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Citations between papers and patents reflect transfer of knowledge between science and technology. Patents commonly cite papers but papers rarely cite patents. Here, we identified 6,033 paper‐to‐patent citations in a collection of 1.5 million PubMed Central open access articles. These citing papers and cited patents contained 132,536 paper‐to‐paper, 200,339 patent‐to‐patent, and 36,342 patent‐to‐paper citations. These four citation datasets were used to model the temporal patterns of knowledge transfer within and across patents and papers. We found that the cited patents are generally much older than the cited papers, regardless of whether they are cited by papers or patents. Discipline, affiliation type, and self‐citation also affect the age of the cited papers and patents. The recency of the citations partly explains the asymmetry in citations between papers and patents. [ABSTRACT FROM AUTHOR]

It is no doubt that now a day's Artificial intelligence (AI) is anemergent technology in the digital marketing industry. Commercial Artificial Intelligence (AI) is an important topic for research. Artificial intelligence is growing quickly more sensitive and popular in the digital marketing field due to the capacity of advertisers to employ it efficiently. In order to provide the capability of the highest level of originality and efficiency in digital marketing ground, artificial intelligence techniques are more fruitful for customers, marketers and, retailers. This paper depicts the impact of artificial intelligence techniques on advertising on a diminutive and average scale in the digital marketing field. Ad targeting, predictive analysis, voice search are different artificial intelligence techniques for digital marketing purposes throughout the consumer life cycle. The topic of Artificial Intelligence (AI) in digital marketing itself can be outsized enough to verifyeliminating the area of research into precise application and application frameworks.However, our objective in this paper is to provide a comparative analysis of the digital marketing field using artificial intelligence techniques and to propose some specific guidelines based on different parameters, tools, and frameworks.Through this paper, we have observed thelast five years (2016-2021) research trends which reflect that out of different parameters, customer relationship and promotional activity are the most widely used parameter in the digital marketing field. Another significant point is, most of the research identifies that artificial intelligence is a compulsory technique used in the modern digital marketing field. Some data collection and data analysis tools are also being used in this field using artificial intelligence techniques. Our research methods try to get a complete view on artificial intelligence (AI) Marketing were multifaceted but were very focused on secondary research sources. Finally in this paper, we propose some recommendationsthat will offer better Artificial Intelligence (AI) implementation in the digital marketing field. [ABSTRACT FROM AUTHOR]

This paper complements an earlier (2019) literature review on workarounds in information systems research by including research that has influenced or been published in core IS outlets during the last five years (2018-2022). Our study captures research that strengthened, widened, and challenged theoretical insights from the previous review. It also provides additional insights and develops seven themes of theoretical insight. The 31 new papers and our updated analysis are most evident in the three themes: Workarounds and power, Temporality of workarounds, and Managing workarounds. We also found additional studies using the term 'workaround' differently to the extent that they have not applied the term to the same empirical phenomena, which questions the validity of some theoretical claims. We also found significantly more studies that used quantitative data-collection methods than the previous review. [ABSTRACT FROM AUTHOR]

Agent-based modeling and simulation (ABMS) is a computational modeling technique that has been used in various fields of science with growing interest. In economics, ABMS has been used to model a wide range of systems, from financial markets to transportation systems. The goal of this paper is to explore the usage of agent-based modeling and simulation in economics, using bibliometric analysis techniques on data from Web of Science platform. The authors collected data on ABMS usage in economics for over five thousand papers from Clarivate Analytics Web of Science databases in terms of publishing frequency, journal bibliometric data, field of application and productivity by country for the period 2000-2022. Journals with highest productivity within this topic are The Journal of Artificial Societies and Social Simulation, Physica A-Statistical Mechanics and its Applications, and PLOS ONE. [ABSTRACT FROM AUTHOR]

Many road and rail tunnels have been constructed in Australia over the past 20 years. Tunnels have become deeper, shallower (low cover), wider, and increasingly complex in shape and arrangement. At the same time, technological advances have transformed construction tunnel instrumentation and monitoring, data collection, interpretation and stakeholder collaboration. Monitoring is a key input in the validation of design assumptions and analyses, as well as to forward predict ground behaviour. This paper presents the development of best practice tunnel instrumentation and monitoring in Australia, achieved via a trifecta of good monitoring design, monitoring team, and review process. Various monitoring philosophies and systems are discussed, with their capabilities and limitations for ensuring safe tunnel construction. Further, this paper discusses the development of a professional monitoring team with the appropriate skills and expertise for monitoring implementation. Lastly, this paper describes the evolution of a robust and formal monitoring review process in construction, involving the designer and the tunnel contractor, and how this process has led to improvements in safety and efficiency of the tunnelling practice. [ABSTRACT FROM AUTHOR]

when conducting business and management research, the most common strategy employed for collecting primary data is either interviews or questionnaires (or both). When questionnaires are used to collect primary data a very common approach used is to construct questions which can be called Likert-type questions or Likert scales. Numbers are allocated to the question responses of each question. Often, this is followed by performing arithmetic or statistical operations on the allocated numbers. In many cases encountered by the author, the analysis has even included techniques such as parametric statistics and factor analysis. This paper explains why such simplistic approaches are completely invalid and should never be used. It goes on to explain how analysis can be done whilst avoiding typical hazards. Often, the writers of such papers do not understand or explain levels of measurement. Of course, Likert scales are at an ordinal level of measurement which would normally preclude the use of arithmetic, statistical, factor analysis techniques there is an additional problem of reliability because different people will interpret terms such as strongly disagree and disagree, differently. Likert was aware of these problems when writing the original paper in 1932 although at that time the term "levels of measurement" was not in use. This paper provides approaches and suggestions for avoiding the problems of data analysis when using Likert-type questions. This paper should be of assistance to those who intend to use Likert-type questions in the questionnaire. [ABSTRACT FROM AUTHOR]

