Miracle-dz/UniFAR-FTUs huggingface dataset:
Image Watermarking Algorithm based on Fast Curvelet Transform

A digital image watermarking algorithm based on fast curvelet transform is proposed.Firstly,the carrier image is decomposed by fast curvelet transform,and then the watermarking image is scrambled by Arnold transform.Secondly,according to the human visual characters and curvelet coefficients the binary watermarking image is embedded into the medium frequency coefficients.Experiment results show that the proposed algorithm has good performance in both invisibility and security,and also of good robustness to the noise,cropping,filtering,JPEG compression and other attacks.
Web Mining — Concepts, Applications, and Research Directions

Web mining is the application of data mining techniques to extract knowledge from web data, including web documents, hyperlinks between documents, usage logs of web sites, etc. A panel organized at ICTAI 1997 (Srivastava and Mobasher 1997) asked the question " Is there anything distinct about web mining (compared to data mining in general)? " While no definitive conclusions were reached then, the tremendous attention on web mining in the past five years, and a number of significant ideas that have been developed, have certainly answered this question in the affirmative in a big way. In addition, a fairly stable community of researchers interested in the area has been formed, largely through the successful series of WebKDD workshops, which have been held annually in conjunction with the
Wireless transceivers in CMOS IC technology. The new wave

Starting from a topic initially confined to academic research the field of RF-CMOS integrated circuits has now progressed to the point that it is on the threshold of important commercial deployment. Progress is on several fronts. New MOS-appropriate circuit techniques have been discovered for many of the RF, IF and baseband blocks required in state-of-the-art wireless transceivers. Transceiver architectures have evolved to take advantage of the strengths of CMOS, and to circumvent its weaknesses. Recent CMOS implementations of RF and IF blocks combine analog circuits with switched and digital functions in unprecedented ways. The object of this paper is to summarize the important concepts underlying good practice in the design of RF-CMOS circuits, and the experience to date in integrating transceivers.
Social Media Surveillance of Multiple Sclerosis Medications Used During Pregnancy and Breastfeeding: Content Analysis

Background Multiple sclerosis (MS) is a chronic neurological disease occurring mostly in women of childbearing age. Pregnant women with MS are usually excluded from clinical trials; as users of the internet, however, they are actively engaged in threads and forums on social media. Social media provides the potential to explore real-world patient experiences and concerns about the use of medicinal products during pregnancy and breastfeeding. Objective This study aimed to analyze the content of posts concerning pregnancy and use of medicines in online forums; thus, the study aimed to gain a thorough understanding of patients’ experiences with MS medication. Methods Using the names of medicinal products as search terms, we collected posts from 21 publicly available pregnancy forums, which were accessed between March 2015 and March 2018. After the identification of relevant posts, we analyzed the content of each post using a content analysis technique and categorized the main topics that users discussed most frequently. Results We identified 6 main topics in 70 social media posts. These topics were as follows: (1) expressing personal experiences with MS medication use during the reproductive period (55/70, 80%), (2) seeking and sharing advice about the use of medicines (52/70, 74%), (3) progression of MS during and after pregnancy (35/70, 50%), (4) discussing concerns about MS medications during the reproductive period (35/70, 50%), (5) querying the possibility of breastfeeding while taking MS medications (30/70, 42%), and (6) commenting on communications with physicians (26/70, 37%). Conclusions Overall, many pregnant women or women considering pregnancy shared profound uncertainties and specific concerns about taking medicines during the reproductive period. There is a significant need to provide advice and guidance to MS patients concerning the use of medicines in pregnancy and postpartum as well as during breastfeeding. Advice must be tailored to the circumstances of each patient and, of course, to the individual medicine. Information must be provided by a trusted source with relevant expertise and made publicly available.
A novel path planning method for biomimetic robot based on deep learning

Purpose This paper aims to design a multi-layer convolutional neural network (CNN) to solve biomimetic robot path planning problem. Design/methodology/approach At first, the convolution kernel with different scales can be obtained by using the sparse auto encoder training algorithm; the parameter of the hidden layer is a series of convolutional kernel, and the authors use these kernels to extract first-layer features. Then, the authors get the second-layer features through the max-pooling operators, which improve the invariance of the features. Finally, the authors use fully connected layers of neural networks to accomplish the path planning task. Findings The NAO biomimetic robot respond quickly and correctly to the dynamic environment. The simulation experiments show that the deep neural network outperforms in dynamic and static environment than the conventional method. Originality/value A new method of deep learning based biomimetic robot path planning is proposed. The authors designed a multi-layer CNN which includes max-pooling layer and convolutional kernel. Then, the first and second layers features can be extracted by these kernels. Finally, the authors use the sparse auto encoder training algorithm to train the CNN so as to accomplish the path planning task of NAO robot.
A Method of Recruiting Default in Data Based on the Decision

