Miracle-dz/UniFAR-FTUs huggingface dataset:
A Survey to Predict Cardiovascular Disease Using Data Mining

: Cardiovascular diseases are the most common cause of humanity and injury in India. People of all ages are affected particularly the elderly people. They are most prone to emerging heart diseases because of old age. A record of people pretentious by heart disease is of utmost importance. This is essential to predict the group of people commonly affected, age, sex, risk factors, diagnosis and management of heart diseases. A huge number of people are pretentious by heart diseases and hence it is quite difficult to predict accurately. Data mining technique helps to collect file and predict the population affected by heart problems accurately. Data mining is used in various fields. Data mining procedures serve as a key for advancement in the field of medicine. It is very easy to access the information about heart problems and their risk factors including the hidden information for proper diagnosis and treatment. Proper mining methods can save an enormous number of people from mortality due to heart diseases. Various forms of algorithms have been used in data mining.
Climate Change and Mine Closure – A Practical Framework for Addressing Risk

The two largest disturbances mining presents which requiring addressing are disturbances to the water balance and energy balance; both of which will be influenced by climate change. This paper presents a framework to incorporate climate change into mine closure planning from a risk perspective, as risk management will be a key component in decision making for mine closure designs. The newest Representative Concentration Pathway (RCP) emission scenarios allow for ranking climate change outcomes from “very likely” to “less likely” to occur. By combining the likelihood of occurrence for various climate outcomes with the magnitude of the potential failures, a risk based design criteria can be developed for each closure component. This paper will focus on cover systems as closure technology to illustrate application of the framework presented in this paper. The creation of realistic and attainable design criteria begins on a conceptual framework, allowing nontechnical persons to better understand complexities of detailed design. The framework presented utilizes the Köppen-Geiger climate classification system to differentiate climates, largely because of its ability to reflect seasonal differences. Boundaries are determined by a global dataset of long-term monthly precipitation and temperature records, which can been adapted to future climate change predictions. Understanding how climate is expected to change at a seasonal level is more valuable from a planning perspective than from an annual basis. Köppen-Geiger’s strong ties to landscape signals such as vegetation and water availability make it ideal for closure planning. Implications for understanding the required equilibrium between the closure landscape and the existing landscape provide an indication of timescales involved. For example, it is not realistic to believe engineered structures will provide the expected performance following a glaciation event. Closure timeframes are typically 100 years, if not longer, therefore an appropriate framework to address the challenge of designing structures with defensible controls on identified risk is required.
Numerical Solution of Imbibition Phenomenon in a Cracked Porous Medium with Magnetic Fluid

In this paper, we have discussed imbibition phenomenon in double phase flow through cracked porous media. The mathematical formulation leads to non linear partial differential equation governing the phenomenon in a cracked porous medium with magnetic fluid. The mathematical solution has been obtained by finite element method with appropriate initial and boundary condition. Finite element method is a numerical method for finding an approximation solution of differential equation in finite region or domain. We obtained graphical representation of the solution using a Matlab coding.
Fully Automated Atomic Force Microscopy Measurement and Analysis Using Park NX System

meet market demand for faster and more efficient designs every year. Current projections have the first devices using a 7 nm manufacturing process debuting as soon as 2017. To meet this challenge, manufacturers must have the capability to meet metrology requirements that simultaneously call for enhancements in resolution, precision, and accuracy. One automated metrology software solution, Park XEA, is designed to enable engineers to use Atomic Force Microscopy to acquire accurate and repeatable nanoscale images of target devices according to user-defined procedures in custom recipe files. The corresponding increase in productivity is attractive for wafer-level device fabrication plants everywhere. In this investigation, five identical NOR Gate devices on a three-inch patterned silicon wafer consisting of rectangular pits with 10 um pitch and 120 nm step height with the device area were accurately and repeatedly imaged using a Park NX-HDM automated AFM system and Park XEA. This accomplishment clearly exhibits automated AFM’s utility in overcoming the metrological challenges faced by the semiconductor industry both now and in the future.
mpacts of climate change on roundwater resources: a case tudy of the Sardon catchment, pain

lines 23-24 Annual precipitation is expected to decrease by about 5.7%, 5.5% and 125 for the 2020s, 2050s and 2080s respectively. Annual precipitation is expected to decrease by about 5.7%, 5.5% and 12% for the 2020s, 2050s and 2080s respectively under the A2 scenario. Page 17, second paragraph line 1 Page 58, last paragraph, line 3 A1B A1 Page 35, last paragraph, line 4 Figure 5-1 Table 5-1 Page 38, first paragraph, line 7 Figure 4-3 Figure 5-2 Page 48, paragraph 4, line1 Figure 6-2 Figure 6-5 Page 52 under caption Figure 6-7 See Fig 4-3 See Fig 5-2 Page 53, paragraph 1, line 1 Figure 6-9 Figure 6-8 Page 54, paragraph 1, line 2 Figure 6-10 Figure 6-9
Shocks and Household Welfare in Sudan

