Miracle-dz/UniFAR-FTUs huggingface dataset:
Advanced Data Fusion for Classification and Extraction

: This paper describes the fusion of information extracted from multispectral digital aerial images for land use classification. The proposed approach integrates spectral classification techniques and spatial information. The multispectral digital aerial images consist of a high resolution panchromatic channel as well as lower resolution RGB and NIR channels and form the basis for information extraction. Our land use classification is a 2-step approach that uses RGB and NIR images for an initial classification and the panchromatic images as well as a digital surface model for a refined classification. The digital surface model is generated from the high resolution panchromatic images of a specific photo mission. Based on the aerial triangulation using area and feature based points of interest we are able to generate a dense digital surface model by a dense matching procedure. This approach produces the desired land use classification results and exploits the high redundancy of the source data set to automatically perform after a short interactive training phase.
NEURO-FUZZY SYSTEM FOR MANAGING THE AERATION MODE IN THE PERIODIC PROCESS OF FERMENTATION

The given article describes a new intelligent decision support system for managing the aeration mode in a complex periodic fermentation process. Given the instability and low repeatability of the process, the procedure for fuzzy neural network training has been implemented by means of a hybrid method. The given method of training uses both the backpropagation algorithm and the least square method. It was also shown that, under conditions of low repeatability of the fermentation process, the use of information on the dynamics of the process state parameters – the concentration of gases О 2 and СО 2 dissolved in the liquid – corresponds to the efficient distinction of the biomass growth and biosynthesis modes of the target product and contributes to the reliability of the decision made. The results of modeling the fuzzy neural network using FlexTools and Fuzzy Logic Toolbox for MATLAB confirm the effectiveness of the proposed approach to developing an intelligent decision support system for managing the weakly formalized fermentation process.
An Efficient Interesting Weighted Association Rule Mining

: Mining association rules is an important problem in the field of data mining due to its wide applications. Weighted Association rule mining has recently been proposed, in which transactions are attached with weighted values according to some criteria. The weights in these approaches may be thought of as an extension of traditional support in association-rule mining. Weighted association rules can be discovered in a variety of forms, like weighted association rules, fuzzy weighted association rules, and weighted utility association rules. We have used HITS algorithm to automatically calculate transaction weights. We presented a new algorithm for finding interesting weighted association rules. The interestingness of an item can be computed at the multiplication of weight and support. Interestingness, in some case, can be “the potentially useful for finding association rules. Our experimental result shows that proposed interesting weighted Association Rule Mining out performs the existing algorithm in terms of efficiency, time and valued rules.
PHASE PRESERVING DENOISING AND BINARIZATION OF ANCIENT DOCUMENT IMAGE

: In this paper, we present a phase-based binarization model for degraded document images, also a post processing method that can improve any binarization method and a ground truth generation tool. Usually, many binarization techniques are implemented in the literature for different types of binarization problems. It include an adaptive image contrast based document image binarization technique that is tolerant to different type of document degradation such as uneven illumination document smear involving smudging of text, seeping of ink to the back side of page, degradation of paper ink because of aging and so on similar reasons. An objective evaluation based methodology for handwritten document image binarization techniques that aims to reduce the human involvement in the ground truth construction and consecutive testing Image binarization is the method of separation of pixel values into dual collections, foreground for black and background for white. In images the grayscale and color images into black and white images. Ancient and degraded document improvement using image processing is attracting many researchers in the recent period. Binarization is very popular cleaning the document for further processing.
TIRE PRESSURE MONITORING SYSTEM INTERFERENCE SUPPRESSION USING BEAM FORMER TECHNIQUES

Abstract: This paper presents the interference suppression based on different beam form techniques. The Tire Pressure Monitoring System (TPMS) is a system for measuring the temperature and pressure of each tire of vehicles. In the past minimum-variance distortion less-response (MVDR) technique is used to removing the external interference and receiving the accurate data, but it is high computational complexity and high power consumption. In this work, we suggested a recursive least square algorithm (RLS) based on angle of arrival for suppress the interference, low computation complexity and low power consumption of a battery. The simulation results show the performance of different beam form techniques.
MINIMIZATION OF HANDOVER USING EFFICIENT ROUTING IN MOBILE WIRELESS SENSOR NETWORK

