Miracle-dz/UniFAR-FTUs huggingface dataset:
Protective role of Ellagic acid in modulating Iron induced Nephrotoxicity in rats

Iron (Fe) is an environmental and industrial pollutant that affects various organs in human and animals. A body of evidence implicates that the free radical generation with subsequent oxidative stressis involved in the mechanism of Fe toxicity. Since the kidney is critical target of Fe toxicity we carried out this study to investigate the effect of Ellagic acid (EA), a polyphenolic compound on renal injury induced by Fe. In this study, Fe (30mg/kg body weight was administered intraperitoneally for 10 days to induce toxicity. EA was administered orally (15, 30 and 60mg/kg body weight) for 10days along with Fe. Fe induced renal damage was indicated by the increased activities of serum urea and creatinine along with reduced renal clearance. A significant increase in lipid peroxidation markers (TBARS and lipid hydroperoxide) was observed in kidney of Fe treated rats. Rats subjected to Fe toxicity also showed a decline in the levels of reduced glutathione (GSH), vitamin C and vitamin E together with significantly decreased levels of enzymic antioxidants superoxide dismutase (SOD), catalase (CAT) and glutathione peroxidase (GPX). Administration of EA at 60 mg/kg body weight attenuated the Fe induced nephrotoxicity indicated by significantly decreased levels of serum urea and creatinine with normalization of creatinine clearance. On administration of EA, the depleted renal antioxidant defense system (enzymatic and non enzymatic antioxidants) was significantly increased in Fe treated rats. The biochemical observations were supplemented by histopathological examination of kidney section. Our results suggest that supplementation of EA might be helpful to alleviate the Fe induced oxidative injury in kidney.
Security Improvement on Balise-Based Train Control System

: Balise remains the most crucial component of the Train Control System (TCS) due to its significant importance to the safety and control of High-Speed Railways (HSR) through its data storage and signal transmissions. Nonetheless, little focus is given to the security of this stored data as well as the signal transmission protocol. This makes it vulnerable to a variety of attacks such as faking of telegram data, impersonation of BTM to collect telegram data, data replay, displacement attack, etc. In this paper, we improve the Balise security by employing the Deoxys-II algorithm which is a nonce-based symmetric AE scheme. It is known for its effective and efficient prevention of faking and replaying of balise telegrams. Deoxys-II security is guaranteed in aspect of its compliance to nonce misuse resistance property of AE. Conducted experiments show the security improvement of the baliseand devoid of any deficiencies of tampering, faking or replaying the telegram again. In addition, real-time test comparison with other existing algorithms depict that our scheme gives the shortest latency from the time spent at the track side encryption of the plaintext to the decryption part at the on-board unit of the train.
Area efficient FPGA based LDPC decoder using Stochastic decoding scheme

: This paper demonstrates the FPGA implementation of area efficient LDPC decoder using stochastic decoding scheme . Error correcting codes in communication systems are of high importance to achieve stability in wireless communication system. This paper presents the overview of designing an area efficient LDPC decoding architecture using stochastic decoding scheme. The Implementation results of fully parallel LDPC decoder displays 1% of slice using Xilinx vertex-4, 4vfx12sf363-10 device. The implementation of decoder architecture using stochastic decoding algorithm has reduced the number of slices required thereby reducing reducing the number of resources used and thus increasing the area efficiency of the decoder. The decoding scheme has also reduced the interconnect complexity of decoder architecture.
On the Kinematics of Hyper Redundant Mobile Robot

The kinematics of any ‘n’ DOF hyper redundant mobile robot of interconnected links is considered for this analysis. The kinematic configuration facilitates to find out the joint parameter. Precise calculations decide the closeness of the actual consideration of every kinematic configuration. Only the centre line of the robot is considered for this analysis. The existence of acceptable free space conform the alignment chord, termed as backbone curve, which resemble the chain of interconnected links. The kinematics of the robot in free space is defined by the Denavit and Hertenberg principle. In our analysis each link has two joints and all the joints have the ability to pass through the backbone curve. To find the existence of each joint on the backbone curve we construct a Cardinal Spline in between two consecutive path points on the backbone curve and on this spline a large number of points are constructed. We use error minimization strategy to evaluate the position of all the joints except the frontal one which is the end of the virtual link and its position is obtained by the path points. Each pair of joints results the pose information of that segment. The proposed algorithm is validated through computer simulation.
QUAGGA ROUTING PLATFORM: APPLICATION AND PERFORMANCE

