Miracle-dz/UniFAR-FTUs huggingface dataset:
De-Convolution of Camera Blur From a Single Image Using Fourier Transform

- The paper presents an effective technique to remove blur from single photograph. The most common cause of a blur image is camera shake. Camera shake means movement of camera during given exposure time. Some of the conventional blind deconvolution methods use multiple images taken through a burst mode, a feature available in all modern cameras, and combine them to get more clear image. However there are certain limitations and disadvantages of using these conventional techniques. The proposed work is based on a technique that uses an original single input image, a blur is introduced in original image with known PSF value. This is done to understand the efficiency of proposed algorithm to remove blur from input image. This blurred image is used to estimate blur parameters by applying dual Fourier transform on it - for determining values for blur length and blur angle. After restoring this blur image is divided in to smaller sub images with an assumption that each sub image is uniformly blurred which is decided by calculating PSNR value. With the help of these estimated values of blur parameters viz. blur length and blur angle, a local parametric blur model is prepared. These models are then deconvolved with blurry sub images. The resultant of this algorithm is a reconstructed, original, blur free image. The proposed technique is an effective solution to the most common challenge of blurry images and serves the important requirement of clear images of various crucial fields.
Circulating Endothelial Cells And Cardiovascular Risk In Systemic Lupus Erythematosus

Premature atherosclerosis seen in systemic lupus erythematosus (SLE) patients is not explained by traditional risk factors. Circulating endothelial cells (CECs) have been shown to be a surrogate marker of endothelial dysfunction. The aim of this study was to assess the number of CECs in SLE patients and to determine any potential correlation between CEC count and endothelial function (FMD%), disease activity, organ involvement and therapy used. Also, to investigate VCAM-1and ICAM-1 levels as markers of vascular inflammation and injury. This study was performed on 30 premenopausal female SLE patients and 20 age and sex matched healthy controls (HC). Patients were subjected to full history taking, complete clinical examination and assessment of disease activity using (SLAM) score. For both patients and controls, endothelial function (FMD%), laboratory estimation of CEC count, and serum level of VCAM-1 and ICAM-1 were performed. CEC count was significantly elevated in SLE patients comparing to HC (P<0.001). CEC count was positively correlated with SLAM score, while negatively correlated with FMD%. Serum levels of VCAM-1 and ICAM-1 were significantly increased in SLE patients than controls. Moreover, VCAM-1 correlated significantly with disease activity and CEC count while ICAM-1 did not correlate with any of them. There was significant correlation between CEC count and skin vasculitis, renal involvement and anti-malarial medications. In conclusion, increased number of CEC may be a biomarker of disease activity and disseminated vasculopathy occurring in the course of SLE and may represent one of the first specific cellular markers to provide a direct link with the pathophysiology of cardiovascular disease (CVD). VCAM-1 is considered a marker of activation of endothelial cells. Taking together, this may predict patients at increased risk of CVD complications, lupus nephritis or vasculitic skin affection. [Elham Kassem, Mervat El-Sergany, Hanan El-Saadany Abeer Shahba and Wesam Salah. Circulating Endothelial Cells And Cardiovascular Risk In Systemic Lupus Erythematosus. Journal of American Science 2010;6(11):700707]. (ISSN: 1545-1003).
Computer Vision-Based Sensor of Autonomous Mobile Robot for Detection of Stairs

Autonomous navigation of a robot in an unknown environment is still a challenge for engineers. This paper deals with a simple method for detecting obstacles in a robot’s way and stairs in multi-storey buildings. As there may be low light conditions, a structured light-based approach was chosen. A mathematical model was developed to describe the formation of traces of structured light in images. Various scenarios of a robot’s position in relation to stairs were simulated. It was established that light source traces depend on the position and distance of the camera from the light source. Computer simulation revealed characteristic changes of light source patterns in images. It was proved that a cross-form pattern of is attractive for obstacle detection and object recognition.
FERROMAGNETIC STATE OF UNDOPED AND Co, Mn DOPED ZnO NANOPARTICLES

For the first time room temperature ferromagnetism (RTFM) is registered and analyzed in these materials. The detail description of the measured magnetization of the material, namely pure and doped ZnO nanoparticles, obtained by microwave solvothermal synthesis, is presented from the experimental and analytical point of view. Comparing announcements of room temperature ferromagnetic state reported by many authors and own experimental results one can claim that ferromagnetic state in pure and doped ZnO exist. But there are questions with lacking answers, like the stability of the room temperature ferromagnetic state, the nature of RTFM. This paper is focused on experimental registration using SQUID and description of ferromagnetic state. The Brillouin function fitting was applied to analyze the paramagnetic contribution of transitional metal (TM) dopands in the material. The magnetization of zinc oxide nanoparticles (NPs) doped with TM ions was obtained for the samples with nominal concentration 1% and 15% Co2+ and Mn2+ +each. The most unusual magnetic properties perform co-doped NPs Zn(1-x-y)MnxCoyO. The nominal content of Co2+ and Mn2+ in the zinc oxide co-doped NPs was x = y = 1, 5, 10 and 15 mol%.
Factors Influencing the Growth of South Africa’s Agricultural Exports to World Markets

