Miracle-dz/UniFAR-FTUs huggingface dataset:
Assembly Language Program Evolution in Tierra-based On-Board Computer through Single Event Upset

—This paper explores the feasibility of Tierra-based OBC that evolve programs through a bit inversion caused by single event upset (SEU) in spacecraft. In particular, Tierra-based OBC is applied to the evolution of an assembly language program in order to extend its application region. This paper also proposes a novel method that can recover a correct program even if all programs are broken in Tierra-based OBC. Intensive experiments that simulate the SEU environment reveal that (1) Tierra-based OBC cannot only maintain the assembly language program through SEU but also can evolve it, i.e., minimize its program size, (2) the proposed recover method improves the robustness of Tierra-based OBC to high SEU rate in comparison with Tierra-based OBC without it, and (3) Tierra-based OBC with the proposed recover method can reliably recover a correct program by modifying broken programs even if a correct program is lost due to SEU.
A Survey on Secure Anti Collusion Mechanism with Distributed Storage in Cloud Computing

: Benefited from cloud computing, users can do a good and economical approach for information sharing among cluster members within the cloud with the characters of low maintenance and tiny management value. Meanwhile, it should offer security guarantees for the sharing information files since they're outsourced. sadly, attributable to the frequent amendment of the membership, sharing information whereas providing privacy-preserving continues to be a difficult issue, particularly for AN untrusted cloud because of the collusion attack. [5] what is more, for existing schemes, the protection of key distribution is predicated on the secure line, however, to possess such channel may be a robust assumption and is troublesome for observe. During this paper propose a secure information sharing theme for dynamic members. Firstly, propose a secure method for key distribution with none secure communication channels, and therefore the users will firmly get their non-public keys from cluster manager. [6] Second, this theme can do fine-grained access management, any user within the cluster will use the supply within the cloud and revoked users cannot access the cloud once more when they're revoked. Thirdly, system will defend the theme from collusion attack, which implies that revoked users cannot get the initial record even though they conspire with the untrusted cloud. [1] During this approach, by leverage polynomial perform, it can do a secure user revocation theme.
Haematological and molecular characterization of sickle cell-β thalassemia in Dera Ismail Khan Division of Pakistan

Sickle cell-β thalassemia (HbS-β thalassemia) is an inherited erythrocyte disorder affecting multiple organs. It results from compound heterozygosity for sickle cell trait and β thalassemia trait. As individuals are living well into middle age due to advances in diagnosis and treatment, further disease-related complications are being recognized. The present study was undertaken to determine the genetic factors responsible for hematological and molecular variability of HbS-β thalassemia patients in Dera Ismail Khan (D.I.Khan), Pakistan. The current study was observed to analyse both molecular and haematological characterization of HbS-β thalassemia patients using Hb electrophoresis and allele specific primers through polymerase chain reaction to determine both  and βthalassemia, and restriction enzymes for characterization of -globin gene arrangement. A total of fifteen HbS-β thalassemia cases with variable clinical manifestations were investigated. Ten patients showed milder clinical presentation against five patients who had severe clinical manifestations. Six β thalassemia mutations were identified: IVS 1-5 (G>C), codon 8/9 (+G), codon 30 (G>C), Cap+1 (A>G), -88 (C>T) and Cd 41/42 (-TCTT). Codon 30 (G>C) and -88 (C>T) mutations were found only in Pashtoon ethnic group while Cap+1 (A>G) mutation was observed only in Balochi ethnic group. HbS homozygous in Pashtoon ethnic group is being observed for the first time. α thalassemia and XmnI polymorphism in homozygous condition (+/+) were found to be common among the milder cases. The βS chromosomes were linked to the typical Arab-Indian subcontinent haplotype. Saudi haplotype is mostly associated with HbS and haplotype III is associated only with Pashtoon ethnic group. The phenotypic expression of HbS-β thalassemia is not uniformly mild and α thalassemia and XmnI polymorphism in homozygous condition (+/+) are additional genetic factors modulating the severity of the disease in the Pakistan. [Jabbar KHAN, Nafees AHMED, Sami SIRAJ, Shahid Niaz KHAN, Hamid SHAFIQ. Haematological and molecular characterization of sickle cell-β thalassemia in Dera Ismail Khan Division of Pakistan. J Am Sci 2018;14(3):84-89]. ISSN 1545-1003 (print); ISSN 2375-7264 (online). http://www.jofamericanscience. org. 12. doi:10.7537/marsjas140318.12.
Comparative Analysis of Graph Database and a Relational Database

