Miracle-dz/UniFAR-FTUs huggingface dataset:
Interference Reduction by Using RPCA and Variational Mode Decomposition in 3D Pulse Images

Pulse diagnosis can non-invasively measure holistic health and has been developed for two thousand years. Single-point pulse waves (SPPWs) were typically applied to quantification analysis pulse diagnosis. However, SPPWs lack the expression of spatial information, such as the length of wrist pulse and the width of wrist pulse, which is an important diagnostic indicator in pulse diagnosis. The three-dimensional pulse images (3DPI), proposed by Luo, can be applied to extract temporal and spatial properties of arterial pulsation. Moreover, base-plane wander and static pressure have become new problems in the research on pulse signal. The present study proposes a novel method to preprocess the 3DPI by using robust principal component analysis (RPCA) and variational mode decomposition (VMD). The experimental results demonstrate that our method can remove interference effectively and have the best capability to tackle the interference problems.
Efficient Tracking of Breaking News in Twitter

We present an efficient graph-based method for filtering tweets relevant to a given breaking news from large tweet streams. Unlike existing models that either require manual effort, strong supervision, and/or not scalable, our method can automatically and effectively filter incoming relevant tweets starting from just a small number of past relevant tweets. Extensive experiments on both synthetic and real datasets show that our proposed method significantly outperforms other methods in filtering the relevant tweets while being as fast as the most efficient state-of-the-art method.
How to Account for Contemporaneous and Time Dependence in Business Research?

In the analysis of balanced panel data sets used in Business Research, the commonly used methods are either OLS with adjusted standard errors such as cluster standard errors or Fama-Macbeth. In this paper we show through extensive simulations that Maximum Likelihood Generalized Least Squares (ML-GLS) method outperforms the aforementioned methods. We also present the results from the analysis of a Corporate Finance panel data-set in this context.
Bone Crevice Revelation Proving with Open CV

Image processing is any form of signal processing for which the input is an image, such as a photograph or video frame the output of image processing may be either an image or a set of characteristics or parameters related to the image. Edge detection is a basic and important subject in computer vision and image processing. The purpose of this Paper is to find out the accuration of an X-Ray Bone Fracture Detection using Canny Edge Detection Method. A bone fracture is a medical condition in which there is a break in the continuity of the bone. A bone fracture can be the result of high force impact or stress, or a minimal trauma injury as a result of certain medical conditions that weaken the bones, such asosteoporosis, bone cancer, or osteogenesis imperfecta, where the fracture is then properly termed a pathologic fracture. This paper proposes OpenCV library combined with Canny Edge Detection method to detect the bone fracture. The Canny edge detector is an edge detection operator that uses a multi-stage algorithm to detect a wide range of edges in images. The Simulation results are shown how canny edge detection can help to determine the location of fractures in X-ray images.
A Doppler estimation for UMTS-FDD based on channel power statistics

A Doppler estimation based on a statistical analysis of the channel power variations is proposed for the frequency division duplex (FDD) mode of Universal Mobile Telecommunication Systems (UMTS). Its implementation is considered in both cases of constant power and closed-loop power controlled transmissions. Performance is analyzed in terms of velocity estimation error under various conditions of speed, estimation delay and signal-to-interference-plus-noise ratio (SINR). The influence of a SINR-based power channel estimation is also taken into account. Results show the reliability of this Doppler estimation technique that yields estimates with less than 15 km/h error in a velocity range from 0 km/h to 100 km/h. Results also present the impact of the closed-loop power control on the Doppler estimation reliability.
Functional Disability Among Emirati Senior Citizens In The Home Care Program-Ras Al-Khaimah , UAE

Background: The scientific & technological developments world over has culminated into the numerous benefits to mankind. Increased in life span of man is one of such benefit that is experienced all over the globe. The United Arab Emirates like other many countries world-wide is experiencing demographic transition where the number of elderly in the UAE has increased threefold between 1995 to 2010 and is expected to be 20 per cent of the population by 2020, so a fifth of the population will be composed of the elderly. As disability is associated with increasing age, therefore, the Emirati senior citizens population will exposed to the risk of disability. Aim: to assess the prevalence of functional disability and its associated factors among Emirati senior citizens. Methodology: A cross sectional descriptive and correlation designs were carried out during routine home visits as a part of health care services in Julphar health center, Ras Al-Khaimah-UAE. The study sample size was 154 senior citizens where selected randomly from the sampling frame using sample criteria. Participants were interviewed individually to assess the functional disability using self-reported activities of daily living (ADL/IADL) scales and the Short Portable Mental Status Questionnaire (SPMSQ) to measure their cognitive function. Results: The overall prevalence of functional disability among elderly participants was (31.0%) and only the total dependent participants were (7.0%). Increased risk of functional disability was significant associated with advanced age (P= .003, χ2 =19.49) , female gender (P= .001, χ2 =16.62), cognitive status (P= .000, χ2 =33.02), history of chronic illnesses (P= .001, χ2 = 17.18), and functional limitation (P= .000, χ2 =77.8). In ddition, there were no statistical significant associations between functional disability and marital status, living arrangement, smoking status and alcohol intake. Conclusion and recommendation : Functional disability is one of a major health problem among Emirati senior citizens who are enrolled in the home care program in UAE and this target population need more attention from the community health nurse to incorporate functional assessment tools into elderly care to detect earlier the older adults who have functional limitation which may enhance disability for the first time in later life and to have further planning to eliminate disability as well as to reduce the negative impacts of this disability on the quality of life and increasing the quality of the services provided.
Mining in Persian Language Using Supervised Algorithms