Generally speaking, before acquiring useful information from database, the original data which are got by sampling and collecting may not be applied to acquiring knowledge directly. Usually, original data need to be processed and default filled. Based on the profound research of rough set theory, the decision table is default filled by using tolerance relation, which proves efficient.
Analysis of Microcontroller Embedded SRAMs for Applications in Physical Unclonable Functions

The growth of the Internet of Things (IoT) market has motivated widespread proliferation of microcontroller(MCU) based embedded systems. Suitable due to their abundance, low cost, low power consumption and small footprint. The memory architecture typically consists of volatile memory such as block(s) of SRAM, and non-volatile memory (NVM) for code storage. Authentication and encryption safeguard these endpoints within an IoT framework, which requires storage of a secure key. Keys stored within integrated circuits (ICs) are susceptible to attack via reverse engineering of the NVM. Newer approaches use Physical Unclonable Functions (PUFs), which produce unique identi ers that takes advantage of device-level randomness induced by manufacturing process variation in silicon. The unclonable property of PUFs is demonstrated with an analytical model. The unpredictable yet repeatable start-up values (SUVs) of SRAM bit-cells form the basis of an SRAM PUF. Performance measures, such as reliability, randomness, symmetry, and stability, dictate the quality of a PUF. Two commercial o -the-shelf (COTS) ARM-Cortex based MCU products, the STM32F429ZIT6U and ATSAMR21G18A, underwent automated and manual power cycling experiments that examined their embedded SRAM SUVs. The characterization framework provided acquires data via debug software and a developed C program, power cycling using a USB controlled relay and post-processing using Python. Applications of PUFs include cryptographic key generation, device identi cation and true random number hardware generation. Statistical results and a comparative analysis are presented. Amongst the total bitcell count of the embedded SRAM in STM and ATSAM MCUs, 36.86% and 28.86% are classi ed as nonor partially-skewed, respectively across N = 10, 000 samples. The Atmel MCU outperforms the STM MCU in reliability by 1.42 %, randomness by 0.65 % and stability by 8.00 %, with a 4.74 % SUV bias towards a logic '1'. Max errors per 128-bit data item is 22 and 38 bits for MCU #1 and MCU #2, respectively. The STM MCU exhibits column-wise correlation illustrated in a heatmap, where the Atmel MCU shows a random signature. The embedded SRAM in the Atmel MCU outperforms the STM MCU's and is thereby considered the more suitable PUF. iii
Crytography Bases Solution FOR Distributed Denial of Service Attack in Manet

In mobile ad-hoc network nodes communicate with each other or forward data by making route with the help of other nodes. Infrastructure of the network does not fix topology change due to movability of nodes that’s why attacking condition in this network become high. There are lots of attacks for this network. In this paper we study about denial of service attack and its prevention and detection technique, in our propose work we give a novel solution to detect or prevent denial of service attack we implement our work in NS-2.35. Efficiency of our work we proof with the help of results.
Secure multivariate large-scale multi-centric analysis through on-line learning: an imaging genetics case study

State-of-the-art data analysis methods in genetics and related fields have advanced beyond massively univariate analyses. However, these methods suffer from the limited amount of data available at a single research site. Recent large-scale multi-centric imaging-genetic studies, such as ENIGMA, have to rely on meta-analysis of mass univariate models to achieve critical sample sizes for uncovering statistically significant associations. Indeed, model parameters, but not data, can be securely and anonymously shared between partners. We propose here partial least squares (PLS) as a multivariate imaging-genetics model in meta-studies. In particular, we propose an online estimation approach to partial least squares for the sequential estimation of the model parameters in data batches, based on an approximation of the singular value decomposition (SVD) of partitioned covariance matrices. We applied the proposed approach to the challenging problem of modeling the association between 1,167,117 genetic markers (SNPs, single nucleotide polymorphisms) and the brain cortical and sub-cortical atrophy (354,804 anatomical surface features) in a cohort of 639 individuals from the Alzheimer's Disease Neuroimaging Initiative. We compared two different modeling strategies (sequential- and meta-PLS) to the classic non-distributed PLS. Both strategies exhibited only minimal approximation errors of model parameters. The proposed approaches pave the way to the application of multivariate models in large scale imaging-genetics meta-studies, and may lead to novel understandings of the complex brain phenotype-genotype interactions.
Seleção Estatística de Dados para Classificadores Neurais de Sinais de Sonar Passivo