MWSN is routing data from its source to the destination. When data has to transfer from source to destination it has to go through by various nodes which are considered as hops. When data pass from one hop to another its link deteriorate which cause the problem of handover. Nodes have to search for other relay nodes without interrupting the communication channel. In previous work three method used and this work was conducted with the IEEE 802.15. 4 standard but this also have some drawbacks like low bandwidth, operating frequency and network range. Our goal is reduce the unnecessary handover. For this work, we will use 802.11x IEEE standard, to predict the future position of nodes so that if they are going outside from the range of node than they become active mode and also to use duty cycle to improve the network performance.
An intervention to manage depression after hip fracture

AUTHORS Debbie Duignan, RMN, BA, is research sister, University of Manchester; Yvonne Woodward, BSc, MRes, is trainee clinical psychologist, University of Liverpool; Emily Daniel, BSc, is research assistant, University of Manchester; Alistair Burns, MBChB, FRCP, FRCPsych, MD, MPhil, DHMSA, is professor of old age psychiatry, University of Manchester. ABSTRACT Duignan, D. et al (2007) An intervention to manage depression after hip fracture. Nursing Times; 103: 28, 32–33. Depression can have a negative effect on recovery following hip fracture. In a large trial a psychiatric nursing intervention proved effective in reducing mental health difficulties and promoting recovery. This article outlines how the intervention can be applied in practice and includes a comprehensive case study.
Cyclin Dependent Kinase 2 Inhibitors an Artificial Neural Network Regression QSAR Study

Cyclin dependent kinase (CDK) plays a major role in regulating the cell dynamic. Kinases are present in all known eukaryotes and their regulatory function pathway was evolutionary conserved, suggesting this pathway plays a dominant role in cell growth control and its disruption may result in cell death. Three-dimensional quantitative structure-activity relationships (3D-QSAR), molecular docking and molecular dynamics (MD) simulation strategies were applied to investigate the molecular interaction between active ligands and cyclin dependent kinase 2 (CDK2). A QSAR model was computed using artificial neural network (ANN) regression, with a good predictive ability in internal and external validation. Results were compared with the prototype inhibitor of CDK, Staurosporine. A mixed analysis embodying the QSAR model, molecular docking and molecular dynamics, enabled the pharmacophore high definition. Data provided by MD were highly consistent with the findings of 3D-QSAR model
Predicting Rate of Biogas Production from Abattoir Waste using Empirical Models

Rate of biogas production using Zango-Zaria abattoir waste as substrate was monitored in a 10 litter laboratory scale batch reactor. 2.5 kg of the substrate with substrate to water ratio of 1:1 was used. The retention time was found to be 47 days. Analysis of the substrates gave an average COD of 19350 mg/L, average carbon-to-nitrogen ratio of 14.95, and concentrations of inhibitory substances below the minimum inhibitory values. AAS analysis of the biogas using NDIR Gas Analyzer, GASBOARD 3100P indicated that its' methane and CO2 content were 67.76 % and 31.13 % respectively.Two empirical models based on the Gompertz and the Modified Logistic equations were used to fit the experimental data based on non-linear regression analysis using Solver tool in Microsoft Excel. Gompertz model gave a better goodness of fit than the Modified Logistic model with correlation coefficients of 0.998 and 0.996 for Gompertz and Modified Logistic models respectively.
Performance Analysis of Space-Time Block Codes Achieving Full Diversity with Linear Receivers Using MIMO