: Database can accommodate a very large number of users on an on-demand basis. The field of database technologies has undergone drastic changes. The advent of complex connected data has given rise to database technologies that diverge from the traditional relational databases (RDBMS). Graph-based database, which abstracts data in the form of nodes, edges and properties, is one such innovative idea for highly associative data. In this paper, we have described a graph database model based on the graph theory and a prototype implementation of the same. The prototype implementation has a complete set of insertion, selection and deletion graph queries and a cache for fast data processing and retrieval. RDBMSs are a major technology that stores large portions of structured data which rely on providing ad-hoc querying facilities by using Structured Query Language (SQL). Oracle, MS SQL Server, MS Access, MySQL as well as Sybase are examples of relational database management systems which are utilized to store, manipulate and retrieve data. In this paper we will do theoretical analysis of Graph base database and relational base database.
Optimization of CMOS based Analog Circuit Using Particle Swarm Optimization Algorithm

We know that the world is basically analog in nature so that design of CMOS analog circuits are very significant in electronic system design. Day by day design complexity of electronic circuit is increased. So that the optimization procedures should be automatic using great precision. The key problems concern with electronic design automation are robustness and cost. Usually, optimization is a very exciting and time consuming task with many conflicting benchmarks and a wide range of design parameters. In this graft Particle swarm optimization (PSO) is presented as an effective process to explore the search space and to handle constrained optimization difficulties. Effectiveness of PSO algorithm is tested with some standard benchmark function. PSO algorithm has been used for the optimum design of CMOS analog circuits with high optimization skill in small computational time. Parameters values obtained from PSO algorithm are verified using spice circuit simulator. In this work, C code of PSO algorithm has been interfaced with Ngspice circuit simulator for circuit optimization. In this effort different CMOS based analog circuits like CMOS triple cascode current mirror, CMOS voltage divider, CMOS cascode amplifier and CMOS differential amplifier with current mirror load are optimized using different CMOS technologies.
Breast Cancer Tumor Detection Using Ann Classification In Image Processing Application

: Breast cancer is the most common malignancy of women and is the second most common and leading cause of cancer deaths among them. At present, there are no effective ways to prevent breast cancer, because its cause is not yet fully known. Early detection is an effective way to diagnose and manage breast cancer can give a better chance of full recovery. This paper gives a clear idea of classification from the mammogram image to find cancer affected area which is a crucial step in breast cancer detection. The output of the classifier differentiates the normal, benign and malignant cases from applied digital mammographic images.
Studying yhe Effect of Nano Silver on Some Properties of Acrylonitrile Butadiene Styrene Copolymer for Medical Devices

