Hasil untuk "Information resources (General)"

Peter Maurice Catt

Forecasting accuracy is bounded by the information available about the future. This paper makes that statement precise using information-theoretic tools. Under logarithmic loss, the expected performance of any probabilistic forecast decomposes into two parts: an irreducible component and an approximation component. The irreducible term is the conditional entropy of the future given the available information, while the approximation term is the divergence between the true conditional distribution and the forecasting method. The gap between this conditional-entropy limit and an unconditional baseline is exactly the mutual information between the future observation and the declared information set. This leads to a definition of forecastability as the maximum achievable reduction in expected log loss. Evaluated across horizons, forecastability forms a profile that describes how predictive information varies with lead time. This profile reflects the dependence structure of the process and need not be monotone: predictive information may be concentrated at particular lags, including seasonal horizons, even when intermediate horizons contain little useful signal. From this profile, the paper defines the informative horizon set: the horizons at which forecastability exceeds a practical threshold. At horizons not in this set, the achievable gain over the unconditional baseline is necessarily small, regardless of the forecasting method used. The framework therefore separates what is learnable from what is not, and distinguishes limits imposed by the data from errors introduced by modelling. The result is a pre-modelling diagnostic that identifies where meaningful prediction is feasible before any model is chosen, providing a principled basis for allocating modelling effort across forecast horizons.

Taiwo S. Olutoberu, Mutiu A. Busari, Olusegun Folorunso et al.

Maize production per hectare in Southwest Nigeria ranks among the lowest compared to other regions worldwide. Digital methodologies focusing on soil fertility determinants and geographic data were used to evaluate land suitability. We explored a methodology that combined ordinal logistic regression with continuous soil characteristic modeling in a two-step mapping approach to assess land suitability. A stepwise forward regression analysis was performed on environmental variables to identify those that significantly influenced the outcomes at a 95 % confidence level (p < 0.05). Most areas in the region, from the north to the south, had organic carbon concentrations below 1 %. In the northern part, a significant portion showed total nitrogen levels below 0.1 g kg−1. The majority of the area had exchangeable phosphorus levels ranging from 23 to 28 mg kg−1, while some eastern locations had extractable potassium levels above 0.40 g kg−1. Only a few sites in the southern region showed pH values of 5.50 or lower; others exceeded that level. According to the FAO land suitability classification, 29.87 % was rated as unsuitable, 69.08 % as moderately suitable, and just 1.06 % as suitable for maize cultivation. We recommend developing and enforcing policies to oversee infrastructure development and protect agricultural land. It is crucial to discourage non-regenerative farming practices, and both the government and private sectors should support farmers by providing access to modern soil resources.

Siti Ramdiah, Ria Mayasari, A. Abidinsyah

Issues in learning, particularly the utilization of learning resources, have not been maximized to facilitate teachers in guiding students to learn certain concepts related to the surrounding environment. This study aims to analyze the motives and colors of Sasirangan as a source of biology learning in high schools and the knowledge of high school biology teachers in Banjarmasin regarding the existence of Sasirangan. This survey research involved 40 sasirangan craftsmen from 20 sasirangan production houses and 38 high school biology teachers in Banjarmasin, South Kalimantan. The instruments used were interview sheets and questionnaires. Data analysis was descriptive using percentage techniques. The results of expert validation indicated that the interview sheets and questionnaires were suitable, with scores of 89.63 and 92.5. sasirangan has great potential to become a source of biology learning, both in terms of motives and natural colors used by craftsmen. However, high school biology teachers in Banjarmasin have not fully utilized and conveyed it as a biology learning resource. While in other statements, teachers stated that they understood and explained that the existence of Sasirangan is very important to be conveyed in biology learning. Some teachers were able to provide information on biology concepts related to the existence of Sasirangan.

Melanie Jane Nicholls, Alexandra Almeida, Justin Castello et al.

