Miracle-dz/UniFAR-FTUs huggingface dataset:
Toxicity Evaluation of Waste Treatment Plant of Textile Effluent Using Fish: Nile tilapia, Oreochromis niloticus

The experiment was conducted to evaluate the acute toxicity level of effluents from inlet and outlet of the biological lagoons of Hawassa Textile waste treatment plant using Nile tilapia, Oreochromis niloticus as test organism. Data for 24hrs, 48hr, 72hrs and 96hrs were recorded, and were analysed to determine the effects of toxicants of the effluent on behavioural responses and survival rate of Oreochromis niloticus. The results revealed that normal swimming behaviours were observed on the fish stocked at lower effluent concentration, while erratic swimming, gasping and frequent surfacing behavioural responses were observed on the fish stocked at higher effluent concentration. There was no fish mortality in control and 10% (v/v) outlet effluent concentration. The highest percentage mortality was observed at 100% (v/v) inlet effluent concentration followed by 100% (v/v) outlet and 40% (v/v) inlet effluent concentrations. The 96hrs fifty present lethal concentration (LC50) and acute toxicity unit (ATU) values for inlet and outlet wastewater were 30.5% (v/v), 3.279, 71.5% (v/v) and 1.399, respectively. The safe effluent concentration for both inlet and outlet wastewater is set to be 3.05% and 7.15%, respectively. As a whole the present results revealed that the total efficiency level of the treatment plant to remove toxicants was 57.33% (v/v). However, efficiency of the treatment plant should be improved to use the water for irrigation and other domestic purposes; otherwise, the use of the wastewater at present condition is unsafe.
SALIENT REGION DETECTION BASED ON AVERAGE SALIENCY MAP WITH SPATIAL VARIANCE

Salient region detection is one of a pre-processing method which are useful for several image processing application. Image processing application includes image retrieval, object recognition, face recognition, adaptive compression and image retargeting. Thus salient region detection is detecting the more attracted regions in an image. It can be define as contrast difference between the visually attracted regions and its neighbourhood in an image. In this paper we proposed a novel method by creating a saliency map by average of the three feature maps added by colour spatial variance of an image. Main feature maps are frequency map and spectral map.
An Efficient Ciphertext Policy Attribute based Encryption Scheme for Hierarchical File Sharing in Cloud Computing

— Cloud file sharing refers to a range of cloud services that allows people to store and synchronize documents, photos, videos and other files in the cloud—and share them with other people. These services also allow users to share and synchronize data among multiple devices for a single owner. These services are accessible through desktops, notebooks, smart phones and media tablets, and provide a simple mechanism for synchronizing data across multiple devices. In cloud computing, to protect data from leaking, users need to encrypt their data before being shared. In this paper we propose an efficient encryption scheme based on layered model of the access structure is proposed in cloud computing, which is named file hierarchy CP-ABE scheme (or FH-CP-ABE, for short). FH-CP-ABE extends typical CP-ABE with a hierarchical structure of access policy, so as to achieve simple, flexible and fine-grained access control.
Encryption of Message Block using Binary Tree in Block Cipher System: An Approach

Block cipher system is generally used to encrypt a block of message instead of character by character encryption. Block cipher produces more complexity than stream cipher system. The complexity of block cipher can be increases drastically when we use the binary tree concept for encryption of the message. In this paper, we provide an approach which increases the complexity of the block cipher system and cannot be broken easily. We are also looking the performance of this approach against some standard approaches.
Ethanolic extract of Ficus religiosa prevents Cisplatin toxicity by Enhancing antioxidant status in Mice