Rapid growth of Internet results in large amount of user-generated contents in social media, forums, blogs, and etc. Automatic analysis of this content is needed to extract valuable information from these contents. Opinion mining is a process of analyzing opinions, sentiments and emotions to recognize people’s preferences about different subjects. One of the main tasks of opinion mining is classifying a text document into positive or negative classes. Most of the researches in this field applied opinion mining for English language. Although Persian language is spoken in different countries, but there are few studies for opinion mining in Persian language. In this article, a comprehensive study of opinion mining for Persian language is conducted to examine performance of opinion mining in different conditions. First we create a Persian SentiWordNet using Persian WordNet. Then this lexicon is used to weight features. Results of applying three machine learning algorithms Support vector machine (SVM), naive Bayes (NB) and logistic regression are compared before and after weighting by lexicon. Experiments show support vector machine and logistic regression achieve better results in most cases and applying SO (semantic orientation) improves the accuracy of logistic regression. Increasing number of instances and using unbalanced dataset has a positive effect on the performance of opinion mining. Generally this research provides better results comparing to other researches in opinion mining of Persian language.
A Review on License Plate Detection and Recognition

License plate recognition is process of extracting License plate area from image and converting them into human recognizable characters. License Plate Recognition has been widely used for Traffic surveillance, law enforcement, Parking and toll collection System. Automatic License plate recognition (ALPR) is also called as automatic number plate recognition (ANPR). ANPR system is divided into Image acquisition, License Plate extraction and Segmentation, and Character recognition. This paper represents different algorithms proposed by researchers for recognizing license plate from captured image.
High pressure processing for pea spread shelf life extension : a preliminary study

The effects of high pressure processing – HPP – (500 and 700 MPa/10, 20 and 30 min/20 °C) on the microbiological quality and colour of maple pea spread were compared to thermal processing (sous vide 80 °C/15 min). Microbiological quality during 15 days at 4 °C was evaluated. Pea spread was filled in polyamide/polyethylene film pouches, packaged in vacuum and hermetically sealed. Pea spreads were made of cooked peas ‘Bruno’ (Pisum sativum var. arvense L.), to which salt, citric acid, oil and herb spice were added. Total plate count was determined on Plate Count agar, Enterobacteriaceaeon Violet Red Bile agar with Glucose, coliformson Endo agar. Decontamination of seasonings was carried out using UV-C treatment and sterilization. Identification of bacteria was completed with API biochemical test system. Colour analysis was carried out in L*a*b* colour space. Total plate count in untreated pea spread was 3.41 log10 CFU g, all processed samples showed significantly reduced microbial contamination (p<0.05). Coliforms were not detected and Enterobacteriaceae count was <10 CFU g after two week storage at +4.0±0.5 °C. Spores of B. subtilis and B. licheniformis were found in all pea spread samples; source of these bacteria was herb spice. UV-C treatment showed considerable decrease in microbiological contamination of seasonings, however, sterilization did not destroy spores. HPP did not influence pea spread colour (p>0.05). HPP (at 700 MPa) demonstrates improvement in pea spread shelf life compared to untreated sample and thermal processing, and is suitable for pea spread shelf-life extension.
Number : WUCSE-2005-61 2005-1201 Architecture and Execution Model for a Survivable Workflow Transaction Infrastructure

We present a novel architecture and execution model for an infrastructure supporting fault-tolerant, long-running distributed applications spanning multiple administrative domains. Components for both transaction processing and persistent state are replicated across multiple servers, ensuring that applications continue to function correctly despite arbitrary (Byzantine) failure of a bounded number of servers. We give a formal model of application execution, based on atomic execution steps, linearizability and a separation between data objects and transactions that act on them. The architecture is designed for robust interoperability across domains, in an open and shared Internet computing infrastructure. A notable feature supporting cross-domain applications is that they may declare invariant constraints between data objects and furthermore declare dependencies on constraints maintained by other applications, leading to flexible, incidental atomicity between applications. The architecture is highly evolvable, maintaining system availability and integrity during upgrades to both application components and the system software itself. Type of Report: Other Department of Computer Science & Engineering Washington University in St. Louis Campus Box 1045 St. Louis, MO 63130 ph: (314) 935-6160 Architecture and Execution Model for a Survivable Workflow Transaction Infrastructure Haraldur D. Thorvaldsson Kenneth J. Goldman Dept. of Computer Science and Engineering Washington University in St. Louis, St. Louis, MO 63130 { harri, kjg}@cse.wustl. edu
LAS for Dysarthric Speech Recognition