The Sudanese economy has faced several shocks over the years—sometimes resulting in devastating impacts on the economy and the welfare of Sudanese households. Poor households are often particularly vulnerable to shocks. The extent of the impacts of shocks on household welfare depends on the nature and severity of the shocks as well as households’ capacity to manage its risk of exposure to shocks ex ante and/or mitigate the impact of shocks ex post. This paper applies this framework to examine the impact of shocks on the welfare of Sudanese households and explore coping strategies typically utilized by households to mitigate the negative effects of shocks. The paper uses the 2009 National Baseline Household Survey (NBHS) and the 2014/15 National Household Budget and Poverty Survey (NHBPS) to document the main types of shocks that Sudanese households are exposed to and describe the profile of Sudanese households likely to be vulnerable and/or resilient to shocks. To complement this analysis, the paper uses the most recent round of the data collected in 2014/15 (containing information on idiosyncratic shocks) together with data on covariate shocks such as rainfall and conflict obtained from other sources to estimate the impact of shocks on household welfare. Since the impact of shocks on household welfare is likely to be multidimensional, various indicators of household welfare such as consumption, poverty status, assets, dietary quality, and diversity are considered in the paper. Results from the analysis are used to highlight the state of social protection in Sudan and discuss the need for an expansion of the existing system. The prevalence of shocks in Sudan is most common among poor, agricultural, and rural households. Floods/droughts have the largest negative effect on the welfare of Sudanese households. The large negative effects of shocks on the welfare of Sudanese households (particularly those with low capacity to cope with shocks) highlight significant limitations in households’ ability to fully mitigate the impact of shocks.
Combining Review Text Content and Reviewer-Item Rating Matrix to Predict Review Rating

: In recent years, shopping online is becoming more and more popular. When it need to decide whether to purchase a product or not on line, the opinions of others become important. It presents a great opportunity to share our viewpoints for various products purchase. However, people face the information overloading problem. How to mine valuable information from reviews to understand a user’s preferences and make an accurate recommendation is crucial. Traditional recommender systems consider some factors, such as user’s purchase records, product category, and geographic location We have seen a twist of review websites. It displays an incredible chance to share our perspectives for different items we buy. In any case, we face the information overloading issue. Instructions to mine important data from reviews to understand a client’s preferences and make an exact recommendation are pivotal. Traditional recommender System (RS) think of some as elements, for example, client's buy records, item classification, and geographic area. In this work, we propose a sentiment based rating prediction technique (RPS) to enhance expectation precision in recommender frameworks. Firstly, we propose a social client sentimental measurement approach and compute every client's sentiment on items/products. Besides, we consider a client's own sentimental attributes but also take interpersonalsentimental influence into consideration. At that point, we consider item reputation, which can be induced by the sentimental distributions of a client set that reflects clients' complete assessment. Finally, we combine three factors client sentiment comparability, interpersonal sentimental influence, and item’s reputation similarity into our recommender system to make an accurate rating prediction. We lead anperformance evaluation of the three sentimental factors on a real-world dataset gathered from Yelp. Our test comes about demonstrate the sentiment can well characterize client preferences, which enhance the recommendation performance.
Design of High Speed Hardware Efficient 4-Bit SFQ Multiplier

: A 2-bit Booth encoder with Josephson Transmission Lines (JTLs) and Passive Transmission Lines (PTLs) is designed. The Booth encoding method is one of the algorithms to obtain partial products. With this method, the number of partial products decreases down to the half compared to the AND array method. The circuit area of the multiplier designed with the Booth encoder method is compared to that designed with the AND array method. The proposed 4-bit modified booth encoders are designed using Quartus II. The area, delay and power performance of the booth encoder and modified Booth Encoder have been evaluated from the simulated output analysis shows that modified Booth encoder implemented SFQ multiplier better compared to conventional booth encoder.
A Survey on Super-Resolution Techniques