The clinical use of Cisplatin, has been limited due to the major side effects such as nephrotoxicity and hepatotoxicity. Recent reports have shown that the impairment of antioxidant defense systems is the main offender for side effects of cisplatin. The present study was undertaken to assess the protective effect of aqueous extract of Ficus religiosa, leaf against Cisplatin-induced oxidative dysfunction in mice. Three different doses of Ficus religiosa, leaf (250, 500 and 1000 mg/kg) were administered daily for fifteen days and Cisplatin was administered intra-peritoneally in 3 days interval. The animals were sacrificed 24 h after the last treatment. The liver and kidney were prepared for the biochemical investigations. Cisplatin significantly induced oxidative stress, ultimately leading to increased serum levels of liver enzymes such as alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, total bilirubin and Lactate dehydrogenase. Renal toxicity also characterized by a significant increase in concentrations of serum creatinine and blood urea nitrogen. Supplementation of Ficus religiosa ameliorated the side effects of Cisplatin referenced to improved antioxidant status of liver and kidney. The results of this study concluded that the extract of Ficus religiosa leaf could be proposed to protect the liver and kidney damage induced by Cisplatin. This protective effect might be correlated with the antioxidant properties of leaves extract of Ficus religiosa.
ROLE & FUTURE ASPECTS OF PRIMAQUINE IN MALARIA THERAPY

Malaria is major problem in malaria prone zone. This review gives a detail idea about primaquine role and it’s significance in malaria therapy. Nanomedicine drug-delivery systems of primaquine may be developed in the effort to overcome delivery barriers and short half life. Some research articles have shown that primaquine derivatives show better results in comparison to primaquine. In relapsing malaria treatment primaquine 30 mg daily dose is necessary. To overcome this problem transdermal drug delivery system of primaquine may be good choice. Transdermal drug delivery system can minimize side effects like abdominal pain, which produced by orally taken primaquine. In this review, the attention is focused to give a basic idea about primaquine role and its future consideration.
Performance evaluation of filters VDF and VMF against impulsive noise in video sequences

— In this paper, we present a study on VDF and VMF filters in terms of efficiency for filtering impulsive noise in video sequences. These nonlinear filters are used in improving the quality of image/video and especially the noise attenuation and detail preservation of the image/video. We evaluate the performance of the two filters by using three CIF (Common Intermediate Format) sequences (Akiyo, Foreman and Tb420). We used for the evaluation of filter performance three quality assessment criteria (PSNR, SSIM and DVQ). For all quality metrics (PSNR, SSIM, DVQ), we can conclude that the VDF filter gives poor quality scores compared same to the noise sequence. On the other hand, the VMF filter provides good performance against impulsive noise. We test the performance of two filters using our metric PSNR with CSF. For short viewing distance, the VMF filter is more efficient for the less eventful sequences. For long viewing distance, the VMF filter is more efficient for the most animated sequences.
A New Neuro-Fuzzy Classifier based on TSK Model

This work presents a Neuro-fuzzy classifier based on Takagi-Sugeno-Kang (TSK) model that train data using scaled conjugate algorithm. The aim of the neuro-fuzzy classified is to optimize the results of the modified k-means algorithm proposed earlier [1]. The previously proposed modified k-means algorithm is two phase algorithm. The first phase identifies actual number of clusters and second phase gives clustering results. Number of clusters and cluster centers are initially provided by the modified K-means algorithm and then apply Takagi-Sugeno-Kang model to generate rule base and finally, speeding up Scaled conjugate gradient algorithm is used to train the model. Experiments were done on three benchmark datasets IRIS, Thyroid, Wisconsin Diagnostic Breast Cancer and one synthetic dataset to evaluate the performance of proposed neuro-fuzzy classifier.
Functional Discrimination of fMRI Data from Multiple Subjects

