Miracle-dz/UniFAR-FTUs huggingface dataset:
Designing and Performance Evaluation of Advanced Hybrid OFDM System Using MMSE and SIC Method

: A Multiple inputs multiple output (MIMO) systems in wireless communication is referred as a wireless communication system where more than one antenna is used at both sides of the communication path i.e. Transmitter side and Receiver side. The communication systems, which utilizing multiple transmit and multiple receive antennas are commonly known as multiple input multiple output (MIMO) systems. The coverage area and the transmission capacity of a wireless communication system can be improved by using this wireless networking technology. In digital signal processing, the processing algorithms for interference suppression are becoming more and more complex with more than one antenna at both ends of the transmission channel. Also, the growing demand for these networks has turned the frequency spectrum into a precious resource. For this reason, there is a strong need of a method which can pack more and more bits/Hz. Such a system is called multiple-input multiple-output (MIMO) system. The uplink coverage and capacity of OFDM systems with the conventional multi user detector receiver are interference limited. Particularly, during the roll–out phase, the coverage of OFDM system is uplink limited. A cheaper solution to improve the overall performance is using serial interference cancellation (SIC) at the base station. In this research work, a new hybrid (MMSE+SIC) receiver structure for interference cancellation for multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems is proposed. Also, a general minimum mean square error (MMSE) channel estimation algorithm is given for multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems in spatially correlated multipath fading channels. The proposed method not only increases the capacity of system but also low down the Bit error rate. It can make full use of the channel correlations in space, time, and frequency to estimate the channel state information for various systems, including pilot-symbol assisted systems, pilot-embedded systems, and blind systems. MATLAB R2013a has been used to evaluate the performance of proposed algorithm using wireless communication toolbox and general MATLAB toolbox. The performance of the proposed method and existing method is measured using BER.
AN OVERVIEW OF FUZZY DATABASE MODELLING USING LOGICAL DATABASE MODELS

: Imperfect, incomplete, ambiguity, uncertain, imprecision, inconsistence and vague data present in the database is handled by fuzzy logic. Fuzzy database models are used to deal with such data. In this paper a number of logical database models that are used to deal with uncertain data are presented. Logical database model is of two types: relational database models and object-oriented database models. Some more data models that deals with uncertain and imprecision data is also presented in this paper.
Design and Analysis of Ashok Leyland Chassis Frame Under 25 Ton Loading Condition

ABSTRACT: The present scenario in automotive industry is an sum in demand of trucks not only on the cost and heaviness aspects but too on improved total vehicle features and overall work performance. The chassis plays an important role in the design of any truck. Truck chassis forms the structural backbone of a commercial vehicle. The main function of the truck chassis is to support the components and payload placed upon it. When the truck travels along the road, the chassis is subjected to vibration induced by road roughness and excitation by vibrating components mounted on it. The responses of the truck chassis which include the stress distribution and displacement under various loading condition are also observed. The mode shape results determine the suitable mounting locations of components like engine and suspension system. Some modifications are also suggested to reduce the vibration and to improve the strength of the truck chassis.The chassis design in general is a complex methodology and to reach at a solution which yields a good performance is a tedious task. Since the chassis has a complex geometry and loading patterns, there is no well defined analytical procedure to analyze the chassis. So the numerical route of analysis is adopted, in which Finite Element Technique is most widely used route.
A Device to Measure the Internal Resistance of an Automobile Battery

Battery and battery parameters are very important as far as the automobiles are concerned. Automotive batteries are designed to give high current especially at the time of starting of the engine. Battery parameters like State of Charge (SOC) and State of Health (SOH) are crucial for proper functioning of the vehicle. Internal resistance of the battery at a particular temperature is yet another important parameter for a battery. In this paper, a new device is discussed which calculates the battery internal resistance in a very small interval of time. It is designed as a handheld device and no external power supply is needed for the operation. All the power needed for the operation of device is derived from the battery to be tested. It works on the principle of two pulse discharge method. The battery receives a brief discharge lasting for few milliseconds. The test results conducted in Lead Acid batteries are found to be accurate and repeatable. The response time of the device is less than 100ms.
SVM and HMM Based Hybrid Approach of Sentiment Analysis for Teacher Feedback Assessment

: Sentiment analysis view from broad range of field of natural language processing and opinion mining. Most of the researcher focus on the product and services. This paper design to automate teacher feedback assessment system. As know, teacher is important part of education. Therefor progress and performance monitoring of teacher is also important factor of education system. It could be measure by taking feedback from student for particular teacher. Data collect from student is larger in size to concluding result is difficult task. Here, sentiment analysis play the role with help of HMM and SVM base hybrid sentiment classification model with advent feature extraction method.
The Influence of Autocorrelated Errors on the Bias of Multilevel Time Series Parameter Estimates

