Miracle-dz/UniFAR-FTUs huggingface dataset:
Predictors of Health-related Quality of Life and Self-care in a Large Sample of Spanish Adults with Diabetes Mellitus

Objective: To assess health-related quality of life (HRQoL) and self – care behaviors in a large sample of diabetic patients (DPts) and to examine which patients’ characteristics influence on them. Methods: This cross - sectional study included 1,039 DPts (561/478, Men/Women, 156/883 DM1/DM2, mean age 62±15 years old; mean diabetes duration 15±10 years) evaluated in a diabetes (DM) specialized outpatient office, at St Carlos Hospital, in Madrid, from 2012 to 2014. HRQoL was assessed with the EuroQoL- Visual Analogue Scale (EQoL-VAS) and the Diabetes Quality of Life Score (DQoL). Treatment adherence was evaluated using the Self-Care Inventory-revised (SCI- r). Multiple logistic regression analysis were used to examine the relationship between HRQoL, adherence to treatment and several demographic and clinical patients’ characteristics. Results: A lower quality of life was associated with the female gender, the presence of chronic complications and a poor glycemic control (all p < 0, 05). After adjustment for confounders, obese middle-aged men showed the lowest adherence to treatment. However, women with a prolonged duration of the DM (> 15 years) and DPts receiving insulin treatment showed a better DM self-care (p <0.05). Conclusions and Implications: The duration of the DM, metabolic control, the type of therapy, and the presence of chronic complications are important determinants of HRQoL and treatment adherence in patients with DM, and should be taken into account when treating DPts. Data obtained could be useful to plan patient-based health decisions. index; GFR: glomerular filtration rate; MDRD: Modification of Diet in Renal Disease; NDS: Neuropathy Disability Score; NSS: Neuropathy Symptoms Score; MNIS: Memphis Neuropathy Instrument Score.
A Research: Hyperspectral Image Processing Techniques

— Hyperspectral image contains more information which are gathered from numerous narrow wavebands from one or more regions, and large amount of data are huddled. An basic problems in hyperspectral image processing are dimension reduction, target detection, target identification, and target classification. In this document, we reviewed the latest activities of target classification, most frequently used techniques for dimension reduction, target detection. Hyperspectral image processing is a complicated process which rely on mixed agents. Here we also recognized and reviewed problems faced by some methods and to overcome the problems, current techniques are discussed and highlighted good methods. To improving correctness, genuine classification techniques and Detection Techniques analysis are recommended.
Enhanced Personalized Search Query Log Analysis on User Logs

User profiles can be used by search engines to provide personalized search results. Users are increasingly pursuing complex task oriented goals on the web, like making travel arrangement, planning purchase or managing finance. Organizing the user search logs is rapidly increasing in the field of data mining for finding the user interestingness and organizing the user search requirements in a proper way. Searchers create and use external records of their actions and the corresponding results by writing/typing notes using copy and paste functions. Daily billions of queries can be passed to the server for relevant information most of the search engines retrieves the information based on the query similarity score or related links with respect to given query. To better support users in their long-term information quests on the Web, the search engines keep track of their queries and clicks while searching online. This paper proposes to enhance search query log analysis by taking into account the semantic properties of query terms. User profiles were created by classifying the collected information into concepts in a reference concept hierarchy. We study the problem of organizing a user’s historical queries into groups in a dynamic and automated fashion.
Supporting Spatial-Tempo Ad

