Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving Fault Tolerance in High-Precision Clock Synchronization

The very popular Precision Time Protocol (PTP or IEEE 1588) is widely used to synchronize distributed systems with high precision. The underlying principle is a master/slave concept based on the regular exchange of synchronization messages. This paper investigates an approach to enhance PTP with fault tolerance and to overcome the transient deterioration of synchronization accuracy during a recovery from a master failure. To this end, a concept is proposed where a group of masters negotiates a fault-tolerant agreement on the system-wide time and transparently synchronizes the associated IEEE 1588 slaves. Experimental verification on the basis of an Ethernet implementation shows that the approach is feasible and indeed improves the overall synchronization accuracy in terms of fault tolerance.
Understanding consumer perception of technological product failures: an attributional approach

Besides the widely promoted advantages the influx of new technology is bringing to consumers, the disadvantages due to increasing cognitive complexity of such technological advanced products have also been recognized. Among other things, an increasing number of unknown field complaints is one of the evidences. Since consumers often perceive a product's (mal)functioning differently than designers do, we propose an attributional approach to evaluate potential product failures. In this paper, we present the results of an exploratory empirical study to evaluate the attribution of picture quality failures in LCD televisions for a diverse group of consumers. This approach is aimed to provide designers better insight into how consumers perceive (potential) product failures, in order to support critical design decisions in the product development process.
A new algorithm for difference image analysis

In the context of difference image analysis (DIA), we present a new method for determining the convolution kernel matching a pair of images of the same field. Unlike the standard DIA technique which involves modelling the kernel as a linear combination of basis functions, we consider the kernel as a discrete pixel array and solve for the kernel pixel values directly using linear least squares. The removal of basis functions from the kernel model is advantageous for a number of compelling reasons. First, it removes the need for the user to specify such functions, which makes for a much simpler user application and avoids the risk of an inappropriate choice. Secondly, basis functions are constructed around the origin of the kernel coordinate system, which requires that the two images are perfectly aligned for an optimal result. The pixel kernel model is sufficiently flexible to correct for image misalignments, and in the case of a simple translation between images, image resampling becomes unnecessary. Our new algorithm can be extended to spatially varying kernels by solving for individual pixel kernels in a grid of image subregions and interpolating the solutions to obtain the kernel at any one pixel.
RtrASSoc - adaptable superscalar reconfigurable programmable system on chip - the embedded operating system - EOS

This paper describes the development of the (embedded operating system), part of RtrASSoc - an adaptable, superscalar, reconfigurable system in a programmable chip (PSOC), to be implemented in a FPGA Virtex from Xilinx. RtrASSoc will be used in embedded applications that need larger capacity, better acting, and dynamic reconfiguration, at a low cost, where the application is who defines the whole structure of the platform RtrASSoc. The resource of dynamic reconfiguration to be used will be the model run-time reconfiguration-Rtr, present in FPGAs Virtex from Xilinx. The function of the embedded operating system will be to manager the units: PSE (embedded superscalar processor), and RR (reconfigurable routines), all belonging to RtrASSoc. RtrASSoc will be used in the recognition of patterns and it will be developed in language VHDL.
SQSTM1/p62 mediates crosstalk between autophagy and the UPS in DNA repair

ABSTRACT SQSTM1/p62 (sequestosome 1) selectively targets polyubiquitinated proteins for degradation via macroautophagy and the proteasome. Additionally, SQSTM1 shuttles between the cytoplasmic and nuclear compartments, although its role in the nucleus is relatively unknown. Here, we report that SQSTM1 dynamically associates with DNA damage foci (DDF) and regulates DNA repair. Upon induction of DNA damage SQSTM1 interacts with FLNA (filamin A), which has previously been shown to recruit DNA repair protein RAD51 (RAD51 recombinase) to double-strand breaks and facilitate homologous recombination (HR). SQSTM1 promotes proteasomal degradation of FLNA and RAD51 within the nucleus, resulting in reduced levels of nuclear RAD51 and slower DNA repair. SQSTM1 regulates the ratio between HR and nonhomologous end joining (NHEJ) by promoting the latter at the expense of the former. This SQSTM1-dependent mechanism mediates the effect of macroautophagy on DNA repair. Moreover, nuclear localization of SQSTM1 and its association with DDF increase with aging and are prevented by life-span-extending dietary restriction, suggesting that an imbalance in the mechanism identified here may contribute to aging and age-related diseases.
Scaling Java-based Dynamic Web Services : Second-Year Project

