Miracle-dz/UniFAR-FTUs huggingface dataset:
OUTLIER DETECTION USING CLUSTER-BASED APPROACH: A REVIEW

: Outlier detection is a crucial task in data mining which aims to detect an outlier from given data set. The data is said to be an outlier which appears to have inconsistent observation with the remaining data. Outliers are generated because of improper measurements, data entry errors or data arriving from various sources than remaining data. Outlier detection is the technique which discovers such type of data from the given data set. Several techniques of outlier detection have been introduced which requires input parameter from the user such as distance threshold, density threshold, etc. The goal of this proposed work is to partition the input data set into the number of clusters and then outlier is detected for each cluster. The computational time is affected as the data set size is reduced in first phase due to clustering. This work aims at studying two-three different methods of outlier detection with two different data sets. Also analyzing the performance of each method based on system accuracy.
An Investigation on Mobility Influence on MAC Protocols of Wireless Sensor Networks

— The collection of sensor nodes, which form a dynamic and arbitrary network by connecting on a wireless medium is called wireless sensor networks. This definition implicitly describes that links may appear or disappear at any time because of node mobility & other factors. The communication is completely dependent on the nodes (source and destination) of network. For a network to work efficiently various protocols for routing have been developed. These protocols provide the path among distant nodes via multi-hop links to improve network efficiency. The Protocols’ performance affected by the various factors, such as mobility of nodes, varying network size, bandwidth and power consumption of node. This paper describes comparative analysis of protocols with reactive routing such as (AODV, DSR and DYMO) used in day-to-day scenario, under the Influence of different mobility models: like File, Group Mobility and Random-Way Point Model. The differentials of performance are investigated by altering the number of nodes and different mobility models, depending on the simulation results, how the efficiency of each protocol can be improved is also recommended. By using simulator we simulates throughput, average jitter packet delivery ratio and average end to end delay, in network layer hop count and RTS, CTS and ACK in MAC of protocols. For the above parameters simulation is performed with QualNet 5.0 simulator. The results show expressively noticeable Influence of mobility models on performance of routing protocols.
Crystal structure, characterization and Hirshfeld analysis of bis{(E)-1-[(2,4,6-tribromophenyl)diazenyl]naphthalen-2-olato}copper(II) dimethyl sulfoxide monosolvate

In the title CuII complex, a newly synthesized dye, the metal atom is coordinated by two N atoms and two O atoms from two bidentate (E)-1-[(2,4,6-tribromophenyl)diazenyl]naphthalen-2-olate ligands.
Flow cytometry visualization and real-time processing with a CMOS SPAD array and high-speed hardware implementation algorithm

Time-domain microfluidic fluorescence lifetime flow cytometry enables observation of fluorescence decay of particles or cells over time using time-correlated single photon counting (TCSPC). This method requires the fluorescence lifetime measured from a limited number of photons and in a short amount of time. In current implementations of the technique, the low throughput of state of the art detectors and lack of real-time statistical analysis of the current technology, the timedomain approaches are usually coupled with off-line analysis which impedes its use in flow cell sorting, tracking and capturing. In this work, we apply a 32×32 CMOS SPAD array (MegaFrame camera) for real-time imaging flow cytometry analysis. This technology is integrated into a 1024-beam multifocal fluorescence microscope and incorporating a microfluidic chip at the sample plane enables imaging of cell flow and identification. Furthermore, the 1.5% native pixel fill-factor of the MegaFrame camera is overcome using beamlet reprojection with <10 μW laser power at 490 nm for each beam. Novel hardware algorithms incorporating the center-of-mass method (CMM) with real-time background subtraction and division are implemented within the firmware, allowing lossless recording of TCSPC events at a 500 kHz frame rate with 1024 histogram bins at 52 ps time resolution. Live calculation of background compensated CMM-based fluorescence lifetime is realized at a user-defined frame rate (typically 0.001 ~ 27 kHz) for each SPAD pixel. The work in this paper considers the application of the SPAD array to confocal fluorescence lifetime imaging of multiple coincident particles flowing within a microfluidic channel. Compared to previous flow systems based on single-point detectors, the multi-beam flow system enables visualization, detection and categorization of multiple groups of cells or particles according to their fluorescence lifetime.
Challenging Bullwhip Effect of Supply Chain through Case-Based Multi-Agent System: A Review