In this paper, we proposes a new model-free approach to analyse fMRI time series data. Instead of testing a parametric model which estimates a brain regional activity during a cognitive task, we use the synchronization of fMRI voxels as the basis of our analysis. Synchronization between large voxel cross sections are expected when the brain responds to a stimulus. The paper shows using a simple definition of synchronization that the phenomenon is insensitive to the choice of thresholds over a broad range of thresholds, and is thus statistically more robust than the average activation profile, which depends sensitively on the baseline assumed. We then explains how a functional picture of the brain’s response to a visual-motor task can be obtained by examining differential fractional synchronizations in the primary motor cortex, the supplementary motor cortex, the primary visual cortex, and the occipital cortex. Finally, the paper demonstrates an unbiased method to compare multiple subjects functionally by constructing and singular value decomposing a discrimination matrix enumerating the different synchronization patterns seen in the different subjects. Keywords— fMRI time series; synchronization; functional discrimination; subject-to-subject comparisons; singular value decomposition
Wavelet-Based Multi-Modality Medical Image Fusion CT/MRI for Medical Diagnosis Purpose Human Visual Perception Compute-Processing Image

: Medical image fusion has been used to derive useful information from multimodality medical image data. The idea is to improve the image content by fusing images like computer tomography (CT) and magnetic resonance imaging (MRI) images, so as to provide more information to the doctor and clinical treatment planning system. This paper aims to demonstrate the application of wavelet transformation to multi-modality medical image fusion. This work covers the selection of wavelet function, the use of wavelet based fusion algorithms on medical image fusion of CT and MRI, and the fusion image quality evaluation. We introduce the peak-to-peak signal-to-noise ratio (PSNR) method for measuring fusion effect. The performances of other two methods of image fusion based on pyramid-decomposition and simple image fusion attempts are briefly described for comparison. The experiment results demonstrate the effectiveness of the fusion scheme based on wavelet transform.
Quality of Life in Crohn’s Disease : Post Surgical Evalutation

Aim: Purpose of the study was to analyze the quality of life and psychiatric symptomatology in post-surgical Crohn’s patients. Methods: In this study were enrolled post-surgical Crohn’s patients; they were subjected to Self-Report Symptom Inventory – Revised (SCL-90-R) to analyze general psychiatric symptomatology; Hamilton depression rating scale (HAMD) to analyze depressive symptomatology; SHORT FORM-36 (SF-36) to evaluate their quality of life. Results: The sample has major limitations in phisical activities; they complain about daily activities; they consider their general health as the most poor and destined to deteriorate further in time. Conclusion: Post-surgical Crohn’s disease patients present a significant impairment in several areas of life quality and a psychiatric symptomatology that shows emotional – psychological discomfort due to the underlying disease and to the recurrence fear.
HPTLC method validation of reserpine in Rauwolfia serpentina – A High Value medicinal Plant

Rauwolfia serpentina medicinal value well known in various system of medicine all over the world. Reserpine is an indole alkaloid and is important constituent of Rauwolfia which is reported to posses anti hypertensive and tranquilizing activity. In the present study High Performance Thin Layer Chromatography has been developed for quantification of Reserpine in Rauwolfia and its allied preparations, which was found to be rapid and accurate. The method proposed was highly precise, sensitive, specific and reproducible with an average recovery of 78%. The limit of quantification was observed to be 112 ng. [Hema Lohani, Harish Chandra Andola* Ujjwal Bhandari, Nirpendra Chauhan. HPTLC method validation of reserpine in Rauwolfia serpentina – A High Value medicinal Plant. Researcher. 2011;3(3):34-37]. (ISSN: 15539865). http://www.sciencepub. net.
ANALYSIS OF FACE RECOGNITION SYSTEM WITH FACIAL EXPRESSION USING CONVOLUTIONAL NEURAL NETWORK AND EXTRACTED GEOMETRIC FEATURES

