Common Set Of Tools Research Articles

Advancing Language Assessment with AI and ML–Leaning into AI is Inevitable, but Can Theory Keep Up?

ABSTRACT Following the burgeoning growth of artificial intelligence (AI) and machine learning (ML) applications in language assessment in recent years, the meteoric rise of ChatGPT and its sweeping applications in almost every sector have left us in awe, scrambling to catch up by developing theories and best practices. This special issue features studies of recent AI and ML advances and thought pieces and attempts to unify our field with a collection of work towards a common set of tools, frameworks, and practices. In this editorial, I briefly review the five studies and four commentaries and discuss the key validity issues around the AI applications covered. To unpack complex validity issues for lay users, I propose accessible questions to ask when evaluating these applications. I stress the importance of developing best practices guiding ethical and responsible use of AI and improving users’ AI literacy skills. In light of users’ increasing access to AI tools in real-world communication, I raise the need for redefining the constructs of language tests to be in sync with what is happening in the real world. These new conceptions of language ability are expected to result in significant changes in task design, scoring, and test interpretation and use.

Fighting/Fat: Fighting Game Characters and the Emptiness of Video Game Fatness

The fatness of fat characters in screen media, video games included, is well understood on an aesthetic level. However, this research asks: Is there a mechanical dimension to the fatness of these characters? Fighting games, with their need for common toolsets among playable characters, offer a useful ground to explore that question. While the characters in this study did not exhibit a “mechanical fatness,” they do reveal that certain combinations of aesthetic fatness with gameplay mechanics may offer a potential site of resistance to the pervasive fatphobic tropes present in video games.

Governors, states discuss prevention, resilience in youth MH

On Oct. 18–19, 2022, in Salt Lake City, Utah, National Governors Association (NGA) Chair, New Jersey Gov. Phil Murphy, and Vice Chair, Utah Gov. Spencer Cox, held the first of four roundtables to discuss the 2022‐2023 NGA Chair's Initiative: Strengthening Youth Mental Health, according to an NGA news release. A strong state contingent was represented, including Alabama, Arkansas, Minnesota, New Mexico, and Pennsylvania, according to an NGA news release. Representatives from these states were joined by over 50 community leaders, academic experts, and representatives from partner organizations and funders. The convention centered on practical solutions for the first of the initiative's four pillars: prevention and resilience building. Discussions forged connections across the public and private sectors, shared best practices across states and territories to amplify their impact, and aligned on ways that governors can further support youth mental health. Discussions suggested that a set of common tools should emerge to successfully drive prevention and resilience building efforts and that.

Standardized Tools, Generalizability of Human Capital, and Employee Mobility

The mobility of highly skilled knowledge and creative workers is an important determinant of innovation. Existing studies have not considered how the use and diffusion of standardized technologies and tools influence the mobility of individual knowledge workers. We theorize that the diffusion of standardized tools increases the generalizability of human capital and, in turn, increases the ability of individuals to move between companies. Using data on the use of middleware in the console games industry, we find that this diffusion of standardized middleware tools lead to an increase in labor mobility on average, but was associated with higher mobility for individuals with skills that complemented those tools, in comparison to those that were substituted by these tools. Worker experience with standardized tools amplified these effects, as individuals who were experienced in using these tools saw the largest shift in the likelihood of mobility. We do not find that this diffusion led to individuals leaving the industry, but we do find evidence that the diffusion of a common set of tools within an industry was associated with workers being less likely to leave that industry. These results highlight the potential unintended effects of technological standardization and the broad diffusion of standardized tools, which may enable workers to more easily shift between competitors.