Managing distributed state is a di cult challenge for building scalable, distributed, wide-area applications. This project presents the design of an infrastructure, called Ivory, to simplify construction of distributed applications by automatically caching and replicating data structures and code. We illustrate the use of our infrastructure in service caches that replicate Web service code and data used to generate dynamic content. The service cache relies on Ivory to maintain consistency of cached data as a basis for scalable dynamic Web services. Ivory is designed to automate key aspects of state management in a exible, e cient, and scalable way. A key element to our approach is the use of bytecode transformers that automatically adapt Java applications to the Ivory infrastructure. Bytecode transformers insert new code into compiled applications to notify Ivory of data structure modi cations and to invoke operations for maintaining consistency; the transformation is powerful but requires only minimal application programmer involvement. Furthermore, to reduce the space and communication overhead necessary for maintaining data, we use conits|groups of application-de ned related objects|as the granularity for caching, consistency, and synchronization. Using bytecode transformers and the conit granularity in the infrastructure design allows authors to choose application-appropriate data management and consistency policies.
Logo recognition system

The objective of this research is to develop computer software for recognizing a company logo. The system is called "Logo Recognition System or LRS". There are 2 parts of the LRS, namely: a client part and server part. The client part consists of common device, which is owned by the user, such as a mobile device, tablet and smart phone. On the client part, the LRS provides an easy graphic user interface for capturing a logo image. After that the device sends the logo image to the server part. The server part is a computer server, which does a process of recognizing with several algorithms and generates a result with a link of the logo's company website. The LRS consists of 4 components, namely: 1) Image Acquisition 2) Image Preprocessing 3) Image Recognition, and 4) Result Presentation. The system uses the python program to develop the logo recognition system on both client and server. The LRS can recognize the rotation image with any angle. The precision rate of the system is around 79.6 percent.
The influence of sex, handedness, and washing on the diversity of hand surface bacteria

Bacteria thrive on and within the human body. One of the largest human-associated microbial habitats is the skin surface, which harbors large numbers of bacteria that can have important effects on health. We examined the palmar surfaces of the dominant and nondominant hands of 51 healthy young adult volunteers to characterize bacterial diversity on hands and to assess its variability within and between individuals. We used a novel pyrosequencing-based method that allowed us to survey hand surface bacterial communities at an unprecedented level of detail. The diversity of skin-associated bacterial communities was surprisingly high; a typical hand surface harbored >150 unique species-level bacterial phylotypes, and we identified a total of 4,742 unique phylotypes across all of the hands examined. Although there was a core set of bacterial taxa commonly found on the palm surface, we observed pronounced intra- and interpersonal variation in bacterial community composition: hands from the same individual shared only 17% of their phylotypes, with different individuals sharing only 13%. Women had significantly higher diversity than men, and community composition was significantly affected by handedness, time since last hand washing, and an individual's sex. The variation within and between individuals in microbial ecology illustrated by this study emphasizes the challenges inherent in defining what constitutes a “healthy” bacterial community; addressing these challenges will be critical for the International Human Microbiome Project.
Linear and nonlinear speech feature analysis for stress classification