: Information revealed by Low Resolution (LR) images is so limited that the accuracy of the resulting recognition is very low. Thus the Low Resolution (LR) problem forms one of the most challenging issues in recognition. Recently, super-resolution techniques have been employed to address the Low Resolution (LR) problems of imaging system. Super-Resolution techniques estimate a high resolution image from one or more low resolution images. Super Resolution (SR) is an under-determined problem, especially when only one Low Resolution (LR) image is available for a scene-a problem known as single image super-resolution (SISR). We present a learning-based single image super-resolution method to obtain a High Resolution (HR) image from a single given low resolution LR image. Our method not only tests and trains faster, it also requires a smaller number of training samples while achieving competitive reconstruction accuracy compared to other learning based methods. We met these objectives by posing the HR reconstruction problem as an estimation of a function to predict the pixels of an HR patch using its corresponding LR pixels and their spatial neighborhood. These goals were achieved by careful selection of input and output patch sizes, use of Dimensionality Reduction Methods as a pre-processing step, and use of learning based single image super-resolution.
Survey on Improving Web Search by Analysing Various Facets

: Query Faceted search is a way for searching users to find, analyze, and navigate through search data from online web pages. It is widely used in e-commerce and digital libraries. An effective approach for faceted search is the scope of this implementation. The majorities of the presented facets creation systems are based on a precise province or already defined facet categories. For example, Web search mining for an unsupervised contents by involuntary separate the facets which are relevant to the result that already search for personal web search as user search interest pattern from databases. Facet collection is generated for collection, rather for a single given query. Proposed facets searching system used for information search and media exploration in online search results. Proposed system extracts and aggregates the useful information from the specific knowledge database Wikipedia. In this paper, a proposed system explores to involuntarily find query related aspect of search for open-domain queries in the search engine. Facets of a query are directly mined from the top important searchesrelated to the query without any additional domain knowledge required. As query facets are excellent summary of a query and are potentially helpful for users to appreciate the query and assist them discover information, they are probable data sources that enable a general open-domain faceted exploratory search.
Search nearest Keyword Set in Multi-Dimensional Datasets

: In this paper consider objects like images, docu-ments are tagged with keywords. These objects characterized by a collection of features and represented as points in a multidimensional feature space. In this paper it look at nearest keyword set queries on textual content high multidimensional dataset. Existing techniques using tree-based indexes suggest viable solutions to NKS queries on multidimensional datasets but performance of these algorithms deteriorates with the growth of length or dimensionality in datasets. In this paper it propose Projection and Multi Scale Hashing (ProMiSH) to permit fast processing for NKS queries and also it uses random projection and hash-based index structures to achieves high scalability.
Implementing Clinical Accommodations for Students With Physical Disabilities in Nursing Education

Summary: Many nursing faculty lack the knowledge and expertise needed to appropriately accommodate students with disabilities, especially in clinical settings. Research was conducted to determine what processes are needed to guide faculty in providing accommodations to students with physical disabilities in a clinical nursing course. Research results will be shared. Content Outline: Introduction 1. Disability regulations in Higher Education 2. Current Status of Students with Disabilities in Nursing Education
Swelling capacity of mixed talc-like/stevensite layers in white/green clay infillings (“deweylite”/“garnierite”) from serpentine veins of faulted peridotites, New Caledonia

Abstract White (Mg-rich) and green (Ni-rich) clay infillings (“deweylite”/“garnierite”) found in serpentine veins of faulted peridotite formations from New Caledonia consist of an intimate mixture of fine-grained and poorly ordered 1:1 and 2:1 layer silicates, commonly referred to as non-expandable serpentine-like (SL) and talc-like (TL) minerals. New data on the swelling and shrinking capacity of these layer silicates were gathered from X‑ray diffraction (XRD) after saturation of the clay fractions with different cations (Ca2+, Li+, K+), ethylene glycol (EG) solvation, and heat treatments. Simultaneously, layer charge distribution and vacancy density, respectively, were investigated by FTIR spectroscopy on NH4-saturated clay fractions and XRD on Li-saturated clay fractions before and after heating (Hofmann Klemen treatment). Five clay infillings, with dominant 2:1 layer silicates and variable Ni contents, were selected for this study, from a large set of veinlets, according to their swelling capacity. The crystal chemistry of these samples was characterized by FTIR spectroscopy and bulk chemical analyses. The swelling ability of the clay infillings is attributed to the 2:1 layer silicates. It does not seem to be affected by the relative fraction of Mg and Ni in their octahedral sheets. In XRD patterns, the swelling ability is reflected by slight shifts of the basal reflection of the 2:1 layer silicates toward low angles for bulk samples and by splitting of the peak into two contributions for clay fractions saturated with Ca (or Li) and solvated with EG. The split increases with the swelling capacity of the sample. It originates mainly from octahedral-layer charge generated by vacant sites. Such results lead us to consider the 2:1 layer silicates of the infillings as an intimate mixture of non-expandable (TL) and expandable (stevensite) phases. In agreement with previous studies that suggested a contribution of hydrothermal processes in the alteration of serpentine species into 2:1 layer silicates, we propose that the proportion of expandable phases in the clay infillings (or vacancy sites in the octahedral sheets of the 2:1 layer silicates) could be used as an efficient means for assessing the temperature of their formation. Clay infillings mostly made of stevensite would have formed at ambient temperatures, whereas those consisting mainly of non-expandable TL would have formed at higher temperatures.
Relationship between Excavation-Geometry and Blast-Geometry with reference to Indian Coal Mines