The paper assesses the factors influencing South Africa’s agricultural export growth to its cardinal destinations between 2001 and 2014. A gravity model was used to present investigation of trade flows that has been validated as a suitable tool in determining export growth. The findings indicate that an improvement in South Africa’s and importer’s GDP causes an increase in agricultural exports. Distance and political stability have been shown to have no influence on the growth of agricultural exports to its trading partners. The importer’s population and the export capacity showed a positive relationship on the growth of South Africa’s agricultural exports to its trading partners. Trading agreements, which include AGOA and the TDCA with the EU, show a positive impact on increase in export performance. Therefore, the results suggest that South Africa should focus on countries with a growing population and GDP to improve agricultural export growth and market diversification.
Fuzzy Inference System based Detection of Wolff Parkinson‟s White Syndrome

–ECG based diagnosis of heart condition and defects play a major role in medical field. Most of the ECG diagnosis uses the shape and features of ECG signal to determine the presence of one or more types of heart problems. In this paper a fuzzy logic based expert system is suggested for detection of a type of heart blockage known as Wolff Parkinson’s White (WPW) Syndrome. Fuzzy logic is an expert tool for decision making. A Fuzzy Inference System is made for classification of ECG signal using if then rules. The database for ECG is taken from physiobank. The suggested system is tested for 10 different signals with and without WPW presence. The system gives almost complete agreement with the visual results.
Detecting Digital Image Forgeries By Multi-illuminant Estimators

Nowadays digital images are widely used in day-today life. With the increase of the Internet and low-price digital cameras, as well as a powerful image editing software (such as Adobe Photoshop and Illustrator, and GNU Gimp), it is easy to manipulate on digital images and difficult to detect the original and tampered one. Thus a new field of image forensic has been attracting many of the researchers. With this challenge there were different techniques to detect the authenticity of an image. In this paper, one of the most common forms of photographic manipulation, known as image composition or splicing is analysed. A forgery detection method is a method that detects the inconsistencies in the color of the illumination of images. The proposed approach is a machine-learning based and requires minimal user interaction. The particular approach can be applied to images that contain a couple of persons and require no expert relationship to the tampering decision. To attain this, both physics and statistics-based illuminant estimators used on image regions of comparable material. From these illuminant estimates, extract texture and edge-based options, and then provided in a machine-learning approach for automatic decision-making. The classification performance is done using a naïve-Bayes classifier is promising.
Fault Prediction using Metric Threshold Value of Object Oriented Systems

: Software metrics helps in analyzing many factors of software quality such as fault proneness, reusability, and maintenance effort. Software metrics are values collected from software source code to analyze and evaluate where problems are more probable to occur. These values are used to flag warnings of the problem causing parts of software code using threshold values. However, the proposed techniques did not consider the data distribution and skewness in data. A methodology based on removing redundancy and then log transformation to improve the metrics quality has been implemented. To explore the effect of removing redundancy and performing log transformation on data analysis, we conduct analysis of using software metrics after transformation in identifying fault-prone areas on multiple releases of 8 products (30 releases). This methodology results show that the removing redundancy and then doing log transformation can be used to derive threshold values for all metrics under investigation and then performing the fault classification for each metric. In this research, we aim to propose a methodology to remove redundancy in datasets record values of 8 products (30 releases) after which again log transformation technique is used to calculate threshold value. The results of the transformation after removing redundancy are then used to conduct fault-proneness classification based on threshold values and compared against the results of fault classification based on threshold value after log transformation without removing redundancy in dataset record values. The fault classification after removing redundancy in dataset record values is better than fault classification without removing redundancy in dataset record values.
Stability Analysis and State Feedback Stabilization of Inverted Pendulum