The Engineering Libraries Division (ELD) of ASEE has been in existence since 1967, and since then, members of this division have been active participants in the programs of the ASEE annual conference. In this survey, we will present a descriptive analysis of articles published in the Proceedings of ASEE. Data was collected from the ELD webpage, the ASEE Proceedings webpage, and from Ei Compendex for the last 40 years (1976-2016). This study is based on bibliometric analysis and includes the use of visualization techniques with Sci2 Tool software. Although it is recognized that publishing policies for the Proceedings by the ELD Division and ASEE have changed throughout the years, this study aims to present an analysis of the papers published during this period. [ABSTRACT FROM AUTHOR]

EMG is a medical technique that measures muscle response or electrical activity in response to a nerve’s stimulation of the muscle [10]. In this paper we have classified multiple hand gestures using small number of electrodes. This report aims to review current use of EMG based control system and explain the existing challenges. The stages involved includes data acquisition, feature extraction, classification and controller. Some of the application includes Arm rehabilitation, game controller, wheel chair controllers, etc. [ABSTRACT FROM AUTHOR]

In this research paper Understanding the Dynamics of Consumer Behaviour, A study of how the customer recognise there needs before buying process in the Indian Market context is consider. This study is based on primary data collection. The conclusion and finding are based on the data which are collected through various category of customer who have different gender, different age, different education, different income, and different environment. In this research paper we find out that exactly or which elements are used to decide need recognition by the consumer in buying process. The features of Indian customer are very different as compare to other customer. So in this research I am doing the research on the one of the element of buying process that is the need recognition. For this research paper is based on primary data, which was collected through google form from various parts of the country. This research is mostly useful for manufacturer as well as marketing management teams for selecting the proper marketing mix policy for the fulfilment of their objectives in the best way. [ABSTRACT FROM AUTHOR]

Risks related to the ground are generally regarded as critical technical risks on tunnelling projects. In the context of this paper, ground related risks cover geotechnical, hydrogeological, and environmental risks related to the ground. Transportation related tunnelling projects in New South Wales are generally procured with contracts that assign all ground related risk to the contractor. In more recent times, instances of incentivised target cost procurement models, where risk allocation is more generally shared, have been utilised. However, within the contractor's team, it is often not clear who owns ground related risk. For instance, is the risk related to a design issue or a construction issue; and where there are numerous designers used on projects, which designer is responsible for managing a particular risk? Recent litigation (NSWSC, 2016) and prosecutions (ICNSW 2009a, 2009b, IRCNSW 2012a, 2012b, 2012c) have identified a lack of clarity as to how ground related risk has been managed on projects. This lack of clarity has resulted in significant incidents from which lessons should be learned and applied. This paper discusses an approach applied to the management of ground related risk on road tunnels in New South Wales. The approach includes identification of all credible ground related hazards that are assessed as project risks with mitigation strategies identified for risks that could impact the project or third-party infrastructure. The approach also requires the workflow associated with ground related construction processes from data collection through to data validation to be identified; and accountabilities and responsibilities assigned for each stage in the workflow. [ABSTRACT FROM AUTHOR]

This paper depends on the modern standard 4.0 conventions used at each period of crucial industrial applications. In view of ping demand reaction, idleness and throughput, examination is made between their upgraded exhibition in businesses like oil and gas, vitality utility, media transmission and some more industries. Likewise this paper outlines the advancement of IoT (Internet of Things) from HTTP (Hyper Text Transfer Protocol) to lIoT(Industrial Internet of Things) for strategic models. This paper manages examination of proficient convention to deal with dynamic contributions according to SCADA (Supervisory Control and Data Acquisition). The Trial outcomes is acquired through demo industrial set up and recognized through Message Queuing Telemetry Transport (MQTT) and resultant checked through Wireshark and LCD in real-time. [ABSTRACT FROM AUTHOR]

In 2019, the TL0200559 project entitled "Safe Cities for Pedestrians and Seniors" was launched. Part of the solution of this project was also a survey and analysis of the use of pedestrian roads in selected cities. The town of Chotěboř was chosen for pilot processing. In the first half of 2019, a questionnaire was compiled for the questionnaire survey. At the same time, a local survey was conducted. In October and early November, data were collected by a questionnaire survey. In the following five months, the digitization of paper forms of the questionnaires took place. Their evaluation was interrupted by ongoing quarantine measures due to SARS-CoV-2 (Covid-19). In 2021, quarantine measures (especially the return of children and students to full-time school attendance) were relaxed to the extent that it was possible to return to the standard scientific research work and analyze and verify the obtained data by re-conducting local surveys. The procedure for compiling the questionnaire for this survey, the course of the actual data collection, and the results of this pilot survey are presented in this paper. [ABSTRACT FROM AUTHOR]

