on September 15, 2022 and bibliometric analyses were visualized by HistCite Pro, VOSviewer, Scimago Graphica, CiteSpace, and R language. There were 3414 articles in 680 journals by 10,522 authors in 2441 institutions and 74 countries/regions worldwise are included in the analyses. Since the discovery of MMD, output of publications has shown an upward trend. Japan, the United States, China, and South Korea are 4 major countries in MMD. The United States has the strongest cooperation with other countries. China's Capital Medical University is the output-leading institution worldwide, followed by Seoul National University and Tohoku University. The 3 authors with the most published articles are Kiyohiro Houkin, Dong Zhang, and Satoshi Kuroda. World Neurosurgery, Neurosurgery, and Stroke are the most recognized journals for researchers. Hemorrhagic moyamoya disease, susceptibility gene, and arterial spin are the primary focus areas of MMD research. "Rnf213,""vascular disorder," and "progress" are the top keywords. We analyzed publications of global scientific research on MMD systematically by bibliometric methods. This study can provide one of the most comprehensive and accurate analyses for MMD scholars worldwide.

Virtual Scene Construction of Wetlands: A Case Study of Poyang Lake, China

Due to the complexity of wetland ecosystems, wetlands have a wide area of alternating land and water zones and complex vegetation composition, making it challenging to achieve dynamic displays of virtual wetland scenes using three-dimensional modeling. This study proposes a workflow of game engine-based virtual wetland scene construction for the rapid modeling of virtual wetland scenes. The virtual wetland scene construction work utilized Poyang Lake as the primary research area. It integrated unmanned aerial vehicle data collection technology and geographic information technology with 3D (three-dimensional) modeling of wetland elements and scene program modeling of the game engine to complete the construction and dynamic development of virtual wetland scenes. In addition, it used various virtual reality technologies to display the virtual wetland scene. The virtual scene of Poyang Lake combined with actual data was more realistic and had higher simulation. In reality, the digital wetland scene of Poyang Lake realizes multiple forms of virtual experience and provides users with a profoundly immersive virtual experience. This comprehensive virtual scene workflow in the study can serve as a technical resource for building 3D scenes. It can also provide a technical reference for the digital twin watershed project of Poyang Lake, which has practical application value.

Overview of the synergistic use of radiotherapy and immunotherapy in cancer treatment: current challenges and scopes of improvement

ABSTRACT Introduction Oncological treatments are changing rapidly due to the advent of several targeted anticancer drugs and regimens. The primary new area of research in oncological medicine is the implementation of a combination of novel therapies and standard care. In this scenario, radioimmunotherapy is one of the most promising fields, as proven by the exponential growth of publications in this context during the last decade. Areas covered This review provides an overview of the synergistic use of radiotherapy and immunotherapy and addresses questions like the importance of this subject, aspects clinicians look for in patients to administer this combined therapy, individuals who would benefit the most from this treatment, how to achieve abscopal effect and when does radio-immunotherapy become standard clinical practice. Expert opinion Answers to these queries generate further issues that need to be addressed and solved. The abscopal and bystander effects are not utopia, rather physiological phenomena that occur in our bodies. Nevertheless, substantial evidence regarding the combination of radioimmunotherapy is lacking. In conclusion, joining forces and finding answers to all these open questions is of paramount importance.

Numeričko ispitivanje uticaja konfiguracije svećica na performanse u cilindru motora

A numerical investigation of combustion inside single and twin-spark engines was performed to study the effect of a spark plug, positions and spark timings on engine performance. Improvement in engine performance is one of the automotive industry's primary research areas. Consequently, the study's results can be utilised to optimise engine configurations to achieve maximum performance. The investigation was conducted using a finite volume-based open-source software, OpenFOAM, for computational simulations. Simulations were conducted using the XiEngineFOAM solver with a transport equation for modelling flame fronts. The Standard k-e turbulence model was used to predict turbulence parameters. The simulation was conducted for compression and power stroke (crank angle between - 180° and 180°), assuming an even distribution of the air-fuel mixture within the pentroof 4-valve engine cylinder. Simulations were conducted for four cases, including variations in the position and timing of spark plugs in single-spark and twin-spark engines. According to the results of the simulations, the single-spark engine provides the best performance when the spark plug is ignited early and positioned at the cylinder's centre. When placed at an optimal position determined by flame travel and collision, the twin-spark engine gives the best performance at the highest difference between the spark timings of the two spark plugs.