BackgroundMedications for opioid use disorder (MOUD), such as methadone and buprenorphine, are the gold standard for opioid use disorder (OUD) treatment. Owing to various barriers, MOUD access and retention are low in the United States. The internet presents a digital solution to mitigate barriers, but a comprehensive and reliable resource is lacking. We present a user-friendly, web-based resource, the MOUD Hub, that provides reliable information on MOUD. ObjectiveThis study aims to assess the safety, acceptability, feasibility of dissemination, and reach of the MOUD Hub using focus groups and advertising on 1 key search engine and 1 social media platform. MethodsThis protocol describes the development of the MOUD Hub and the descriptive observational feasibility study that will be undertaken. The MOUD Hub uses motivational interviewing principles to guide users through the stages of change. The website provides evidence-based information from national health and substance use agencies, harm reduction organizations, and peer-reviewed literature. First, pilot focus groups with 10 graduate students who have lived experience with OUD will be conducted to provide feedback on safety concerns. Then, focus groups with 20-30 potential MOUD Hub users (eg, people with OUD with and without MOUD experience, friends and family, and health care providers) will be conducted to assess safety, acceptability, reach, and usability. Data will be analyzed using inductive thematic analysis. The website will be advertised on Google and MOUD-specific Reddit forums to assess dissemination, reach, and user acceptability based on the total user volume, sociodemographic characteristics, pop-up survey responses, and 1-year engagement patterns. This information will be collected through Google Analytics. Potential differences between users from Google and Reddit will be assessed. ResultsThe MOUD Hub will be launched in January 2025. Data collected from 5 focus groups (approximately 30-40 participants) will be used to improve the website before launching it. There is no target sample size for the second stage of the study as it aims to assess dissemination feasibility and reach. Data will be collected for a year, analyzed every 3 months, and used to improve the website. ConclusionsThe MOUD Hub offers an innovative theory-based approach, tailored to people with OUD and their family and friends, to increase access to and retention in MOUD treatment in the United States and provides broader harm reduction resources for those not currently in a position to receive treatment or those at risk of resuming illicit opioid use. Findings from this feasibility phase will serve to better tailor the MOUD Hub. After modifying the website based on our findings, we will use a randomized controlled trial to assess its efficacy in increasing MOUD access and retention, contributing to growing research on web-based interventions for OUD. International Registered Report Identifier (IRRID)PRR1-10.2196/57065

Faisal Hamman, Sanghamitra Dutta

This paper introduces a novel information-theoretic perspective on the relationship between prominent group fairness notions in machine learning, namely statistical parity, equalized odds, and predictive parity. It is well known that simultaneous satisfiability of these three fairness notions is usually impossible, motivating practitioners to resort to approximate fairness solutions rather than stringent satisfiability of these definitions. However, a comprehensive analysis of their interrelations, particularly when they are not exactly satisfied, remains largely unexplored. Our main contribution lies in elucidating an exact relationship between these three measures of (un)fairness by leveraging a body of work in information theory called partial information decomposition (PID). In this work, we leverage PID to identify the granular regions where these three measures of (un)fairness overlap and where they disagree with each other leading to potential tradeoffs. We also include numerical simulations to complement our results.

Abubakar Haruna, Juliette Blanchet, Anne‐Catherine Favre

Abstract Intensity‐duration‐frequency (IDF) curves are useful in water resources engineering for the planning and design of hydrological structures. As opposed to the common use of only extreme data to build IDF curves, here, we use all the non‐zero rainfall intensities, thereby making efficient use of the available information. We use the extended generalized Pareto distribution to model the distribution of the non‐zero rainfall intensities. We consider three commonly used approaches for building IDF curves. The first approach is based on the scale‐invariance property of rainfall, the second relies on the general IDF formulation of Koutsoyiannis et al. (1998, https://doi.org/10.1016/S0022-1694(98)00097-3), and the last approach is purely data‐driven(Overeem et al., 2008, https://doi.org/10.1016/j.jhydrol.2007.09.044). Using these three approaches, and some extensions around them, we build a total of 10 models for the IDF curves, and then we compare them in a split‐sampling cross‐validation framework. We consider a total of 81 stations at 10 min resolution in Switzerland. Due to the marked seasonality of rainfall in the study area, we performed a seasonal‐based analysis. The results reveal the model based on the data‐driven approach as the best model. It is able to correctly model the observed intensities across duration while being reliable and robust. It is also able to reproduce the space and time variability of extreme rainfall across Switzerland.

