Miracle-dz/UniFAR-FTUs huggingface dataset:
Biomedical Image Processing with Morphology and Segmentation Methods for Medical Image Analysis

: - Modern three-dimensional (3-D) medical imaging offers the potential and promise for major advances in science and medicine as higher fidelity images are produced.It has developed into one of the most important fields within scientific imaging due to the rapid and continuing progress in computerized medical image visualization and advances in analysis methods and computer-aided diagnosis[1],and is now,for example,a vital part of the early detection,diagnosis, and treatment of cancer.The challenge is to effectively process and analyze the images in order to effectively extract, quantify,and interpret this information to gain understanding and insight into the structure and function of the organs being imaged.The general goal is to understand the information and put it to practical use.A multitude of diagnostic medical imaging systems are used to probe the human body.They comprise both microscopic (viz. cellular level) and macroscopic (viz.organ and systems level) modalities.Interpretation of the resulting images requires sophisticated image processing methods that enhance visual interpretation and image analysis methods that provide automated or semi-automated tissue detection,measurement, and characterization [2–4]. In general,multiple transformations will be needed in order to extract the data of interest from an image,and a hierarchy in the processing steps will be evident, e.g., enhancement will precede restoration,which will precede analysis,feature extraction,and classification[5]. Often,these are
A Review on Image Based Graphical User Authentication

: The most widely recognized PC authentication technique is to utilize alphanumerical usernames and passwords. This strategy has been appeared to have noteworthy disadvantages. For instance, clients tend to pick passwords that can be effectively speculat ed. Then again, if a watchword is difficult to figure, then it is regularly difficult to recollect. To address this issue, a few specialists have created authentication techniques that utilization pictures as passwords. In this paper, we lead a far reaching review o f the current graphical secret key methods. We characterize these procedures into two classes: acknowledgment based and review based methodologies. We talk about the qualities and restrictions of every technique and bring up the future research headings around there. We additionally attempt to answer two vital inquiries: "Are graphical passwords as secure as content based passwords? "; "What are the real outline and usage issues for graphical passwords? " This review will be valuable for data secu rity specialists and professionals who are occupied with finding a contrasting option to content based authentication strategies.
Efficient Rendering of Glossy Reflection Using Graphics Hardware

Recently, techniques for realistic image synthesis using computer graphics have been widely used in many applications. The reality of the computer-generated images can be greatly improved by taking into account the reflections observed in mirrors, cars, glass walls of a building, etc. Therefore, there has been extensive research into rendering these reflections. However, the computational cost associated with reflections is generally very high because of the complexity. On the other hand, recent advancements in graphics hardware have encouraged researchers to develop hardware-accelerated methods for realistic image synthesis. This paper proposes such a fast method for rendering reflections using graphics hardware. The proposed method can render not only the ideal specular reflection such as from a mirror but also the glossy reflections such as those from a metal surface.
Study of an intelligent fuzzy based cluster head selection scheme for WSNs

Wireless Sensor Network is a resource constraint network, in which all sensor nodes have limited resources. In order to save resources and energy data must be aggregated to reduce the amount of traffic in the network. Data aggregation has to done with the help of clustering scheme. Clusters reduce the localized traffic by means of grouping sensor nodes and compress the data together and then transmit only compact data to base station. Therefore optimal cluster head selection is important to maximize the lifetime of the network by utilizing the limited energy in an efficient manner. Various algorithms are proposed for the selection of cluster head for maximizing the network life time. This paper is focused on the survey of such algorithms.
O-H⋅⋅⋅N intramolecular hydrogen bonds in the derivatives of 4-(aminomethylene)-1-methylpyraz olin-5-one and its imine tautomer

Intramolecular hydrogen bondings (IHB) in some deri vatives of 4-(aminomethylene)-1-methylpyrazolin-5-o nes (AMP) and its imine tautomers were investigated usi ng density functional theory (DFT) calculations at B3LYP/6311+G(d,p) level of theory. The relative stability calculations showed that AMP forms are more stable than IMP ones. The strength of the IHB were investigated by means of several quantum descriptors such as geomet rical structural (bond lengths and angles), topological p rameters based of Atoms in Molecules theory (AIM) of Bader (total electronic density and its Laplacian at bond critical point (BCP) and ring critical point (RCP) ), hyper conjugative interaction energy (E CT), related to the LP(O) →σ* (N–H) and LP(N) →σ * (O–H) overlaps, chemical shifts of the bridged hydrogen atom, δH, frequency shifts of the N-H and O-H stretching v ibration modes. The combined results strongly illustrate that the O-H ⋅⋅⋅N exist for IMP forms is stronger that the N-H ⋅⋅⋅O in AMP tautomers. Good linear correlation coefficients between IHB energy, EHB, based on Espinosa’s equation and the abovemention ed descriptors were reported.
Efficient Frequent Pattern Tree Construction