Faces contain a great deal of valuable information in automatic image processing to extract semantic content for effective analysis and pattern recognition. It requires efficient algorithms that are capable to extract relevant semantic information. Recognizing a person on a photograph tells a lot about the overall content of the picture. The principal aim of facial analysis is to extract valuable information from face images such as position in the image, facial characteristics, facial expressions, the person’s gender or identity. Now we consider the most important approaches to facial image analysis and present novel methods based on convolutional neural networks to detect, normalize, and recognize faces and facial features. In this paper the problems of automatic appearance-based facial analysis with machine learning techniques are described and common specific sub-problem like facial feature detection, analyzing geometric features and face recognition which are crucial parts of many applications in the context of indexation, surveillance, access-control or human machine-interaction are handled. To tackle these problems a new technique called Convolutional Neural Network (CNN) is used which is inspired by biological evidence found in the visual cortex of mammalian brains and can be applied to many different classification problems. The proposed system is a CNN-based method for automatic facial feature detection and extraction that employs a hierarchical procedure which first detects the eyes, the nose and the mouth and then refines the result by identifying 10 different facial feature points. The detection rate is 87% to 96% for different databases tolerating an error of 10% of the inter-ocular distance. Finally a novel face recognition system based on CNN architecture learning a non-linear mapping of the image space into a lower dimensional sub-space where the different classes are more easily separable. This approach produces better result for different facial databases in detection and recognition with classical face recognition approaches using PCA or LDA.Back propagation algorithm is used as learning algorithm for CNN which is a Multi-Layer Perceptrons. A Siamese CNN is used for face verification by receiving two face images and comparing to decide
Inter-Channel Interference (ICI) Removal based on MMSE and LMS Equalizer in Communication System

: In this paper, we present the effect of inter channel interference (ICI) on the performance of communication system. Different equalization techniques are employed to reduce the effect of inter-channel interference. Here, we use two equalization techniques to reduce the effect of inter-channel interference. Firstly, Minimum mean square error (MMSE) equalization technique is applied at the receiver to reduce the effect of ICI in channel by applying inverse filtering. Secondly, we use least mean square (LMS) equalization technique is apply at the receiver to reduce the effect of ICI in channel. These techniques are used to compensate the effect of inter-channel interference that is introduced in the system by impulse response of the channel. Experimental results are performed to evaluate the effectiveness of the proposed equalization techniques. Simulation result shows that the bit error rates versus EbNo with 3-taps MMSE and LMS equalization to reduce the effect of inter-channel interference. As the number of tap increases the performance of the equalizer improves. Results reveal that the LMS equalizer performed better than MMSE equalizer in terms of bit error rate.
Performance Evaluation of Adaptive Line Enhancer Implementated with LMS, NLMS and BLMS Algorithm for Frequency Range 3-300Hz

In this paper, an adaptive line enhancer using LMS,BLMS and NLMS algorithm has been simulated for low electromagnetic frequency range (ELF&SLF-3to300Hz.) range using MATLAB software. Firslty,Sinusoidal wave is corrupted with the white noise then we have adaptively filtered corrupted wave over the required frequency range, but in the paper only 60Hz result have been shown. Later on , the adaptive behaviour of the algorithms is analyzed and performance criteria are used in the study of these algorithms are : the minimum mean square error(MSE) and Signal to noise ratio. The paper compares a performances of ALE using LMS, NLMS and the BLMS algorithms for a given range. Different SNR ratio level is obtained as the step-size is changes, their relative SNR result is shown.
Development Characterization and Evaluation of Nasal in situ Gel containing Anti-Asthmatic Drug

Nasal gels are high-viscosity thickened solutions or suspensions. The advantages of a nasal gel include the reduction of post-nasal drip due to high viscosity, reduction of taste effect due to reduced swallowing, reduction of anterior leakage of the formulation, modification of irritation by using soothing/emollient excipients and target to mucosa for better absorption. In-Situ gelation is a process of gel formation at the site of action after the formulation has been applied at the site. In-Situ gel phenomenon based upon liquid solution of drug formulation and converted into the semi-solid mucoadhesive key depot. It permits the drug must be delivered in a liquid form or solution form. International Journal of Pharma Research and Health Sciences
Image Compression Technique using Two Dimensional Discrete Cosine Transform

