Hasil untuk "Information resources (General)"

S. Pirandola, Bhaskar Roy Bardhan, T. Gehring et al.

Quantum sensing has become a broad field. It is generally related with the idea of using quantum resources to boost the performance of a number of practical tasks, including the radar-like detection of faint objects, the readout of information from optical memories, and the optical resolution of extremely close point-like sources. Here, we first focus on the basic tools behind quantum sensing, discussing the most recent and general formulations for the problems of quantum parameter estimation and hypothesis testing. With this basic background in hand, we then review emerging applications of quantum sensing in the photonic regime both from a theoretical and experimental point of view. Besides the state of the art, we also discuss open problems and potential next steps. This Review discusses emerging applications of photonic quantum sensing. The theoretical and experimental developments of quantum reading of classical data, quantum illumination of targets, and optical resolution beyond the Rayleigh limit are described.

Xinlian Liang, V. Kankare, J. Hyyppä et al.

Abstract Decision making on forest resources relies on the precise information that is collected using inventory. There are many different kinds of forest inventory techniques that can be applied depending on the goal, scale, resources and the required accuracy. Most of the forest inventories are based on field sample. Therefore, the accuracy of the forest inventories depends on the quality and quantity of the field sample. Conventionally, field sample has been measured using simple tools. When map is required, remote sensing materials are needed. Terrestrial laser scanning (TLS) provides a measurement technique that can acquire millimeter-level of detail from the surrounding area, which allows rapid, automatic and periodical estimates of many important forest inventory attributes. It is expected that TLS will be operationally used in forest inventories as soon as the appropriate software becomes available, best practices become known and general knowledge of these findings becomes more wide spread. Meanwhile, mobile laser scanning, personal laser scanning, and image-based point clouds became capable of capturing similar terrestrial point cloud data as TLS. This paper reviews the advances of applying TLS in forest inventories, discusses its properties with reference to other related techniques and discusses the future prospects of this technique.

M. Davies, A. Mayne

S. Birley

B. Schmeichel, K. Vohs, R. Baumeister

Some complex thinking requires active guidance by the self, but simpler mental activities do not. Depletion of the self's regulatory resources should therefore impair the former and not the latter. Resource depletion was manipulated by having some participants initially regulate attention (Studies 1 and 3) or emotion (Study 2). As compared with no-regulation participants who did not perform such exercises, depleted participants performed worse at logic and reasoning (Study 1), cognitive extrapolation (Study 2), and a test of thoughtful reading comprehension (Study 3). The same manipulations failed to cause decrements on a test of general knowledge (Study 2) or on memorization and recall of nonsense syllables (Study 3). Successful performance at complex thinking may therefore rely on limited regulatory resources.

M. Wade, J. Hulland

Yupeng LI, Yaning CHEN, Fei WANG et al.

Tajikistan, a mountainous country and a vital water tower for Central Asia, is becoming increasingly vulnerable to snow drought under climate change, threatening its snow- and glacier-fed streamflow. Yet, the impacts of snow drought on the regional hydrology remain insufficiently understood. In this study, we integrated multisource data, including the Fifth Generation European Centre for Medium-Range Weather Forecasts Atmospheric Reanalysis for Land Applications (ERA5-Land) data and hydrological station data, to systematically assess the snow drought patterns and their impacts on streamflow during 1950–2023. We identified snow drought events based on precipitation and snow fraction anomalies relative to climatological means and classified them into warm snow drought, dry snow drought, and warm&dry snow drought. The results revealed that snow drought was a recurrent phenomenon, occurring in 51.70% of the years during the study period, with warm&dry snow drought accounting for 21.90% of the total events. Both the frequency and severity exhibited pronounced spatial variability, largely governed by the elevation and snowfall fraction. Specifically, the frequency of warm snow drought was negatively correlated with the snowfall fraction, decreasing on average by 0.20 per unit increase in snowfall fraction, whereas the frequency of dry snow drought was positively correlated, increasing by 0.07 per unit increase. The streamflow analysis results demonstrated that snow drought typically reduced the warm-season discharge by 5.00%–18.00% in certain rivers, thereby exacerbating the water stress during the dry season. The results of this study advance our understanding by explicitly linking the types of snow drought to hydrological responses in Central Asia’s high mountains, providing a scientific basis for climate adaptation and sustainable water resource management in Tajikistan.

Arafatur Rahaman, Abidur Rahman Efaz, Mushfiq Ali Rajon et al.