An inverted pendulum fitted on the moving cart (IPMC) represents a class of nonlinear system and is inherently unstable. Stabilizing such nonlinear systems is still a challenging objective for control engineers. It is very difficult to keep the pendulum always in upright position as it is highly sensitive to even a small disturbance and tend to fall down. Hence, the objective of the control mechanism is to maintain the pendulum up right position always by moving the cart back and forth, as long as the angle of deviation from upright position is within the admissible range. Several strategies such as Model Reference Control, Adaptive control, Sliding mode control, state feedback control etc., have already been proposed with reasonable accuracy for the control of IPMC problem. In the first part the mathematical model has been derived using fundamental principles, the controller has been designed using state feedback control technique and the entire system has been simulated using MATLAB-Simulink. The simulated results show that the performance of IPMC is satisfactory with state feedback control. KeywordsInverted pendulum, state feedback, nonlinear systems
An Effective Load Balancing In Long Term Evaluation Self Optimization Network Using Multi Objective Optimized Algorithm

— A self-optimizing network is an effective method for network management and maintenance in Long Term Evolution, which supports the co channel deployed heterogeneous networks and significantly increases the quality of service. The Zone based Load Balancing uses several game theoretic approaches to carry out load balancing but it results in uncoordinated load distribution among multiple cells. It may cause the problem of hidden cell case and slow convergence issues. Along with this problem the Nash Equilibrium used in game theory algorithm cannot be obtained, it may continuously finding solution for long duration. It can be solved by introducing the innovative method of meta heuristic search algorithm called Multi objective Bat Algorithm. It is very promising and could outperform the existing algorithms. The Multi Objective Bat algorithm combined with the priori expert knowledge reduces search space and computational time required for designing the MLB controller. The Multi Objective Algorithm provides the best optimization solution in short period of time and the problem of slow convergence time gets eliminated.
Automatic Camera Based Eye Controlled Wheelchair System Using Raspberry Pi

— This paper includes the electronic wheelchair that implemented for the disabled person. The purpose of this eye controlled wheelchair is to eliminate the assistance required for the disabled person. In this system controlling of wheelchair is depend on eye movements and central switch. Camera is mounted on wheelchair in front of the person, for capture the image of eye and tracks the position of eye pupil by using some image processing techniques. According to eye pupil position of user, motor will be move in required direction such as left, right and forward. Ultrasonic sensor is mounted in front of wheelchair for safety to detect static or mobile barriers and stop the wheelchair movement automatically. A central switch is also mounted on wheelchair for emergency purpose and stop to move in require direction if any one call to stop and someone require attention on themselves. This is independent and cost effective wheelchair system. A raspberry pi board is used to control whole system.
An efficient artificial bee colony with boundary value segmentation for shadow detection

: In the area of computer vision shadow detection is important as it provides the image with high resolution with pixel clarity. There are several approaches have already be introduced but scope in this area is wide and open. In this paper an efficient artificial bee colony (ABC) with boundary value segmentation for shadow detection has been proposed. The proposed approach is the hybridization of association rules, Otsu approach, gradient segmentation and ABC algorithm. First the data preprocessing has been applied for adjoin and adjacent matrix. Then association rules have been applied for adjoin and associated pixels and joint correlations have been formed. The Otsu’s approach and gradient segmentation have been applied. It is beneficial in threshold value estimation in case of intra class variations also. Finally ABC algorithm has been applied for the final object detection and tracking. The results indicate that the approach is efficient in shadow detection and tracking.
Optimization of Process Parameters in Abrasive Jet Drilling Of Hastelloy Using Taguchi Method

Machining of nickel base Hastelloys is considered as moderate to difficult. During machining, these alloys work harden rapidly, generate high heat during cutting, weld to the cutting tool surface and offer high resistance to metal removal because of their high shear strengths. Abrasive jet machining (AJM) is a nonconventional machining process which is effective in machining hard and brittle materials. Hence to overcome the difficulties in machining of hastelloy by conventional machining process, Abrasive jet machining is employed. During AJM, the influence of process parameters on machining characteristics were studied using Taguchi method and the results were compared using ANOVA technique. The process parameters chosen were air pressure, standoff distance (SOD) and nozzle diameter. AJM performance was measured in terms of MRR and Kerf. In the Taguchi analysis it is observed that the air pressure has largest effect and nozzle diameter has the smallest effect on the material removal rate whereas the Standoff distance (SOD) has large effect and nozzle diameter has the least effect on Kerf. Similar kinds of results were observed when analyzed by ANOVA.
IMPROVEMENT OF POWER QUALITY (PQ) BY UPQC (UNIFIED POWER QUALITY CONDITIONER) IN POWER SYSTEM USING ADAPTIVE NEURO FUZZY (ANFIS) TECHNIQUE