Integrating the Role of Computational Intelligence and Digital Signal Processing in Education: Emerging Technologies and Mathematical Tools

Rapid progress in the development of technological and computational tools has motivated substantial changes in the educational approach to the different disciplines of signal, image, and video processing. Moreover, the parallel evolution of sensor systems, data acquisition methods, and computational intelligence has emphasized the importance of signal processing and information engineering, particularly its role in integrating different scientific disciplines through the use of a common set of tools and underlying mathematics. Modern educational courses follow these trends and generally combine the teaching of fundamental computational methods of signal and system modeling with applications to selected case studies. The unifying idea is to apply similar mathematical methods for data processing in completely diverse areas. Emerging methods used in education contribute to this progress, and they provide opportunities to bring together specialists from different disciplines. New technologies facilitate real or virtual activities through excursions to remote laboratories, allowing the demonstration of robotic and speech recognition systems, for example. Participation in seminars, videoconferences, and discussions during colloquia meetings, when included in educational courses, can form further progressive and attractive teaching methods for the rapidly developing interdisciplinary area of signal processing.

Orientation averaging of optical chirality near nanoparticles and aggregates

Artificial nanostructures enable fine control of electromagnetic fields at the nanoscale, a possibility that has recently been extended to the interaction between polarised light and chiral matter. The theoretical description of such interactions, and its application to the design of optimised structures for chiroptical spectroscopies, brings new challenges to the common set of tools used in nano-optics. In particular, chiroptical effects often depend crucially on the relative orientation of the scatterer and the incident light, but many experiments are performed with randomly oriented scatterers, dispersed in a solution. We derive new expressions for the orientation-averaged local degree of optical chirality of the electromagnetic field in the presence of a nanoparticle aggregate. This is achieved using the superposition $T$-matrix framework, ideally suited for the derivation of efficient orientation-averaging formulas in light scattering problems. Our results are applied to a few model examples and illustrate several nonintuitive aspects in the distribution of orientation-averaged degree of chirality around nanostructures. The results will be of significant interest for the study of nanoparticle assemblies designed to enhance chiroptical spectroscopies, and where the numerically efficient computation of the averaged degree of optical chirality enables a more comprehensive exploration of the many possible nanostructures.

Lean Construction in a Real Estate Project – A Case Study

More than 70% of construction projects are over budget and delivered beyond thebudgeted time. To overcome the same, the concept of lean integrated project deliverycame into existence. Lean culture focuses on customer by empowering employees. Itinvolves in converting waste into value by reducing waste, improving communication, andpromoting teamwork integration through a common set of tools and techniques. Aim oflean construction is to achieve the affordable cost with optimum utilization of man,material and machinery. Wastes in construction industry which do not add value are supplyin excess materials in inventory for raw material, work in progress, finished goods etc.Waiting for preceding activity, over processing and defects can be reduced through leanconstruction. This paper deals with lean construction techniques for identifying the wastein a construction project and eliminating the same. . In this project estimation of a buildingis done to find cost of the project with respect to specifications and compared thetraditional methods used and lean construction techniques to reduce the cost and improvethe quality in less time with lower cost to satisfy the customer.

Standardized Tools and the Generalizability of Human Capital: The Impact of Standardized Technologies on Employee Mobility

The mobility of highly skilled knowledge and creative workers is an important determinant of innovation. Existing studies have not considered how the growth and diffusion of standardized technologies and tools influence the mobility of individual knowledge workers. We theorize that the diffusion of standardized tools increases the generalizability of human capital and, in turn, increases the ability of individuals to move between companies. Using data on the use of middleware in the console games industry, we find that this diffusion of standardized middleware tools led to an increase in labor mobility on average, but was associated with higher mobility for individuals with skills that complemented those tools. Worker experience with standardized tools amplified these effects, as individuals who were experienced in using these tools saw the largest shift in the likelihood of mobility. We do not find that this diffusion led to individuals leaving the industry, but we do find evidence that the diffusion of a common set of tools within an industry was associated with workers being less likely to leave that industry. These results highlight the potential unintended effects of technological standardization and the broad diffusion of standardized tools, which may enable workers to more easily shift between competitors.

Epigenetic regulation and transcriptional memory in development; selection facilitating prudence.

