Hasil untuk "Information resources (General)"

J. D'Arcy, Anat Hovav, D. Galletta

Fengguo Wei, Sankardas Roy, Xinming Ou et al.

Julia M. Barbarino, Michelle Whirl‐Carrillo, R. Altman et al.

As precision medicine becomes increasingly relevant in healthcare, the field of pharmacogenomics (PGx) also continues to gain prominence in the clinical setting. Leading institutions have begun to implement PGx testing and the amount of published PGx literature increases yearly. The Pharmacogenomics Knowledgebase (PharmGKB; www.pharmgkb.org) is one of the foremost worldwide resources for PGx knowledge, and the organization has been adapting and refocusing its mission along with the current revolution in genomic medicine. The PharmGKB website provides a diverse array of PGx information, from annotations of the primary literature to guidelines for adjusting drug treatment based on genetic information. It is freely available and accessible to everyone from researchers to clinicians to everyday citizens. PharmGKB was found over 17 years ago, but continues to be a vital resource for the entire PGx community and the general public.

Petar Milovanovic, Tatjana Pekmezovic, Marija Djuric

Universities and journals increasingly rely on software tools for detecting textual overlap of a scientific text with the previously published literature to detect potential plagiarism. Although software outputs need to be carefully reviewed by competent humans to verify the existence of plagiarism, university and journal staff, for various reasons, often erroneously interpret the degree of plagiarism based on the percentage of textual overlap shown in the similarity report. This is often accompanied by explicit recommendations to the author(s) to paraphrase the text to achieve an “acceptable” percentage of overlap. Here, based on the available literature and real-world examples from similarity reports, we provide a classification with extensive examples of phrases that falsely inflate the similarity index and argue the futility and dangers of rephrasing such statements just for the sake of reducing the similarity index. The examples provided in this paper call for a more reasonable assessment of text similarity. To fully endorse the principles of academic integrity and prevent loss of clarity of the scientific literature, we believe it is important to shift from pure bureaucratic and quantificational view on the originality of scientific texts to human-centered qualitative assessment of the manuscripts, including the software outputs.

Mohammad Aliannejadi, Jacek Gwizdka, Hamed Zamani

At its core, information access and seeking is an interactive process. In existing search engines, interactions are limited to a few pre-defined actions, such as "requery", "click on a document", "scrolling up/down", "going to the next result page", "leaving the search engine", etc. A major benefit of moving towards generative IR systems is enabling users with a richer expression of information need and feedback and free-form interactions in natural language and beyond. In other words, the actions users take are no longer limited by the clickable links and buttons available on the search engine result page and users can express themselves freely through natural language. This can go even beyond natural language, through images, videos, gestures, and sensors using multi-modal generative IR systems. This chapter briefly discusses the role of interaction in generative IR systems. We will first discuss different ways users can express their information needs by interacting with generative IR systems. We then explain how users can provide explicit or implicit feedback to generative IR systems and how they can consume such feedback. Next, we will cover how users interactively can refine retrieval results. We will expand upon mixed-initiative interactions and discuss clarification and preference elicitation in more detail. We then discuss proactive generative IR systems, including context-aware recommendation, following up past conversations, contributing to multi-party conversations, and feedback requests. Providing explanation is another interaction type that we briefly discuss in this chapter. We will also briefly describe multi-modal interactions in generative information retrieval. Finally, we describe emerging frameworks and solutions for user interfaces with generative AI systems.

Dakota Aaron McCarty, Hyun Woo Kim

Point of interest (POI) data refers to information about the location and type of amenities, services, and attractions within a geographic area. This data is used in urban studies research to better understand the dynamics of a city, assess community needs, and identify opportunities for economic growth and development. POI data is beneficial because it provides a detailed picture of the resources available in a given area, which can inform policy decisions and improve the quality of life for residents. This paper presents a large-scale, standardized POI dataset from OpenStreetMap (OSM) for the European continent. The dataset's standardization and gridding make it more efficient for advanced modeling, reducing 7,218,304 data points to 988,575 without significant resolution loss, suitable for a broader range of models with lower computational demands. The resulting dataset can be used to conduct advanced analyses, examine POI spatial distributions, conduct comparative regional studies, and research to help enhance the understanding of the distribution of economic activity and attractions, and subsequently help in the understanding of the economic health, growth potential, and cultural opportunities of an area. The paper describes the materials and methods used in generating the dataset, including OSM data retrieval, processing, standardization, hexagonal grid generation, and point count aggregations. The dataset can be used independently or integrated with other relevant datasets for more comprehensive spatial distribution studies in future research.

María Virginia Palchetti, Fernando Zamudio, Sebastián Zeballos et al.