People with dysarthria have motor disorders that often prevent them from efficiently using commercial speech recognition systems. In this project, we train a speech recognition system on dysarthric speech using a Listen-Attend-Spell model, which uses a pyramidal bidirectional LSTM and a beam search decoder to predict phonetic transcriptions. The network produces phoneme error rates higher than state-of-theart models on a test set of speakers with low speech intelligibility.
PERCEPTIONS , PRACTICES , AND GUIDING PRINCIPLES OF PRE-SERVICE TEACHERS IN THE QUEST FOR NEWS AND INFORMATION ACROSS INFORMAL MEDIA

The means to access and produce news through social/informal media is ubiquitous. Factors such as the abundance of information coupled with heavy reliance of information and news browsers on the Internet raise dilemmas of trust and credibility. Additionally, the news ecology of today is characterized by rapid news dissemination and subsequent opinion sharing about news stories; hence, finding the true piece of information may be a tedious endeavor. Today more than ever before, the 21st century citizen needs news and information literacy skills to collect, analyze, and synthesize credible information in order to exercise good citizenry. This survey study targeted 124 preservice teachers from a mid-southwest university in Texas, USA, to explore the defining traits of their online news media literacy knowledge and experiences while questing for information. Results revealed a lack of knowledge about news media and information literacy. A disconnect between preservice teachers’ beliefs and practices was discerned, especially amid what we refer to as the influencing powers of media and news consumption. Additionally, exploration of responses to survey items revealed three underlying themes of perceptions, practices, and guiding principles which inform the individual’s personal media ecology.
Estimating Outbreak of Influenza Like Diseases Using Social Media

Early detection of the onset and outbreak of influenza like contiguous diseases followed by timely intervention by authorities with rapid response can greatly reduce the damage caused by them. Unfortunately, until now actual data arrives in the hands of authorities with a lag time of ten days to two weeks. In this research we have used social media, namely Twitter, to predict the state of such disease outbreak by analyzing tweets made by the members of the community. We have used natural language processing techniques to identify and quantify flu related tweets from normal tweets 1 .
TRAINING EFFECTIVENESS OF SELF-EFFICACY AS AN EFFORT TO IMPROVE THE SELF-REGULATED LEARNING

The study aims to prove whether self-efficacy training can improve self-regulated learning. This study looks at two variables, self-efficacy and self-regulated learning. Individual self-efficacy is the belief in his ability to control the behavior and demands of the environment so as to obtain results in line with expectations based on the level, strength and generality. Self-regulated learning is an attempt by individuals to organize them in a study involving metacognition abilities, motivation and behavior. As many as 46 research subjects were divided into two experimental groups was 23 people and the control group was 23 people. Based on the analysis Wilcoxon signed-rank. Showed mean difference 52.96, Asymp sig (2-tailed) = 0.000 (p <0.05), which means there is an increased ability to self-regulated learning students are given training after self-efficacy. Kolmogorov-Smirnov test showed the mean difference 64.65 with Asymp-sig (2-tailed) = 0.02 (p <0.05) means that students in the experimental group had a self-regulated learning level higher than students in the control group. The results showed a significant relationship between self-efficacy and self-regulated learning with a correlation value of 0.708 and significance (2-tailed) 0.015 (p <0.05). Keyword: self-efficacy, self-regulated learning
Challenges of Abattoir Waste Management in Jalingo Metropolis , Nigeria