Олександра Патряк

Мета статті – дослідити роль цифрових навичок у сучасних бізнес-моделях та їх вплив на управління компанією. Методи дослідження. Методологію становлять принципи наукового дослідження. Використано загальнонаукові методи пізнання, проаналізовано глобальні практики оцінки цифрових навичок на основі використання офіційних документів і методологій, вивчено кейси цифрової трансформації та використання цифрових навичок у бізнес-моделях глобальних компаній. Наукова новизна полягає у сформульованих перевагах цифрових навичок, які мають визначальний вплив на трансформацію бізнес-моделей у цифровому середовищі, а також на структуру та тенденції ринку праці, визначаючи базові компетенції робочої сили та формуючи спектр вимог роботодавців. Цифрова трансформація не тільки змінила світ праці, створивши нові робочі ролі та змінивши характер праці як такої, а й розвинула готовність компаній до протистояння сучасним глобальним і регіональним викликам. Найкращі практики оцінювання цифрових навичок охоплюють використання комплексної системи цифрових компетенцій, проведення регулярних оцінок навичок співробітників і надання цільових програм навчання та розвитку для усунення прогалин у навичках. Висновки. Сформульовано, що управління цифровими навичками є постійним процесом, який передбачає визначення навичок і компетенцій, необхідних для кожної ролі в організації, оцінку поточних навичок і надання можливостей навчання та розвитку. Швидкий технологічний прогрес, потреба перенавчання та підвищення кваліфікації, проблема пошуку талантів, цифрова безпека, організаційний опір змінам, відсутність стандартизації, складність інтеграції з наявними процесами тощо становлять виклики для сучасних компаній. Вивчено кейси компанії «Amazon», «Walmart», «General Electrics», «IBM». Вони змогли використати цифрові навички для збору й аналізу даних, покращення співпраці та спілкування команд, а також оптимізації своїх операцій, що призвело до таких переваг, як підвищення ефективності, рівня задоволеності клієнтів, зниження витрат.

Chan Xu, Shuowen Zhang

In this paper, we consider a multiple-input multiple-output (MIMO) radar system for localizing a target based on its reflected echo signals. Specifically, we aim to estimate the random and unknown angle information of the target, by exploiting its prior distribution information. First, we characterize the estimation performance by deriving the posterior Cramér-Rao bound (PCRB), which quantifies a lower bound of the estimation mean-squared error (MSE). Since the PCRB is in a complicated form, we derive a tight upper bound of it to approximate the estimation performance. Based on this, we analytically show that by exploiting the prior distribution information, the PCRB is always no larger than the Cramér-Rao bound (CRB) averaged over random angle realizations without prior information exploitation. Next, we formulate the transmit signal optimization problem to minimize the PCRB upper bound. We show that the optimal sample covariance matrix has a rank-one structure, and derive the optimal signal solution in closed form. Numerical results show that our proposed design achieves significantly improved PCRB performance compared to various benchmark schemes.

Debadutta Dash, Rahul Thapa, Juan M. Banda et al.

Despite growing interest in using large language models (LLMs) in healthcare, current explorations do not assess the real-world utility and safety of LLMs in clinical settings. Our objective was to determine whether two LLMs can serve information needs submitted by physicians as questions to an informatics consultation service in a safe and concordant manner. Sixty six questions from an informatics consult service were submitted to GPT-3.5 and GPT-4 via simple prompts. 12 physicians assessed the LLM responses' possibility of patient harm and concordance with existing reports from an informatics consultation service. Physician assessments were summarized based on majority vote. For no questions did a majority of physicians deem either LLM response as harmful. For GPT-3.5, responses to 8 questions were concordant with the informatics consult report, 20 discordant, and 9 were unable to be assessed. There were 29 responses with no majority on "Agree", "Disagree", and "Unable to assess". For GPT-4, responses to 13 questions were concordant, 15 discordant, and 3 were unable to be assessed. There were 35 responses with no majority. Responses from both LLMs were largely devoid of overt harm, but less than 20% of the responses agreed with an answer from an informatics consultation service, responses contained hallucinated references, and physicians were divided on what constitutes harm. These results suggest that while general purpose LLMs are able to provide safe and credible responses, they often do not meet the specific information need of a given question. A definitive evaluation of the usefulness of LLMs in healthcare settings will likely require additional research on prompt engineering, calibration, and custom-tailoring of general purpose models.