Plants are essential for our lives because they provide food, medicine, fuel, shelter, and immaterial resources. Understanding patterns of plant uses through large-scale plant use analysis may contribute to the development of a biocultural conservation approach. We conducted a systematic review to assess current knowledge of the ethnoflora of Argentina, as well as to identify taxonomic and geographic patterns of ethnobotanical uses of native plants at the large scale. We analyzed 124 articles reporting the use of 1706 species. We found that the most widely studied region and use category were Chaco and medicine, respectively. The number of useful native species within a family was positively related to the total native species in each family at the country level. In general, species of greatest cultural importance at the country level had a wide distribution. Almost 70% of native plants used in one phytogeographic province were exclusive to it, and species with the highest importance were characteristic elements of its vegetation. We found that southern Argentina has an exclusive ethnoflora that differs from that in a large area of central and northern Argentina. Our review highlights that plants used by people are intimately associated with the local environment, and that species with great cultural importance across phytogeographic provinces are frequent in the landscape. We provide the first analysis of ethnobotanical studies and a database of useful native plants across Argentina. This information highlights strengths and gaps in knowledge of useful native species, which is crucial for conservation, sustainability and human well-being.

Maoyu Wang, Zhenxing Feng

Gavin Yamey, Kaci Kennedy McDade, Wenhui Mao et al.

Background Although it is difficult to quantify, previous estimates suggested that China’s global health aid has increased sharply since the early 2000s. Unlike many donors, China has no official aid reporting obligations, nor does it voluntarily disclose detailed aid information. Our study aimed to create a standardised estimate using commonly accepted definitions of aid and frameworks for categorising health projects.Methods We categorised AidData’s Chinese Official Finance Dataset health-related projects according to health aid frameworks from the Organisation for Economic Co-operation and Development (OECD) and the Institute for Health Metrics and Evaluation (IHME). Only projects that complied with the definition of official development assistance were included. We analysed the project count and financial value to assess China’s priority health aid areas.Findings Between 2000 and 2017, China funded 1339 health-related aid projects, or 13% of its total aid project portfolio. Most of these projects were located in sub-Saharan Africa. According to the OECD framework, the priority focus areas of these projects were: medical services, such as specialty equipment and tertiary services (n=489, 37%); basic health care, such as basic medical services and drugs (n=251, 19%); malaria control (n=234, 18%) and basic health infrastructure (n=178, 13%). Under the IHME framework, health systems strengthening accounted for 74% (n=991) of total projects, primarily due to China’s contributions to human resources for health, infrastructure and equipment. The only other major allocation under the IHME framework was malaria (n=234, 18%). When we estimated missing financial values under the OECD framework, China was the fifth largest health aid donor to African countries from 2002 to 2017, after the USA, the UK, Canada and Germany.Conclusion Our findings enable a better understanding of Chinese health aid in the absence of transparent aid reporting, which could contribute to better coordination, collaboration and resource allocation for both donor and recipient countries.

Frans van der Sluis

Rather than using (proxies of) end user or expert judgment to decide on the ranking of information, this paper asks whether conversations about information quality might offer a feasible and valuable addition for ranking information. We introduce a theoretical framework for information quality, outlining how information interaction should be perceived as a conversation and quality be evaluated as a conversational contribution. Next, an overview is given of different systems of social alignment and their value for assessing quality and ranking information. We propose that a collaborative approach to quality assessment is preferable and raise key questions about the feasibility and value of such an approach for ranking information. We conclude that information quality is an inherently interactive concept, which involves an interaction between users of different backgrounds and in different situations as well as of quality signals on users' search behavior and experience.

Onur Günlü, Rafael F. Schaefer, Holger Boche et al.

The problem of secure source coding with multiple terminals is extended by considering a remote source whose noisy measurements are the correlated random variables used for secure source reconstruction. The main additions to the problem include 1) all terminals noncausally observe a noisy measurement of the remote source; 2) a private key is available to all legitimate terminals; 3) the public communication link between the encoder and decoder is rate-limited; and 4) the secrecy leakage to the eavesdropper is measured with respect to the encoder input, whereas the privacy leakage is measured with respect to the remote source. Exact rate regions are characterized for a lossy source coding problem with a private key, remote source, and decoder side information under security, privacy, communication, and distortion constraints. By replacing the distortion constraint with a reliability constraint, we obtain the exact rate region also for the lossless case. Furthermore, the lossy rate region for scalar discrete-time Gaussian sources and measurement channels is established.

Roope Uola, Tristan Kraft, Jiangwei Shang et al.