The epigenetic mechanisms regulating developmental gene expression are examples of a strategy to generate unique expression profiles with global regulators controlling several genes. In a simplified view, a common set of tools, that include DNA motif recognizing proteins (recruiters), binding/interacting surfaces (ARPs- actin related proteins), epigenetic writers (histone methyltransferases, acetylases), readers (chromatin remodeling proteins, PRC1 members) and erasers (demethylases, deacetylases) form complexes which not only regulate transcription, but also retain the transcriptional memory through mitosis. There are two arms of epigenetic regulation: covalent modification of DNA and the post-translational modification of histones. In this review, we discuss both of these aspects briefly to illustrate functional diversity. We discuss our efforts at utilization of the genome sequence data for de novo identification of new players and their functional validation in this remarkable process.

Uniting the Tribes: Using Text for Marketing Insight

Words are part of almost every marketplace interaction. Online reviews, customer service calls, press releases, marketing communications, and other interactions create a wealth of textual data. But how can marketers best use such data? This article provides an overview of automated textual analysis and details how it can be used to generate marketing insights. The authors discuss how text reflects qualities of the text producer (and the context in which the text was produced) and impacts the audience or text recipient. Next, they discuss how text can be a powerful tool both for prediction and for understanding (i.e., insights). Then, the authors overview methodologies and metrics used in text analysis, providing a set of guidelines and procedures. Finally, they further highlight some common metrics and challenges and discuss how researchers can address issues of internal and external validity. They conclude with a discussion of potential areas for future work. Along the way, the authors note how textual analysis can unite the tribes of marketing. While most marketing problems are interdisciplinary, the field is often fragmented. By involving skills and ideas from each of the subareas of marketing, text analysis has the potential to help unite the field with a common set of tools and approaches.

Principles to Support Modular Software Construction

The construction of large software systems is always achieved through assembly of independently written components — program modules. For these software components to work together, they must share a common set of data types and principles for representing structured data such as arrays of values and files. This common set of tools for creating and operating on data objects is provided by the infrastructure of the computer system: the hardware, operating system and runtime code. Because the nature and properties of these tools are crucial for correct operation of software components and their inter-operation, it is essential to have a precise specification that may be used for verifying correctness of application software on one hand, and to verify correctness of system behavior on the other. We call such a specification a program execution model (PXM). It is evident that the properties of the PXM implemented by a computer system can have serious impact on the ability of application programmers to practice modular software construction. This paper discusses the concept of program execution models and presents a set of principles that a PXM must satisfy to provide a sound basis for modular software construction. Because parallel program execution on computer systems with many processing units is an essential part of contemporary computing environments, the expression of parallelism and modular software construction using components involving parallel operations is included in this treatment. The conclusion is that it is possible to build computer systems that implement a PXM within which any parallel program may be used, unmodified, as a component for building more substantial parallel programs.

The pLISA project in ASTERICS

In the framework of Horizon 2020, the European Commission approved the ASTERICS initiative (ASTronomy ESFRI and Research Infrastructure CluSter) to collect knowledge and experiences from astronomy, astrophysics and particle physics and foster synergies among existing research infrastructures and scientific communities, hence paving the way for future ones. ASTERICS aims at producing a common set of tools and strategies to be applied in Astronomy ESFRI facilities. In particular, it will target the so-called multi-messenger approach to combine information from optical and radio telescopes, photon counters and neutrino telescopes. pLISA is a software tool under development in ASTERICS to help and promote machine learning as a unified approach to multivariate analysis of astrophysical data and signals. The library will offer a collection of classification parameters, estimators, classes and methods to be linked and used in reconstruction programs (and possibly also extended), to characterize events in terms of particle identification and energy. The pLISA library aims at offering the software infras tructure for applications developed inside different experiments and has been designed with an effort to extrapolate general, physics-related estimators from the specific features of the data model related to each particular experiment. pLISA is oriented towards parallel computing architectures, with awareness of the opportunity of using GPUs as accelerators demanding specifically optimized algorithms and to reduce the costs of pro cessing hardware requested for the reconstruction tasks. Indeed, a fast (ideally, real-time) reconstruction can open the way for the development or improvement of alert systems, typically required by multi-messenger search programmes among the different experi mental facilities involved in ASTERICS.

Enhancing Safety in a Volcano's Shadow

A new project gives civil authorities and scientists a common set of tools for assessing volcanic hazards and managing associated risks.