Ashley Smyth, H. Dail Laughinghouse, Karl Havens et al.

Nitrogen and phosphorus are two nutrients that are essential for the growth and survival of plants and animals but are often present in short supply. Both nitrogen and phosphorus are applied regularly through fertilizer to increase the yield of crops needed to feed human populations and for residential and commercial landscaping purposes. This publication contains information for stakeholders, students, scientists, and environmental agencies interested in understanding how nitrogen and phosphorus affect water resources. Major revision by Ashley Smyth, H. Dail Laughinghouse IV, Karl Havens, and Thomas Frazer; 5 pp. https://edis.ifas.ufl.edu/sg118 Accessibility Summary: In accordance with Title II regulations this content meets all points of exemption as Archived web content and/or Preexisting conventional electronic documents.

Lutfi Salkin, Khairan Amal, Muin Yasir et al.

Information technology is currently one of the things that almost all universities widely adopt. The development of information technology requires universities to manage potential resources effectively and efficiently. as stated in the regulation of the Minister of Research, Technology, and Higher Education Number 62 of 2017 concerning the governance of information technology in the university environment that is to support the achievement of increasing access, relevance, quality of higher education, innovation, and strengthening governance and accountability of a university. The consequence of the application of information technology is the emergence of information security risks, the threat of this attack is a concern that every university must be wary of to secure network infrastructure from these attacks. Open access provides great potential for everyone to commit crimes against network infrastructure. as explained that computer network security is part of a system that is very important to be maintained, for that it is necessary to make efforts that can be made by the party responsible for securing the University X network from DDoS attacks. the method used to secure the network infrastructure makes a filtering policy to block DDoS attacks, the results obtained from the application according to the filter rules applied to the proxy device successfully block DDoS attacks.

Adam Gronowski, William Paul, Fady Alajaji et al.

Designing machine learning algorithms that are accurate yet fair, not discriminating based on any sensitive attribute, is of paramount importance for society to accept AI for critical applications. In this article, we propose a novel fair representation learning method termed the Rényi Fair Information Bottleneck Method (RFIB) which incorporates constraints for utility, fairness, and compactness (compression) of representation, and apply it to image and tabular data classification. A key attribute of our approach is that we consider - in contrast to most prior work - both demographic parity and equalized odds as fairness constraints, allowing for a more nuanced satisfaction of both criteria. Leveraging a variational approach, we show that our objectives yield a loss function involving classical Information Bottleneck (IB) measures and establish an upper bound in terms of two Rényi measures of order $α$ on the mutual information IB term measuring compactness between the input and its encoded embedding. We study the influence of the $α$ parameter as well as two other tunable IB parameters on achieving utility/fairness trade-off goals, and show that the $α$ parameter gives an additional degree of freedom that can be used to control the compactness of the representation. Experimenting on three different image datasets (EyePACS, CelebA, and FairFace) and two tabular datasets (Adult and COMPAS), using both binary and categorical sensitive attributes, we show that on various utility, fairness, and compound utility/fairness metrics RFIB outperforms current state-of-the-art approaches.

Baban Gain, Dibyanayan Bandyopadhyay, Tanik Saikh et al.

Natural Language Processing (NLP) and Information Retrieval (IR) in the judicial domain is an essential task. With the advent of availability domain-specific data in electronic form and aid of different Artificial intelligence (AI) technologies, automated language processing becomes more comfortable, and hence it becomes feasible for researchers and developers to provide various automated tools to the legal community to reduce human burden. The Competition on Legal Information Extraction/Entailment (COLIEE-2019) run in association with the International Conference on Artificial Intelligence and Law (ICAIL)-2019 has come up with few challenging tasks. The shared defined four sub-tasks (i.e. Task1, Task2, Task3 and Task4), which will be able to provide few automated systems to the judicial system. The paper presents our working note on the experiments carried out as a part of our participation in all the sub-tasks defined in this shared task. We make use of different Information Retrieval(IR) and deep learning based approaches to tackle these problems. We obtain encouraging results in all these four sub-tasks.