The supply chain system grow to be foremost division of all business organizations. Each organization pays the concentration to preserve the procession among the organizations’ services. The bullwhip effect is one of the main sweats faced in soft organization of the supply chain management system. This effect can influence the superiority of the services generated by finicky association. Without proper resolving the bullwhip effect, any organization can not engender the consumer contentment & returns. Such organization may not countenance the business antagonism in extensive time era. There is an abundant solution for overbearing the bullwhip effect. In this paper, first we revise all these solutions for tumbling the possessions of bullwhip effects in the organizations. The multi-agent system is the budding procedure of Artificial Intelligence system. It is used to tenacity real time exertion faced in the business actions. The multi-agent system is self-possessed of the numerous intelligent agents that are autonomous, proactive and decision-taking power. In this paper we will proposition the case-based multi-agent systems that acquire the conclusion on origin of solving ancient times trouble solving incident. Keywords— Supply chain management system, Bullwhip effect, Case-based reasoning, Multi-agent system Controlling Bullwhip effect.
A Image analysis System to Detect Skin Diseases

Skin diseases rate has been increasing for past few decades. Psoriasis is chronic inflammatory skin disease which affects more thgan 3% of population. One of the risk factor in skin cancer is unprotected exposer to UV radiation, which causes various skin diseases. For early diagnosis of skin cancer, psoriasis and dermatophytosis and increases chance for cure significantly. Therefore proposed system used for early prevention and detection named a Image analysis system to detects skin diseases. The image analysis technique where user will able to take skin images of different mole type or rashes type. System will process and analyse the images, which provide notification to user you need medical help. This system provides automatic skin diseases prevention and detection. )
Asymmetric dimethylarginine is not a marker of arterial damage in children with glomerular kidney diseases

Introduction Asymmetric dimethylarginine (ADMA), an endogenous inhibitor of nitric oxide synthase, correlates with cardiovascular risk especially in patients with chronic kidney disease. The aim of our study was to establish significance of ADMA as a biomarker of arterial damage in children with glomerulopathies. Material and methods In 80 children with glomerulopathies (mean age, 11.33 ±4.25 years; 42 with idiopathic nephrotic syndrome [INS], 38 with IgA or Henoch-Schoenlein nephropathy [IgAN/HSN]), we analyzed serum ADMA [nmol/ml], peripheral and central blood pressure, arterial stiffness (augmentation index – AIx75HR, pulse wave velocity – PWV), common carotid artery intima media thickness (cIMT), and selected clinical and biochemical parameters. Results In the study group, mean ADMA concentration was 1.66 ±1.19 [nmol/ml] and did not differ between INS and IgAN/HSN patients. We found no significant correlations between concentration of ADMA, cIMT [mm]/Z-score, PWV [m/s]/Z-score, and AIx75HR [%] in the whole group and in INS and IgAN/HSN patients. In the whole group of 80 children, ADMA correlated (p < 0.05) with BMI Z-score (r = –0.24), uric acid (r = –0.23), HDL-cholesterol (r = –0.25), and central mean arterial pressure (r = –0.25), in children with INS also with total protein (r = 0.37), albumin (r = 0.36), and total cholesterol (r = –0.40, p = 0.028). In multivariate analysis, serum albumin was the strongest determinant of ADMA in the whole group (β = 0.536, 95% CI: 0.013-1.060, p = 0.045). Conclusions 1. In children with glomerulonephritis, measurement of asymmetric dimethylarginine cannot replace well established and validated methods of assessment of subclinical arterial damage. 2. In children with glomerular kidney diseases, ADMA concentration is related primarily to serum albumin concentration.
An Novel FFT Based Error Reduction Algorithm For Textured Image