Abstract The Bangladesh Uprising of July 2024 was a critical period in the country’s political trajectory, synonymous with mass mobilization, regime overthrow, and an unprecedented information blackout. This research explores the pivotal contribution of digital disinformation to the course and perceptions of the revolution. To that end, in addition to a quantitative content and sentiment analysis, we combine this with qualitative interviews, looking specifically at how misinformation was shared, amplified, and debunked across digital platforms. This study draws on 112 verified fact-checking reports, 87 news articles, and 15 semi-structured interviews with journalists, fact-checkers, and digital rights activists to examine how politically charged disinformation shaped the July 2024 protests in Bangladesh. Findings reveal a surge in coordinated campaigns amplified through social media echo chambers, influencing protest narratives and public trust. Although local fact-checking grew rapidly, structural challenges of limited resources limited their effects, which worsened with algorithm amplifications, low media literacy, and partisan mistrust. The article locates these dynamics of disinformation in the context of more general problems of media regulation, political polarization, and digital infrastructures in transitional democracies. It calls for a multi-pronged solution, including institutional reform, algorithmic accountability, and continued digital literacy investments. Through the lens of Bangladesh’s July 2024 crisis, the study adds to the global conversation on disinformation in crony-authoritarianism and underscores the critical nature of context-sensitive verification systems in the Global South.

Raúl Gutiérrez, Víctor Rampérez, Horacio Paggi et al.

The information fusion field has recently been attracting a lot of interest within the scientific community, as it provides, through the combination of different sources of heterogeneous information, a fuller and/or more precise understanding of the real world than can be gained considering the above sources separately. One of the fundamental aims of computer systems, and especially decision support systems, is to assure that the quality of the information they process is high. There are many different approaches for this purpose, including information fusion. Information fusion is currently one of the most promising methods. It is particularly useful under circumstances where quality might be compromised, for example, either intrinsically due to imperfect information (vagueness, uncertainty) or because of limited resources (energy, time). In response to this goal, a wide range of research has been undertaken over recent years. To date, the literature reviews in this field have focused on problem-specific issues and have been circumscribed to certain system types. Therefore, there is no holistic and systematic knowledge of the state of the art to help establish the steps to be taken in the future. In particular, aspects like what impact different information fusion methods have on information quality, how information quality is characterised, measured and evaluated in different application domains depending on the problem data type or whether fusion is designed as a flexible process capable of adapting to changing system circumstances and their intrinsically limited resources have not been addressed. This paper aims precisely to review the literature on research into the use of information fusion techniques specifically to improve information quality, analysing the above issues in order to identify a series of challenges and research directions, which are presented in this paper.

Satyajit Dhadumia, M. Ashok Kumar

In information geometry, statistical models are considered as differentiable manifolds, where each probability distribution represents a unique point on the manifold. A Riemannian metric can be systematically obtained from a divergence function using Eguchi's theory (1992); the well-known Fisher-Rao metric is obtained from the Kullback-Leibler (KL) divergence. The geometric derivation of the classical Cramér-Rao Lower Bound (CRLB) by Amari and Nagaoka (2000) is based on this metric. In this paper, we study a Riemannian metric obtained by applying Eguchi's theory to the Basu-Harris-Hjort-Jones (BHHJ) divergence (1998) and derive a generalized Cramér-Rao bound using Amari-Nagaoka's approach. There are potential applications for this bound in robust estimation.

Franz Louis Cesista, Rui Aguiar, Jason Kim et al.

Business Document Information Extraction (BDIE) is the problem of transforming a blob of unstructured information (raw text, scanned documents, etc.) into a structured format that downstream systems can parse and use. It has two main tasks: Key-Information Extraction (KIE) and Line Items Recognition (LIR). In this paper, we argue that BDIE is best modeled as a Tool Use problem, where the tools are these downstream systems. We then present Retrieval Augmented Structured Generation (RASG), a novel general framework for BDIE that achieves state of the art (SOTA) results on both KIE and LIR tasks on BDIE benchmarks. The contributions of this paper are threefold: (1) We show, with ablation benchmarks, that Large Language Models (LLMs) with RASG are already competitive with or surpasses current SOTA Large Multimodal Models (LMMs) without RASG on BDIE benchmarks. (2) We propose a new metric class for Line Items Recognition, General Line Items Recognition Metric (GLIRM), that is more aligned with practical BDIE use cases compared to existing metrics, such as ANLS*, DocILE, and GriTS. (3) We provide a heuristic algorithm for backcalculating bounding boxes of predicted line items and tables without the need for vision encoders. Finally, we claim that, while LMMs might sometimes offer marginal performance benefits, LLMs + RASG is oftentimes superior given real-world applications and constraints of BDIE.

Abel Centella-Artola, Arnoldo Bezanilla-Morlot, Roberto Serrano-Notivoli et al.