Spatial-Temporal Provence (STP) are quickly becoming immensely popular. In apply that users of the communicate to the services (LBS). Malicious users may lie about their spatial-temporal provenance (STP) without a carefully designed security system for users to prove their past locations. This type of attack will have a severe impact on applications of the period of time traffic office, location based on the access management, the traffic of the process to be in electronic election. In this paper, we present the Spatial provenance Assurance with Mutual Proofs (STAMP) scheme. STAMP is designed for ad-hoc mobile users generating location proofs for each other in a distributed setting. However, LP versions can easily accommodate trusted mobile users and wireless access points. STAMP ensures the integrity and non transferability of the location proofs a users privacy. A semi-trusted Certification Authority is used to distribute cryptographic keys as well as guard users against collusion by a light entropy-based trust evaluation approach. Our prototype implementation on the Android platf shows that STAMP is low-cost in terms of computational and storage resources. Extensive simulation experiments show that our entropy trust model is able to achieve high collusion detection accuracy.
À propos d'un cas d'hypothyroïdie congénitale About a case of congenital hypothyroidism

A boy presented at birth dyspnea, jaundice, meteorism and hypospadias; biochemical testing revealed hyponatremia. He benefited on day 4 of neonatal screening for hypothyroidism and congenital adrenal hyperplasia (CAH) and assays showed high concentrations of 17-OHP and TSH. Because of clinical features and hyponatremia, the diagnosis of CAH was plausible. A serum control (17-OHP and TSH) carried out on day 8 showed a normal concentration of 17-OHP and a persistingly elevated concentration of TSH confirmed by a second assay a few days later. A 131I scan of neck revealed an ectopic lingual thyroid. The considerable progression of false positive screening tests for CAH is mainly due to the increasing number of premature babies. We show by a retrospective analysis (7 yrs), that children with hypothyroidism also present frequently higher concentrations of 17-OHP than normal children. However, whatever the aetiology (apart from CAH), the concentrations of 17-OHP rapidly normalise.
Efficient Hand-dorsa Vein Pattern Recognition using KNN classification with Completed histogram CB in TP Feature Descriptor

: Hand-dorsa Vein Recognition System identifies an individual using the human hand vein features. Image capturing, extracting the features, keeping the features in a descriptor and making classification are important methods in hand-dorsa vein Recognition. In this paper, the feature descriptor and classification method is proposed for an efficient recognition system. A completed CB in TP has been proposed to represent selected features from Hand vein image system. K-nearest classification method with various proximity measure calculations is analysed to make an efficient classification system. A new minimum distance classification is proposed with dataset and the results are checked for accuracy and reliability. The proposed technique is calculated on a NCUT Dataset contains 2040 imagesfrom Prof. Yiding Wang, North China University of
Transformational Leadership and Employees' Job Satisfaction and Commitment: A Structural Equation Investigation

The current study aimed at investigating the relationship between transformational leadership and both employees' generic job satisfaction and organizational commitment. The sample consisted of 160 male employees attending Master of Business Administration program in some private educational institutions in Egypt. Their ages ranged between 25 and 47 years (35.47±6.27 years). Three instruments were used to assess study variables: Multifactor Leadership Questionnaire (MLQ) was used to assess transformational leadership; the Generic Job Satisfaction Scale (GJSS) was used to assess employees' job satisfaction; while Mayer & Allen's Organizational Commitment Questionnaire (OCQ) was used to assess employees' organizational commitment. The results indicated that transformational leadership style is significantly correlated with generic job satisfaction and organizational commitment. Structural investigation of these relationships indicated that job satisfaction mediates the relationship between perceived transformational leadership style and organizational commitment. These results are discussed in line with past theoretical and empirical literature. [Mohamad Saad Mohamad. Transformational Leadership and Employees' Job Satisfaction and Commitment: A Structural Equation Investigation. J Am Sci 2012;8(7):11-19]. (ISSN: 1545-1003). http://www.americanscience. org. 3
A Bi-Objective Model for Worker Assignment in Cellular Manufacturing System Design