—This paper presents an architecture for the fast computation of the 8×8 two dimensional (2D) Inverse Discrete Cosine Transform. The proposed method is the permanent storage of the Basis Matrices of the 8×8 2D Discrete Cosine Transform (DCT). The sparseness property of the 2D DCT coefficient matrix, the computational time decreases as the number of nonzero coefficients decreases. The proposed structure computes all 64 pixel luminance values of an 8×8 block simultaneously. The design was implemented in Xilinx Xc3s500 board and the design used 23% LUT’s and 33% of the total slices. The total power consumed by the device was 0.081W.
Image Inpainting Using Second-Order Derivative-Based Autoregressive Model

: This paper introduces a new method, based full range autoregressive model, for image inpainting. The model parameters are estimated using iterative technique and Bayesian methods. Based on the parameters, coefficients of the model are computed. Autocorrelation coefficients are computed using the model coefficients. Based on the autocorrelation, the damaged region or noised regions are identified. The identified region is inpainted the full range autoregressive model. The performance of the proposed method is measured based on the MSE and PSNR values. The obtained results reveal that the proposed method yields better results than the existing methods.
Solving Big Data Challenges for Enterprise Application Performance Management: A Study

With the increase in the size of data for small as well as big enterprises the complexity of managing the mammoth size of data has also increased. This increase in quantum of data has resulted in need for managing, monitoring and analyzing the stored data has also increased many folds. A number of companies have built sophisticated monitoring and management tools that automatically mitigate the impact of risks due to the mammoth size of data resulting in proper utilization of resources. These tools are known as enterprise application performance management tools. This paper gives an insight into the challenges that enterprises are facing at present due to the increase in the size of data and how to mitigate the impact of these challenges without compromising on quality of the information retrieved from the data. The main aim of this paper is to increase the awareness about the importance of using automated performance management tools to monitor and manage information processing within optimal time and using optimal resources.
SEMU - An Adaptive Policy - Control Based Routing Approach to Provide Effective QoS over Wireless Sensor Networks

Error control mechanism carries vital importance in research aspects of Wireless Sensor Networks (WSNs) due to its limited energy constraints and minimal support for power communication. The survey and analysis provides a comprehensive comparison of FEC / ARQ and hybrid ARQ schemes in WSN. This paper proposes an adaptive QoS routing scheme called SEMU, to support in routing for each variable service sessions based on policy-control rules in order to control transmission errors for different applications such as streaming content delivery over WSN networks using route metrics. A real time test bed approach along with a case study is adopted to test the data error during transmission along with its effective delay and latency. The test results show that SEMU performs to a scalable effective QoS compared to hybrid ARQ schemes and LEACH schemes with minimal latency and delay.
Distance and Priority Based Routing Protocol in VANET

: Vehicular Ad-Hoc Network mainly involves Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communication. This communication accelerates in reducing number of accidents, avoiding traffic congestion, enhancing the transport facility with the aid of infotainment and entertainment application. One of the major challenges of VANET application is in routing the packet in efficient manner since the network topology is dynamic. In this paper, we proposed a solution that improves the efficiency of Distance Based Routing protocol by using a priority of messages. This paper presents a Distance and Priority based Routing Protocol in Vehicular Ad hoc Network (VANET). We focus mainly on a emergency message routing in vanet. The proposed protocol, is evaluated using simulation software NS-2. The performance parameters include average delay, percentage of message reception. The results show that this protocol achieves both message prioritization and maximum delivery of messages in fully dynamic environment.
An Efficient Technique for the cloud Data Retrieval using IBE

— Since Cloud computing is a new fields having more research work to be done specially in the field of security. Cloud Computing enables various users to send the data over internet which is then stored at data centers, but there is less chance that data is secure and can’t be access by the un-authorized users or chances of data loss. Hence Security is an important concern in the cloud computing. Although there are various techniques implemented for the security of cloud data so that it can be access by the un-authorized users and privacy is maintained on user’s data. Here in this paper a new and efficient technique is implemented for the security of cloud storage data and quick retrieval of cloud data.