: Quagga is an open-source software platform that provides routing services. It supports the following IP routing protocols: RIPv1, RIPv2, RIPng, OSPFv2, OSPFv3, IS-IS, BGP4 and BGP4+. Quagga is unique in its design because it uses a separate process for each running protocol. This platform offers true modularity since each protocol module can be upgraded or configured independently of the others. In order to illustrate its capabilities, this paper investigates support of this platform for RIP and OSPF, two most commonly used routing protocols on the Internet. In addition, the results of convergence time measurements are presented. Considering that software defined networking (SDN) promise to be Future Internet platform, brief description of possible application scenario for Quagga in SDN networks is provided.
A Fuzzification Approach for Prediction of Heart Disease

:Data Mining operations and approaches are the improvement over the statistical methods that enables a user to perform the future analysis based on current dataset. One of such analysis provided by data mining approaches is the predication based analysis. In this present work, the heart disease prediction system is designed. The heart disease prediction is actually an expert system application which requires the authenticated dataset to process. A Fuzzy based soft computing approach is been implemented on multiple parameters to predict the heart disease. In this paper, the earlier work done in the area of medical disease prediction is studied as well a new fuzzy rule based approach is suggested to perform the heart disease prediction.
TEACHERS’ ROLES ON ENGLISH LANGUAGE TEACHING: A STUDENTS CENTERED LEARNING APPROACH

This study is about teachers’ roles on english language teaching viewed from the perspective of students centered learning approach, and it is aimed at investigating the teachers’ roles in teaching the language to the students based on students centered learning activity and enlarging the knowledge of the language teachers’ roles in teaching in order to help them to be more professional in their field. The method of the study used in this study was a library research study, where theories from any sources that related to the theory used in this study, were used to provide the answers of the problem of this study. The instruments of this study were books and documents. The results of this study indicated that there are some roles that must be possessed by the teacher during language teaching, such as: an organizer, an assessor, a prompter, a participant, a resource, a tutor, an observer, a performer, a controller and as teaching aid. It can be concluded that in order to succeed the language teaching based on students centered learning approach, a teacher should implement those roles.
Investigation on Wideband E-Shaped Microstrip Patch Antenna with Dielectric Superstrate

This paper describes the effect of the superstrates on bandwidth and gain of E-shaped microstrip patch ante na without superstrate and loaded with dielectric supers trates. It is found that there is a degradation in the performanc e of the antenna when the superstrate is touching the patch a ntenna i.e its height above the patch antenna (H) =0 mm. Further, it is also observed that the degraded performance characterist ics of the patch antenna can be improved by placing the supers trates at optimum height (H) =Hopt. The microstrip patch antenna without dielectric superstrate has an impedance bandwidth of 0.17GHz (SWR 2) at 2.04 GHz, gain is 8.67 dB and return-loss is -19.95 dB. When the superstrate is placed touching the pat ch antenna, the resonant frequency is reduced to 1.59 GHz from 2.04 GHz and bandwidth is reduced 0.15 GHz (SWR ≤ 2) at 1.59 GHz, gain is decreased by about 0.92% (0.08 dB) for Ԑr= 2.2 to 39.5% (3.47 dB) for Ԑr= 10.2. As the height of the superstrate is increase d, the performance of the patch antenna improves and at a p rticular optimum height the gain for all the superstrates wil l be closer to the free space radiation conditions of the patch an te na without superstate. But the resonant frequency decreases with increase in Ԑr2. The variation in the return-loss for H = Hopt. is within ± 1.5 dB of the free space radiation condition for all the d ielectric constant of the superstrate and it is within acceptable limit s. The bandwidth improves (12%) for Ԑr2 up to 4.8. However, the bandwidth decreases for Ԑr2= 10.2. There is a good agreement between simulated and measured results.
Privacy Protected Personalized Web Search using Cache Model

 Abstract - The web search engine has long become the most important portal for ordinary people looking for useful information on the web. However, users might experience failure when search engines return irrelevant results that do not meet their real intentions. Such irrelevance is largely due to the enormous variety of users’ contexts and backgrounds, as well as the ambiguity of texts. Personalized web search (PWS) is a general category of search techniques aiming at providing better search results, which are tailored for individual user needs. As the expense, user information has to be collected and analyzed to figure out the user intention behind the issued query. Personalized web search (PWS) has demonstrated its effectiveness in improving the quality of various search services on the Internet. However, evidences show that users’ reluctance to disclose their private information during search has become a major barrier for the wide proliferation of PWS. This research studies privacy protection in PWS applications that model user preferences as hierarchical user profiles. This project proposes a PWS framework called UPS that can adaptively generalize profiles by queries while respecting user-specified privacy requirements. The proposed runtime generalization aims at striking a balance between two predictive metrics that evaluate the utility of personalization and the privacy risk of exposing the generalized profile. The study presents two greedy algorithms, namely Greedy DP and Greedy IL, for runtime generalization. It also provides an online prediction mechanism for deciding whether personalizing a query is beneficial.
Reinforcement Learning Framework for Energy Efficient Wireless Sensor Networks