Association rule learning is a popular and well researched technique for discovering interesting relations between variables in large databases in the area of data mining. The association rules are a part of intelligent systems. Association rules are usually required to satisfy a user-specified minimum support and a user-specified minimum confidence at the same time. Apriori and FP-Growth algorithms are very familiar algorithms for association rule mining. In this paper we are more concentrated on the Construction of efficient frequent pattern trees. Here, we present the novel frequent pattern trees and the performance issues. The proposed trees are fast and efficient trees helps to extract the frequent patterns. This paper provides the major advantages in the FP-Growth algorithm for association rule mining with using the newly proposed approach.
An Efficient Diagnosis Of Tuberculosis With The Aid Of Chest Radiographs

Tuberculosis (TB) is considered as a major health threat in many regions of the world. It is considered to be the world’s second leading cause of death. So it is necessary to diagnose TB before it becomes fatal. But diagnosis of Tuberculosis is still a challenge and when left undiagnosed and thus untreated, it is seen that the mortality rates of patients with tuberculosis are considerably high. There are various diagnostic methods which are put into practice and those diagnostic methods are developed in the last century is still considered as the standard diagnostics. But these diagnostic methods are unreliable and slow. In order to reduce the burden of the disease, this paper proposes an efficient diagnosis of tuberculosis with the aid of chest radiographs. Lung region is the most affected part of Tuberculosis. So we perform an K means algorithm to segment the lung region from the CXR image which is considered to be the existing work, which is less efficient, we don’t get a clear cut of lungs. So we proposed lung segmentation using region growing segmentation. After performing lung segmentation we perform feature extraction, where various features of the lung region are extracted out. Of these features we consider the best feature mainly the HOG feature. The feature is then fed to a classifier mainly SVM classifier and this SVM classifier is then trained using images from the database and it then perform classification of the CXR image as whether TB is affected or not. Various level of TB affected is also shown according to the input CXR image. The TB affected area is also determined using region based active contour segmentation. The comparisons between various segmentations are also performed.
EFFICIENT MULTIUSER ITINERARY PLANNING FOR TRAVELLING SERVICES USING FKM-CLUSTERING ALGORITHM

- This paper proposes, previous efforts address the problem by providing an automatic itinerary planning service that organizes the points-of-interests (POIs) into a customized itinerary. The search space of all possible itineraries is too costly to fully visit, to simplify the complexity, most work assume that user’s trip is limited to some important POIs and will complete within one day. To address the above Problem, design a more general automatic itinerary planning service, this generates multiday itineraries for the users. All POIs are considered and ranked based on the user’s preference. Since the many users are planning for a trip with various requirements then their search complexity is increased. To overcome this limitation using the concept of grouping or clustering the users based on user’s requirement similarity. The novel modified clustering is using for grouping the user according to their requirement similarity. The membership values are defined for clustering process and it’s based on the users. It is used to reduce the search complexity as well as time complexity of the system.
Web Based Keystroke Dynamics Application for Identifying Emotional State

—Emotion is one of the important features of human being that makes them different from machines. Traditionally, today‘s computer system do not incorporate any emotional exchange in the decision making process. If we could develop an emotional aware system which can interact with human involving emotions then using machines could be more effective and friendly. Conventional emotional identification methods (facial expressional analysis, voice intonation analysis, thermal imaging of the face) use intrusive, lab-based, and expensive tools which are unsuitable for real-world situations. A possible solution for emotion identification without these drawbacks is to determine user emotion by analyzing the rhythm of their typing pattern on a keyboard. This paper presents techniques to recognize the emotional state of the user through analyzing the keystroke patterns of the user.
Estimation of Zanamivir Drug present in Tablets using RP-HPLC Method

A reverse phase isocratic high performance liquid chromatographic method was developed for the estimation of Zanamivir (ZAN) drug in tablet formulation. The separation was achieved by symmetry C8 (4.6x150 mm, 3.5 micron, make: Xterra) and Acetonitrile: potassium Dihydrogen orthophosphate buffer pH 4.0 (60:40 v/v) as mobile phase, at a flow rate of 0.5 ml/min. Detection was carried out at 230 nm. Retention time of ZAN was found to be 3.5 min+or-0.5 min. The method has been validated for linearity, accuracy, precision. Linearity of Zanamivir was in the range 20-100 mcg/ml. The mean recovery obtained for was 100.7. Developed method was found to be accurate, precise, selective and rapid for estimation of Zanamivir drug in tablets.
Experimental Investigation Of Using Concrete Waste And Brick Waste As A Coarse Aggregate

