Long-term Conversation Analysis: Exploring Utility and Privacy

The analysis of conversations recorded in everyday life requires privacy protection. In this contribution, we explore a privacy-preserving feature extraction method based on input feature dimension reduction, spectral smoothing and the low-cost speaker anonymization technique based on McAdams coefficient. We assess the utility of the feature extraction methods with a voice activity detection and a speaker diarization system, while privacy protection is determined with a speech recognition and a speaker verification model. We show that the combination of McAdams coefficient and spectral smoothing maintains the utility while improving privacy.Comment: Submitted to ITG Conference on Speech Communication, 202

FuLeeca: A Lee-based Signature Scheme

In this work we introduce a new code-based signature scheme, called \textsf{FuLeeca}, based on the NP-hard problem of finding codewords of given Lee-weight. The scheme follows the Hash-and-Sign approach applied to quasi-cyclic codes. Similar approaches in the Hamming metric have suffered statistical attacks, which revealed the small support of the secret basis. Using the Lee metric, we are able to thwart such attacks. We use existing hardness results on the underlying problem and study adapted statistical attacks. We propose parameters for \textsf{FuLeeca}~and compare them to an extensive list of proposed post-quantum secure signature schemes including the ones already standardized by NIST. This comparison reveals that \textsf{FuLeeca}~is competitive. For example, for NIST category I, i.e., 160 bit of classical security, we obtain an average signature size of 1100 bytes and public key sizes of 1318 bytes. Comparing the total communication cost, i.e., the sum of the signature and public key size, we see that \textsf{FuLeeca} is only outperformed by Falcon while the other standardized schemes Dilithium and SPHINCS+ show larger communication costs than \textsf{FuLeeca}

Large‐scale hydraulic conductivities inferred from three‐dimensional groundwater flow and 4 He transport modeling in the Carrizo aquifer, Texas

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94983/1/jgrb14187.pd

Antiinflammatory Therapy with Canakinumab for Atherosclerotic Disease

Background: Experimental and clinical data suggest that reducing inflammation without affecting lipid levels may reduce the risk of cardiovascular disease. Yet, the inflammatory hypothesis of atherothrombosis has remained unproved. Methods: We conducted a randomized, double-blind trial of canakinumab, a therapeutic monoclonal antibody targeting interleukin-1β, involving 10,061 patients with previous myocardial infarction and a high-sensitivity C-reactive protein level of 2 mg or more per liter. The trial compared three doses of canakinumab (50 mg, 150 mg, and 300 mg, administered subcutaneously every 3 months) with placebo. The primary efficacy end point was nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death. RESULTS: At 48 months, the median reduction from baseline in the high-sensitivity C-reactive protein level was 26 percentage points greater in the group that received the 50-mg dose of canakinumab, 37 percentage points greater in the 150-mg group, and 41 percentage points greater in the 300-mg group than in the placebo group. Canakinumab did not reduce lipid levels from baseline. At a median follow-up of 3.7 years, the incidence rate for the primary end point was 4.50 events per 100 person-years in the placebo group, 4.11 events per 100 person-years in the 50-mg group, 3.86 events per 100 person-years in the 150-mg group, and 3.90 events per 100 person-years in the 300-mg group. The hazard ratios as compared with placebo were as follows: in the 50-mg group, 0.93 (95% confidence interval [CI], 0.80 to 1.07; P = 0.30); in the 150-mg group, 0.85 (95% CI, 0.74 to 0.98; P = 0.021); and in the 300-mg group, 0.86 (95% CI, 0.75 to 0.99; P = 0.031). The 150-mg dose, but not the other doses, met the prespecified multiplicity-adjusted threshold for statistical significance for the primary end point and the secondary end point that additionally included hospitalization for unstable angina that led to urgent revascularization (hazard ratio vs. placebo, 0.83; 95% CI, 0.73 to 0.95; P = 0.005). Canakinumab was associated with a higher incidence of fatal infection than was placebo. There was no significant difference in all-cause mortality (hazard ratio for all canakinumab doses vs. placebo, 0.94; 95% CI, 0.83 to 1.06; P = 0.31). Conclusions: Antiinflammatory therapy targeting the interleukin-1β innate immunity pathway with canakinumab at a dose of 150 mg every 3 months led to a significantly lower rate of recurrent cardiovascular events than placebo, independent of lipid-level lowering. (Funded by Novartis; CANTOS ClinicalTrials.gov number, NCT01327846.