The paper presents a high-resolution (-3km) gridded dataset for daily precipitation across Cuba for 1961-2008, called CubaPrec1. The dataset was built using the information from the data series of 630 stations from the network operated by the National Institute of Water Resources. The original station data series were quality controlled using a spatial coherence process of the data, and the missing values were estimated on each day and location independently. Using the filled data series, a grid of 3 × 3 km spatial resolution was constructed by estimating daily precipitation and their corresponding uncertainties at each grid box. This new product represents a precise spatiotemporal distribution of precipitation in Cuba and provides a useful baseline for future studies in hydrology, climatology, and meteorology. The data collection described is available on zenodo: https://doi.org/10.5281/zenodo.7847844

ZANG Jie, ZHOU Wanlin, WANG Yan

Considering the matching problem of enterprise resources and customer requirements,the existing methods have the problems that the resource and requirement encapsulation is not accurate enough and the matching effect can't satisfy uses' requirement.In order to solve the problem of diversity and ambiguity of enterprise resource and requirement description,this paper proposes the dynamic user-defined template encapsulation.According to the feature that most of the encapsulated requirements and resources are Chinese short texts,an interactive text matching model which integrates multi-head attention mechanism and sia-mese network is proposed.The semantic differences and similarities between sentences are considered in this model.It uses word mixing vectors as input to enhance the semantic information of the text,combines the Siamese network with the multi-head attention mechanism,and extractes the semantic features of the context as an independent unit to fully interact with the semantic features.In order to verify the effectiveness of the model,the classical data set LCQMC and the self-constructed CSMD data set are used to conduct experiments on the model.The results show that the accuracy and performance of the model are improved in different degrees,which provides a more accurate matching method for enterprise resources and requirements.

Геннадій Гребньов

У статті досліджено інформаційний складник гібридної війни, розв’язаної росією протии України. У цьому контексті розглянуто методи та інструменти, що використовує країна-агресор, а також актуальні питання інформаційної безпеки та «медіагігієни», які постають перед українцями. З’ясовано, що на нинішньому етапі повномасштабної агресії ворог все більше вдається до проведення інформаційно-психологічних спеціальних операцій, продукування та поширення відвертої дезінформації, маніпуляцій та фейків. Як інструменти інформаційної війни широко застосовуються традиційні та новітні ЗМІ, зокрема соціальні мережі. Методом моніторингу, синтезу та контент-аналізу доведено, що з огляду на медіабезпеку найбільш ризикованими джерелами інформації є такі соціальні мережі, як Telegram, YouTube та Facebook. Водночас за період повномасштабного вторгнення росії спостерігається тенденція щодо збільшення кількості громадян, для яких основним джерелом отримання інформації є саме соціальні мережі. А тому особливої актуальності набувають питання медіагігієни, головними складниками яких є вміння оцінити й відфільтрувати «небезпечний» контент та відповідальне ставлення до поширення інформації. Стосується це як пересічних користувачів соціальних мереж, так і професійних журналістів та блогерів. Питання медіаосвіти є надзвичайно важливими не лише для конкретного індивіда, який отримує інформацію зі ЗМІ та соціальних мереж, а й загалом для національної безпеки держави, яка має ефективно реагувати на інформаційні атаки ворога. В умовах війни медіаграмотність населення набуває все більшого значення, тож поліпшення рівня обізнаності співвітчизників має стати одним із пріоритетних завдань органів влади та численних громадських інститутів.

Kieran A. Murphy, Dani S. Bassett

One of the fundamental steps toward understanding a complex system is identifying variation at the scale of the system's components that is most relevant to behavior on a macroscopic scale. Mutual information provides a natural means of linking variation across scales of a system due to its independence of functional relationship between observables. However, characterizing the manner in which information is distributed across a set of observables is computationally challenging and generally infeasible beyond a handful of measurements. Here we propose a practical and general methodology that uses machine learning to decompose the information contained in a set of measurements by jointly optimizing a lossy compression of each measurement. Guided by the distributed information bottleneck as a learning objective, the information decomposition identifies the variation in the measurements of the system state most relevant to specified macroscale behavior. We focus our analysis on two paradigmatic complex systems: a Boolean circuit and an amorphous material undergoing plastic deformation. In both examples, the large amount of entropy of the system state is decomposed, bit by bit, in terms of what is most related to macroscale behavior. The identification of meaningful variation in data, with the full generality brought by information theory, is made practical for studying the connection between micro- and macroscale structure in complex systems.

Baris Arslan, Tayfun Sugur, Osman Ciloglu et al.