Jonathan Huffmann, Martin Mittelbach

Based on the canonical correlation analysis we derive series representations of the probability density function (PDF) and the cumulative distribution function (CDF) of the information density of arbitrary Gaussian random vectors as well as a general formula to calculate the central moments. Using the general results we give closed-form expressions of the PDF and CDF and explicit formulas of the central moments for important special cases. Furthermore, we derive recurrence formulas and tight approximations of the general series representations, which allow very efficient numerical calculations with an arbitrarily high accuracy as demonstrated with an implementation in Python publicly available on GitLab. Finally, we discuss the (in)validity of Gaussian approximations of the information density.

Katherine McDonough, Ludovic Moncla, M. V. D. Camp

ABSTRACT Geographic text analysis (GTA) research in the digital humanities has focused on projects analyzing modern English-language corpora. These projects depend on temporally specific lexicons and gazetteers that enable place name identification and georesolution. Scholars working on the early modern period (1400–1800) lack temporally appropriate geoparsers and gazetteers and have been reliant on general purpose linked open data services like Geonames. These anachronistic resources introduce significant information retrieval and ethical challenges for early modernists. Using the geography entries of the canonical eighteenth-century Encyclopédie, we evaluate rule-based named entity recognition (NER) systems to pinpoint areas where they would benefit from adjustments for processing historical corpora. As we demonstrate, annotating nested and extended place information is one way to improve early modern GTA. Working with Enlightenment sources also motivates a critique of the landscape of digital geospatial data.

Andrea Heckert, Laura P. Forsythe, Kristin L. Carman et al.

Abstract Background There is growing interest in patient and stakeholder engagement in research, yet limited evidence about effective methods. Since 2012, the Patient-Centered Outcomes Research Institute (PCORI) has funded patient-centered comparative effectiveness research with a requirement for engaging patients and other stakeholders as research partners in study planning, conduct, and dissemination. This requirement, unique among large healthcare research funders in the US, provides an opportunity to learn about challenges encountered and specific strategies used by PCORI-funded study teams. The primary objective of this study is to describe -- from the perspective of PCORI investigators and research partners—the most common engagement challenges encountered in the first two years of the projects and promising strategies to prevent and overcome these challenges. Methods Descriptive information about investigators, partners, and their engagement was collected from investigators via annual (N = 235) and mid-year (N = 40) project progress reporting to PCORI, and from their partners (N = 260) via voluntary survey. Qualitative data were analyzed using content and thematic analyses. Results Investigators and partners most often described engagement challenges in three domains: (1) infrastructure to support engagement, (2) building relationships, and (3) maintaining relationships. Infrastructure challenges related to financial and human resources, including funding support and dedicated staff, identifying diverse groups of partners, and partners’ logistical needs. Challenges for both building and maintaining relationships encompass a variety of aspects of authentic, positive interactions that facilitate mutual understanding, full participation, and genuine influence on the projects. Strategies to prevent or mitigate engagement challenges also corresponded overall to the same three domains. Both groups typically described strategies more generally, with applicability to a range of challenges rather than specific actions to address only particular challenges. Conclusion Meaningful engagement of patients and other stakeholders comes with challenges, as does any innovation in the research process. The challenges and promising practices identified by these investigators and partners, related to engagement infrastructure and the building and maintenance of relationships, reveal actionable areas to improve engagement, including organizational policies and resources, training, new engagement models, and supporting engagement by viewing it as an investment in research uptake and impact.

Xiaoqiang JIAO, Derara Sori FEYISA, Jasper KANOMANYANGA, Ngula David MUTTENDANGO, Shingirai MUDARE, Amadou NDIAYE, Bilisuma KABETO, Felix Dapare DAKORA, Fusuo ZHANG