The validity of inferences drawn from statistical test results depends on how well data meet associated assumptions. In a two-level multilevel time series model, the standard assumption that the within-individual (level-1) residuals are uncorrelated are rarely checked ornbsp little information tends to be reported on whether the data satisfy the assumption underlying the statistical techniques used. Using a simulation approach, the consequences of violating the level-1 independence of observations assumption on the parameter estimates of fixed effects and the associate errors due to bias was investigated. It was found that bias which is generally high, increases with increase autocorrelated errors, and Full maximum likelihood (FML) estimates are more biased than Restricted maximum likelihood (REML) estimates.
Scene Labeling using H-LSTM by Predicting the Pixels using Various Functions

Scene Labeling plays an important role in Scene understanding in which the pixels are classified and grouped together to form a label of an image. For this concept, so many neural networks are applied and they produce fine results. Without any preprocessing methods, the system works very well compared to methods which are using preprocessing and some graphical models. Here the neural network used to extract the features is Hierarchical LSTM method, which already gives greater result in Scene parsing in the existing method. In order to reduce the computation time and increase the Pixel accuracy HLSTM is used with Makecform and Softmax functions were applied. The color transformation is applied using the Makecform function. The color enhancement of images has given object as input to H-LSTM function to identify the objects based on the referential shape and color. H-LSTM constructs the neural network by taking the reference pattern and the corresponding label as input. The pixels present in the neighbourhood identified with the help of neural network. In this method, the color image is converted into greyscale and then the Hierarchical LSTM method is applied. Therefore, this method gives greater results when it is implemented in Matlab tool, based on pixel accuracy and computation time when compared to other methods.
Automated Functional Test Case Prioritization For Increased Rate of Fault Detection

Testing plays important role in Software Development Life Cycle. Test Case Prioritization explains how the Test Cases are executed in particular order to achieve certain goals specified by the clients. In previous Fine Grained technique is used to prioritize the test cases. This process is done in random order, due to this Fault Detection Rate is going to be decreased. Our main aim is to increase the fault detection rate, then only we can rectify errors as many as possible which leads to fast delivery of project. Here prioritization process is going to be done between Test cases. Due to this there is no proper order of execution among the test cases, that which test case should execute first. In this paper we are going to use Coarse Grained technique based on Functional coverage to perform prioritization among the test suites rather than test cases. Test suite is the collection of the test cases that are dependent on each other. We are focusing on Functional test suites which means how much extent the test suites are dependent on each other. In previous some authors performed prioritization technique on real time systems and they generated Datasets for those systems. We are going to use those Datasets as reference to our project and we are calculating DSP volume, DSP Height and APFD. With this output we can identify that which test suite should execute first and we can also reduce the repeated execution of test suites.
EVALUATION OF TOXICOLOGICAL PROFILE OF KOJU

Increased morbidity and mortality associated with the use of herbs/ herbal products has raised universal attention in the last few years, making the safety and toxicity evaluations of these preparations imperative. This study evaluated the toxicological profile of Koju ® (KPF) a common Nigerian polyherbal formulation developed from Xylopia aethiopica (root bark), Securidaca longepedunculata (stem bark), Magnifera indica (stem bark), Allium sativum (seed), Citrus aurantifolia (root bark), Morinda lucida (seed) and Saccharum officinarum. Acute oral toxicity (LD50) was carried out in albino rats according to Lorke’s method while sub-chronic toxicity study was carried out with 24 adult albino rats which were divided into 4 groups of 6 animals each. Group one served as control and received normal saline while Groups 2 to 4 received 500, 1000 and 2000 mg/kg KPF respectively for 30 days. Food/ water intake and body weight of the rats were monitored while on day 31, the rats were sacrificed and blood samples and organs were collected for biochemical /hematological analysis and histopathological examination respectively. Results showed that KPF is safe up to 5000 mg/kg following acute oral toxicity test. The sub-chronic toxicity test revealed that KPF had no significant effects on the biochemical, hematological and histopathological parameters. However, the body weight of the animals significantly increased. It was concluded that KPF is safe but despite its safety in few animals, clinical trials and more investigations on a large number of animals are essentially needed to establish safety and efficacy of the herbal formulation.
A Parametric Model Measuring Time- Varying Respiratory Mechanics