There are many stressful environments which deteriorate the performance of speech recognition systems. Examples include aircraft cockpits, 911 emergency telephone response, high workload task stress, or emotional situations. To address this, we investigate a number of linear and nonlinear features and processing methods for stressed speech classi cation. The linear features include properties of pitch, duration, intensity, glottal source, and the vocal tract spectrum. Nonlinear processing is based on our newly proposed Teager Energy Operator (TEO) speech feature which incorporates frequency domain critical band lters and properties of the resulting TEO autocorrelation envelope. In this study, we employ a Bayesian hypothesis testing approach and a hidden Markov model (HMM) processor as classi cation methods. Evaluations focused on speech under loud, angry, and the Lombard e ect1 from the SUSAS database. Results using receiver operating characteristic (ROC) curves and EER (equal error rate) based detection show that pitch is the best of the ve linear features for stress classi cation; while the new nonlinear TEO-based feature outperforms the best linear feature by +5.2%, with a reduction in classi cation rate variability from 8.66 to 3.90.
Translation Of Telugu-Marathi and Vice-Versa using Rule Based Machine Translation

In todays digital world automated Machine Translation of one language to another has covered a long way to achieve different kinds of success stories. Whereas Babel Fish supports a good number of foreign languages and only Hindi from Indian languages, the Google Translator takes care of about 10 Indian languages. Though most of the Automated Machine Translation Systems are doing well but handling Indian languages needs a major care while handling the local proverbs/ idioms. Most of the Machine Translation system follows the direct translation approach while translating one Indian language to other. Our research at KMIT R&D Lab found that handling the local proverbs/idioms is not given enough attention by the earlier research work. This paper focuses on two of the majorly spoken Indian languages Marathi and Telugu, and translation between them. Handling proverbs and idioms of both the languages have been given a special care, and the research outcome shows a significant achievement in this direction.
Continuous User Authentication on Mobile Devices: Recent progress and remaining challenges

Recent developments in sensing and communication technologies have led to an explosion in the use of mobile devices such as smart phones and tablets. With the increase in the use of mobile devices, users must constantly worry about security and privacy, as the loss of a mobile device could compromise personal information. To deal with this problem, continuous authentication systems (also known as active authentication systems) have been proposed, in which users are continuously monitored after initial access to the mobile device. In this article, we provide an overview of different continuous authentication methods on mobile devices. We discuss the merits and drawbacks of the available approaches and identify promising avenues of research in this rapidly evolving field.
Efficacy and safety of olanzapine/fluoxetine combination in the treatment of treatment-resistant depression: a meta-analysis of randomized controlled trials

Background Whether olanzapine/fluoxetine combination (OFC) is superior to olanzapine or fluoxetine monotherapy in patients with treatment-resistant depression (TRD) remains controversial. Thus, we conducted this meta-analysis of randomized controlled trials (RCTs) to compare the efficacy and safety of OFC with olanzapine or fluoxetine monotherapy for patients with TRD. Materials and methods RCTs published in PubMed, Embase, Web of Science, and the ClinicalTrials.gov registry were systematically reviewed to assess the efficacy and safety of OFC. Outcomes included mean changes from baseline in Montgomery–Asberg Depression Rating Scale (MADRS), Clinical Global Impression-Severity (CGI-S), Hamilton Rating Scale for Anxiety (HAM-A), Brief Psychiatric Rating Scale (BPRS) scores, response rate, remission rate, and adverse events. Results were expressed with weighted mean difference (WMD) with 95% confidence intervals (CIs) and risk ratio (RR) with 95% CIs. Results A total of five RCTs with 3,020 patients met the inclusion criteria and were included in this meta-analysis. Compared with olanzapine or fluoxetine monotherapy, OFC was associated with greater changes from baseline in MADRS (WMD =−3.37, 95% CI: −4.76, −1.99; P<0.001), HAM-A (WMD =−1.82, 95% CI: −2.25, −1.40; P<0.001), CGI-S (WMD =−0.37, 95% CI: −0.45, −0.28; P<0.001), and BPRS scores (WMD =−1.46, 95% CI: −2.16, −0.76; P<0.001). Moreover, OFC had significantly higher response rate (RR =1.35, 95% CI: 1.12, 1.63; P=0.001) and remission rate (RR =1.71, 95% CI: 1.31, 2.23; P<0.001). The incidence of treatment-related adverse events was similar between the OFC and monotherapy groups (RR =1.01, 95% CI: 0.94, 1.08; P=0.834). Conclusion OFC is more effective than olanzapine or fluoxetine monotherapy in the treatment of patients with TRD. Our results provided supporting evidence for the use of OFC in TRD. However, considering the limitations in this study, more large-scale, well-designed RCTs are needed to confirm these findings.
Pilot Embedded Channel Estimation for OFDM Systems