Introduction: There are many possible sources of medical information; however, the quality of the information varies. Poor quality or inaccurate resources may be harmful if they are trusted by providers. This study aimed to analyze the quality of coronavirus disease 2019 (COVID-19)-related intubation videos on YouTube. Methods: The term “COVID-19 intubation” was searched on YouTube. The top 100 videos retrieved were sorted by relevance and 37 videos were included. The video demographics were recorded. The quality of the videos was analyzed using an 18-point checklist, which was designed for evaluating COVID-19 intubation. Videos were also evaluated using general video quality scores and the modified Journal of the American Medical Association score. Results: The educational quality was graded as good for eight (21.6%) videos, moderate for 13 (35.1%) videos, and poor for 16 (43.2%) videos. The median safe COVID-19 intubation score (SCIS) was 11 (IQR = 5–13). The SCISs indicated that videos prepared in an intensive care unit were higher in quality than videos from other sources (p < 0.05). The length of the video was predictive of quality (area under the curve = 0.802, 95% CI = 0.658–0.945, p = 0.10). Conclusions: The quality of YouTube videos for COVID-19 intubation is substandard. Poor quality videos may provide inaccurate knowledge to viewers and potentially cause harm.

Li Li, Zhongqun Wang, Chen Li et al.

The collaborative filtering recommendation technique (CFR) is one of the techniques used in recommended systems, in which the most proximal neighbours to a target user are selected. Their profiles are used to predict rating for items as yet unrated by that target user. However, malicious users inject fake user profiles to destroy the security and reliability of the recommender systems, which is called shilling attacks. Therefore, it is crucial to improve the recommendation technique against shilling attacks. Malicious users use a single method to perform shilling attacks. Intuitively, fusing multiple criteria to construct CFR can effectively resist shilling attacks. A novel CFR is proposed against shilling attacks (called CFR-F). In our approach, a similar interest users’ resource set is obtained first by integrating users’ dynamic interest model and social tags. Then, a similar interest user resource set is selected according to a strategy that selects preference influence weight based on user background. Our experimental results show that our approach can recommend accurate information resources and has a lower Mean Absolute Error (MAE) and Average Prediction Shift (APS) than traditional techniques by 50% and 20%, respectively.

Amirreza Asnafi, Mohsen Haji Zeinolabedini, Faezeh Ahmadipour

Access to the required information in all available scientific disciplines is one of the most important factors in the survival of that field. In the architecture field, the type of information format differs from other disciplines. The purpose of this study was to identify the behavior of images in the architecture of Shahid Beheshti University. The present study is an applied target and uses a descriptive survey method. The statistical population of the study consists of two groups of students and professors in the architecture major of Shahid Beheshti University. To determine the sample size, the Cochran formula was used and the sample size in this formula was 296 people. The results showed that the architects mainly used images for identifying creative ideas and taking advantage of the details of architectural structures. The type of image content they used was mostly photos, maps, and charts, which could be found in engines and image databases by limiting the size of the image and following related links as long as the image was taken. One of the major obstacles in finding images for architects was the lack of familiarity with the way they were searched. Creativity, proximity to the subject, credibility, and quality of the images were the criteria for selecting content. Considering the library's share in retrieving research-based images, it is suggested that library and library librarians conduct awareness-raising activities at the university's research groups such as brochures, conferences, library visits, and workshops.

Stanislav Fedorenko, Lesya Vasylenko, Yuliia Bereznytska et al.

The development of environmental management in Ukraine is determined by the urgent need to overcome environmental problems and ensure the environmental safety of society, especially under the conditions of martial law. Today, the domestic economy is three times more resource-intensive than the world economy, the technological base and infrastructure complex of public production are rapidly wearing out, which leads to a decrease in the level of technological and environmental safety. Environmental management is related to the national economy and forms information about the need to use natural resources when promoting effective development. A comprehensive project-targeted approach to the development of new forms of ownership and market economy reflects the interrelationship of all parts of the nature management project. The development of the scientific foundations of nature management is facilitated by the formulation of a general plan for the placement of productive forces. The ecological situation in Ukraine has long been called a crisis. In recent decades, new scientific directions have appeared, the result of which have been new ideas about human, society and nature and their coexistence. One of these directions is environmental management, which today is the ideology of production activity management, as it provides an effective toolkit for solving current problems and preventing the emergence of new production environmental and economic issues.

Jean-François Cardoso

I recall my first encounter with Professor Shun-ichi Amari who, once upon a time in Las Vegas, gave me a precious hint about connecting Independent Component Analysis (ICA) to Information Geometry. The paper sketches, rather informally, some of the insights gained in following this lead.