A model is a precise representation of a system's dynamics used to answer the questions via analysis. The work present here is to provide a method for identification of the changes in human respiratory system in order to allow for an instantaneous diagnosis. The present work provides a methodology for auto regressive exogenous (ARX) modelling of human respiratory system. The proper model structure and model parameters are determine for the human respiratory system. Estimated model parameters will reflect the dynamic changes in respiratory system so the differences between normal and disease person can be detected using this model. The results are promising and models obtained for physiological system are able to describe the difference between the normal patient and disease patent by the diagnosis of change in the model parameters.
Relationship of Seminal Plasma Protein with Semen Characteristics of Murrah Buffalo Bulls

Artificial insemination in cattle and buffalo is the common practice; and to keep the success at high, the quality of the semen must be good. Though efforts have been given by using different extenders to improve keeping qualities of frozen semen, still success is not satisfactory. Seminal plasma, which is a complex mixture of secretions from testis, epididymis and accessory glands, contains factors that modulate the fertilizing ability of sperm (Henalut et al, 1995). Bovine seminal plasma contains a family of major proteins, designated BSP-A1/-A2 and BSP-A3, with apparent molecular masses ranging from 15 to 17 kDa, and the BSP-30 kDa protein with molecular mass of 28–30 kDa, collectively called BSP proteins (Manjunath, 1984). The biological properties of BSP proteins have been extensively studied and it have been indicated that seminal plasma proteins reverts the cold-shock damage on ram sperm membrane (Jobim et al, 2004).
A New Approach of Feature Extraction using Genetic Algorithm and SIFT

Extraction is a process of extracting the point from the image such that the image can be compared and recognized easily and quickly. Since various feature extraction techniques are implemented so that it can be used for variety of applications such as face recognition. The existing technique implemented for the extraction of features such as SIFT, SURF are efficient in terms of accuracy of number of features extraction but can't extracted all features from different types of images. Hence an efficient technique is implemented here for the efficient features extracted from images using combinatorial method of optimizing SIFT features extraction technique so that more number of features can be extracted. KeywordsGenetic Algorithm, SURF, HFE, SVM.
In vitro study of meropenem and colistin combination against multidrug resistant clinical isolates from patients with burns

Background: Nosocomial infections are known in patients treated at tertiary care hospitals. However this acquires significance as some of these are resistant to most of the major categories of antibiotics. Treatment of such infections become more challenging while treating patients in burn wards. There is a pressing requirement to evaluate combinations of some of the available antibiotics to treat these nosocomial infections in burns patients. No study evaluating combination of meropenem and colistin on clinical isolates of burns patients in a tertiary care hospital is available. Objective: To evaluate synergistic effect of meropenem and colistin antibiotic combination on common multidrug resistant bacteria isolated from the burn ward patients. Methods: A total of 46 strains of multidrug resistant bacteria which included 23 strains each of P. aeruginosa and Acinetobacter baumannii were tested forin-vitro synergistic effect of meropenem and colistin combination. MIC and FIC index was calculated for all the bacterial isolates. Result: 18 out of 23 strains of P. aeruginosa and 19 out of 23 strains of Acinetobacter baumannii showed synergistic activity. Conclusion: This study suggests that the combination of meropenem and colistin could be a good alternative for the treatment of Acinetobacter and Pseudomonas infections in burns patients, until a newer antibiotic agent is available.
Intraabdominal Ruptured Hydatid Cyst In A Pregnant Woman During First Trimester

Hydatid disease, also known as echinococcosis or hydatidosis, is a parasitic infection caused by the larval stage of two species of the tapeworms (echinococcus). Hydatosis is endemic in the Mediterranean region. Patients with hydatosis are almost asymptomatic and the liver is the organ most frequently involved. Because of infrequent and masked symptoms in pregnancy, misdiagnosis may happen when a pregnant patient comes with abdominal pain and may lead to critical situations. One of the dangerous complications is anaphylactic shock which may cause death. In this case, we present an 11 weeks pregnant patient who was admitted with abdominal pain followed by anaphylactic shock and treated with emergent laparotomy. So, in conclusion, it is important to consider the hydatid cyst as one of the important differential diagnoses of abdominal pain during pregnancy in endemic regions.
A Comparative Study of Tracking Moving Objects in videos