The upsurge in the prevalence of communicable and zoonotic diseases makes abattoir waste a disease surveillance points. Abattoir operations generates numerous waste and microbial organisms that pollutes the environment. This pose serious threat to human health and quality of life. Most abattoirs in Nigeria are characterized by poor design, obsolete facilities and deteriorating environment. The challenges posed by poor abattoir waste management on public food safety and quality of life in Taraba state and Nigeria has become a source of concern. This paper examined the challenges posed by the poor waste disposal from the abattoir in Jalingo metropolis. Investigative approach to data collection was employed along with secondary desk review of relevant data. The Jalingo main abattoir was considered as the study site. Data on the number of animals (cattle, goats and sheep) slaughtered daily was collected from records on abattoir operations. Additional information was collected through interviews with key informants (veterinary experts and meat inspectors) using interview schedule. The data collected were analyzed using descriptive statistics. The result of the study shows that after over 35years of its establishment, the abattoir has not expanded to accommodate the increasing population and demand for meat. This resulted in overstretch and deterioration of the facility and poor waste disposal. The findings of this study shows that the daily slaughter of animals ranges between 50 – 55 cows and 125-130 goats/sheep. The poor abattoir waste disposal affect air quality (stench), pollutes agricultural land, potable water supply source and aquatic life. The challenges of abattoir waste in the area include poor abattoir designs and obsolete facilities, location of the abattoir in residential areas, apathy by the state government over responsibilities of establishment and management of abattoirs, poor funding and lack of effective abattoir waste disposal equipment. The study recommended the regulation of animal waste disposal system which is better than the present dumping regime, legislative measures on landuse zoning and waste regulation to control the location and management of abattoirs in the state and country.
MAPPING PLANT NITROGEN STATUS BY USING ADS 40 TO AID PRECISION FARMING

Agricultural practices are considered as one of the major contributor for global pollution . Besides other, agriculture related pollution comes from agricultural inputs applied to the filed, such as fertilizer and pesticide. In majority of the agriculture field, flat rate application in wider area, sometimes even in whole region, is being used. However, it is well known fact that soil is not uniformly distributed for its fertility status. Applying fertilizer according to the level of locational soil fertility will not only reduce the pollution, but also increase profitability by reducing input cost. First step for such practice is to assess real time locational plant nutrient deficiency. With the conventional method of field soil and/or plant sampling is not practical for such purpose, specifically while considering the time and crop schedule, spatial preciseness, cost and others. Airborne survey, for example with ADS40 multispectral high resolution sensor, can solve most of the problem. Considering the problem and possibility, a joint collaborative research between PASCO Corporation and Tokyo University of Agriculture and Technology (TUAT) has been initiated since spring (wheat crop) 2001 for Wheat-Soybean -Maize rotation field that is located at TUAT, FUCHU campus, Tokyo, Japan. In this study possibility of modelling for plant nitrogen, which is one of the major plant nutrient, status mapping had been fetched out by using ADS40 imagery along with conventional infrared aerial photo and field observation data, for example SPAD (plant greenness index) reading. A new index, named as Plant Vigour SPAD (PVSPAD) was formulated and its relationship with Normalized Difference Vegetation Index (NDVI) was modelled with sufficient statistical confidence. As the imagery has less than 20 cm resolution, the model can be used to map the nutrient with enough accuracy for varied rate fertilizer application.
Detecting Forged Acknowledgement in Mobile Ad-Hoc Network Using Intrusion Detection System

On the contrary to traditional network architecture, MANET does not require a fixed network infrastructure; every single node works as both a transmitter and a receiver. Nodes communicate directly with each other when they are both within the same communication range. Otherwise, they rely on their neighbors to relay messages. The self-configuring ability of nodes in MANET made it popular among critical mission applications like military use or emergency recovery. However, the open medium and wide distribution of nodes make MANET vulnerable to malicious attackers. In this case, it is crucial to develop efficient intrusion-detection mechanisms to protect MANET from attacks. With the improvements of the technology and cut in hardware costs, we are witnessing a current trend of expanding MANETs into industrial applications. To adjust to such trend, we strongly believe that it is vital to address its potential security issues. In this paper, we propose and implement a new intrusion-detection system named Enhanced Adaptive ACKnowledgment (EAACK) specially designed for MANETs. Compared to contemporary approaches, EAACK demonstrates higher malicious-behavior-detection rates in certain circumstances while does not greatly affect the network performances.
A coupled efficient and systematic full-wave time-domain macromodeling and circuit Simulation method for signal integrity analysis of high-speed interconnects

This paper presents an accurate and systematic approach for analysis of the signal integrity of the high-speed interconnects, which couples the full-wave finite difference time domain (FDTD) method with scattering (S) parameter based macromodeling by using rational function approximation and the circuit simulator. Firstly, the full-wave FDTD method is applied to characterize the interconnect subsystems, which is dedicated to extract the S parameters of the subnetwork consisting of interconnects with fairly complex geometry. Once the frequency-domain discrete data of the S parameters of the interconnect subnetwork is constructed, the rational function approximation is carried out to establish the macromodel of the interconnect subnetwork by employing the vector fitting method, which provides a more robust and accurate solution for the overall problem. Finally, the analysis of the signal integrity of the hybrid circuit can be fulfilled by using the S parameters based macromodel synthesis and simulation program with integrated circuits emphasis (SPICE) circuit simulator. Numerical experiments demonstrate that the proposed approach is accurate and efficient to address the hybrid electromagnetic (interconnect part) and circuit problems, in which the electromagnetic field effects are fully considered and the strength of SPICE circuit simulator is also exploited.