Sustainable food production to feed the growing population in Africa remains a major challenge. Africa has 64% of the global arable land but produces less than 10% of its food locally due to its inherently low soil nutrient concentrations. Poor soil fertility and a lack of fertilizer use are the major constraints to increasing crop yields in Africa. On average only about 8.8 kg NPK fertilizer is applied per hectare by African smallholder farmers. There is therefore considerable potential for increasing food production through sustainable intensification of the cropping systems. The low crop yields in Africa are also partly due to limited farmer access to modern agronomic techniques, including improved crop varieties, a lack of financial resources, and the absence of mechanisms for dissemination of information to smallholders. This study analyzed the Science and Technology Backyards (STBs) model and investigated its use for the transformation of agriculture in Africa. Some key lessons for sustainable crop intensification in Africa can be found from analysis of the STB model which is well established in China. These include (1) scientist-farmer engagement to develop adaptive and innovative technology for sustainable crop production, (2) dissemination of technology by empowering smallholders, especially leading farmers, and (3) the development of an open platform for multiple resource involvement rather than relying on a single mechanism. This review evaluates the benefits of the STB model used in China for adoption to increase agricultural productivity in Africa, with a perspective on sustainable crop intensification on the continent.

A. V. Polyanin, Yu. P. Soboleva, V. V. Tarnovskiy

The role of small and medium-sized enterprises in the economic life of society cannot be overestimated: it contributes to economic growth in the country, increases the level of employment of the population, forms healthy competition, promotes the development of innovation activities and solves many social problems. In this regard, State support for entrepreneurship is essential in order to create an enabling environment for its further development. To date, a national project on the formation of support mechanisms for small and medium-sized enterprises has been adopted and is being implemented. The relevant national project is implemented within the framework of five federal projects aimed at improving the conditions of entrepreneurship, access of business entities to financial resources, acceleration of business entities, popularization of entrepreneurship, and development of rural cooperation. At the same time, in the context of digital globalization, the effective implementation of these directions is impossible without the introduction of information technologies into the activities of the business entities themselves. Research on the introduction of information technologies into business structures is not systematic and reveals certain aspects of this issue. The relevance of the study is due to the fact that within the framework of the national projects approved in our country, no mechanism has been developed to form a business model that ensures the effective introduction of such technologies into the activities of small and medium-sized businesses. Most scientific works of this topic reveal issues of implementation of specific information technologies by business entities. Therefore, the formation of a generalized model of effective introduction of IT-technologies in the activities of small and medium-sized enterprises is a pressing task that contributes to the achievement of the tasks set for national projects.The purpose of this study is to develop methodological and practical recommendations to increase the efficiency of Russian small and medium-sized enterprises on the basis of the implementation of the concept of digitalization of business. The study was aimed at national projects “Small and medium-sized entrepreneurship and support for individual entrepreneurial initiative” and “Digital economy of the Russian Federation,” interim results of their implementation. The subject of the study is the system of support for the development of Russian small and medium-sized enterprises.The scientific novelty of this study consists in the development of an algorithm for the transition of small and medium-sized enterprises to digitalization of business processes, in the systematization of business entities by the level of introduction of digital technologies into the activities, as well as in the grouping of the main directions of digitization of business entities.

María Amelia Linari, Alejandro Daín, María Lidia Ruíz et al.

Innovative technologies bring great possibilities of increasing human well-being. However, technological progress does not guarantee equitable health outcomes. While technological advances define the way in which people, systems and information interact, communities with fewer resources tend to be left excluded, and that will subsequently have an impact on quality. Publications explain that in communities where technological solutions have been imposed, there has later been abandoned equipment, software that is incompatible and frustrated management policies. Nevertheless, there are some cases of general technological implementations that undermine equity, justice and human rights. For example, the use of high technology in medical interventions as preventive measures or diagnosis, the use of genes which prevent the reuse of crop seeds allowed for consuming, and many more. To obtain equitable results, the design and planning of the technology must respect the ethical principles, local values and their folklore, among other points. Decisions require compromise in the medium and long term and local leadership.

Gamal G. L. Nashed, Salvatore Capozziello

We derive magnetic black hole solutions using a general gauge potential in the framework of teleparallel equivalent general relativity. One of the solutions gives a non-trivial value of the scalar torsion. This non-triviality of the torsion scalar depends on some values of the magnetic field. The metric of those solutions behave asymptotically as Anti-de-Sitter/ de-Sitter (AdS/dS) spacetimes. The energy conditions are discussed in details. Also, we calculate the torsion and curvature invariants to discuss singularities. Additionally, we calculate the conserved quantities using the Einstein-Cartan geometry to understand the physics of the constants appearing into the solutions.