This paper presents a reconstruction of missing textures based on error reduction algorithm using fourier transform magnitude estimation method. In this method fourier transform magnitude is estimated for a target patch including missing areas, and the missing intensities are estimated by retrieving its phase based on error reduction algorithm. In this method the errors are monitoring in the error reduction algorithm, the fourier transform magnitude of known patches are similar to that of target patch. After that, the fourier transform magnitude of the target patch is estimated from those of the selected known patches and their corresponding errors. So this method has to estimate both the fourier transform magnitudes and phases by using error reduction algorithm to
Evaluation of Outcome of Correction of Clubfoot by Conventional Ponseti and Accelerated Ponseti

Introduction: Congenital idiopathic clubfoot is a common orthopedic condition in children. It has been associated with neuromuscular disorders and various syndromes. The Ponseti method has transformed the management of children with clubfoot producing good long-term results. The condition is more common in male childs. Aim: To analyze the efficacy of accelerated Ponseti in the management of clubfoot and compare with the standard Ponseti. Materials and Methods: We selected 40 children with idiopathic clubfoot <1 year and compared both standard and accelerated Ponseti methods. All were treated on outpatient basis. Each clubfoot was scored using Pirani score before cast application each week. Each foot manipulated and corrected with AK cast weekly in standard Ponseti and twice weekly in accelerated Ponseti. Results: Out of the 20 patients corrected with standard Ponseti only 3 patients (11.5%) had relapse and only four cases among 20 patients corrected with accelerated Ponseti had relapse (20%). Conclusion: Based on our study, we conclude that standard method of Ponseti correction is more effective than accelerated method of Ponseti correction.
An Improved Classification Technique Using Adaptive Gaussian Mixture Model for User Behavior Modeling

: The purpose of Web usage mining is to extract the knowledge that is concealed in the web log files of a Web server. By implementing statistical and data mining techniques to the Web log data, curious patterns regarding the users’ navigational behaviour can be grabbed, such as user and page clusters, as well as possible correlations between Web pages and user groups. In this paper, we propose a Classification method based on Adaptive Gaussian Mixture Model (AGMM). Under the AGMM, user's navigational behaviour in a Web site can be seamlessly classified to discover the cluster of likeminded users. Our experimental results show that our method can achieve better classification accuracy when compared to standard classification approaches based on Gaussian Mixture Model.
Development of Replica Free Repositories using Particle Swarm Optimization Algorithm

The increasing volume of information available in digital media becomes a challenging problem for data administrators. Usually built on data gathered from different sources, data repositories such as those used by digital libraries and ecommerce brokers present records with disparate schemata and structures. The increased volume even created redundant data also in the database. So a system or method is become immense to control the redundancy and duplication. In the proposed approach, a method that makes use of PSO (Particle Swarm Optimization) algorithm for generating the optimal similarity measure to decide whether the data is duplicate or not. PSO algorithm is used to generate the optimal similarity measure for the training datasets. Once the optimal similarity measure obtained, the deduplication of remaining datasets is done with the help of optimal similarity measure generated from the PSO algorithm.
Application of Consistency and Efficiency Test for Forecasts

The purpose of this study is to evaluate forecast efficiency by using forecast of food price inflation, consumer price index general, GDP per capita and Money supply data of Pakistan. It is therefore designed to analyze forecasting efficiency by applying consistency and efficiency criteria for annual data covering the period 1975 to 2008. Forecasts are obtained from ARIMA (auto regressive integrated moving average) model specification. Four forecasting accuracy techniques, such as, Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and Theil’s Inequality Coefficient (TIC) are used to be able to select the most accurate forecast model . Later on these forecasts are evaluated on the basis of consistency and Efficiency criterion defined. We found food price forecast are consistent and efficient, therefore can be used in policymaking and management decision. Forecasts test may be used before any further appliance. Keywords: Food price Forecasts, ARIMA forecasts, Consistency test, Conditional Efficiency test.
An Efficient Approach to Enhance Throughput in Layered Overlay Multicast using Network Coding Technique