- In recent years, there has been an increasing interest in Wireless Sensor Networks. Sensor nodes in Wireless Sensor Networks are energy constrained. Therefore, in WSNs one of the major design challenges is to minimize consumed energy at the sensor nodes. Hence, a number of routing schemes are designed that make efficient use of limited energy of the sensor nodes. Hierarchical routing protocols are best known in regard to energy efficiency. Our first aim is an implement of routing strategies using Q-routing algorithms and compared them for the energy efficient aspects. Our second step is to develop an energy efficient shortest path Q-routing algorithm using Reinforcement Learning property of ML techniques and compared it with an existing energy aware Q-routing algorithm. We have applied these algorithms on different topologies like heterogeneous, homogeneous and introduced a novel hybrid topology by combining heterogeneous and homogeneous topologies.
Performance Measurement of Refinding Queries in Context Based Search

: In this paper we are measuring the performance of refinding queries that contains the information retrieval for Personal Information Management System. When user needs the already searched web pages repeatedly then this search engine provides the user interface for saving the title and the web page URL for reference . In this keyword and related web pages are stored we can refind needed. Also search engine contains the association and clustering of context instances.
A Review of Literature On Image Inpainting And Super Resolution

 Abstract — Inpainting is the process of reconstructing lost or deteriorated part of images based on the background information. i. e. image Inpainting fills the missing or damaged region in an image utilizing spatial information of its neighboring region. Inpainting algorithm have numerous applications. It is helpfully used for restoration of old films and object removal in digital photographs. Super resolution reconstruction produces high resolution image from sequence of low resolution images. The main aim of super resolution is to improve visual quality of available low resolution image. Also existing Low Resolution (LR) imaging can be utilized with help of super resolution reconstruction. Super resolution based inpainting consists in performing first the inpainting on a coarse version of the input image. A hierarchical super-resolution algorithm is then used to recover details on the missing areas. The advantage of this approach is that it is easier to inpaint low-resolution pictures than high-resolution ones. The gain is both in terms of computational complexity and visual quality.
Optimization of Fuzzy C Means with Darwinian Particle Swarm Optimization on MRI Image

— Image segmentation is one of the most important and most difficult low-level image analysis tasks. Automatic target recognition (ATR) often uses segmentation to separate the desired target from the background . Fuzzy c-means (FCM) algorithm is one of the most popular fuzzy clustering techniques because it is efficient, and easy to implement. Fuzzy clustering is a main problem which is the subject of dynamic research in several real world applications. However, FCM is sensitive to initialization and is easily trapped in local optima. In this paper, DPSO is used to escape from local optima and to determine the global optima which are calculated on comparing with single swarm and similar set of swarms, operating on the test problem obtained for PSO
Implementation of Password Guessing Resistant Protocol (PGRP) to Prevent Online Attacks

-The inadequacy of login protocols designed to address large scale online dictionary attacks (e.g., from a botnet of hundreds of thousands of nodes). Brute force and dictionary attacks on password-only remote login services are now widespread and emerging technique. Convenient login for legitimate users while preventing such attacks is a difficult problem. Automated Turing Tests (ATTs) continue to be an effective, easy-to-deploy approach to identify automated malicious login attempts with reasonable cost of inconvenience to users. In this paper, we propose a protocol called Password Guessing Resistant Protocol (PGRP), derived upon revisiting recent proposals designed to avoid such attacks. In PGRP limits the total number of login attempts from unknown remote users to as low as a single attempt per username, the users in most cases (e.g., when attempts are made from known, frequently-used machines) can make multiple failed login attempts before being challenged with an ATT. We evaluate the performance of PGRP with two real-world data sets and find out more than the existing proposals.
EFFECT OF BIOCHAR, FARMYARD MANURE AND NITROGEN FERTILIZER ON AVAILABILITY OF PLANT NUTRIENTS IN SINANA DISTRICT, SOUTH EASTERN OROMIA, ETHIOPIA

Integrated soil fertility management could be a useful tool to maintain, preserving and improving soil fertility. Therefore, the experiment was conducted with the objective to investigate the influence of biochar, farmyard manure, and mineral nitrogen fertilizer on selected soil properties. The treatments consisted of two levels of farmyard manure (0 and 6 tons ha-1), three levels of biochar (0, 5, and 10 tons ha-1) and three levels of nitrogen (0, 23 and 46 kg N ha-1). The results revealed that the interaction effects of biochar, farmyard manure, and mineral nitrogen fertilizer significantly influenced the soil properties of major contents of soil available potassium, phosphorus, and nitrate and ammonium ion after two months of treatments application. The interaction effect of biochar, farmyard manure and nitrogen levels and that of farmyard manure and nitrogen levels as well as farmyard manure and biochar levels on cation exchange capacity and total nitrogen were significant (P < 0.05). Generally, the availability of plant nutrients concentration in the soil solution after two months of farmyard manure and biochar application was higher than that of a post-harvest.
Self-Esteem and Personality Traits as Predictors of Mental Well Being