The practices of data collection in training sets for Automatic Music Generation (AMG) tasks are opaque and overlooked. In this paper, we aimed to identify these practices and surface the values they embed. We systematically identified all datasets used to train AMG models presented at the last ten editions of ISMIR. For each dataset, we checked how it was populated and the extent to which musicians wittingly contributed to its creation. Almost half of the datasets (42.6%) were indiscriminately populated by accumulating music data available online without seeking any sort of permission. We discuss the ideologies that underlie this practice and propose a number of suggestions AMG dataset creators might follow. Overall, this paper contributes to the emerging self-critical corpus of work of the ISMIR community, reflecting on the ethical considerations and the social responsibility of our work. [ABSTRACT FROM AUTHOR]

Engineering Programs and the Writing Assessment Center of Washington State University Vancouver conducted a 4 day summer professional development workshop for a group (n=12) of faculty and graduate teaching assistants, who instruct first-year composition and introductory engineering laboratory courses. This professional workshop was designed to provide professional development on rhetoric and writing transfer, to build community of practice among instructors from English and engineering to share a passion for engineering students' writing, and to complete the writing transfer module draft so the participants can use them in the academic year of 2016-2017. The workshop contents consisted of three parts, which include 1) rhetorical writing review and rubric development for students' first-year composition course research papers and engineering lab reports, 2) student writing assessment using the developed rubric both collaboratively and individually, and 3) the instructional materials development to implement writing for transfer into the participants' courses. The external evaluation team collected data at the beginning and end of the 4-day workshop as well as at the end of every day of the workshop in order to accurately assess the development on a day to day basis as well as the overall impact of the workshop. Through days one, two, and three the level of agreement steadily increased for both disciplinary groups (English and engineering) with participants reporting in the post survey that they strongly agreed or agreed that they had learned rhetorical elements and writing pedagogy. [ABSTRACT FROM AUTHOR]

This paper is both descriptive and analytical in nature. The main objective of the present paper is to identify the reasons for opting taxis via transportation network apps over the traditional taxis. Further, an attempt was made to assess the significant difference in the user's satisfaction towards the services of the transportation network apps based on their demographic profile. Attempt was also made to identify the services of the transportation network apps, in which customers are most satisfied and least satisfied. Data were collected from both secondary and primary sources. The Secondary data were collected from various books, journals, websites etc. The Primary data were collected from 60 user of the Transportation Network Apps. Purposive sampling method was adopted to collect the data. A well-structured questionnaire was designed for the purpose. Collected data were analysed using various statistical and graphical tools like percentages, mean, standard deviation, independent sample t-test, one-way ANOVA, bar chart etc. The results of the study indicate that most of the users opted for App-based ride-hailing services over the traditional taxis because of the different online payment modes available and because they need not even have to make a call for booking the taxi. It was also found that there is statistically significant difference in user satisfaction towards the services provided by transportation network apps based on the frequency of travel. In addition to this, it was found that frequent travellers are less satisfied of the services as compared to that of the infrequent travellers. The research also revealed that the users are most satisfied of home screen layout feature of the transportation network apps. Whereas, they are least satisfied in the offers and discounts being offered by transportation network apps. [ABSTRACT FROM AUTHOR]

The aim of this paper is to innovate the role of data in sustainable production chain management by identifying drivers, challenges and future solutions related to sustainability and data utilisation. The research data was collected from a literature review, a sustainability seminar entitled “Strong Stronger Responsible” and interviews with company representatives. The interviewees represented operators in the renewable forest and chemical industries and the companies serving them. This study examines sustainability data on the wood fibre-based production chain, from the forest to the consumer. The results show that for sustainability data, production chains have challenges and development needs in terms of indicators, data collection, quality and sharing. Sustainability data should guide decision making in processes at all levels of the organisation, as well as in the production chain. [ABSTRACT FROM AUTHOR]

Database maintenance and migration are critical but under‐supported activities in libraries, archives, museums (LAMs), and other scholarly spaces. Existing guidelines for digital curation rarely account for the maintenance needed to keep digital curation infrastructures functioning over time. Though many case studies have been published describing individual instances of migration, there has been little generalizable research done in this area. Thus, it is challenging to understand overall trends or best practices in this space. We bridge this gap by conducting an integrative literature review of papers describing database migrations and maintenance in LAMs and other scholarly contexts. By qualitatively coding 75 articles from 58 publication venues, we identify common motivations for database migrations and maintenance actions. We find that databases are migrated to support changing user needs as well as to ward off technological obsolescence; we also find that common challenges include schema crosswalking and a need for data cleaning. Practitioners describe community collaboration as key in surmounting these challenges. Through this integrative review, we build a base for further best practices development and identify a need to better model database curation as part of the digital curation lifecycle. [ABSTRACT FROM AUTHOR]