Cellular manufacturing system (CMS) is a manufacturing system that produces families of parts within a cell of machines operated by a worker who plays a crucial role in running the system and determine the quality level. A bi-objective mathematical model is proposed to solve a three-dimensional part-machineworker assignment problem that improves productivity and efficieny in CMS. The two objectives considered in this model are cost and quality. The costs include the interand intra-cell material handling costs as well as the production costs while the quality is calculated as overall percentage. The performance of workers on different machines is measured by the average scrap or defect rate of parts processed on each machine by dedicated workers. The novelty in this model lies in addressing the cell formation problem simultaneously with the layout planning and worker assignment problems. As the proposed problem is NP-hard, a genetic algorithm (GA) is used to effectively solve the problem. Finally, several problems from related literature were used to verify the proposed model. The results are compared to previous researches and demonstrate the advantages of the proposed integrated approach. Keywords-Cellular Manufacturing System; Cell Formation; Facility Layout; Worker Assignment; Genetic Algorithm; Bi-Objective Optimization
Survey on Anti discrimination in Data Mining

-Data mining refers to the extracting knowledge from large amount of data. Data Mining automates the detection of relevant patterns in databases. Classification rule is one of the techniques used in data mining for making automated decision, like loan granting, staff selection. However, if the training data sets are unfair in what regards discriminatory attributes like age, caste, gender, nationality, etc., discriminatory decisions may ensue. To prevent such situation, antidiscrimination techniques comprising discrimination discovery and prevention have been introduced in data mining. The primary goal of this survey paper is to review and identify advantages and limitations of discrimination discovery and discrimination prevention techniques.
INTEGRATED ELLIPTIC CURVE CRYPTOGRAPHY AND FEEDBACK INCENTIVE SCHEME FOR DYNAMIC TRUST MODEL IN MULTI-AGENT SYSTEMS

— Multi-agent systems are open, anonymous and dynamic in nature. Trust and reputation models fail to properly evaluate the trust of an agent if malicious agents behave in an unpredictable way. These models are ineffective in providing quick response to malicious agent’s oscillating behavior and critical for sustaining good service quality . The dynamic trust computation model called Secured Trust analyze different factors related to evaluate the trust of an agent but it fails to address Sybil attack and man in middle attacks. In this paper Elliptic curve cryptography and Feedback Incentive scheme is presented in-order to improve the trust model of multi-agent systems and also the load balancing algorithm is used to improve the quality of service among the service providers. This integrated scheme resists more influential malicious adversaries in the network and also provides efficient distribution of workload among service providing agents under stable condition.
Demodulation of PPM signal based on sequential Monte Carlo model

— Demodulation of the constant-amplitude Polynomial Phase Modulation (PPM) signal [1] Based on Polynomial Phase Transform (PT) [2] and High-order Ambiguity Function (HAF) [3] generally requires very large oversampling rate. They also did not consider the multipath channel environment and Inter Symbol Interference (ISI). In this paper, a demodulation method for PPM signal based on Sequential Monte Carlo (SMC) algorithm is proposed. Compared with the conventional code division multiple access (CDMA) technique, where the spread factor is fixed in one modulation coding scheme, the proposed SMC PPM demodulation method can dynamically adjust the oversampling rate (corresponding to the spread factor in CDMA) according to the available bandwidth and performance requirement. This is attractive to Cognitive Radio (CR) and Software Defined Radio (SDR) system. The proposed SMC PPM demodulation methods can also cope with the multipath channel and ISI. Simulation results under fixed narrow-band channel with AWGN shows that, with the proposed SMC PPM demodulation method, the PPM can provide significant performance improvement over the conventional modulations, such as QPSK and 8PSK.
MICROWAVE ASSISTED SYNTHESIS, CHARACTERISATION AND ANTI MICROBIAL ACTIVITIES OF FEW COBALT (II)- THIOSEMICARBAZONES COMPLEXES