In this paper, we investigated both first-order statistics (FOS) and second-order statistics (SOS)-based channel estimators for PE-OFDM system, and proposed a novel channel estimator, which joint the FOS and SOS to estimate channel state information. Numerical simulation illustrate that the FOS-based approach outperforms the SOS-based approach, and the proposed joint estimator has better MSE and BER performance compared with the previous schemes which only use the first-order statistics or the second-order statistics.
Alleviation of Heat Strain by Cooling Different Body Areas during Red Pepper Harvest Work at WBGT 33 ̊C

The purpose of the present study was to examine the effects of different types of personal cooling equipments (PCE) on the alleviation of heat strain during red pepper harvest simulated in a climatic chamber. The experiment consisted of eight conditions: 1) Control, 2) Neck cooling scarf A with a cooling area of 68 cm2, 3) Neck cooling scarf B (cooling area 154 cm2), 4) Brimmed hat with a frozen gel pack, 5) Cooling vest (cooling area 606 cm2), 6) Hat+Neck Scarf B, 7) Hat+Vest, and 8) Hat+Neck Scarf B+Vest. Twelve subjects worked a red pepper harvest simulated in a climatic chamber of WBGT 33 ̊C. The result showed that rectal temperature (Tre) was effectively maintained under 38 ̊C by wearing PCE. Mean skin temperature (T̄sk) and heart rate (HR) became more stable through wearing PCE. When wearing the ‘Hat+Scarf B+Vest’, particularly, T̄sk and HR quickly decreased to the comfort level during the mid-rest stage. We confirmed that the vest with a cooling area of only 3.3% body surface area (BSA) was effective in alleviating heat strain in a simulated harvest work. Furthermore, the heat strain of farm workers can be considerably eliminated by the combination of the cooling vest, a scarf, and a brimmed hat, with the total cooling area of 4.2% BSA.
Careful treatment planning enables safe ablation of liver tumors adjacent to major blood vessels by percutaneous irreversible electroporation (IRE)

Abstract Background. Irreversible electroporation (IRE) is a tissue ablation method, which relies on the phenomenon of electroporation. When cells are exposed to a sufficiently electric field, the plasma membrane is disrupted and cells undergo an apoptotic or necrotic cell death. Although heating effects are known IRE is considered as non-thermal ablation technique and is currently applied to treat tumors in locations where thermal ablation techniques are contraindicated. Materials and methods. The manufacturer of the only commercially available pulse generator for IRE recommends a voltage-to-distance ratio of 1500 to 1700 V/cm for treating tumors in the liver. However, major blood vessels can influence the electric field distribution. We present a method for treatment planning of IRE which takes the influence of blood vessels on the electric field into account; this is illustrated on a treatment of 48-year-old patient with a metastasis near the remaining hepatic vein after a right side hemi-hepatectomy. Results. Output of the numerical treatment planning method shows that a 19.9 cm3 irreversible electroporation lesion was generated and the whole tumor was covered with at least 900 V/cm. This compares well with the volume of the hypodense lesion seen in contrast enhanced CT images taken after the IRE treatment. A significant temperature raise occurs near the electrodes. However, the hepatic vein remains open after the treatment without evidence of tumor recurrence after 6 months. Conclusions. Treatment planning using accurate computer models was recognized as important for electrochemotherapy and irreversible electroporation. An important finding of this study was, that the surface of the electrodes heat up significantly. Therefore the clinical user should generally avoid placing the electrodes less than 4 mm away from risk structures when following recommendations of the manufacturer.
Building and Maintaining Halls of Fame over a Database