This study analyzes the relation between author affiliation reputation and uncitedness. We use 2015 U.S. News Best Global University Subject rankings as representative of affiliation reputation and collect uncited papers from 24 journals in six subjects from WoS. Preliminary correlation analysis results indicate that: (1) there is a significant correlation between affiliation reputation and uncitedness. (2) their relation is negatively and weakly correlated. And secondary data collection and correlation analysis proved that relation between affiliation reputation and uncitedness vary in different subjects. The findings of this study would attract scientists' attention to avoid Matthew Effect and focus more on research papers rather than reputation when citing references. [ABSTRACT FROM AUTHOR]

Despite growing interest in the rising popularity of electronic word of mouth (EWOM), many unanswered questions about its effects on online brand outcomes still need to be answered. This paper explores the interactive impact of message characteristics (valence, credibility and format) on online brand evaluation and engagement. We tested our hypotheses using a web-experiment with a fictitious airline brand explicitly developed as the research context to collect data from a sample of Facebook users (N=480) drawn from an online Australian consumer panel. All the participants were randomly assigned to one of 16 conditions in a 2 (EWOM message valence: positive vs. negative) x 2 (EWOM message credibility: high vs low) x 4 (message format: text, picture, audio-visual and audio) between-subjects factorial design. The data were analysed using a Confirmatory Factor Analysis (CFA) conducted with AMOS 26.0 to test the measurement model, ANOVA and Hayes' PROCESS Macro with SPSS software to test the moderated mediation model proposed in this study. We found that a positive valence has a stronger effect on brand evaluation than negative EWOM valence. Moreover, we found that the effect of message valence on online brand evaluation is significantly moderated (enhanced) by credibility. We also found significant differences in the impact of valence (but not credibility) on brand evaluation across different message formats. Finally, brand evaluation mediates the impact of message valence (but not credibility) on online brand engagement. This paper has contributed to the growing EWOM literature by introducing an integrative conceptual model. Moreover, this paper has contributed to the field of ELM theory of persuasion by forming its assumptions in a new context (Airline) in Australia using popular social media platforms. [ABSTRACT FROM AUTHOR]

This article presents an overview of Artificial Intelligence (AI) research applied in the Management Information Systems field by analyzing the databases of the AIS journal basket list representing the major international journals on MIS. An initial set of 438 published papers was identified based on our search criteria. From those, 74 were selected because of their appropriate fit with the research questions. They were organized into domains, type of research, data collection strategy and AI technique. We found: (1) MIS Quarterly published 42% of the papers; (2) 50% of studies were on Information Systems applications, followed by 15% on Knowledge Management; and (3) 7 AI techniques were presented. This paper provides an overview of applied AI in Management, highlights the most studied related topics and techniques and contributes to a research agenda on the subject. [ABSTRACT FROM AUTHOR]

The prolonged COVID-19 pandemic has severely hampered microentrepreneurs' economic activities and pushed them towards poverty and vulnerability. In this situation, digitalising business is considered an effective means to resume business activities and, thus, scale-up micro-business owners' financial status. By relying on the literature review method, this paper offers a conceptual model for micro-business digitalisation focusing on its sustainability governance through data acquisition. Various points such as electronic financial transaction systems (e-wallet), e-marketplace, integrated social networks, crowdfunding sources, and the other stakeholders' involvement have been taken as the potential gateways for data acquisition. This model is deemed a convenient e-platform to the Malaysian underprivileged micro-entrepreneurs while being effectively and sustainably governed by the authority. The outcomes of this paper will help policymakers to create an alternative platform to rescue impoverished micro-business holders. It will further create opportunities for future research. [ABSTRACT FROM AUTHOR]

This is a pilot study which tries to investigate the reliability of a subscale of the questionnaire. The other purpose of the study is to identify the factors affecting the perception of Famer Producing Companies (FPCs) regarding Six Sigma implementation in farming. Further the study also aims to investigate if there exists any significant relationship between such factors and perceived challenges in implementation of Six Sigma in farming. A structured questionnaire was developed and used for data collection. Total 20 FPCs were requested for the responses. All FPCs agreed and gave their responses. The study found that perception of challenges in implementation of Six Sigma vary among FPCs having different size of land. Further such perception also changes significantly among FPCs according to services availed from external agencies. Limitations and scope for future studies are discussed in the paper. [ABSTRACT FROM AUTHOR]

This bibliometric pilot study presents a modified assessment taxonomy devised originally by Leeder, Markey, and Yakel (2012) and demonstrates how to apply it to assess the resources used in the construction of student academic research papers. Besides discussing this assessment tool, we present empirical data of its application, the result of a pilot study conducted at a medium sized Midwestern American university, based on the analysis of a sample of papers written for a freshman level English composition class. Our findings, among many, demonstrate that just one in 700 academic resources cited in these papers comes from a resource like Wikipedia, and that 52% of resources cited in student papers fall into the five taxonomic category combinations. Besides being used for assessment, this taxonomy may reveal models of information usage in future research. [ABSTRACT FROM AUTHOR]