Neste trabalho, discute-se a seleção de dados para o projeto de classificadores em problemas sujeitos a restrições estatı́sticas do banco de dados. Considerando a classificação de espectros de sonar passivo, provenientes de 25 navios pertencentes a 8 classes distintas, é mostrado que a seleção dos conjuntos de projeto e teste, por meio de técnicas de análise de agrupamentos, permite, com um menor custo computacional, obter classificadores de maior eficiência média e melhor desempenho para as classes mais crı́ticas. Utilizando esta técnica, um classificador com uma eficiência média de 94,6% foi obtido, o que é significativo para o problema em questão.
Maximal oxygen uptake and concentric isokinetic muscle strength in pubertal football trained and untrained boys of the same biological age

The purpose of the present study was to examine the effects of long term (prolonged) football training on maximal oxygen uptake ( V® O2) and isokinetic muscle strength in young football players and untrained boys of the same biological age. Twenty football competitive boys (mean age 14 ± 0 yrs; height 165.5 ± 8.5 cm; weight 59.9 ± 9.5 kg; years of training 7 ± 3) and eighteen untrained school boys (mean age 14 ± 0; height 168.22 ± 10.46 cm; weight 59.3 ± 9.9 kg) of the same biological age volunteered to participate in the study. Sexual maturation classified according to Tanner’s stage 3. The football players participated both in their school’s physical education program and in their football team training program while the untrained group participated only in their school’s physical education program (2–3 times per week for 40 min). All subjects were tested for maximal oxygen uptake (V® O2) and respiratory exchange ratio (RER) on the treadmill using an open circuit spirometry. The isokinetic peak torque values of quadriceps (Q) and hamstrings (H) as well as the H : Q strength ratios were recorded. Hcon : Qcon was calculated as the ratio of the peak concentric torque of H to the peak concentric torque of the Q. Results showed that the trained group had significantly lower heart rate in rest (p < 0.001), higher RER (p < 0.001), maximal blood lactate (BLmax) (p < 0.001) and higher (V® O2) max in both relative and absolute values (p < 0.001) compared to the untrained group. At angular velocities of 60 ° s−1 and 180 ° s−1 the relative peak torque of Q and H were significantly higher (Q = p < 0.01; H = p < 0.01). However, the absolute values of Q and H as well as the H : Q ratios at all angular velocities did not differ significantly between the two groups. The results suggest that systematic football training (intensity and duration) has a positive effect in metabolic capacity, cardiorespiratory system and neuromuscular function.
Conditioning LSTM Decoder and Bi-directional Attention Based Question Answering System

Applying neural-networks on Question Answering has gained increasing popularity in recent years. In this paper, I implemented a model with Bi-directional attention flow layer, connected with a Multi-layer LSTM encoder, connected with one start-index decoder and one conditioning end-index decoder. I introduce a new end-index decoder layer, conditioning on start-index output. The Experiment shows this has increased model performance by 15.16%. For prediction, I proposed a new smart-span equation, rewarding both short answer length and high probability in start-index and end-index, which further improved the prediction accuracy. The best single model achieves an F1 score of 73.97% and EM score of 64.95% on test set.
Comparing patient safety culture in Bulgarian, Croatian and American hospitals – preliminary results