Blasting is the cheapest and the fastest method of rock breaking and is extensively used for winning minerals. Blasting operations causes excessive noise and vibration which affects the nearby communities. Excessive levels of structural vibration caused by ground vibration from blasting can result in damage to structures. The objective of this research was to investigate the most appropriate blast holediameterswith reference to the prevailing bench heights for coal mines and other excavation jobs based on the correlation. To achieve this objective, field observations and data collection were carried out at different coal mines in Telangana, India. Based on the analysis of the data, reconsideration of hole diameter for blasting operations is suggested. A new model for estimating hole diameter for blasting operations is developed based on multiple regression methods. The measured variables that are used as independent ones (regressors) and included in the model development are hole depth (H), burden (B), and spacing (S). The hole depth and spacing were found to be statistically significant and were included in the final model. Though the burdenwas included in the final model, its effect was statistical less significance.This research could help mining, civil and blasting professionals to accurately design blasting operations and develop effective strategies to mitigate various hazards associated with blasting.
In-house texture measurement using a compact neutron source

The RIKEN compact neutron source and related neutron diffractometer were successfully upgraded for precise in-house texture measurement, as judged by comparison with two other well established neutron diffractometers. This provides a good example for the technical development and the scientific application of neutron diffraction techniques based on compact neutron sources.
A Novel Approach to Construct Community QA Systems

: The data-driven approach can yield high levels of performance and nicely complements traditional question answering techniques driven by information extraction. In order for question answering systems to benefit from this vast store of useful knowledge, they must copy with large volumes of useless data. Question Answering systems (QA) uses similarity in questions and ranking the relevant answer to user. The web gives large data and that require more time as well as no relevancy in answers. To solve this problem proposed system proposed novel Pairwise Learning to rANk model i.e PLANE which can quantitatively rank answer candidates from the relevant question pool. Specifically, it uses two components i.e one offline learning component and one online search component. Our model is effective as well as achieves better performance than several existing questions answer selection system.
CIA_A_239053 293..300

Krannert School of Physical Therapy, University of Indianapolis, Indianapolis, IN, USA Introduction: The purpose of this study was to determine if correlations exist between strength and mobility and psychological measures of anxiety and depression in communitydwelling older adults. Methods: One hundred and eleven participants randomly completed trials of grip strength (GS), the Timed Up and Go (TUG), the 10-meter walk test (10MWT), the Geriatric Anxiety Scale (GAS), and the Geriatric Depression Scale (GDS) in a prospective, correlational study. Results: This study found significant correlations between and within physical measures of strength and mobility and psychological measures. Age, GS, GDS, and education were significant predictors of gait speed (10MWT). Age, GS, and GDS were predictors of TUG scores. Grip strength was found to be a significant predictor of fall status; fallers had significantly weaker GS than non-fallers. Symptoms of anxiety (GAS) were predictive of symptoms of depression. Discussion: Objective measures of physical performance can provide information regarding an individual’s symptoms of anxiety and depression. Health professionals should understand the correlations between mood and physical ability to better treat their patients.
Comparing Attractive and Unattractive Facebook Posts in Selected Companies/ Institutions in Mogadishu City, Somalia

This paper aimed at comparing attractive and unattractive Facebook posts among Mogadishu Facebook users. The political climate in Mogadishu motivated us to adopt an online computer-based monitoring of various posts posted by each of the three institutions that participated. In-depth interviews were administered to few accessible participants at Jamhuriya University who were knowledgeable about these companies’ Facebook engagements. Desk review was adopted in order to obtain scholarly materials on social media posts and particularly Facebook. Key findings in this study indicate that video posts receive more comments and likes than other posts like photos for reasons valued by the respective customers. Facebook fans, mostly young people such as students and youth tend to enjoy action related posts than photos. Findings further reveal that Facebook interaction is at the peak during midyear for three months of June, July and August. This is attributed to the fact that this is usually summer time, the time when most Somalis in the diaspora come home for vacation perhaps largely attracted to various events taking place in the country. Findings also indicate that social media addicts in Mogadishu start commenting on Facebook as early as 4am in the morning, some of these are Facebook fans who find it hard to sleep again after 4am prayers. The study concludes that the use of social media especially Facebook is subtly gaining prominence and remains the most viable avenue for Somalis to interact freely; exchange social, political and economic ideas; and get updates on what is happening around the world and within in their societies.