This paper investigates the relationships between scientists' international mobility and their academic disruptiveness, by using data collected from the ORCID website and the Web of Science database (2008‐2017). Specifically, our observations contain 1,388 scholars who joined "brain gain" and "brain drain" and moved to China in the past decades. Results illustrate that scientists' disruptiveness significantly increased after they moved to China. [ABSTRACT FROM AUTHOR]

This paper discusses a data acquisition system (DAQ) development of a low-cost health monitoring system for a person with suspected COVID-19, named CovWatch. The system's design is based on the overall function of the CovWatch and the design requirements for low-cost and widely available devices that support extensive data collection using IoT. Two phases of the development process started from a DAQ of a single smartphone collecting data from a single smartband (point-to-point device) to a DAQ of a single smartphone for multiple smartbands (multipoint-to-point device) data. Changes in the system adopted the clinical protocol needs from self-isolation to inpatient care. Each type of data acquisition device (DAD) has a unique DAQ that requires customizing the data acquisition tools. This paper emphasized reporting each customization process. It involves analyzing the validity, reliability, and limitation of the DAD so that the CovWatch shall function according to the design requirements. From this paper, we know that CovWatch can acquire, collect, and send heart rate, blood oxygen saturation, and blood pressure data from 1-4 patients every 62 seconds with a data acquisition's success rate of 99.04%. CovWatch can be used to monitor patients for 72 hours. [ABSTRACT FROM AUTHOR]

Nowadays Online purchase possesses a vital role in our day to day life. People started purchasing goods through online rather than offline. This paper reveals the impact of consumer perceptions and awareness of goods and services offered online and also helps to understand how it provides goods and services to its clients. E-Commerce is one of the wonderful technological advancement platform which has made our life very easy. It is also helping us to manage time, work life balance, stress, depression etc. Online platform is used by working people, home makers, children, organization etc without which we cannot think about our life. Let us discuss in this paper about consumer motivation behind online purchases with the help of the data collected and analyze the real situation faced during this current era. [ABSTRACT FROM AUTHOR]

The solar energy system based on PV (photovoltaic) parameters monitoring techniques compromise of the both the electrical and environmental data, the number of parameters being measured in a PV plant that combine and analyze to observe and/or evaluate its efficiency. with a view to vouch the responsible and stable performance of any solar system, an effective measuring system is essential. large scale solar energy plants are respectable complicated and increase the cost and complexity on PV parameters measuring systems, so we can note in the past decennium, numerous ideas of monitoring systems were determined in vast number of research papers. For this review article different PV measuring systems were be studied and reviewed in details. The review manner included the most of solar parameters measuring techniques of PV system, and its efficiency and performance. The most of PV monitoring techniques which exhibited and examined. in other hand the different sensors and their operation principle, microcontroller, data acquisition technologies, data transmission units and types, and information modules storage and display are studied and reviewed in this paper. at last, this survey sustains the selective suggestions for upcoming researches. A massive solar PV monitoring techniques in this review paper concise an inclusive survey of techniques, these techniques based the phenomenal information handling units and different and novel data transmission protocols. The innovative photovoltaic measuring technology's especially that based on the internet of things discussed and investigated in innovative manners. The review will confidently completely the emphasized perceptions progress to improved exertions on the road to improvement of the monitoring technologies in future maintainable solar PV efforts. [ABSTRACT FROM AUTHOR]

Scientific research often requires researchers to adhere to strict schedules for time-sensitive experiments and data collection activities. Punctuality and alertness are crucial for the success of these endeavors. This paper proposes an intelligent wake-up vehicle designed to provide efficient and reliable wake-up calls to researchers involved in scientific investigations. This paper presents the design and implementation of an innovative wake-up vehicle for scientific research purposes. The vehicle incorporates advanced features such as a robust iron body, dual-wheel configuration, kinematics-based motion control, and a mechanical arm for providing personalized wake-up services. The objective of this research is to explore the feasibility and effectiveness of employing an autonomous vehicle to facilitate wake-up calls in various scientific research scenarios. The technical specifications, design considerations, operational principles, and results of initial field tests are discussed. The findings demonstrate the potential of this vehicle as a reliable and efficient solution for wake-up services in scientific research domains. [ABSTRACT FROM AUTHOR]

The operating conditions defining the current data taking campaign at the Large Hadron Collider, known as Run 3, present unparalleled challenges for the real-time data acquisition workflow of the LHCb experiment at CERN. To address the anticipated surge in luminosity and consequent event rate, the LHCb experiment is transitioning to a fully software-based trigger system. This evolution necessitated innovations in hardware configurations, software paradigms, and algorithmic design. A significant advancement is the integration of monotonic Lipschitz Neural Networks into the LHCb trigger system. These deep learning models offer certified robustness against detector instabilities, and the ability to encode domain-specific inductive biases. Such properties are crucial for the inclusive heavy-flavour triggers and, most notably, for the topological triggers designed to inclusively select b-hadron candidates by exploiting the unique kinematic and decay topologies of beauty decays. This paper describes the recent progress in integrating Lipschitz Neural Networks into the topological triggers, highlighting the resulting enhanced sensitivity to highly displaced multi-body candidates produced within the LHCb acceptance. [ABSTRACT FROM AUTHOR]