A series of four novel Cobalt(II) aryl thiosemicarbazones complexes having the general composition [Co(L1)2Cl2], [Co(L2)2Cl2], [Co(L3)2Cl2] and [Co(L4)2Cl2]{where L1= 4-Nitroacetophenone thiosemicarbazones (4NAT), L2 = 3-Nitrobenzaldehyde thiosemicarbazones (3NBT), L3 = 4-Hydroxybenzaldehyde thiosemicarbazone (4HBT) and L4 = 4-Aminoacetophenone thiosemicarbazone (4AAT)} have been synthesized by the reaction of thiosemicarbazide with substituted aromatic aldehydes and ketones by conventional heating as well as microwave irradiations method followed by complexation with Cobalt(II) metal. The synthesized compounds have been characterised by elemental analysis, melting point determination, FTIR, UV-visible spectral analysis. The synthesized ligands and their new metal complexes have been screened in vitro for antibacterial activity against Escherichia coli, Staphylococcus aureus and Bascillus subtilis bacteria.
An Efficient Facial Annotation with Machine Learning Approach

: In machine learning process facial annotation methods are very favorable. One of the main problem for searchbased face annotation scheme is how toannotation by exploring the most of same facial images and their weak labels that are incomplete. We propose an unsupervised label refinement method for achieving the labels ofweb facial images using machine learning techniques.
Mri Brain Images Tumor Detection and Feature Extraction Using Clustering and Morphology

Segmentation refers to classification of an image into different regions. Eventually days medical field is to an extraordinary degree rely upon image segmentation process. This paper aims to segment MRI image using clustering and morphology technique to detect tumor and after that extracting static components of the tumor area. Brain tumor is very hurtful infection. It is demonstrate that the probability of survival can be broadened if tumor is identified or recognized effectively. So an effective diagnosis and detection of brain tumor is very important for the treatment. In this manner we need a more productive tumor detection method with some favored properties such as minimum client interaction, quick computation and accurate outcomes. In this paper an efficient and capable segmentation method is used for tumor detection and feature extraction of brain MRI images.
Youth, Luxury and the Willingness to Pay

The concept of luxury has existed for as long as the emergence of hierarchies in society, and has been in a constant state of flux ever since. At its inception it was characterised by exclusivity, superior quality and price. However, as it has evolved over time it has come to mean different things to different people, meaning that the motivation for consuming luxury products change from place to place and even between groups within the same society. A comprehensive review of the literature available on this topic revealed a gap; the motivation of undergraduate students for consuming luxury products still remains unclear. The aim of this study is to study undergraduate students in the United Kingdom and determine whether or not they are willing to pay premium prices for luxury products. This paper goes a step further and also examines their motivation for this behaviour. A qualitative inquiry was carried outon six respondents with the help of semi-structured interviews. This study concluded that students are in fact willing to pay premium prices for luxury, but only if they are satisfied that they were able to get the best deal. This research also reveals that undergraduate students in the United Kingdom are more interested in luxury items if they offer a previously absent convenience, therefore, are willing to pay a higher price for this expediency.A conceptual framework has also been proposed to aid luxury marketers in targeting undergraduate students.
An Automated Leucocyte Classification For Leukemia Detection

- Acute lymphoblastic leukemia is a form of blood cancer caused due to the abnormal increase in the production of immature white blood cells in the bone marrow, mostly affecting children below 5 years and adults above 50 years of age.Here a system is proposed to detect acute lymphoblastic leukemia from a standard dataset of ALLIDB1.Two methods were proposed for recognition of the disease based on the image processing techniques.First method is based on the traditional feature extraction method where the features like area,perimeter,major axis,minor axis and number of nucleus are extracted and given to the classifier for classification.In this method the images are subjected to segmentation by adaptive kmeans for extracting the nucleus before feature extraction.In the second method the images from the dataset is subjected to CNN based deep neural network.A comparative analysis of classification such as SVM(Support Vector Machine) and ANN(Artificial Neural Network) is done with features extracted from the first method.First method provides a recognition efficiency of 89.47% with SVM and 92.10% with ANN.CNN(Convolutional Neural Network) based feature extraction method provides recognition efficiency of 93%.
Performance Evaluation of BigData Analysis with Hadoop in Various Processing Systems