Resource theories can be used to formalize the quantification and manipulation of resources in quantum information processing such as entanglement, asymmetry and coherence of quantum states, and incompatibility of quantum measurements. Given a certain state or measurement, one can ask whether there is a task in which it performs better than any resourceless state or measurement. Using conic programming, we prove that any general robustness measure (with respect to a convex set of free states or measurements) can be seen as a quantifier of such outperformance in some discrimination task. We apply the technique to various examples, e.g., joint measurability, positive operator valued measures simulable by projective measurements, and state assemblages preparable with a given Schmidt number.

Joo-Kyung Kim, Young-Bum Kim, R. Sarikaya et al.

Training a POS tagging model with crosslingual transfer learning usually requires linguistic knowledge and resources about the relation between the source language and the target language. In this paper, we introduce a cross-lingual transfer learning model for POS tagging without ancillary resources such as parallel corpora. The proposed cross-lingual model utilizes a common BLSTM that enables knowledge transfer from other languages, and private BLSTMs for language-specific representations. The cross-lingual model is trained with language-adversarial training and bidirectional language modeling as auxiliary objectives to better represent language-general information while not losing the information about a specific target language. Evaluating on POS datasets from 14 languages in the Universal Dependencies corpus, we show that the proposed transfer learning model improves the POS tagging performance of the target languages without exploiting any linguistic knowledge between the source language and the target language.

Yuri Phedorovich Kartavtsev

Application of molecular genetic markers appeared to be very fruitful in achieving many goals, including (i) proving the theoretic basements of general biology and (ii) assessment of worldwide biodiversity. Both are provided in the present meta-analysis and a review as the main signal. One of the basic current challenges in modern biology in the face of new demands in the 21st century is the validation of its paradigms such as the synthetic theory of evolution (STE) and biological species concept (BSC). Another of most valuable goals is the biodiversity assessment for a variety of social needs including free web-based information resources about any living being, renovation of museum collections, nature conservation that recognized as a global project, iBOL, as well as resolving global trading problems such as false labeling of species specimens used as food, drug components, entertainment, etc. The main issues of the review are focused on animals and combine four items. (1) A combination of nDNA and mtDNA markers best suits the identification of hybrids and estimation of genetic introgression. (2) The available facts on nDNA and mtDNA diversity seemingly make introgression among many taxa obvious, although it is evident, that introgression may be quite restricted or asymmetric, thus, leaving at least the “source” taxon (taxa) intact. (3) If we consider sexually reproducing species in marine and terrestrial realms introgressed, as it is still evident in many cases, then we should recognize that the BSC, in view of the complete lack of gene flow among species, is inadequate because many zoological species are not biological ones yet. However, vast modern molecular data have proven that sooner or later they definitely become biological species. (4) An investigation into the fish taxa divergence using the BOLD database shows that most gene trees are basically monophyletic and interspecies reticulations are quite rare.

Steven Delong, Alireza Farhadi, Rad Niazadeh et al.

We study the classic online bipartite matching problem with a twist: offline vertices, called resources, are $\textit{reusable}$. In particular, when a resource is matched to an online vertex it is unavailable for a deterministic time duration $d$ after which it becomes available again for a re-match. Thus, a resource can be matched to many different online vertices over a period of time. While recent work on the problem have resolved the asymptotic case where we have large starting inventory (i.e., many copies) of every resource, we consider the (more general) case of $\textit{unit inventory}$ and give the first algorithms that are provably better than the naive greedy approach which has a competitive ratio of (exactly) 0.5. Our first algorithm, which achieves a competitive ratio of $0.589$, generalizes the classic RANKING algorithm for online bipartite matching of non-reusable resources (Karp et al., 1990), by $\textit{reranking}$ resources independently over time. While reranking resources frequently has the same worst case performance as greedy, we show that reranking intermittently on a periodic schedule succeeds in addressing reusability of resources and performs significantly better than greedy in the worst case. Our second algorithm, which achieves a competitive ratio of $0.505$, is a primal-dual randomized algorithm that works by suggesting up to two resources as candidate matches for every online vertex, and then breaking the tie to make the final matching selection in a randomized correlated fashion over time. As a key component of our algorithm, we suitably adapt and extend the powerful technique of online correlated selection (Fahrbach et al., 2020) to reusable resources, in order to induce negative correlation in our tie breaking step and to beat the competitive ratio of $0.5$. Both of our results also extend to the case where offline vertices have weights.