Visual tracking is considered to be one of the most important challenges in computer vision with numerous applications such as object recognition and detection. In the present paper, five tracking techniques will be introduced circulant structure with kernels (CSK), Kernelized correlation filters (KCF), Adaptive color attributes (ACT), distractor – awareness tracker (DAT), and Multi-Template Scale KCF (MTSc-KCF) for the visual object tracking (VOT14), and VOT15 challenge datasets. Performance evaluation for each method was calculated using four measures; center location error (CLE), overlap precision (OP), distance precision (DP), and speed in frames per second (FPS). Results have shown that KCF tracker is the fastest technique in VOT14 but the CSK tracker is the fastest in VOT15. They are used in time-critical application with satisfactory performance. MTSc-KCF, and KCF achieve the best results in most sequences and the highest precision at lower threshold. Each tracker performs favorable and competitive results in some sequence and fails in others. So it is noted that the choice of the tracker is application dependent.
Attitude of Patients towards Public Healthcare Services in Kolkata Metropolitan Area

In this study, an attempt was made to investigate the attitudes of patients towards the public healthcare system in the Kolkata Metropolitan area. The research findings suggest that poor and middle class families of the state generally avail the public healthcare facilities, due to high cost in private hospitals. The behaviour of doctors and nurses are generally cordial in the hospital and prescribed medicines are available from the hospital pharmacies. In public hospitals, nepotism and favouritism are very common. It is a very common practice in this metropolitan city, that, to get admission for treatment in the hospital, one needs a doctor’s recommendation, political link or third party’s help. The management authority is serious enough to bring about good administration and wants to keep the hospital neat and clean.
Implementation and Validation of Artificial Intelligence Techniques for Robotic Surgery

The primary focus of this study is implementation of Artificial Intelligence (AI) technique for developing an inverse kinematics solution for the Raven-II TM surgical research robot [1]. First, the kinematic model of the Raven-II TM robot was analysed along with the proposed analytical solution [2] for inverse kinematics problem. Next, The Artificial Neural Network (ANN) techniques was implemented. The training data for the same was careful selected by keeping manipulability constraints in mind. Finally, the results were verified using elliptical trajectories. The originally proposed analytical solution was found to be computationally inefficient, gave multiple solutions and its existence necessitates the use of the Standard Raven-II TM Tool [2]. The solution devised using ANN technique gave a single solution which was thirteen times faster than the original solution. Moreover, it is generic in nature and can be used for any type of tool. Thus, a novel solution for solving the inverse kinematics problem of the Raven-II surgical robot was formulated and
Innovative Theme Based Innovative Theme Based Innovative Theme Based Innovative Theme Based Fantastic Fantastic Fantastic Fantastic Facebook Facebook Facebook Facebook SystemSystemSystemSystem

It has become gradually more difficult to ignore the importance of Facebook as a social network act throughout the world. Over the past few years researchers have high lightened the need of Facebook system as more and more human interaction become possible with the involvement of Information Technology. More over individuals, organizations and countries are investing considerably in Facebook system from business point of view. In today’s global village Bilaltiger Innovative Theme Based Fantastic Facebook System (BITBFFS) is at the heart of our consideration in this research paper. This paper seeks to address the following questions. How the information of Facebook users can be secured? How Facebook Users can perform meaningful tasks? This paper also compared statistically issues between educated and uneducated persons using Facebook. We used mixed research methodology in our paper.
A Unique Approach to Multimedia Based Dynamic Symmetric Key Cryptography

: In the past decades, Most of the cryptography and steganography based techniques emphasized on securing text or images only. They made use of traditional approaches like transpositions or substitutions for text security and image transformation techniques for image security. None of them completely ensures the safety of data from bruit-force methods, applied by spy-bots. To provide more security large key size and complex procedures have been adopted. This creates extra computational overhead for CPU. Some algorithms introduced security of MMS and Videos, but they primarily focused on encrypting few image frames from entire video with traditional image cryptography. In this paper, we propose an efficient symmetric key based security approach that generates dynamic key from a multimedia file to encrypt any type of multimedia data. In this technique, the dynamic key is chosen randomly from the multimedia file using a special function. This approach gives zero loss results in terms of all the user data and the multimedia content used for encryption. The use of simple operations to select the key and to encrypt the data makes it faster.
Potency of Various Types of Stem Cells and their Transplantation

Stem cells are stirring great excitement in medical research. Stem cells are characterized by their three special properties of self renewal, differentiation and unspecialized nature. The capacity to differentiate into specialized cell types and be able to give rise to any mature cell type is referred to as potency. Human stem cell research holds an enormous potential and contribute to the understanding of fundamental human biology. Stem cell therapy is an amazing modern medical advancement that goes straight to the source of the problem and treats various disorders. Stem cell therapies are playing a major role in cell transplantation biology. This review describes various types of stem cells, their potency and transplantation.