Background and aims Patient safety culture (PSC) is an essential component of the quality of healthcare. Improving PSC is considered a priority in many developed countries. A specialized software platform for registration and evaluation of hospital patient safety culture has been developed with the support of the Medical University Plovdiv Project №11/2017. The aim of the study is to assess the status of PSC in Bulgarian hospitals and to compare it to that in USA and Croatian hospitals. Methods The study was conducted from June 01 to July 31, 2018 using the web-based Bulgarian Version of the Hospital Survey on Patient Safety Culture Questionnaire (B-HSOPSC). Two hundred and forty-eight medical professionals from different hospitals in Bulgaria participated in the study. In order to quantify the differences of positive scores distributions for each of the 42 HSOPSC items between Bulgarian, Croatian and USA samples, the χ2-test was applied. The research hypothesis assumed that there were no significant differences between the Bulgarian, Croatian and US PSCs. Results The results revealed 14 significant differences in the positive scores between the Bulgarian and Croatian PSCs and 15 between the Bulgarian and the USA PSC, respectively. Bulgarian medical professionals provided less positive responses to 12 items compared with Croatian and USA respondents. The Bulgarian respondents were more positive compared to Croatians on the feedback and communication of medical errors (Items - C1, C4, C5) as well as on the employment of locum staff (A7) and the frequency of reported mistakes (D1). Bulgarian medical professionals were more positive compared with their USA colleagues on the communication of information at shift handover and across hospital units (F5, F7). The distribution of positive scores on items: “Staff worry that their mistakes are kept in their personnel file” (RA16), “Things ‘fall between the cracks’ when transferring patients from one unit to another” (RF3) and “Shift handovers are problematic for patients in this hospital” (RF11) were significantly higher among Bulgarian respondents compared with Croatian and US respondents. Conclusions Significant differences of positive scores distribution were found between Bulgarian and USA PSC on one hand and between Bulgarian and Croatian on the other. The study reveals that distribution of positive responses could be explained by the cultural, organizational and healthcare system differences.
Determining the Differences between English Language Learners Who Exit Services and English Language Learners Who Become Long-Term ELLs: A Discriminant Analysis

The purpose of this study was to find study differences between ELLs who exit ELLs services and ELLs who do not exit based on regularly collected demographic and standardized achievement data. The variables included: ACCESS scores for reading, writing, speaking, and listening, state CRT scores for reading and math, MAP benchmark scores for reading and math, initial English proficiency, IEP status, number of years in the US education system, and the following risk factors, attendance, suspension, transiency, and retention. The study was based on data related to ELLs in third, fifth, and ninth grade from one urban school district in the west during the 2013-14 school year. There were 1096 third grade cases, 591 fifth grade cases, and 261 ninth grade cases. Six discriminant analyses were calculated to find the variables with the highest predictive power. One discriminant function was produced for each analysis at each grade level. The variables that had the highest predictive power in the third grade discriminant function were the ACCESS scale scores for reading, writing, and listening. The variables that had the highest predictive power in the fifth grade discriminant function were the ACCESS reading and writing scale scores. The variables that had the highest predictive power in the ninth grade discriminant function were the ACCESS comprehension composite score and the writing scale score. In addition the graduation rates for seniors during the 2013-2014 school year who had been ELL at one time was different depending on when they exited ELL. Students who exited in third grade had an 82% graduation rate. Students who exited in fifth grade had a 72% pass rate, and students who exited in ninth grade had a 59% pass rate.
Service Function Chaining: Framework & Architecture

IP networks rely more and more on the combination of advanced functions (besides the basic routing and forwarding functions) for the delivery of added value services. This document defines a reference architecture and a framework to enforce Service Function Chaining (SFC) with minimum requirements on the physical topology of the network.
Accessibility Evaluation of Computer Based Tests

Computer-based tests (CBTs) play an important role in the professional career of any person. Universities use CBTs for admissions. Further, many large courses use CBTs for evaluation and grading. Almost all software companies use CBTs to offer jobs. However, many of these CBTs do not take attention to the accessibility barriers for persons with disabilities, specifically visually impaired persons. In this paper, we present a study of accessibility barriers in various CBTs as faced by visually impaired persons in India. These barriers have been identified by a questionnaire survey approach. Our analysis of the responses shows that most CBTs do not meet the expectations of visually impaired persons. We conclude the paper with some recommendations to improve accessibility.
Research on product change range extraction of satellite based on model-driven

Determination of product change range is the basis of the change analysis and management. Taking the aerospace satellite as example, a method of product change range extraction of satellite based on model-driven is proposed. The product change conflict model is constructed, and the product change can be described in standardization and formalization. Several types of product change conflicts are analyzed and the reasons causing change conflicts are discussed. An algorithm of product change range extraction is proposed, and the product change range can be determined in different stages in lifecycle, which is the basis of the subsequent modification scheme generation and evaluation. Taking some a satellite as example, the feasibility and effectiveness of this method is verified.
Wakefield excited by ultrashort laser pulses in near-critical density plasmas

Laser wakefield acceleration (LWFA) using high repetition rate mJ-class laser systems brings unique opportunities for a broad range of applications. In order to meet the conditions required for the electron acceleration with lasers operating at lower energies, one has to use high density plasmas and ultrashort pulses. In the case of a few-cycle pulse, the dispersion and the carrier envelope phase effects can no longer be neglected. In this work, the properties of the wake waves generated by ultrashort pulse lasers in near-critical density plasmas are investigated. The results obtained may lead to enhancement of the quality of LWFA electron beams using kHz laser systems.