— In overlay networks, the available bandwidth between sender and different receivers are different.In this paper, a solution is proposed to improve the throughput of an overlay multicast session with heterogeneous receivers by organizing the receivers into layered data distribution meshes and sending substreams to each mesh using layered coding.Recent advances in information theory show that the throughput of a multicast session can be improved using network coding.The solutions utilize alternative paths and network coding in each mesh.The problem is first formulated into a mathematical programming,whose optimal solution required global information.Hence we present a distributed heuristic algorithm. The heuristic progressively organizes the receivers into layered meshes. Each receiver can subscribe to a proper no of meshes to maximize its throughput by fully utilizing its available bandwidth. The benefits of organizing the topology into layered mesh and using network coding are demonstrated clearly through extensive simulations. Numerical results indicate that the average throughput of a multicast session is significantly improved (up to 50% to 60%) with only slightly higher delay and network resource consumption.
Characterization of tattoos in human skin using pulsed photothermal radiometry and diffuse reflectance spectroscopy

We have recently introduced a novel methodology for noninvasive assessment of structure and composition of human skin in vivo1. The approach combines pulsed photothermal radiometry, involving time-resolved measurements of midinfrared emission after irradiation with a millisecond light pulse, and diffuse reflectance spectroscopy in visible part of the spectrum (400–600 nm). The experimental data are fitted simultaneously with respective predictions from a fourlayer Monte Carlo model of light transport in human skin. The described approach allows assessment of the contents of specific chromophores (melanin, oxy-, and deoxy-hemoglobin), as well as scattering properties and thicknesses of the epidermis and dermis. In present study we evaluate the potential of this approach for quantitative evaluation of tattoos. For this purpose, we apply a three-layer optical model of skin consisting of epidermis, upper dermis, and bottom dermis which includes the tattoo ink. The study involves healthy volunteer with black tattoo undergoing tattoo removal treatment with Q-switched Nd:YAG laser. The measurements are performed in four tattoo sites and one nearby healthy site before and after laser removal treatment. The results indicate the depth of tattoo, amount of tattoo ink and scattering properties in the dermis. This information can be used to improve our understanding of laser tattoo removal procedure.
Compression Of Images Based on Resolution In Noisy And Noiseless Channels

— The main purpose of image compression is to reduce the memory space or transmission time and that of cryptography is to keep the security of the data. These two technologies are separate. But in some cases an image can be compressed if necessary, and then encrypted. Once the data are decrypted, all secrets will be leaked. Hence compression is performed after encryption of the image if there is a need to transmit the redundant data over an insecure and bandwidth constrained channel. The reverse system is also used now a days and it ensures more security. In both cases there is no compromise in compression efficiency. For compression and encryption several techniques are used. Some of these techniques are applicable to grayscale images, some others to color images and others do both. To encrypt the compressed data and for transformation function many techniques are used in several areas. In this work, A Discrete Wavelet Transform based method, Resolution Progressive Compression is used. In Resolution Progressive Compression three decomposition levels are used. Greater compression performance can be achieved by increasing the number of levels. The one fundamental problem that is coming in encryption before compression is, there is no utilization of the pixel redundancy for subsequent compression. In other words encryption mask the pixel redundancy that is there in the image. Therefore before encrypting the original image it can reduce the dimensionality of the gray scale image and obtain a decorrelated image using PCA and its variants. If the compression efficiency is poor PCA and encryption will be suffice the needs. In the decoding stage it can project the principal directions back to get the original image.
Depth-resolved investigation of multiple optical properties and wrinkle morphology in eye-corner area by multi-functional Jones matrix optical coherence tomography