Mental Well-Being is an integral part of good mental health and indicator of the ability of the individuals to cope up with daily stresses and work productively. Many predisposed and acquired factors influence the Mental Well-Being of an individual. The present study investigated the SelfEsteem and Personality traits as the predictors of mental well being. The results indicated that Neuroticism, Extraversion and Openness to experience came out as significant predictors of Mental Well-Being.
The Role of Regional Autonomy in Poverty Reducing in Kediri City, East Java - Indonesia

Regional autonomy provides excellent dedication to poverty reducing, especially to realize equity and distribution justice for the poor. As one of the pilot areas, the City of Kediri received much appreciation from the government because of their strategic programs in poverty alleviation. Not without reason, poverty alleviation is an annual agenda of the Indonesian government that continues to experience ups and downs, especially in the face of inflation that is increasingly clear in plain sight. The role of regional autonomy is one of the government's efforts to encourage progress and gain the potential of existing resources, especially productive people and natural resources. The research was conducted based on a literature study to reveal the role of regional autonomy in Kediri City. As an autonomous region that has a variety of potential resources and is able to reduce poverty levels in the region, it will be quite interesting to know the role of local governments in poverty reducing. The results of the study mentioned that the efforts of local governments have a positive role in poverty alleviation through various excellent programs and cooperation of all related parties.
Multiple Sclerosis Lesions Identification Technique

In this paper a new effective diagnosis method is introduced to identify the Multiple Sclerosis (MS) lesions in Brain tissues. The method involves the implementation a number of digital image processing techniques. First, removing the skull bones (i.e. extracting the brain tissues) by converting the MRI image into a binary format (utilizing threshold value), determining a seed point at the center of the binary image (i.e. representing the middle of coordinates), then proceed from the seed point radially and stop at the borders of the brain material (zero) values. Isolating the brain substance is performed by multiplying the retained binary patches (having values one) by the original image. Image edge detection (based on convolution with Laplacian-Gaussian operator) is then performed to identify the single pixel and closed borders of the brain materials (including the lesion areas). The lesions areas can then identified by determining a seed point for each unexpected small contour areas within brain tissue, and moving radially from these seeds (outward) to the delineated border of each lesion.
Carbon Nanotubes, its Synthesis and Applications: A Review

The Carbon Nanotubes (CNTs) are versatile materials for the development of biosensors because these have many unique physical, optical, electrical and mechanical properties. These properties of CNTs change with a slight change in Surface to Volume Ratio. So, we can exploit these properties in such a way that CNTs can be used in a wide range of applications ranging from drug delivery to water purification and many healthcare applications. In the recent times, CNTs have allured the attentions of Academicians, Researchers and also Industries due to its wide range of applications. But still there is not a single commercial product based on Carbon Nanotubes due to certain challenges. This paper provides the review of the recent vigorous researches done in the field of Biosensors based on Carbon Nanotubes Keywords— Biosensors, SWCNTs, MWCNTs, Carbon Nanotubes, Functionalization.
(MWCNT) loading, Spin coating speed and Ultrasonication time for enhancement in β phase crystal content of Polyvinylidene fluoride (PVDF) /MWCNT thin films using Taguchi L9 array technique. The thin films were synthesized by spin coating technique and were characterized byFourier

2086 ISSN: 2278 – 7798 All Rights Reserved © 2014 IJSETR  AbstractThe purpose of this research work was to optimize the process parameterslike Multi Walled Carbon Nanotube (MWCNT) loading, Spin coating speed and Ultrasonication time for enhancement in β phase crystal content of Polyvinylidene fluoride (PVDF) /MWCNT thin films using Taguchi L9 array technique. The thin films were synthesized by spin coating technique and were characterized byFourier transform infrared(FTIR), X-Ray Diffraction (XRD), Scanning electron microscope (SEM) techniques. Maximum of 82.04% of β crystals were formed in specimen S3 (0.1wt. %, 1000rpm, 90min). Analysis of Variance (ANOVA) &Response Surface Methodology(RSM)weredone using Minitab V16 to optimize the process parameters.
A Pedestrian Detection Method Based on Active Basis Model

Pedestrian detection from video sequences is still a challenging problem. In this paper, we mainly use active basis model which consists of a small number of Gabor wavelet elements at selected locations and orientations to detect pedestrian. In order to enhance the detection rate, we propose an adaptive background modeling method for background subtraction method to detect objects in video sequence which emphasize background and remove foreground using mask technology. After acquiring many pedestrian templates of different poses and orientations, active basis model can be applied in pose estimation and human action analysis. The detection results indicate that our approach is capable of obtaining better detecting effects and pose estimation even under conditions of noise and illumination changes.