Indexing Metric Spaces for Exact Similarity Search

With the continued digitalization of societal processes, we are seeing an explosion in available data. This is referred to as big data. In a research setting, three aspects of the data are often viewed as the main sources of challenges when attempting to enable value creation from big data: volume, velocity and variety. Many studies address volume or velocity, while much fewer studies concern the variety. Metric space is ideal for addressing variety because it can accommodate any type of data as long as its associated distance notion satisfies the triangle inequality. To accelerate search in metric space, a collection of indexing techniques for metric data have been proposed. However, existing surveys each offers only a narrow coverage, and no comprehensive empirical study of those techniques exists. We offer a survey of all the existing metric indexes that can support exact similarity search, by i) summarizing all the existing partitioning, pruning and validation techniques used for metric indexes, ii) providing the time and storage complexity analysis on the index construction, and iii) report on a comprehensive empirical comparison of their similarity query processing performance. Here, empirical comparisons are used to evaluate the index performance during search as it is hard to see the complexity analysis differences on the similarity query processing and the query performance depends on the pruning and validation abilities related to the data distribution. This article aims at revealing different strengths and weaknesses of different indexing techniques in order to offer guidance on selecting an appropriate indexing technique for a given setting, and directing the future research for metric indexes

A Closer Look at the Security Risks in the Rust Ecosystem

Rust is an emerging programming language designed for the development of systems software. To facilitate the reuse of Rust code, crates.io, as a central package registry of the Rust ecosystem, hosts thousands of third-party Rust packages. The openness of crates.io enables the growth of the Rust ecosystem but comes with security risks by severe security advisories. Although Rust guarantees a software program to be safe via programming language features and strict compile-time checking, the unsafe keyword in Rust allows developers to bypass compiler safety checks for certain regions of code. Prior studies empirically investigate the memory safety and concurrency bugs in the Rust ecosystem, as well as the usage of unsafe keywords in practice. Nonetheless, the literature lacks a systematic investigation of the security risks in the Rust ecosystem. In this paper, we perform a comprehensive investigation into the security risks present in the Rust ecosystem, asking ``what are the characteristics of the vulnerabilities, what are the characteristics of the vulnerable packages, and how are the vulnerabilities fixed in practice?''. To facilitate the study, we first compile a dataset of 433 vulnerabilities, 300 vulnerable code repositories, and 218 vulnerability fix commits in the Rust ecosystem, spanning over 7 years. With the dataset, we characterize the types, life spans, and evolution of the disclosed vulnerabilities. We then characterize the popularity, categorization, and vulnerability density of the vulnerable Rust packages, as well as their versions and code regions affected by the disclosed vulnerabilities. Finally, we characterize the complexity of vulnerability fixes and localities of corresponding code changes, and inspect how practitioners fix vulnerabilities in Rust packages with various localities.Comment: preprint of accepted TOSEM pape

The relationship between Comprehensive Geriatric Assessment parameters and depression in elderly patients

BackgroundDepression is common and serious among elderly patients. The treatment of elderly depression is often delayed owing to insufficient diagnosis, which eventually leads to adverse consequences.AimsTo explore the association between the parameters of the Comprehensive Geriatric Assessment and depression in elderly patients.MethodsA cross-sectional study of 211 outpatients and inpatients aged ≥ 65 years from the Comprehensive Geriatric Assessment database was conducted. A Comprehensive Geriatric Assessment inventory was prepared by compiling and screening general characteristics, chronic diseases (cardiovascular disease, diabetes, and peptic ulcer disease), nutritional status, daily living ability, anthropometric measurements (body mass index (BMI), upper arm circumference, and calf circumference), and blood biochemical indicators (hemoglobin, albumin, prealbumin, triglycerides, and low-density lipoprotein cholesterol). The Geriatric Depression Scale was also conducted for each elderly patient to screen for depression. A multivariable logistic regression analysis was used to determine the association between the parameters of the Comprehensive Geriatric Assessment and geriatric depression.ResultsThere were 63 patients in the depression group with a median age of 84.00 years, and 148 patients in the non-depression group with a median age of 78.50 years. After controlling for confounders, the risk of depression in elderly patients with cardiovascular diseases was 6.011 times higher than that in those without cardiovascular diseases (p < 0.001); and the risk of depression in elderly patients with peptic ulcer diseases was 4.352 times higher than that in those without peptic ulcer diseases (p < 0.001); the risk of depression in elderly patients decreased by 22.6% for each 1-point increase in the Mini Nutritional Assessment (p < 0.001). The risk of depression in elderly patients decreased by 19.9% for each 1-point increase in calf circumference (p = 0.002), and by 13.0% for each 1-point increase in albumin (p = 0.014).ConclusionOur findings suggest that Comprehensive Geriatric Assessment parameters, such as cardiovascular disease, peptic ulcer disease, Mini Nutritional Assessment score, calf circumference, and albumin, were associated with depression. The Comprehensive Geriatric Assessment can assist in the early identification of depression in the elderly population