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Learning EMG control of a robotic hand: Towards Active Prostheses

Abstract- We introduce a method based on support vector machines which can detect opening and closing actoins of the human thumb, index finder, and other fingers recorded via surface EMG only. The method is shown to be robust across sessoins and can be used independently of the position of the arm. With these stability criteria, the method is ideally suited for the control of active prosthesis with a high nummber of active degrees of freedom. The method os successfully demonstrated on a robotic four-finger hand, and can be used to grasp objects

Two-Stage Voice Anonymization for Enhanced Privacy

In recent years, the need for privacy preservation when manipulating or storing personal data, including speech , has become a major issue. In this paper, we present a system addressing the speaker-level anonymization problem. We propose and evaluate a two-stage anonymization pipeline exploiting a state-of-the-art anonymization model described in the Voice Privacy Challenge 2022 in combination with a zero-shot voice conversion architecture able to capture speaker characteristics from a few seconds of speech. We show this architecture can lead to strong privacy preservation while preserving pitch information. Finally, we propose a new compressed metric to evaluate anonymization systems in privacy scenarios with different constraints on privacy and utility.Comment: submitted to INTERSPEEC

Advanced Computer-Based Education on the World Wide Web

this paper is to show that CBE is not a new topic that appeared with the WWW, but that the WWW offers a new set of software tools that can extend the usefulness of existing CBE tools. Starting with the popular acceptance of the WWW there has been a flood of "educational" material appearing on the WWW. There have also been people proclaiming the WWW as a remarkable educational resource. But how one defines "educational" can be a tricky and touchy subject. Some of the material is educational in the way some magazines are educational. That is, this material contains information of use in an easy to digest form. Some of the material is educational in the manner that a reference book is educational where one can learn about specific topics by looking up the subject and reading about it. Some of the material is educational in the same way that a written tutorial is educational. If one starts at the beginning and works out the given example problems, then one should learn the subject. These divisions of levels continue up to the level of being CBE in the classical sense. CBE, "in the classical sense," can be thought of as attempting to include one-to-one interaction between the student and the computer in much the same way the student would interact with an individual instructor. This interaction would take the form of queries and responses flowing in both directions. The student can ask for help, look up definitions, etc., by "asking" the computer. In turn, the computer can try to find the student's level of understanding by asking questions and proposing problems to the student. At the highest level the computer tracks all of the student's actions in order to try to extract the student's weaknesses and provide appropriate help. While the computer cannot replace the human ins..

A Comparative Analysis of Web-Based Testing and

this paper, we describe testing and evaluation features that Web-based courseware should offer and survey some of the existing system

Healthcare costs of failed rotator cuff repairs

Background: The goal of this study was to estimate the short-term (∼2 years) healthcare costs of failed primary arthroscopic rotator cuff repair (RCR) in the United States. Methods: A review of current literature was performed to estimate the number of RCR performed in the United States in the year 2022 and the rate of progression of these patients to lose repair continuity, reach clinical failure, and progress to nonoperative intervention and revision procedures. A review of the current literature was performed to estimate the costs incurred by these failures over the ensuing 2-year postoperative time period. Results: The direct and indirect healthcare costs of structural and clinical failure of primary RCR performed in 2022 are estimated to reach $438,892,670 in the short-term postoperative period. The majority of the costs come from the estimated$229,390,898 in nonoperative management that these patients undergo after they reach clinical failure. Conclusion: The short-term healthcare costs of failed arthroscopic RCR performed in the United States in 2022 are predicted to be $438,892,670. Although RCR improves quality of life, pain, function, and is cost-effective, there remains great potential for reducing the economic burden of failed RCR repairs on the US society. Investments into research aimed to improve RCR healing rates are warranted. Clinical Relevance: Although RCR improves quality of life, pain, function, and is cost-effective, this study provides evidence that there remains great potential for reducing the economic burden of failed RCR repairs on the US society. Investments into research aimed to improve RCR healing rates are warranted