To generate a study on concrete which incorporate Over Burnt Brick Ballast and concrete waste partially due to their abundance. 25%, 50% (M15, M25) incorporation was used as partial replacement of natural coarse aggregate in concrete. Analysis of incorporated concrete was done in fresh state as well in hardened state to evaluate different properties of concrete i.e. slump, compaction factor test, unit weight, and compressive strength are evaluated. From all the results and experimental approach it is concluded that Concrete formed with over burnt brick ballast and concrete waste aggregate showed beneficial performance as compared with the concrete made up of natural aggregate obtained from local resources. It reduces the cost of concrete by reducing the aggregate cost and produces economical infrastructure system. It has been observed that the use of waste materials results in the formation of light weight concrete. Uses of such waste materials will not only cut down the cost of construction, but will also contribute in safe disposal of waste materials. Apart from the environmental benefits, the addition of such wastes, also improves certain properties of resultant concrete. Cubes of concrete were prepared and tested to study the compressive strength. The results were compared with concrete made with river wash gravel as coarse aggregates which at present is the only coarse aggregate. It can be concluded that by reducing the water-cement ratio from 0.60 to 0.40 the compressive strength of crushed over burnt bricks sand concrete and gravel sand concrete increase by more than 30%. Use of broken over burnt bricks as coarse aggregate for structural concrete is recommended when natural aggregate is not easily available, high strength of concrete is not required and the bearing capacity of the soil is low.
PGP3 is a Chlamydial Plasmid-Encoded Virulence Factor

Sexually transmitted infections with Chlamydia can lead ectopic pregnancy and tubal infertility. However, the precise pathogenic mechanisms remain unclear. The chlamydial cryptic plasmid is known to play a critical role in chlamydial pathogenesis in the genital tract. C. muridarum depleted of plasmid or deficient in the plasmid-encoded pGP3 protein was highly attenuated in ascending infection and inducing upper genital tract pathology, demonstrating that the plasmid-encoded pGP3 is a key virulence factor. pGP3 was found to neutralize the antichlamydial activity of the host antimicrobial peptides particularly the cathelicidin peptide LL-37 (human) or CRAMP (mice). This pGP3mediated neutralization was dependent on Pgp3 to form stable complexes with LL-37. The complex formation was further mapped to the middle domain of pGP3. These observations suggest that Chlamydia may secrete Pgp3 for trapping antimicrobial peptides during chlamydial spreading from cell to cell in the genital tract mucosal tissue. The tertial structure of pGP3 reveals that pGP3 may also directly participate in the induction of tubal inflammation by activating TNF signaling pathway. Finally, pGP3 was recently reported to be essential for chlamydial colonization in the gastrointestinal tract. Thus, careful analyses of pGP3 functionality may reveal novel information on how Chlamydia interacts with its host and induces pathologies in the upper genital tract.
Isolation and identification of bacteria isolated from different parts of cell phones

Microbiological standards in hygiene are necessary for a healthy life. However, practices that shift from normal standards of hygiene have been observed in both the developing and developed world. This investigation confirms such a deviation, as a variety of bacteria were found on mobile phones. Mobile phones have become an integral and indispensable part of daily life. In many countries, mobile phones outnumber landline telephones. Most adult and many children now own mobile phones. At present, Asia has the fastest growth rate of cellular phone subscribers in the world. A mobile phone can spread infectious diseases by its frequent contact with hands [1]. Tagoe et al (2011) have reported that the result that pathogenic bacteria are present on approximately 40% of mobile phones belonging to patients in a hospital, and on approximately 20% of mobile phones belonging to hospital staff [2]. Microbiologists say that the combination of constant handling with the heat generated by the phones creates a prime breeding ground for many microorganisms that are normally found on the skin. Staphylococci, particularly Staphylococcus epidermidis are members of the normal flora of the human skin, respiratory and gastrointestinal tracts. Nasal carriage of S. aureus occurs in 20-50% of human beings [3]. S. aureus, a common bacterium found on the skin pneumonia and meningitis, and is a close relative of methicillin resistant S. aureus (MRSA). The main reservoir of S. aureus is the hand from where it is introduced into food during preparation [4]. The hand serves and in the noses of up to 25% of healthy people and aniABSTRACT
A Novel Saliency Detection Framework for Effective Saliency Measurement

— Salient objects are portions of an image or a video which are likely to be get noticed first when it is viewed by a person. The human vision system (HVS) of a human being has the ability to notice the most salient regions from a video or image. It enhances this ability by using the inherent visual attention mechanism. Here in this work, tries to simulate a model of the HVS of a person, that is a saliency model. For an effective saliency detection here in the proposed work integrated the concept of diffusion based compactness and local contrast. Compactness and Local contrast can enhance the efficiency of a saliency detection model. Moreover, the concept of superpixel generation is also implemented in this saliency model.
Combined Mining process on complex data