New frontiers in inflammation: from translational research to clinic (information about the 15th World Congress on Inflammation (WCI2022)).

The following provides a summary of the 15th World Congress on Inflammation (WCI2022), which took place in Rome (Italy) from June 5 to 8, 2022. Presented are the main trends and most promising research developments in the field of inflammation, including identification of cellular and molecular mechanisms and investigation of new pathogenetic pathways, target molecules, genetic mechanisms, and new therapeutic strategies. In addition, described are the primary areas of research engaged in by leading scientific groups and national societies from various countries in the field of inflammatory pathology mechanisms.

An Integrated Methodology for Bibliometric Analysis: A Case Study of Internet of Things in Healthcare Applications.

This paper presents an integrated and easy methodology for bibliometric analysis. The proposed methodology is evaluated on recent research activities to highlight the role of the Internet of Things in healthcare applications. Different tools are used for bibliometric studies to explore the breadth and depth of different research areas. However, these Methods consider only the Web of Science or Scopus data for bibliometric analysis. Furthermore, bibliometric analysis has not been fully utilised to examine the capabilities of the Internet of Things for medical devices and their applications. There is a need for an easy methodology to use for a single integrated analysis of data from many sources rather than just the Web of Science or Scopus. A few bibliometric studies merge the Web of Science and Scopus to conduct a single integrated piece of research. This paper presents a methodology that could be used for a single bibliometric analysis across multiple databases. Three freely available tools, Excel, Perish or Publish and the R package Bibliometrix, are used for the purpose. The proposed bibliometric methodology is evaluated for studies related to the Internet of Medical Things (IoMT) and its applications in healthcare settings. An inclusion/exclusion criterion is developed to explore relevant studies from the seven largest databases, including Scopus, Web of Science, IEEE, ACM digital library, PubMed, Science Direct and Google Scholar. The study focuses on factors such as the number of publications, citations per paper, collaborative research output, h-Index, primary research and healthcare application areas. Data for this study are collected from the seven largest academic databases for 2012 to 2022 related to IoMT and their applications in healthcare. The bibliometric data analysis generated different research themes within IoMT technologies and their applications in healthcare research. The study has also identified significant research areas in this field. The leading research countries and their contributions are another output from the data analysis. Finally, future research directions are proposed for researchers to explore this area in further detail.

Examining the Current Status and Emerging Trends in Continuous Authentication Technologies through Citation Network Analysis

Continuous Authentication (CA) technologies enable users to be authenticated beyond just the point of entry. In this article, we conduct a comprehensive review of over 2,300 articles to (a) identify the main components of CA research to date, and (b) explore the current gaps and future research directions. Through a Citation Network Analysis (CNA), we identified that there are currently three primary focus research areas on CA - Keystroke Dynamics; Mouse Movements; and Mobile Device Touch, as well as identify an emerging trend in more recent studies on multi-modal CA authentication which utilises the numerous sensors that are embedded in modern mobile devices. This study also highlights the current gaps in the literature such as the need for a consensus over how to evaluate the application and utility of CA, and the need to examine the feasibility of CA technologies that currently exist based on more use case studies.

Equivalence in international business research: A three-step approach

A primary research area within the field of international business (IB) is to establish the extent to which concepts, theories, and findings identified in one country are applicable to other contexts and which are unique and cannot be found in other contexts. Researchers in IB acknowledge the importance of the context in their studies, but the practice of assessing equivalence (or invariance) is not widely diffused within the community. We first discuss the components of equivalence (construct, method, and item equivalence), and we offer a three-step approach to address equivalence in the writing and revision of a paper. We aim to help editors, reviewers, and researchers produce more reliable research and navigate the tension between generalizable relationships and context-specific ones, both theoretically and empirically, before performing analysis and hypothesis testing. We then apply equivalence to the construct of firm economic performance as a case study, but the same logic can be applied to other constructs as well.

ИЗ ФОЛКЛОРА СРБА У ДУНАВСКОЈ КЛИСУРИ

The author of this paper conducted field research on the traditional culture and folklore of Serbs in the Danube gorge in June 2017. within the project Research of the History and Culture of Serbs in Romania. Field conversations included, in addition to topics related to traditional culture, oral history, everyday life and the like. The scientific interests and the primary area of research of the author conditioned the more intensive introduction of issues related to verbal folklore, and a relatively wide corpus of folklore material was obtained. Attention is focused on the folklore material recorded in the interview with the interlocutor from Belobreška: ballads, wedding songs, love songs. The texts are commented through the analysis of stylistic and motive characteristics and comparison with previously published variants.