The ATLAS EventIndex is the global catalogue of all ATLAS real and simulated events. During the LHC long shutdown between Run 2 (20152018) and Run 3 (2022-2025) its components were substantially revised, and a new system was deployed for the start of Run 3 in Spring 2022. The new core storage system is based on HBase tables with a Phoenix interface. It allows faster data ingestion rates and scales better than the old system. This paper describes the data collection, the technical design of the core storage, and the properties that make it fast and efficient, namely the compact and optimized design of the events table, which already holds more than 400 billion entries, and all the auxiliary tables, and the EventIndex Supervisor, in charge of orchestrating the whole data collection, now simplified thanks to the Loaders, the Spark jobs that load the data into the new core system. The extractors, in charge of preparing the pieces of data that the loaders will put into the final back-end, have been updated too. The data migration from HDFS to HBase and Phoenix is also described. [ABSTRACT FROM AUTHOR]

The article provides information regarding a project to enhance the GreyNet's existing collections of conference preprints, to include commentaries and to establish workflow for future GreyNet publications. The goal of the project is GreyNet will be facilitating the data entry in repository. There are no direct costs involved in this project. It is expected that the project will harvest optimal results.

This study explores the topic of pay inequity, with a particular focus on how it impacts on women working in the UK today. Theoretical and methodological gaps exist across the literature, which to date have focussed on quantitative approaches to hypothesis connected to (i) equity theory (Adams, 1965; Homans, 1958), (ii) the gender pay gap (Olson, 2013; Metcalf, 2009; Rubery, 2015) and (iii) equal pay law (The Equal Pay Act, 1970). This study seeks to address these gaps by taking a feminist and qualitative approach to the collection of narratives that describe the lived experience of female pay inequity victims. Semi-structured interviews are used to collect the rich narratives and unique perceptions of women who have experienced this phenomenon for themselves, and provides us with deep insights into the events, behaviours and perceptions that surround their experiences (Blaikie, 2007; Oakley, 1981). This paper provides justification for the methodological approach, and how it has been used to address the gaps in our knowledge that are preventing the theoretical advancement of the topic. As this study is currently in the data collection and analysis phase for a PhD project, no findings are presented in this paper. [ABSTRACT FROM AUTHOR]

Games with purposes beyond entertainment, the so-called serious games, have been useful tools in professional training, especially in engaging participants. However, their evaluation and, also, their adaptable characteristics to different scenarios, audiences and contexts remain challenges. This paper examines the application of serious games in professional training, their results and adaptable ways to achieve certain goals. Using the Design Science Research (DSR) methodology, a framework was built to develop and evaluate serious games to improve user experience, learning outcomes, knowledge transfer to work situations, and the application of the skills practised in the game in real professional settings. At this stage, the investigation presents a framework regarding the triangulation of data collected from a systematic literature review, focus groups and interviews. Following the DSR methodology, the next steps of this investigation, listed at the end of the paper, are the demonstration of the framework in serious game development and the evaluation and validation of this artefact. [ABSTRACT FROM AUTHOR]

This paper explores Morabaraba, a strategy-based African indigenous game, to develop problem-solving skills in computer programming students enrolled in higher education institutions in South Africa. This paper will not test any hypothesis or analyse any data collected, but rather explore the Morabaraba game play required to successfully solve programming problems. Morabaraba is a traditional South African game that has been passed down through generations of Africans which requires strategic and analytical thinking to win the game. The result of the research identifies the critical thinking skills and abstract thoughts required for successful problem solving and correlates these to the skills that Morabaraba develops. [ABSTRACT FROM AUTHOR]

This work in progress paper investigates the aesthetic failures in food delivery services. It aims to extend our understanding of food consumption which is a multisensory experience disrupted by the lack of plating due the nature of delivery services. Our initial data collection explores Yelp reviews in a netnographic nature and next steps of data collection will include in depth interviews and experimental design. In the end, we are planning to offer concrete solutions to food preparation and service companies as well as third party delivery service operators in terms of how-to respond to service failures and recover customer satisfaction. [ABSTRACT FROM AUTHOR]

This paper discusses the impact of the REU Program at California State Polytechnic University, Pomona (Cal Poly Pomona) on the success of Participants in industry or graduate school. The REU Program titled "Research Experience for Undergraduates in UAV Technologies" has been funded by the NSF's EEC Program. The main goal of the Program is to increase undergraduate students' participation and interest in research on unmanned aerial vehicles (UAV) technologies. Undergraduate students from 2- and 4-year institutions have been involved in a multidisciplinary research projects at Cal Poly Pomona. The REU Site has so far hosted a total of 43 diverse group of students for 8-10 weeks of summer research since 2017, with the projects focusing on research on the Dynamics and Control of UAVs, Collision Detection and Avoidance System for UAVs, Artificial Intelligence, Computer Vision, Navigation in GPS-Denied Environments, application of UAVs for search and rescue missions, object detection and tracking, and Flight Test experience. Another goal of the Program is to attract students from community colleges to STEM programs at 4-year institutions and encourage the participants to pursue their studies for graduate degrees. The Program has been tracking the past Participants. Most of the participants are now pursuing their educational or professional career in the area of UAVs and other related areas. The program has also been successful in motivating the Participants to graduate degrees in STEM disciplines. Some of the participants are already pursuing their studies for Master's or PhD degrees or are planning to do so. Information about the Participants' current employment or graduate school enrollment and relevance of current work to aerospace and/or UAV technology was gathered using a follow-up survey that also included open-ended qualitative feedback from the Participants about the long-term impact of the Program on their career. The paper presents the results obtained from the data collected from the Participants of the first three cohorts of the Program who were hosted during summers of 2017 to 2019. The paper focuses on the impact of the Program on the Participants' career choice, career advancement, and motivation for graduate degrees. The paper also presents written feedback/comments from the Participants. [ABSTRACT FROM AUTHOR]