-Space-time block codes have been shown to perform well with Multiple-Input Multiple Output (MIMO) systems. STBC is a MIMO transmit strategy which exploits transmit diversity and high reliability. The existence of real orthogonal design has been proved by Radon. As for a complex orthogonal design, it was proved by Tarokh that for the corresponding STBC one cannot achieve a full transmission rate and full diversity when the number of transmitting antennas is larger than two. Therefore, some Quasi-orthogonal space-time block codes have been designed. In most of the existing space-time code designs, achieving full diversity is based on maximum-likelihood (ML) decoding at the receiver that is usually computationally expensive. Orthogonal space-time block codes (OSTBC) achieve full diversity when a linear receiver, such as, zero-forcing (ZF) or minimum mean square (MMSE), is used. By choosing different parameters, codes with different symbol rates and orthogonality can be obtained.In this paper, we compare the performance of a family of space-time codes that achieve full diversity when linear receivers, such as, zero-forcing (ZF) or minimum mean square error (MMSE) is used.
A New Technique of Mastopexy for Mastoptosis: With the Upturned Glandular Flap

A new surgical procedure was introduced for correction of moderate mammary ptosis in this paper. The double-ring incision around areola was taken, tongue-shaped gland flap at the lower part of breast was turned over and filled in the posterior space of breast. The glands at both sides of the lower part were sutured together, and the basal part of the breast was tighten fully. Then, the upper pole gland was sutured by raising so that the nipple-areola complex is fully raised. The breasts were conical through this shaping, thus the correction effect of breast ptosis was satisfactory. This technique is ingenious in design, convenient in operation and exact in curative effect. It can be used as one of the options
DRAG AND DROP:DATA TRANSFER BETWEEN TWO DIGITAL DEVICES-A SURVEY

— In computer graphical user interfaces, Drag and Drop is a pointing device gesture in which the user selects a virtual object by “grabbing” it and “dragging” it to different location or onto another virtual object. This drag and drop operation is basically the operation of moving or coping files from one location to another. It is one type of data transferring from one location to another. In this paper, we have shown different approaches for transferring data between two digital devices which looks likes the operation of Drag and Drop. There is comparison of all methods are also presented. All the methodologies have been tried to achieve Augmented Reality for transferring data from one screen display to another.
Providing Security in Granting Agency Using Workflow CRBAC Model

Summary There have been many security solutions to secure representation in the work flow used in business processes and Grid Networks. Most of these solutions try to provide maximum security in workflow processes and most of them are used Role-Based Access Control model (RBAC). Capability Role-Base Access Control (CRBAC) is one of the models that are used to model RBAC which in this paper, we introduce these models and our proposed solution. Central idea of the model and the solution is secure Transfer ability of one user to other users within a safe and secure workflow.
Normalized graph-cut based Necrotic Image Segmentation of Brain Tumours

— This paper aims at enhancing Necrotic regions based Normalized graph –cut segmentation of Brain Tumour on contrast T1 Magnetic Resonance (MR) Images. Image segmentation means a process of partition an image into more distinct regions. The brain tumour segmentation methods rely on the intensity enhancement. A large Varity of different tumour segmentation approaches used for medical image segmentation. Among them, a clustering method have been investigated and used. In this paper, CA (Cellular Automata) based seeded tumour segmentation algorithm is proposed. Which determine the Volume of Interest (VOI) and seed selection. First, establish the connection of the CA-based segmentation to the graph-cut method to show that the iterative CA framework solves the shortest path problem. This paper describe segmentation method consist of two phases. In the first phase, the MR Image is acquired from patient database and contrast enhancing the image. In the second phase, the CA algorithm run twice for background seed (healthy cell) and foreground seed (tumour cell) for probability calculation. Furthermore, apply Graph-Cut (GC) method to differentiate necrotic and enhancing tumour tissue content, which gains importance for a detailed assessment of radiation therapy response.
Accurate Image Search using Local Descriptors into a Compact Image Representation