Antibacterial polymeric composites were prepared to manufacture medical devices and seats for hospitals. These composites prepared by adding nano silver (Ag NPs) by three ratios (3, 6, and 9 wt %) to Acrylonitrile butadiene styrene (ABS) terpolymer. The antibacterial activity was investigated against S. aureus and Salmoulla microorganisms using Agar well Diffusion method. Results showed that these composites have antibacterial ability against both S. aureus and Salmoulla microorganisms. At low Ag NPs concentration, the activity against Salmoulla is higher than that against S. aureus microorganism. But at higher concentrations, the activity against Salmoulla will be less than that against S. aureus microorganism. The mechanical properties improved due to the new interactions between nano silver and ABS matrix. Ag NPs addition reduces the surface wettability, enhances self-cleaning tendency, decreases the surface roughness and the groove continuity, enhances the surface bearing index, reduces both the core roughness depth and core fluid retention and shifted the thermal transitions towards low temperatures.
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A major challenge for automatic speech recognition (ASR) relates to significant performance reduction in noisy environments. Recently, the study of the emotional content of speech signals got more importance and hence, many systems have been proposed to identify the emotional content of a spoken utterance. The important aspects of the design of a speech emotion recognition system are pre-processing, feature extraction, training and classification, recognition. Typically, extracted speaker features are short-time cepstral coefficients such as Mel-frequency cepstral coefficients (MFCCs) and perceptual linear predictive (PLP) coefficients, or long-term features such as prosody. Such systems usually do not perform well under noisy conditions because extracted features are distorted by noise, causing mismatched likelihood calculation. By introducing a novel speaker feature, gammatone frequency cepstral coefficient (GFCC), based on an auditory periphery model, and show that this feature captures speaker characteristics and performs substantially better than conventional speaker features under noisy conditions. An important finding in the study is that GFCC features outperform conventional MFCC features under noisy conditions.
FPGA Based Implementation of Edge and Corner Detection in MRI Brain Tumor Image

: This work presents a flexible feature detectors for image with reduced area, power and memory requirements, supporting a variable input resolution. It focuses on processing an image pixel by pixel and in modification of pixel neighborhoods and the transformation that can be applied to the whole image or only a partial region and identify sudden changes in an image. The proposed work is optimized for feature detection, more specifically, the Canny edge detector and the Harris corner detector. The detector contains neighborhood extractors and threshold operators that can be parameterized at runtime. We implement the feature detection on segmentation of brain tissue in the magnetic resonance imaging for detecting the existence and outlines of tumors. Furthermore, we present the proposed architecture implementation on an FPGA-based platform the results show a clear advantage of the proposed architecture in terms of power consumption and maintain a reliable performance with noisy images. FPGAs are increasingly used in modern imaging applications, image filtering and medical imaging.
ACE GENE INSERTION /DELETION GENOTYPES BASED EVALUATION OF RESPONSE TO ANTI-HYPERTENSIVE’S IN CASES OF ESSENTIAL HYPERTENSION AND T2DM WITH HYPERTENSION – A PHARMACOGENOMIC STUDY

The objective of present study was to investigate the pattern of response to anti-hypertensive in T2DM patients with hypertension and cases of essential hypertension having different ACE gene Insertion/ Deletion genotype. Blood samples from 45 cases of T2DM + hypertension and 40 cases belonging to essential hypertension (ET) were analyzed for ACE Insertion/deletion genotypes and correlated with response to anti-hypertensive’s being taken by these patients. Blood samples from 50 healthy individuals served as controls, for comparing frequencies of the three different genotypes. The frequencies of DD genotype were found to be significantly (P<0.05) increased in both the clinical groups (31% in T2DM + HTN and 35% in E.T cases) compared to control. Genotype based analysis of responses to anti-hypertensive’s revealed that 33.3% T2DM patients with hypertension having DD genotype responded to ACE inhibitors, while none in the essential hypertension group responded to ACE inhibitors. However, 77.7% ET patients with DD genotype responded to ARBS (either alone or in combination with calcium channel blockers/ Beta blockers). Interestingly the II genotype patients of both clinical groups responded in a comparable manner to ARBs (75% in ET and 80% in T2DM + HTN cases). In case of T2DM patients with ID genotype 72.2% responded to ARBs while only 57.14% cases in ET group Responded to ARBs either alone or in combination (P<0.05). Higher percentage of T2DM + HTN cases (II and ID genotypes) responded to ARBs than those in the essential hypertension group which may be attributed to higher rate of oxidative stress in T2DM + HTN cases.
Age Classification with Co-Occurrence Features on LBP Based Texton Matrix