– The data mining and knowledge discovery in databases have been the latest trend for researchers, media attention, and industry. The stake of the people has grown tremendously in business to analyze the data in all sectors. It has discovered the ways of using the data scattered as one system for better understanding and management of the business. The Enterprise data mining consist of applications which includes complex data such as multiple heterogeneous large data sources, business impact and user preferences. For this situation single method is often limited in discovering informative knowledge from complex database. It is critical to develop effective methods for mining patterns combining necessary information from multiple related business rules, catering for real business needs and decision-making actions rather than just providing a single line of patterns. The mechanism describes the basic processes for complex data like multi method combined mining, multi feature combined mining and multi source combined mining. The mechanism will be evaluated with complex data sets to show the flexibility and instantiation capability in discovering informative knowledge in complex data using combined mining.
A Survey of Different Reconfigurable Antennas for Various Wireless Applications

Different reconfigurable wireless communication antennas are studied and discussed detail in this paper. Properties of antenna such as gain, bandwidth, directivity, radiation pattern, return loss, radiation efficiency etc are varied based on their shapes, dimensions, thickness, dielectric constant, and conducting material and feeding techniques. Reconfigurable antennas are used to operate the antenna for various applications just by change their pattern, polarization and frequency. Reconfiguration techniques and types of antennas are varied based on their applications.
EXTINCTION AND ABSORPTION EFFICIENCY FACTORS OF A FINITE-LENGTH CYLINDER IN THE DISCRETE DIPOLE AND WENTZEL- KRAMERS-BRILLOUIN APPROXIMATIONS

The values of light scattering extinction and absorption efficiency factors of an optically “soft” ( 1 1 << − m , where χ i n m + = is the relative refractive index of the cylinder) finite-length circular cylinder irradiated by linear polarized light in the direction at any angle to the cylinder symmetry axis are compared in the WentzelKramers-Brillouin (WKB) approximation and in the Discrete Dipole Approximation (DDA). The amended expressions of light scattering extinction and absorption efficiency factors in the WKB approximation for an optically “soft” finite-length circular cylinder are presented. The differences between parallel and perpendicular polarizations of light scattering extinction and absorption efficiency factors for a finitelength circular cylinder are calculated in the WKB approximation and in the DDA. As a result of the minimal error of comparison of light scattering extinction and absorption efficiency factors in the WKB approximation and in the DDA is equal about 10%. The correctness of the new revised formulas for light scattering extinction and absorption efficiency in the WKB approximation of a finite-length circular cylinder in the vector form is validated numerically.
Effect of Hydro and Hormonal Priming on Seedling Vigour during Initial Vegetative Growth of Rice (Oryza sativa L.)

In the present piece of work, rice seeds were primed with distilled water and different concentrations of kinetin (0 to 30 ppm) T2 to T11, whereas; seeds without any treatment referred as control (non-primed) (T1). Various physio-morphological (shoot and root lengths, root number, fresh and dry weights) and biochemical (proline content, total chlorophyll content and superoxide dismutase activity (SOD at 20 days after sowing)) parameters were studied in the seedlings, obtained from 10, 15 and 20 DAS old primed and non-primed plants. Among treatments, 2.5 ppm treatment (T3) was found to perform best and the T1 was the poorest.
Semantic Based Hypergraph Reranking Model for Web Image Search

— The image search reranking is emphasis on the text based searching to the image.The existing reranking works on the low level visual feature.Depends on the classifier the semantic attributes for image searching are predefined attributes,each image works on the attribute feature categorization or classifiers.The system must need the responses from the classifiers.Therefore we simply uses the hypergraph to show images relation between the combining low level visual feature and the attribute features.The relation simply represent the hypergraph ranking.The hypergraph reranking is nothing but to order the images that is mean similar visual should have similar ranking scores.We work on the visual as well as attribute joint hypergraph learning.This is beneficial for working on two different information sources concurrently.
Indian Stock Market Prediction Using Differential Evolutionary Neural Network Model

— This paper presents a scheme using Differential Evolution based Functional Link Artificial Neural Network (FLANN) to predict the Indian Stock Market Indices. The Model uses Back-Propagation (BP) algorithm and Differential Evolution (DE) algorithm respectively for predicting the Stock Price Indices for one day, one week, two weeks and one month in advance. The Indian stock prices i.e. BSE (Bombay Stock Exchange), NSE, INFY etc. with few technical indicators are considered as input for the experimental data. In all the cases, DE outperforms the BP algorithm. The Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE) are calculated for performance evaluation. The MAPE and RMSE in case of DE are found to be very less in comparison to BP method. The simulation study has been done using Java-6 and NetBeans.