Progress in image retrieval by using low-level features, such as colors, textures and shapes, the performance is still unsatisfied as there are existing gaps between low-level features and high-level semantic concepts. In this work, we present an improved implementation for the bag of visual words approach. We propose a image retrieval system based on bag-of-features (BoF) model by using scale invariant feature transform (SIFT) and speeded up robust features (SURF). In literature SIFT and SURF give of good results. Based on this observation, we decide to use a bag-of-features approach over quaternion zernike moments (QZM). We compare the results of SIFT and SURF with those of QZM. We propose an indexing method for content based search task that aims to retrieve collection of images and returns a ranked list of objects in response to a query image. Experimental results with the Coil-100 and corel-1000 image database, demonstrate that QZM produces a better performance than known representations (SIFT and SURF).
Hybrid Speech Segmentation Algorithm for Continuous Speech Recognition

– In this a hybrid segmentation methods are proposed for Automatic Speech Recognition. The segmentation methods are based on time domain features and frequency domain features . The time domain features are short time energy, short time zero crossing rate. The frequency domain features are spectral centroid and spectral flux. After features are extracted, a simple thresholding method is used to detect the word boundaries. The segmentation is used to divide the continuous speech into a sequence of words or sub words. In this project, short time energy and spectral centroid are combined. Among these methods, hybrid of short time energy and spectral centroid has high segmentation accuracy. The results shown to be computationally efficient for real time applications and it perform better than conventional methods.
Obstructive Sleep Apnea and Lymphocytic Sialadenitis: The Focus isn’t Just Sjögren’s Syndrome

Objective: We examined the presence of lymphocytic infiltration and measured focus scores in uvular specimens of patients with obstructive sleep apnea (OSA). Methods: We reviewed the histopathology of 101 uvular specimens obtained from patients with OSA and uvular hypertrophy. A lymphocyte focus score assessment was performed for each case. Results: Of the 101 cases, 42 (42%) cases had a positive focus score (score ≥ 1). Of those cases with a positive focus score, 22 (52%) had a focus score of 1, 14 (33%) had a focus score of 2, 4 (9%) had a focus score of 3, and 2 (5%) had a focus score of 4. Of the 59 patients (58%) with negative focus scores, 39 (66%) had minor lymphocytic infiltrates; 17 (29%) had features of chronic sialadenitis or extensive fibrosis; 3 (5%) had salivary mucosa without any apparent lymphocytes. Conclusion: Our findings indicate that patients with OSA may exhibit focal lymphocytic sialadenitis (FLS). It remains to be determined whether mucosal changes occur elsewhere in the oral cavity of patients with OSA. If so, the presence of OSA may complicate the histologic evaluation of Sjögren’s syndrome. Further investigations to determine the prevalence of FLS in the uvulae of individuals without history of OSA, the extent of FLS elsewhere within the oral cavity of patients with OSA and the relationship between the local inflammatory reaction and the systemic consequences of OSA are needed.
in Computer

— Monitoring and tracking vehicles for law enforcement and other security purposes is difficult problem because of number of automobiles on road today. It is time consuming for officer to physically check license plate of every vehicle. There must be a way for detecting, identifying and tracking vehicle path without constant human intervention. As a solution, we have proposed a system that will extract the licence plate number of a vehicle from given video stream. All the processing of video will be perform on Microsoft Azure cloud. An operator only specifies license plate number. Then video streams are automatically fetched from cloud storage. Framing of that fetched video will be performed on a single virtual machine and then output obtained by framing will be parallely processed on multiple virtual machines for processing purpose. Result will be in the form of licence plate number in text format along with the path travelled by the vehicle by considering respective CCTV ID’s.
Factors Influencing Consumers’ Intentions towards Purchasing Islamic Hotel Service: Moderating Role of Religiosity