Modular ABM development for improved dissemination and training

Agent-based models (ABMs) have become an important tool for advancing scientific understanding in a variety of disciplines and more specifically have contributed gains to natural resource management in recent decades. However, a key challenge to their utility is the lack of convergence upon a common set of assumptions for representing key processes (such as agent decision structure), with the outcome that published ABM tools are rarely (if ever) used beyond their original development team. While a number of ABM frameworks are publicly available for use, the continued development of models from scratch is a signal of the continuing difficulty in capturing sufficient modeling flexibility in a single package. In this study we examine ABM sharing by comparing co-citation networks from several well-known ABM frameworks to those used in the land-use change modeling community. We then outline a different publication paradigm for the ABM community that could improve the sharing of model structure and help move toward convergence on a common set of tools and assumptions.

TH-AB-303-01: Benchmarking Real-Time Adaptive Radiotherapy Systems: A Multi- Platform Multi-Institutional Study

Purpose: The era of real-time adaptive radiotherapy is here: patients are being treated by CyberKnife (since 2004), Vero (2011) and MLC tracking (2013) technology, with couch tracking planned to be clinical in 2015. We have developed a common set of tools for benchmarking real-time adaptive radiotherapy systems and to test the hypothesis that, across delivery systems and institutions, real-time adaptive radiotherapy improves the dosimetric accuracy over non-adaptive radiotherapy in the presence of realistic tumor motion. Methods: Ten institutions with CyberKnife, Vero, MLC or couch tracking technology were involved in the study. Common materials were anonymized lung and prostate CT and structure sets, patient-measured motion traces (four lung, four prostate) and SBRT planning protocols (lung: RTOG1021, prostate: RTOG0938). The institutions delivered lung and prostate plans to a moving dosimeter programmed with tumor motion. For each trace the plan was delivered twice; with and without motion adaptation, each measurement was compared to the static dosimeter dose and the percentage of failed points for γ-tests recorded. Results: Eleven measurement sets were obtained for this study; two CyberKnife, two Vero, five MLC and two couch tracking sets. For all lung traces all sets show improved dose accuracy from a mean 2%/2mm γ-failrate of 1.6% with adaptation and 14.7% with no motion correction(p<0.001). For all prostate traces the mean 2%/2mm γ-failrate was 1.6% with adaptation and 17.4% with no motion correction (p<0.001). The difference between the four adaptive systems was small with an average 2%/2mm γ-failrate of <3% for all systems with adaptation for lung and prostate. Conclusion: A common set of tools has been developed for benchmarking real-time adaptive radiotherapy systems and a multi-platform multi-institutional study performed. The results show the systems all account for realistic tumor motion accurately and performed to a similar high standard, with real-time adaptation significantly outperforming non-adaptive methods.

Big data, bigger dilemmas: A critical review

The recent interest in Big Data has generated a broad range of new academic, corporate, and policy practices along with an evolving debate among its proponents, detractors, and skeptics. While the practices draw on a common set of tools, techniques, and technologies, most contributions to the debate come either from a particular disciplinary perspective or with a focus on a domain‐specific issue. A close examination of these contributions reveals a set of common problematics that arise in various guises and in different places. It also demonstrates the need for a critical synthesis of the conceptual and practical dilemmas surrounding Big Data. The purpose of this article is to provide such a synthesis by drawing on relevant writings in the sciences, humanities, policy, and trade literature. In bringing these diverse literatures together, we aim to shed light on the common underlying issues that concern and affect all of these areas. By contextualizing the phenomenon of Big Data within larger socioeconomic developments, we also seek to provide a broader understanding of its drivers, barriers, and challenges. This approach allows us to identify attributes of Big Data that require more attention—autonomy, opacity, generativity, disparity, and futurity—leading to questions and ideas for moving beyond dilemmas.