Ehsan Hamzei, Stephan Winter, Martin Tomko

In everyday communication, where-questions are answered by place descriptions. To answer where-questions automatically, computers should be able to generate relevant place descriptions that satisfy inquirers' information needs. Human-generated answers to where-questions constructed based on a few anchor places that characterize the location of inquired places. The challenge for automatically generating such relevant responses stems from selecting relevant anchor places. In this paper, we present templates that allow to characterize the human-generated answers and to imitate their structure. These templates are patterns of generic geographic information derived and encoded from the largest available machine comprehension dataset, MS MARCO v2.1. In our approach, the toponyms in the questions and answers of the dataset are encoded into sequences of generic information. Next, sequence prediction methods are used to model the relation between the generic information in the questions and their answers. Finally, we evaluate the performance of predicting templates for answers to where-questions.

Maud Ehrmann, Matteo Romanello, S. Clematide et al.

F. Ramalho, P. Ekel, W. Pedrycz et al.

Abstract This study is concerned with a multiobjective allocation of resources (or their shortages), delivering an answer to the fundamental question “How to do?” arising in different types of planning activities (strategic, innovation, new business, research and development, expansion, operational, maintenance, etc. planning). The solution to the problem is associated with the extension of the general scheme of multicriteria decision making under uncertainty. This scheme is based on a possibilistic approach and involves a fuzzy set-based generalization of the classic approach to deal with the uncertainty to produce solutions, including robust solutions, in multicriteria analysis. Its usage, in the original form, helps one to use available quantitative information to the highest extent to reduce the decision uncertainty regions. If the quantitative information does not lead to a unique solution, the scheme presumes the application of information of qualitative character (based on knowledge, experience, and intuition of experts) used at the final decision stage. However, increasingly, we encounter problems whose essence requires the consideration of the objectives (investment attractiveness, political effect, maintenance flexibility, etc.) formed on the basis of qualitative information, at all decision process stages. Considering this, the study is aimed at generating multicriteria solutions, including multicriteria robust solutions, by constructing representative combinations of initial data, states of nature or scenarios with direct using qualitative information (with the possibility for experts to apply diverse preference formats processed by transformation functions) presented along with quantitative information, realizing a process of information fusion within the multiobjective models. The corresponding results are of a universal character and applicable to diverse classes of multiobjective problems. The paper also proposes a new approach to the homogeneous and expert-acceptable formulation of specific allocation objectives. Examples are presented to illustrate the study results.

Ali Asghar Salarnezhad, Maryam Shoar

The introduction of cloud computing techniques revolutionized the current of information processing and storing. Cloud computing as a competitive edge provides easy and automated access to the vast ocean of resources through standard network mechanisms to businesses and organizations. Due to the vast diversity of service providers and their respective variety of available services with different qualities, top managements often face difficulty for choosing the best available option. So, considering the growing significance of the mentioned issue, this study aims to identify and rank contributing factors in selection of cloud service providers. In that attempt, this research approaches its goal by going through three major phases. Firstly, in phase one, prior studies are reviewed for extracting related elements of selection. Secondly, by employing Fuzzy Delphi method and obtaining results by interviewing experts in this field such as IT managers and technicians, this study tries to finalize the list of contributing factors. Lastly, by utilizing Fuzzy best-worst multi-criteria decision-making method, which is one of the most recent techniques employed to statistically rank variables, this research introduces a list of vital factors for cloud service selection. Based on the findings of this study, there are five major categories involved in the selection process which are: performance, security, data management, personal data protection and environmental-organizational. The finalized result of ranking shows that, performance related factors such as accessibility, response time and capacity are the first priority. The runner-up is security with reliability and governance. Environmental-organizational variables lands in the third place by considering rental and network costs.

Vahid Bekhradi Nasab, Ehsan Kamali, Khadije Ebrahimi Kahrizsangi

Macro accounting introduces the cost stickiness behavior of all companies as aggregate cost stickiness. This theory states that since the periods of aggregate cost stickiness are more likely to be reserved for resources by companies facing with fall in sales (declining sales), periods of this sequence are associated with low unemployment. Every certain unemployment rate creates a certain increase in wages because wage costs represent General, administrative and sales costs. Based on this, the present study has applied macro accounting information to forecast the unemployment rate. The statistical population of this study includes all companies listed on the TSE. Macro accounting emphasizes economists' view of seasonal accounting. Therefore, data collection every quarter, and observations include 44 times (2008: Q1-2018: Q4). The method of model VAR. Also, to study the forecast's accuracy, the methods of the mean absolute value of error, mean of square error, and criterion of the average percentage of the absolute value of error have been used. Evidence suggests that aggregate cost stickiness forecast changes in the unemployment rate in the future. Reducing the cost stickiness by 1% reduces the unemployment rate by 0/34% in the next quarter. Another result of the research is the accuracy of the regression pattern's forecast in the short term