We examined the relationship between depth-resolved local optical properties of eye-corner skin measured by multifunctional Jones matrix optical coherence tomography (JM-OCT) and corresponding wrinkle morphology of aged women (n=21; age range, 71.7±1.7). Wrinkle morphology parameters were analyzed by measuring surface topography of three-dimensional silicone replicas. The same regions were measured three-dimensionally by JM-OCT and the means of several optical properties were computed at each depth. Optical properties include birefringence (BR), attenuation coefficient (AC), and degree-of-polarization uniformity (DOPU). BR and AC were correlated with mean wrinkle depth (WD), although DOPU was not. Significant correlations were found between WD and BR at 88.2 to 138.6 μm depth region from the skin surface (highest correlation at 113.4 μm), and between WD and AC at 12.6 to 18.9 μm and 189 to 459.9 μm depth regions from the skin surface (highest correlations at 18.9 μm and 415.8 μm). This suggests that the collagen structure of the papillary dermis and the microstructure and/or tissue density of the upper epidermis and reticular dermis may be associated with wrinkle morphology. Multiple regression analysis was used to examine the highest significant correlations of BR (113.4 μm) and AC (18.9 μm, 415.8 μm). A significant regression coefficient (R2=0.547, p = 0.001) was obtained, indicating that only BR and AC could sufficiently explain WD. Beta coefficients of BR (113.4 μm), AC (18.9 μm), and AC (415.8 μm) were −0.384, −0.369, and −0.354, respectively. This suggests that the upper epidermis, papillary dermis, and reticular dermis may contribute similarly to wrinkle formation.
Person Recognition from Activity using Bag of Words

— In this paper the discriminant pattern hidden in the way of doing an activity for every person is explored. This pattern can be utilized for person recognition purpose in uncontrolled scenarios unlike finger print, iris, retina etc. (based on physical biometrics). This method is based on single video camera based data. From the video of various activities, background subtraction is done to remove insignificant data. From the binary video obtained after background subtraction structural tensor based features are detected and extracted. The extracted features defines the variation from the mean position are then clustered by means of k-means clustering. Histogram of cluster centroids is calculated using Bag Of Words (BOW) and classified by category classifier. Histogram of input video action sequence is compared with each of dataset and predicts the category, which corresponds to the label of person.
Image Compression based on Modified Block Truncation Code using Gray Scale Image

-In the present era of multimedia, the requirement of image/video storage and transmission for video conferencing, image and video retrieval, video playback, etc. are increasing exponentially. As a result, the need for better compression technology is always in demand. Modern applications, in addition to high compression ratio, also demand for efficient encoding and decoding processes, so that computational constraint of many real-time applications is satisfied.Since these method involves lessnumber of simple computations, the time taken by thisalgorithm is also very less when compared with BTC.The given image is divided into non overlapping rectangular regions. For the sake of simplicity the blocks were let to be square regions of size m x m. They differ in the way of selecting the quantization level in order to remove redundancy. Objectives measures were used to evaluate the image quality such as: Peak Signal to Noise Ratio (PSNR).
Enhanced the Image Segmentation Process Based on Local and Global Thresholding

Image processing plays an important role in computer vision. The process of image segmentation provides the partition of image into different segments according to their feature attribute. Region based segmentation is a type similarity based segmentation. Another type of segmentation is called thresholding based segmentation. In thresholding based segmentation method some thresholding techniques are used. Thresholding techniques are classified into two major categories as, Global and Local. In global thresholding, pixel values are categorized in two classes, one class belong to object and another class belong to background. We use one threshold value in global thresholding for whole image that belongs to single level thresholding and if threshold value used in segmentation is more than one, technique is called multilevel thresholding. Local thresholding belongs to multilevel thresholding method. In this paper a comparative analysis of global thresholding and local thresholding methods is made according to time taken for image segmentation. Experimental results provide a conclusion that Global thresholding takes less time than local thresholding.