The main motive of power utilities is to provide uninterrupted sinusoidal voltage of constant amplitude to their customers. This depends upon the loads and their sensitivity to supply voltage fluctuations. In the last few years the quality of power is the very serious issue in the power system. These issues related to power system quality are more attentive in power electronic devices. So these all power electronic devices are largely affected by the PQ disturbances. Various devices are used for compensation of problems related to power quality for continuously change in voltage. There is one device named Unified Power Quality Conditioner (UPQC) is used for the loss due to PQ fluctuations. It is a combination of series compensator DVR (Dynamic Voltage Restorer) & Shunt Active Power Filter (APF) or Distribution STATCOM connected with the help of a DC link capacitor. This device used successfully for almost all the disturbances such as voltage and current harmonics, unbalanced voltage and current, voltage flicker, Voltage sag and voltage swell [12] etc. There are many optimization techniques to improve the PQ in the transmission and distribution system.
Adaptive User-Device Interface Generation for Websites

- One of the hottest issues in web developer circles lately is accessibility of websites on various devices other than the standard desktop or laptop screens. With mobile devices, tablets, and similar gadgets becoming ubiquitous, it behoves organizational stakeholders to address the issues encompassing user interactions and acceptance of their websites on these latest diminutive gizmos and mobile devices with web-enabled screens. Desktop, tablets, and mobile devices are fundamentally different and are used in very different ways. There is a difficulty of delivering web content on all these multiple devices. This paper seeks to help find a solution to these challenges by using adaptive web design technique as a tool for adapting web sites to the preference of the user irrespective of their device.
Environment–economic Growth Nexus: A Comparative Analysis of Developed and Developing Countries

This study aims to examine the interaction between carbon emissions, income, and trade openness in developed and developing countries for the period from 1980 to 2010 by using recently developed panel data econometric methods. The results are as follows: (i) There is an evidence of the cross-sectional dependence for each variable. (ii) The cross-sectionally augmented and Smith et al.’s panel unit root tests are indicate that all variables are stationary at their first difference. (iii) A Durbin–Hausman cointegration test shows that there exists a long-term relationship between variables. (iv) The results from the common correlated effect estimator presents that there is evidence of the validity of the environmental Kuznets curve (EKC) hypothesis in developed countries. (v) The EKC hypothesis is not valid in developing countries.
Evaluation of the Biological Activities of a Multicomponent-Product as Sheep and Goat Feed Supplement

The in vitro assessment of the biological activities of a multicomponent-product as sheep and goat feed supplement towards enteropathogenic bacteria as well as inflammation-associated-bacteria is reported. The bacteria, namely, Clostridium perfrigens, Escherichia coli, Staphylococcus aureus, Streptococcus uberis, and Pseudomonas aeruginosa were considered in the experiment. The percent bacterial growth reduction revealed at 100 μL, 10 μL, 1 μL, and 0.1 μL product dilutions was in the range 50.81 ± 1.15 86.31 ± 1.15; 37.21 ± 2.11 81.20 ± 1.38; 5.23 ± 1.69 67.56 ± 1.13; and 3.60 ± 0.89 51.88 ± 1.00, respectively. There is a significant difference of antibacterial activity among the isolates and the dilutions tested. In addition, the product showed adhesive activity and biofilm dispersive activity. The highest binding activities were recorded at 100 μL and 10 μL dilutions towards: C. perfrigens (V50 5.8), E. coli NLK99-3 (V50 5.6), E. coli CVVI KH10B strain (V50 5.2), S. aureus (V50 6.3), P. fluorescens (V50 5.6), and E. coli ATCC® 51813TM (V50 7.0), S. aureus ATCC® 29213TM (V50 6.8), Str. Uberis ATCC® 700407TM (V50 6.7), and P. aeruginosa (V50 6.3), respectively. The highest biofilm dispersive activities were recorded using 100 μL and 10 μL of product dilutions towards S. uberis (4.5%), E. coli CVVI KH10B (4.5%), P. aeruginosa (4.31%), E. coli NLK99-3 (4.3%), and E. coli CVVI KH10B (4.4%), C. perfrigens (3.31%), P. aeruginosa (3.1%), respectively. Finally, the product anti-inflammatory activity as inhibitor of COX enzymatic activity was investigated. The highest percent inhibitions were observed at 10 μL (COX1 33.2 ± 1.4; COX2 33.2 ± 1.4) and 1 μL (COX1 39.2 ± 1.4; COX2 32.1 ± 0.9) product treatments. Molecular biology analysis let to either identify and characterize isolated microorganisms or together with PMATM dye to detect bacteria viable cells after product treatments. The applied methodologies let to reveal the efficacy of the feed additive to constrain, as claimed in product label, microorganisms attack and inflammatory processes that can alter the herd wellbeing and the quality of animal production.