: Age classification from facial images is increasingly receiving attention in computer vision applications. To address this classification problem, the present paper proposes a method, computes the local binary pattern on the image and Texton matrix on this LBP image is represented and then Co-occurrence features are evaluated. The age varying of persons is observed with these features. The proposed method is experimented on facial image datasets FG-Net and other scanned images. The experimental results indicate that proposed method outperforms with other existing methods.
Effect of stress on erythryocytic osmotic fragility in healthy individuals

Background: The aim of the study was to examine relationship between severity of stress and onset/completion of erythrocyte haemolysis in normal healthy individuals. Materials and Methods: The study was conducted in Physiology department, Deccan College of Medical Sciences, Hyderabad, after approval from the Institutional Review Board. The study included 50 healthy individuals of both the sexes aged between 20 to 50 years. Individuals working for minimum 8 to 10 hours a day were included and individuals suffering from hypertension, obesity, diabetes mellitus, musculo-skeletal disorders, sickle cell disease and goitre were excluded. Osmotic fragility was determined by collecting 2ml of blood from each individual and stored in EDTA tubes. A drop of blood was added to saline solutions of different tonicity arranged in 12 test tubes. The test tubes were seen for onset and end of hemolysis after an hour. Stress was measured by Cohen’s perceived stress questionnaire and individual were divided into 3 groups viz. low, moderate and high stress categories as per their scores. Results: Findings were analysed by student’s t-test and completion of hemolysis was earlier in severe stress group compared to mild and moderate. There is no significant difference between males and females regarding point of onset of hemolysis (p=0.41) and end of hemolysis (p=0.37). Stress increases fragility and it was found that RBC fragility was significantly related to severity of stress. Fragility is not affected by gender. Conclusion: RBC fragility was significantly related to severity of stress and it was found that fragility is not affected by gender.
Topic Mining for Time Stamped Text Document Using PLSA Method

- In the real-world applications, time stamped document or text sequences, are begin anywhere. Various text sequences are related to each other by sharing common topics. The correlation between these sequences provides more meaningful and complete clues for topic mining than those from each particular sequence. so it shows the interrelationship between the different documents with the existence of asynchronism. i
Knowledge Generation in Java API Reference Documentation

Application Program Interface (API) allows programmers to use predefined functions instead of writing them from scratch. Description of API elements that is Methods, Classes, Constructors etc. is provided through API Reference Documentation. Hence API Reference Documentation acts as a guide to user or developer to use API’s. This work focuses on Knowledge generation in the Java API Reference Documentation.
Content Based Classification of Audio Using MPEG-7 Features

— The segmentation plays important role in audio classification. The audio data can be divided into silent or non-silent segments. The non-silent segments or sub-clips are further classified into five types namely music, speech over music, pure speech, speech over environmental sound, and environmental sound. The rule based and model-based are the two types of approaches used in classification. There are various model-based methods such as Neural Network (NN), Hidden Markov Model (HMM), Support Vector Machine (SVM), and Gaussian Mixture Model (GMM) are used for classifying audio segments. In this paper, both HMM and SVM statistical models are used to classify audio segments. The MPEG-7 has four audio features namely Audio Spectrum Centroid (ASC), Audio Spectrum Spread (ASS), and Audio Spectrum Flatness (ASF), Audio Spectrum Projection (ASP).
INVESTIGATIONS ON THE INTRINSIC FREQUENCY OF THE CARDIAC CELLS IN EFFECTING SYNCHRONIZATION