Construction claims can be categorized into a few types, and it is important to manage claims and conflict immediately before they turn into disputes. Claim for loss and expense is one of the popular claims in construction since it usually occurs when the regular progress of the works was delayed. However, there is always a dispute happened regarding this claim. Resolving disputes can be expensive and time-consuming. Hence, this paper aimed to evaluate contractual issues on loss and expense claims in the Malaysian construction industry. This paper examines the causes of issues arising in the claim for loss and expense. The data collection for the research methodology was through documentary analysis which is based on litigation cases. Findings show the most causes of issues in the claimfor loss and expense that lead to the dispute are due to three main causes which are contractual, documentation, and procedure. The suggestion from this paper is to identify the best practices in submitting a claim for loss and expense to minimize disputes amongst construction players. [ABSTRACT FROM AUTHOR]

Making the city center physically accessible is crucial to ensure that everyone has equitable access to the city center for various reasons. There should be no discriminatory practices restricting anyone from participating in society. Numerous studies, however, reveal that persons with disabilities (PWD) have fewer opportunities to engage in built environment activities than non-disabled individuals owing to the inaccessible design of buildings, public spaces and transportation services. Despite the fact that PWD's inclusion is tied to physical space, little effort has been made to explore PWD's lived experience in reaching the city center by using different transportation options. The purpose of this paper is to illustrate a go-along interview as one of the key data collection methods for examining barriers faced by PWD in using various transportation modes in Klang Valley. This qualitative study involves twenty go-along interviews with mobility-impaired travelers to learn about their actual experiences traveling using land transportation from around Klang Valley to Kuala Lumpur city center. Mobility-impaired travelers, notably wheelchair users, still need help to reach their destination with the current transportation services. In general, the use of transportation in Klang Valley has several issues, such as the lack of transportation-related facilities and lack of safety concerns from the service providers. The go-along journeys also demonstrated that, besides physical barriers, PWD encounters attitudinal and psycho-emotional barriers, which may lead to exclusion. [ABSTRACT FROM AUTHOR]

This paper proposes a new machine learning (ML) model to predict the percentage change of a certain cryptocurrency within a day or a week using sentiments, subjectivity, ticker mention and other parameters that can be extracted from users' activity on different crypto community platforms such as Reddit and Bitcointalk. The results show quite good correlation between these parameters and the price change, and in almost 85% of the cases the price is moving into the predicted direction. [ABSTRACT FROM AUTHOR]

Cryptography is a concept to protect information and communication from adversaries through the use of codes. Graph theory is ultimately the study of graphs. In this paper we are using cryptographic technique together with graph labeling to protect our message being hacked by any adversaries as well as safeguarding the communication. This paper proposes an enriched technique of coding a message based on Polybius cipher and permutation cipher for the regular graph using product edge labeling techniques. The resulting cipher text is forwarded to the receiver in a structure of cipher graph which admits our proposed edge labeling. The receiver, thus decrypts the edge labels using secret keys shared by the sender. Here we make use of symmetric key cryptosystem as we perform both encryption and decryption using the same key. The main advantage of symmetric cryptosystem is that it is effective and fast for a huge collection of data. [ABSTRACT FROM AUTHOR]

The Electrical motors being versatile in various aspects, have found a wide application in present day industry as well as in day to day life of human beings. A modern and dependable control system is very much desirable. The main objective of this paper is to present the technical aspect of motor controls and its Industrial applications using PLC and SCADA. Automation is the process of using advanced technology to control equipment, which usually involves electrical hardware. Some of the practical circuits which involves the control of electrical motors for various applications including Agriculture in industrial automations are demonstrated in this paper. The control circuits are designed for PLC, Supervisory control and data acquisition and VFD. By applying any set of rules and proper ladder logic diagrams, any desired motor can be controlled and the results are made accurate for Industrial applications. Also there is a scope for improvement in the control structure which will make it more versatile and extensively used in the Automation Industries. [ABSTRACT FROM AUTHOR]

Many businesses and services are taking into account the result of Business Intelligence. When it comes to actual meaningful analyzation, it is the specified Business Intelligence Architecture, which observes clear principals of extracting, transforming, loading, storing and presenting data in front of the user/client. Of course, in this architecture a key position is defined for the Data Warehousing. The role of qualified collecting data is not only related to the store space, speed of transaction and consistency of the data, but also to the ability of the data storage to transform and administrate raw data from different sources. The focus of this paper is to show where exactly the place of Data Warehousing in the Business Intelligence process is and how important is its usage by the help of actual technology example. [ABSTRACT FROM AUTHOR]