The aim of this study is to investigate the influencing factor on consumers’ intentions towards purchasing Islamic hotel service. It also investigates the moderating influence of religiosity on these relationships. Data collected using the survey method and 200 usable questionnaires were received from respondents. Regression analysis was conducted to test the hypothesis. The results show a positive and significant relationship between halal awareness, norms and attitude. It also shows that there are non-significant relationships between brand image and price and consumers ‘intentions toward purchasing Islamic hotel service. The study indicates that religiosity has a moderating effect on the relationships between the factors (halal awareness and subjective norms) and consumers’ intentions towards purchasing Islamic hotel service. By understanding the relationship among the constructs in the research model, hotel managers could improve consumer intention. They can focus on the halal awareness, subjective norm and religiosity in their marketing activities. 1 Corresponding author’s email: raselataul@gmail.com International Journal of Management, Accounting and Economics Vol. 5, No. 7, July, 2018 ISSN 2383-2126 (Online) © Authors, All Rights Reserved www.ijmae. com 483
Dementia Knowledge among Kuwait University Students: a Descriptive Study

Background: In regards to prevention and early intervention for dementia, knowledge of the population is a key factor. The aim of this study is to determine the level of understanding about dementia among students at all campuses at Kuwait University and so be able to better plan for future intervention. Methods: A cross-sectional study was conducted in order to examine the knowledge of dementia among Kuwait University students across different campuses. An Arabic version of the DKAS was cross culturally developed and used in this study. The comparison of the DKAS subscales and the dementia total score were obtained. Results: A total of 1350 students participated in this study. The results indicated that the students in different campuses had a significant difference in the dementia total score (p = 0.000) as well as a significant difference between all subscales of the DKAS. Total score of dementia knowledge among students in all campuses was a mean of 15.09 out of 25 and S.D of 3.05. The Causes and Characteristics subscale was (p = 0.000) with a mean of 4.22 out of 7. The Communication and Behavior subscale was (p = 0.005) with a mean of 2.88 out of 6. The Care Consideration subscale was (p = 0.019) with a mean of 4.67 out of 6. The Risks and Health Promotion subscale was (p = 0.000) with a mean of 3.31 out of 6. Conclusion: The baseline knowledge of the students was moderate. Although there were differences in students’ knowledge across all campuses, all students required improved knowledge of dementia. This will help us to implement more appropriate care and support.
Design and Implementation of Hybrid CMOS-SET Half Adder and Full Adder Circuits

Single Electron Transistors (SETs) have high integration density and ultra-low power consumption, which makes them promising candidates as basic circuit elements of the future generation ULSI circuits. However, Single electron transistors have extremely poor driving capabilities so that direct application to practical circuits is as yet almost impossible. A technique to overcome this problem is to build hybrid circuits of SETs and CMOS. In this work, hybrid SET-CMOS Half Adder and Full Adder are designed and implemented. The MIB compact model for SET device and BSIM4.6. 1 model for CMOS are used. All the circuits are verified by means of T-Spice simulation software.
Enhanced Outlier Detection for High Dimensional Data Using Different Neighbor Metrics

: The task of identifying patterns that do not take after the built up customary conduct is termed as outlier detection. It has varied applications in number of fields like fraud detection, intrusion detection, abnormal weather detection, detecting unexpected entries in text data, etc. Majority of the aforementioned applications are concerned with high dimensional data. As the dimensions of data increases, performance of many traditional outlier detection methods deteriorates because of curse of dimensionality. Here a novel method for outlier detection is proposed. The proposed system uses reverse nearest neighbor along with shared nearest neighbor. Reverse nearest neighbor gives the count of number of times a particular object occurs among k nearest neighbors of all other points in a data set. Shared nearest neighbor finds similarity between points. Shared nearest neighbor when used as a secondary measure can beat the curse of dimensionality.
Modeling of MIMO propagation in Tunnels

Wireless communication draws the attention of various and this is because, it increases in data throughput and also the link range without the increased transmit power or additional bandwidth. The explanation and/or prediction of the inside distribution field such tunnels are excited by the electric antenna which is essential for deployment of wireless communication system. Primary objective of the study is to understand and model propagation of multiple input multiple output channel through a tunnel. Secondary objectives are to analyze the applications of modal theory, To explore how modal theory can be applied in identifying MIMO propagated through tunnels and to simulate MIMO propagation through tunnel using MATLAB.