Halls of Fame are fascinating constructs. They represent the elite of an often very large amount of entities---persons, companies, products, countries etc. Beyond their practical use as static rankings, changes to them are particularly interesting---for decision making processes, as input to common media or novel narrative science applications, or simply consumed by users. In this work, we aim at detecting events that can be characterized by changes to a Hall of Fame ranking in an automated way. We describe how the schema and data of a database can be used to generate Halls of Fame. In this database scenario, by Hall of Fame we refer to distinguished tuples; entities, whose characteristics set them apart from the majority. We define every Hall of Fame as one specific instance of an SQL query, such that a change in its result is considered a noteworthy event. Identified changes (i.e., events) are ranked using lexicographic tradeoffs over event and query properties and presented to users or fed in higher-level applications. We have implemented a full-fledged prototype system that uses either database triggers or a Java based middleware for event identification. We report on an experimental evaluation using a real-world dataset of basketball statistics.
Music Genre Classification and Variance Comparison on Number of Genres

1 Abstract In this project we apply machine learning techniques to build a music genre classifier. Focusing on the sonic properties of music, as opposed to metadata, we examine the classification accuracy of two types of features coefficients, Mel-Frequency Cepstral Coefficients and Chroma Features, using multi-class support vector machines. We hope to achieve significant improvements over random guessing and identify which coefficient yields higher accuracy. Additionally, we will classify songs into different numbers of genres, to analyze how the number of classes affects accuracy for each model.
Blind Separation of Acoustic Signals Combining SIMO-Model-Based Independent Component Analysis and Binary Masking

A new two-stage blind source separation (BSS) method for convolutive mixtures of speech is proposed, in which a single-input multiple-output (SIMO)-model-based independent component analysis (ICA) and a new SIMO-model-based binary masking are combined. SIMO-model-based ICA enables us to separate the mixed signals, not into monaural source signals but into SIMO-model-based signals from independent sources in their original form at the microphones. Thus, the separated signals of SIMO-model-based ICA can maintain the spatial qualities of each sound source. Owing to this attractive property, our novel SIMO-model-based binary masking can be applied to efficiently remove the residual interference components after SIMO-model-based ICA. The experimental results reveal that the separation performance can be considerably improved by the proposed method compared with that achieved by conventional BSS methods. In addition, the real-time implementation of the proposed BSS is illustrated.
Performance of a Natural Language Processing (NLP) Tool to Extract Pulmonary Function Test (PFT) Reports from Structured and Semistructured Veteran Affairs (VA) Data

Introduction/Objective: Pulmonary function tests (PFTs) are objective estimates of lung function, but are not reliably stored within the Veteran Health Affairs data systems as structured data. The aim of this study was to validate the natural language processing (NLP) tool we developed—which extracts spirometric values and responses to bronchodilator administration—against expert review, and to estimate the number of additional spirometric tests identified beyond the structured data. Methods: All patients at seven Veteran Affairs Medical Centers with a diagnostic code for asthma Jan 1, 2006–Dec 31, 2012 were included. Evidence of spirometry with a bronchodilator challenge (BDC) was extracted from structured data as well as clinical documents. NLP’s performance was compared against a human reference standard using a random sample of 1,001 documents. Results: In the validation set NLP demonstrated a precision of 98.9 percent (95 percent confidence intervals (CI): 93.9 percent, 99.7 percent), recall of 97.8 percent (95 percent CI: 92.2 percent, 99.7 percent), and an F-measure of 98.3 percent for the forced vital capacity pre- and post pairs and precision of 100 percent (95 percent CI: 96.6 percent, 100 percent), recall of 100 percent (95 percent CI: 96.6 percent, 100 percent), and an F-measure of 100 percent for the forced expiratory volume in one second pre- and post pairs for bronchodilator administration. Application of the NLP increased the proportion identified with complete bronchodilator challenge by 25 percent. Discussion/Conclusion: This technology can improve identification of PFTs for epidemiologic research. Caution must be taken in assuming that a single domain of clinical data can completely capture the scope of a disease, treatment, or clinical test.