The Fuzzy Delphi Method (FDM) is one of the research methods used in obtaining experts' consensus on specific issues. FDM is a combination of the Delphi method and fuzzy theories. Although there are benefits of using FDM, but literature review on its application in the domain of Human-Computer Interaction (HCI) is still insufficient. Thus, this paper provided a review on FDM, including its application in the HCI domain. This paper begins with presenting a background on methods, discussing its benefits and weaknesses, comparing between the Delphi method and FDM, as well as steps in FDM. Several articles between 2015 and 2021 were reviewed. The study also examined FDM application in HCI in terms of field domain, number of experts, and data collection. This paper revealed FDM as one of the methods to obtain expert group consensus using a new construct of model or evaluation framework for user experience, augmented reality, usability, mobile applications, and online learning domain. The number of experts suggested for FDM implementation is ten. This paper mainly contributes in providing an overview on FDM in terms of conceptual, steps, and applications with a clear understanding for future studies. [ABSTRACT FROM AUTHOR]

The application of AI has switched the dimension of the construction industry. In upgrading the several aspects of the construction, AI has made it easier and possible by automatic data collection and analysis. In this paper, two sensors are used (i.e motion sensor and RFID). The motion sensor will automatically detect the human and animal within its range of danger zone. It contains a pyroelectric sensor that will notice the movements human and animals within its range. This sensor works by noticing the heat energy in the form of an infra-red signal. Further, this paper deals with the application of AI in construction sites. Similarly, the paper gives some focus on RFID use in the safety of construction. RFID deals with personal warning systems, real-time tracking, and location. Finally, the outcome of the developed platform figure-out that it is feasible to be applied in construction sites for better safety management. [ABSTRACT FROM AUTHOR]

This paper reviewed the Hand Sign Recognition system from 2018 to 2022. Based on the review, much research is done on Deep learning-based hand sign recognition. Many of these studies are published annually in article, journals, and conference proceedings. Additionally, we also examined the performance of the HGR system in terms of recognition accuracy. In this paper we concentrate on the data environment, the data acquisition, and the hand gesture presentation— three crucial components of the vision-based HGR system. We also looked at how well the vision-based HGR system performed regarding recognition accuracy. [ABSTRACT FROM AUTHOR]

The hospitality sector contributes positively towards the SDG's by addressing youth employment and economic challenges, specifically in South Africa. Therefore, awareness and knowledge regarding careers and opportunities that are available within the hospitality industry are vital. As a result, high schools are encouraged to incorporate the relevant knowledge about careers within the curriculum. Hence, this paper reports on the level of hospitality knowledge of high school learners in Cape Town townships. This was a cross-sectional study that followed a quantitative approach, whereby data was collected using questionnaires. Respondents were 720 pre-matric (Grade 11) learners who attended school in townships. Data were analysed using the Number Cruncher Statistical System (NCSS) 9. Thirty-seven per cent (37,2%) of the learners indicated that they received information about the hospitality industry through various platforms. The findings above are substantiated by the results that indicate that most learners (67.2%) know nothing about the hospitality industry. Furthermore, a few learners (28,5%) indicated to know about the industry. To support this statement, 8,8% mentioned available careers to be within the medical field. The present findings showcase the knowledge gaps that exist at the high school level, and this has a negative effect on the career choice and employment opportunities the hospitality industry offers. This calls for an intervention from higher education and industry to address identified gaps. The findings of the study share valuable insights regarding limited access to hospitality careers. This is a challenge because it hinders knowledge of career and employment opportunities. [ABSTRACT FROM AUTHOR]

Driving cycle is very important to the vehicle manufacturer and automotive suppliers mainly for product evaluation purposes. Driving cycle is as representation of traffic behavior in an area or city. This paper discusses about the driving data collection and development for Kuala Terengganu city using MATLAB Mobile application. The objectives of this paper are; to collect the driving data along the main road in Kuala Terengganu city using MATLAB Mobile application, to analysis the driving data stored in the cloud of MATLAB Mobile application and lastly to develop a Kuala Terengganu Driving Cycle. The methodology involves three major steps which are; driving data collection, driving data analysis and driving cycle development. The KTDC is successfully developed with average speed of 48.92 km/h and total of nine micro trips. [ABSTRACT FROM AUTHOR]

Despite the implementation of training during the onboarding process, weekly safety training, and on the job training a contractor experienced a disturbing trend in incidents reported during the 2022 work season. To understand the details surrounding and attributing to these incidents' general safety data from the past five years was collected for analysis. An in-depth analysis of the 2022 safety data was also generated from a series of incident reports. These reports contain both quantitative and qualitative data. The information provided in this paper covers both the general data collected and a detailed analysis of the 2022 reports. Based on the information collected program improvements are provided. Improvement to both the safety and the training program is necessary and a marriage of the two will be critical moving forward. These improvement suggestions are presented through refined training program proposals, technology incorporation examples, and include incentives for safe work. The improvements have not been adopted but are in the process of proposal. To ensure a safe completion to the 2023 work season several goals based on the information are generated. [ABSTRACT FROM AUTHOR]