Biological rhythms, like the cardiac rhythm are often generated by large populations of mutually interacting cellular oscillators. The ability of such a population to generate a stable, regulated rhythm depends critically on the nature of interactions among the oscillators, as a network of nonlinear oscillators is intrinsically unstable. Although the entire cardiac system beats in perfect synchronization invivo, intrinsic frequencies of auto rhythmic cells have a significant dispersion. The sinoatrial node is a thin sheet of cardiac muscle fibers composed of several hundred thousand cells, each of which is an electrical oscillator. Studies of cells isolated enzymatically from the sino atrial node indicate that the intrinsic frequency of oscillation for each cell is different. Despite these differences, a coherent oscillatory electrical wave known as the pacemaker potential is generated within the node. This wave is conducted throughout the heart, determining its rate of beating. The pace making cells in the Rabbit heart beat at a wide range of frequencies (80-330 beats per minute) in culture, but within the heart they beat at a common frequency set by the normal sinus rhythm. As a result the synchronization within the heart becomes extremely difficult with such a wide range of intrinsic frequencies. The adjustment of rhythms due to an interaction is the essence of synchronization, the term originating from the Greek words chronos meaning time and syn meaning the same, common. This work attempts to explore the issues in the much desired synchronization within the rabbit heart with a valid electro physiological model of cardiac pacemaker cells in the cardiac system. For the species Rabbit, a matlab code for sinoatrial node cell was developed and the simulated results were validated against the prevailing experimental data. The existence of a free parameter that can influence the intrinsic frequency of the so generated action potential was investigated that resembled Gap Junction conductance in real electrophysiology. The functional role of the gap junctions in effecting the much desired synchronization issues with the aid of variations in the intrinsic frequency of the cell within the cardiac system was elucidated and the results indicated that the intrinsic frequency of the cells varied only for a limited range of adjustment. An external neural input was effected via integrate and fire neuron model that further coaxed the cells to oscillate at varied intrinsic frequencies that ascertained the fact that neural influence is much essential to enhance synchronization. This paper investigates with the aid of the simulation results, that the external neural input can also play a part in influencing the intrinsic frequency of the cardiac cells thereby effecting synchronization.
Model Reference Adaptive System (MRAS) Based Speed Sensorless Vector Control of Induction Motor Drive

This paper presents a Model Reference Adaptive System (MRAS) based speed sensorless estimation of vector controlled Induction Motor Drive. MRAS based techniques are one of the best methods to estimate the rotor speed due to its performance and straightforward stability approach. Depending on the type of tuning signal driving the adaptation mechanism, MRAS estimators are classified into rotor flux based MRAS, back e.m. f based MRAS, reactive power based MRAS and artificial neural network based MRAS. In this paper, the performance of the rotor flux based MRAS for estimating the rotor speed was studied. Overview on the IM mathematical model is briefly summarized to establish a physical basis for the sensorless scheme used. Further, the theoretical basis of indirect field oriented vector control is explained in detail and it is implemented in MATLAB/SIMULINK.
Clustering Algorithm for Text Classification Using Fuzzy Logic

Feature clustering is a powerful method to reduce the dimensionality of feature vectors for text classification. We propose a fuzzy similarity-based self-constructing algorithm for feature clustering. The words in the feature vector of a document set are grouped into clusters, based on similarity test. Words that are similar to each other are grouped into the same cluster. Each cluster is characterized by a membership function with statistical mean and deviation. When all the words have been fed in, a desired number of clusters are formed automatically. We then have one extracted feature for each cluster. The extracted feature, corresponding to a cluster, is a weighted combination of the words contained in the cluster. By this algorithm, the derived membership functions match closely with and describe properly the real distribution of the training data. Besides, the user need not specify the number of extracted features in advance, and trial-and-error for determining the appropriate number of extracted features can then be avoided. Experimental results show that our method can run faster and obtain better extracted features than other methods. Indexing terms: fuzzy, training data, cluster, membership function
The effects of eye masks and earplugs on the sleep quality and anxiety of hospitalized patients-a randomised controlled trial

Introduction Sleep is essential for people to stay in good health and for the prevention of disease [1,2]. Motivation, culture, lifestyle, dietary habits, alcohol intake, caffeinated beverages, smoking, environmental factors, psychological stress, illness, and medications are some of the factors which can affect the quantity of sleep [2,3]. Sleep deprivation is common in individuals with acute and chronic illnesses [4]. At times of illness, the need for sleep increases [1], and sleep promotion is important for recovery [1,5-7].