— In recent years BigData has become most popular area for research and development. In Business, Organizations need to focus towards their data-driven approach for gaining the competitive advantage. When more data is processing, interacting and integrating it provides meaningful data for making good decision. All this happened with the advent of advanced computational and storage system required for BigData [1] . On one side BigData help in giving a panoramic view on decision making, on other side it increases the performance complexity and expenditure of the process. This paper presents a study of data analysis using Hadoop on various capacities of systems. The data is being created through an algorithm and analysis is done in multiple systems to understand the limitations and constraints of systems. The experimental results helped in concluding that how the system performance can be affected using different memories & processors. The study could be further extrapolated to optimize the system performance by reducing the time complexity by controlling the RAM size in multiple systems.
IN-VITRO ANTIBACTERIAL AND ANTIOXIDANT ACTIVITY OF EMBLICA OFFICINALIS LEAVES EXTRACT

Emblica officinalis (Amla) has been considered the best of the ayurvedic rejuvenative herbs, because it is tridosaghna. The aim of the present study was to investigate antimicrobial and antioxidant activity of hydro-methanol (20:80) extract of leaves of Emblica officinalis (HMLEO). HMLEO was evaluated for its antimicrobial activity by using agar well diffusion method & their possible antioxidant assay by three complementary test systems, namely DPPH, hydrogen peroxide and reductive potential scavenging activity. The bacteria used in the study were Bacillus subtilis, Salmonella typhi, Klebsiella pneumonia, Pseudomonas aeruginosa, Staphylococcus aureus and Escherichia coli. The extract exhibited antibacterial activity with zone of inhibition ranging from 8.10 ± 0.65 to 23.37 ± 0.12 mm at different concentrations. Screening of crude extract showed notable minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) at concentrations of 12.50 to 50 and 200 to 300 mg/ml respectively. Crude extract showed maximum relative percentage inhibition against Escherichia coli (70.53 %) and lowest relative percentage inhibition against Salmonella typhi (33.58%). For antioxidant activity, DPPH & hydrogen peroxide scavenging activity, the IC50 value of extract was 45. 38μg/ml & 42. 87μg/m respectively. Preliminary phytochemical tests of hydro-methanolic extract of leaves of Emblica officinalis revealed the presence of flavonoids, terpenoids, tannins, and phenolic compounds. The organisms were sensitive to extract of the Emblica officinalis leaves, and could be considered as a potential source of natural antimicrobial and antioxidants.
A Study of the Relationship between Empowerment and Organizational Learning among Employees of Gas Transmission Company. J. Life Sci. Biomed. 4(6): 550-556

The present research investigated the relationship between empowerment and organizational learning among employees of Gas Transmission Company. The research was a correlational, descriptive field study. The research population included 240 tenure staff, out of whom 145 were sampled randomly. A questionnaire, based on Spritzer’s Psychological Empowerment questionnaire and Mishra's, was used, totalling to 18 items. For organizational learning, Niphe's questionnaire with 31 items was used. The reliability of instruments was approved by Cronbach’s alphas of %807 for empowerment and %796 for organizational learning. The results indicated that there was a significant relationship between empowerment and organizational learning (r=%481). Each dimensions of empowerment was significantly related, the highest (r=%578) belonging to the trust dimension.
Intelligent Vision Based Surveillance Framework for ATM Premises

: Automatic teller machine (ATM) is a service provided to carry out banking transactions and has become the necessity of everyday life. ATM’s enables access to the bank in order to make variety of transactions such as cash withdrawal, check balance or transfer money. However, besides facilitating the banking needs, the ATM’s lacks in providing the security against the several ATM frauds like money snatching and attacks on customers. In recent years there has been lot of work shown in the field of abnormal activity recognition in ATM surveillance to meet the security requirements. In this paper, we present a framework to detect the unusual activities practiced at the ATM installations. The proposed approach makes use of medial frames and combination of Zernike moments with gradient based descriptors to extract the relevant features from video. The features obtained are classified using Random forest classifier. The proposed method is successful in determining the normal and abnormal human activities with an average accuracy of 95.52%.