Deep learning for manufacturing sustainability: Models, applications in Industry 4.0 and implications

Recent advancements and developments in artificial intelligence (AI) based approaches have shifted the manufacturing practices towards the fourth industrial revolution, considered as Industry 4.0 practices. A positive impact of AI-based techniques on sustainability can be seen in manufacturing organisations’ at the system, product and process levels. Adopting AI-based strategies in manufacturing improves decision making, productivity and system performance. Despite sustainability and other benefits, the adoption of AI-based approaches in manufacturing organisations is still limited due to employees’ knowledge and digital skills. In the present time, due to the digitalisation of manufacturing activities, intelligent sensors, and supply chain activities, industries are facing challenges with the generation of high volume, different variety and velocity of data. This data can be helpful for manufacturing organisations to enhance their performance and sustainability. However, managing this big data is still a significant challenge due to a lack of knowledge and limited literature. Deep learning (DL) based models can be a suitable choice to provide advanced analytics tools for manufacturing data processing and analysis. However, literature on the DL is still limited in the manufacturing context with its relationship to sustainability. The present study discusses the evolution of DL approaches in manufacturing and different DL-based models. This study also highlights how DL-based approaches can enhance the sustainability performance of industries. In the study, primary research areas, i.e., fault diagnosis, quality management, and predictive maintenance, have been discussed. Finally, a conceptual DL-based framework is proposed for the manufacturing industries to enhance their sustainability performance in manufacturing activities.

The 28th Annual Prostate Cancer Foundation Scientific Retreat report.

The 28th Annual Prostate Cancer Foundation (PCF) Scientific Retreat was held virtually over 4 days, on October 28-29 and November 4-5, 2021. The Annual PCF Scientific Retreat is a leading global scientific conference that focuses on first-in-field, unpublished, and high-impact basic, translational, and clinical prostate cancer research, as well as research from other fields with high probability for impacting prostate cancer research and patient care. Primary areas of research discussed at the 2021 PCF Retreat included: (i) prostate cancer disparities; (ii) prostate cancer survivorship; (iii) next-generation precision medicine; (iv) PSMA theranostics; (v) prostate cancer lineage plasticity; (vi) tumor metabolism as a cancer driver and treatment target; (vii) prostate cancer genetics and polygenic risk scores; (viii) glucocorticoid receptor biology in castration-resistant prostate cancer (CRPC);(ix) therapeutic degraders; (x) new approaches for immunotherapy in prostate cancer; (xi) novel technologies to overcome the suppressive tumor microenvironment; and (xii) real-world evidence and synthetic/virtual control arms. This article provides a summary of the presentations from the 2021 PCF Scientific Retreat. We hope that sharing this knowledge will help to improve the understanding of the current state of research and direct new advances in prostate cancer research and care.

Task offloading in fog computing: A survey of algorithms and optimization techniques

The exponential growth in Internet of Things (IoT) devices and the limitations of cloud computing in terms of latency and quality of service for time-sensitive applications have led to the unfolding of the efficient middleware technology called fog. Fog computing circumvents the limitations of the cloud by creating a seamless continuum between the things/IoT/end-user devices and the cloud and reducing the effective distance. However, fog computing faces challenges for offloading tasks for their remote computation at some level. Hence, the optimality of task offloading is the primary research area in fog computing. Several contemporary papers exist on this important subject. The research gap in reviewing all these task offloading algorithms has motivated us for their presentation in the form of a detailed survey in this paper. There exist some survey papers which deal with the task offloading. However, none of them has covered the basics of optimization techniques and their solution approaches. The primary objective of this paper is to provide the readers with a complete overview of the journey from a task offloading idea to its mathematical problem formulation and finally to its solution with all details of optimization techniques. We begin by introducing fog computing, and task offloading process followed by several task offloading factors governing decision-making process and their surveys. A section is fully dedicated to the survey of offloading objectives with examples. We also present several optimization approaches used in task offloading. Finally, the last section dedicates to the challenges and future direction in fog computing. The outcomes of the survey will benefit readers in learning the optimization used in task offloading, and it will also provide them a systematic design of offloading scheme with specific objectives.