Russian cyclical indicators and their usefulness in real time. (Report)

This report investigates the predictability of cyclical turning points in Russia. For years, anyone interested in Russia had access to a full set of common tools for business cycle analysis, such as several composite leading indicators, a purchasing managers’ index, enterprise and consumer sentiment indexes, and so on. However, the 2008-09 world financial crisis spread throughout Russia quite unexpectedly for most politicians, businessmen and experts alike. Is it possible that none of existing indexes were able to say anything about the approaching decline? Using a simple rule of thumb proposed in this report one may easily see that that in reality this was not the case. So then why did a more or less definite forecast provided by some indexes have no consequences for common economic sentiments in Russia? This report gives some answers to this question. Keywords: recession; growth cycles; cyclical indicators; leading indicators; turning points; Russia JEL classification: E32

TRADER: A package for Tree Ring Analysis of Disturbance Events in R

Studies using tree-rings to reconstruct forest disturbance dynamics are common and their number has been increasing in the recent years. Despite the evident need for a common set of tools for verification, replication and comparison across studies, only a few DOS programmes for disturbance detection exist and they are for limited purposes only. Currently, the ideal statistical environment for the task is R, which is becoming the primary tool for various types of tree-ring analyses. This has led to the development of TRADER (Tree Ring Analysis of Disturbance Events in R), an open-source software package for R that provides an analysis of tree growth history for disturbance reconstructions. We have implemented four methods, which are commonly used for the detection of disturbance events: radial-growth averaging criteria developed by Nowacki and Abrams, 1997, the boundary-line method (Black and Abrams, 2003), the absolute-increase method (Fraver and White, 2005), and the combination of radial-growth averaging and boundary-line techniques (Splechtna et al., 2005). TRADER, however, enables the analysis of disturbance history by a total of 24 published methods. Furthermore, functions for the detection of tree recruitment and growth trends were also included. The main features of the presented package are described and their application is shown on a real tree-ring datasets. The package requires little knowledge of the R environment giving straightforward analyses with suitable parameters, but at the same time it is easily modifiable by the more experienced user. The package improves research efficiency and facilitates replication of previous studies. One of its major advantages is that it offers the possibility for comparison between different methods of disturbance history reconstruction.

Process Monitoring Using Hidden Markov Models

Autocorrelated data arise in a variety of processes. To statistically monitor such processes, special statistical tools are needed to account for these correlations. The most common set of tools for such purpose is the autoregressive integrated moving average (ARIMA) models. Implementation of ARIMA models requires a fair amount of background understanding of how these models work, because the model selection step is essential. In this paper, we propose a new monitoring technique based on the use of hidden Markov models. The proposed monitoring method is powerful yet simple to use technique because it only requires a basic knowledge in statistics. Simulation results show that the proposed method performs similar to the ARIMA models in terms of average run length for detecting out of control processes and false alarms. Copyright © 2013 John Wiley &amp; Sons, Ltd.

Outcome Measures for Individuals With Stroke: Process and Recommendations From the American Physical Therapy Association Neurology Section Task Force

The use of standardized outcome measures (OMs) can support clinicians' development of appropriate care plans, guide educators in curricular decisions, and enhance the methodological quality and generalizability of clinical trials. The purposes of this case report are: (1) to describe a framework and process for assessing psychometrics and clinical utility of OMs used poststroke; (2) to describe a consensus process used to develop recommendations for stroke-related OMs in clinical practice, research, and professional (entry-level) physical therapist education; (3) to present examples demonstrating how the recommendations have been utilized to date; and (4) to make suggestions for future efforts. A task force of 7 physical therapists with diverse clinical and research expertise in stroke rehabilitation used a 3-stage, modified Delphi consensus process to develop recommendations on OM use. An evidence-based systematic review template and a 4-point rating scheme were used to make recommendations on OM use by care setting and patient acuity, for research, and for inclusion in professional education. An initial list of 77 OMs was developed based on input from numerous professional sources. Screening measures and duplicate measures were eliminated. Fifty-six OMs received full review. Measures spanned the constructs of body structure/function (21), activity (28), and participation (14). Fourteen measures received a rating of "highly recommend." Use of highly recommended OMs may provide a common set of tools enabling comparisons across patients, interventions, settings, and studies. The use of a clearly defined, comprehensive assessment template may facilitate the pooling of data on OMs and contribute to best practice guidelines. Educational recommendations may inform curricular decisions.