Facial expression recognition using Eigen face approach

Emotion recognition via identification of face emotion is the primary areas of research between human and the machine communication. In order to identify facial emotion, one device must locate different variabilities of human face including color, stance, emotions, direction, and so on. Initially, the human facial expressions are recognized by the various features such as eye, nose, mouth, etc. must be detected and then classified using an appropriate expression recognition classifier compared to the qualified results. In this analysis a method of identification of human facial expression is modeled on its own hands. The approach proposed uses the color model HSV (Hue-Saturation-Value) to identify the facial image. Principal Component Analysis reduce the size of the space, later the test image is projected on the space. The Euclidean distance between the test image and the mean individual of the training data and categorized the phrases. For testing purposes, a standardized dataset is used. The device uses the gray representations of the face to categorize five simple emotions including surprise, sadness, anxiety, indignation and satisfaction.

Development Strategy of College Sports Information Management System Using Data Mining in Mobile Internet Environment.

A strong basis has been set for the digitization of school management by the growth of big data and the Internet. However, there is not specialised software that can be used in schools to handle teaching materials and carry out teaching activities, particularly in school physical education. Most teachers struggle with significant information management issues in the conventional college sports management information system. Along with people's interest in physical education in colleges and universities, the study of the college sports management information system's development plan has emerged as the primary research area in the present day. The use of data mining in the development strategy of the sports management information system was therefore considered in conjunction with the actual situation of school sports information management. The experiment also introduced and provided a detailed explanation of the algorithm used in data mining. To fully explore the system strategy's development impact was the specific goal. In order to realise the management function of the sports management information system, serve the information management of each school, increase information management efficiency by 6.58%, and improve user satisfaction; data mining was introduced into the development strategy of management information system through the discovery of experimental data.

Conglomerate Energy Efficient Elgamal Encryption Based Data Aggregation Cryptosystems in Wireless Sensor Network

Wireless sensor networks (WSN) are growing rapidly since the past decade mainly due to its efficiency and Ad-Hoc feature. The data aggregation has been extensively employed in WSN that also impact on the data transferring between the sensor nodes. The security issues, data integrity and confidentiality become vital during the deployment of sensor network in a hostile environment. The entire network comprises of sensors, base stations, gateways and nodes which are connected for the purpose of digital transmission. Many existing works have been evolved to address the security issues in WSN but all focused only on basic security features but lack to obtain reliable and effective results in terms of parameters like energy consumption, packet delivery ratio, and computational cost. This paper focussed on the primary research area of data aggregation and the mode of transmission in an energy efficient way without congestion. To obtain the objective, an integration of Conglomerate ElGamal energy efficient protocol has been employed and the performance of the proposed system are evaluated. Since the resource constraint nodes of the wireless sensor network requires less energy to cope up with limited battery power, the main purpose of the work is to build an efficient security mechanism that enhances the performance of the network with less energy, minimum delay, and maximum throughput. The performance parameters like packet delivery ratio, throughput, estimation of alive nodes and dead nodes for different rounds has been performed in the study. Furthermore, the effectiveness of the proposed system has been compared with state of art methods in terms of residual energy and depicted that deliberates the superior performance of the presented framework

A Design Task for Sivas Grand Mosque’s Minaret: Vertical Construction/Formal Articulation/Visual Stimuli

As well as a design process, experimental practices in architectural education are associated with the analytical approaches of visual thinking and visual reasoning. The main purpose of this study was to explore creative methods for devising a vertical construction through visual reasoning. In terms of experimental practices, design research is based on exploration while the primary research area in architecture is reframed by constantly renewed approaches. Accordingly, the hypothesis of this study was that creative methods would improve when the creation of a vertical construction in architectural education is nourished by visual stimuli. The study searched for a construction that plasticized the vertical spatiality of Sivas Grand Mosque’s minaret. The method was shaped by a prerequisite dialogue that rests on visual stimuli. The expected outcome of this dialogue was that the minaret as a pure form would be subjected to an abstraction and, a design proposal then developed for its current structural problems. The results indicated a two-fold appreciation of design. First, when the minaret was maintained within the idea of stabilization rather than being construed as a pure form, the search for a creative method of vertical construction was handled in the context of static preservation. Second, when Sivas Grand Mosque’s minaret as an imaginary design tool was construed as a pure form and the abstraction level increased through visual reasoning, the outcomes gradually demonstrated an approach akin to experimental practices