Miracle-dz/UniFAR-FTUs huggingface dataset:
Spectrum Sensing Technique Based on CAF and 3rd Order Cumulant for Cognitive Radio

Cognitive radio system provide us a solution for spectrum congestion problem, but the effectiveness of the system is only depends on the technique used for spectrum sensing, that how effectively the detection is performing at very low SNR. In this research paper we proposed a technique of spectrum sensing based on CAF and third order cumulant. And the proposed algorithm effectively able to detect the presence of primary user at very LOW SNR, as compared to existing technologies present in literature.
Analysis of D2D Communication over N *Nakagami Channels

In this paper, performance of device-to-device (D2D) communication system over an N*Nakagami channel is presented. The N*Nakagami distribution can effectively model cascaded Nakagami fading channels. Multiple co-channel interferers are considered in the system. The channel of the co-channel interference is assumed to be Gamma distributed. The expressions for the probability density function (PDF) and cumulative distribution function (CDF) of the signal-to-interference ratio (SIR) are presented. Using the PDF expression, expressions of the outage probability, success probability, outage capacity, channel capacity and symbol error rate (SER) are then presented. The expressions are functions of path-loss exponents, D2D and interference channel fading parameters, distance between interferers and the D2D receiver, and the distance between D2D pair. The effects of D2D fading channel parameters, interference channel fading conditions, and the path-loss conditions on the performance of D2D system are then analyzed and discussed.
Improved Object Detection Algorithm using Ant Colony Optimization and Deep Belief Networks Based Image Segmentaion

— Object detection is a very important application of image processing. It is of vital importance for object dynamic surveillance and other applications. So far, object detection has been widely researched. It shows an efficient coarse object locating method based on a saliency mechanism. The method could avoid an exhaustive search across the image and generate a small number of bounding boxes. After that, the trained DBN is used for feature extraction and classiﬁcation on sub-images. This paper represents that the a variety of strategies based on object detection and efficiency of object detection framework using a saliency prior and DBNs for remote sensing images. This research works proposed an efficient object detection using the ant colony optimization and deep belief networks. The motivation behind the proposed approach is easy and efficient .
Development of a Real-Time Activity Classification and Stability Assessment System for Activity of Daily Living

Our daily life is composed of various human movements known as activities of daily living (ADLs), which include standing, sitting, and walking. Under standard conditions, these activities can be performed during daily life without conscious thought. However, an individual’s ability to complete ADLs can be jeopardized by environmental, physical, and biological conditions such as a slippery surfaces, uneven floors, or degeneration of movement control due to factors including chronic disease or increased age. This ultimately leads to a decrease in quality of life [1,2]. Under these circumstances, providing real-time stability assessments for real-life situations becomes crucial [3]. Activity classification is a recently developed concept utilizing wearable [4-6] sensing technology to automatically recognize different activities [7,8]. To extract authentic information on ADLs in real-life situations, wearable sensing technologies must be unobtrusive, reliable, and capable of continuous, long-term measuring and recording. One type of biomechanical sensor, the accelerometer, has been used to measure both tilt angles under static conditions and applied acceleration along sensitive axes in dynamic situations; a combination which makes them superior to another current sensor technology [8-11].
Implementing Gronroos Service Quality Model: The Role of Image and Service Quality Perception on Customer Satisfaction in the Iran Hotel Industry

Today's service Industry, particularly hotels, faces increasing competition in the hospitality industry. In such an environment, differentiation in offering services is necessary for managers. The general purpose of this research was to understand how the hotel industry can achieve more customer satisfaction based on good service quality in Mashhad. Using the SEM tools of Linear Structure Relation (LISREL) to verify the various path relations, this study developed and empirically tested a model examining the relationship among functional quality, technical quality, image and service quality perceptions on customer satisfaction. The researchers collected approximately 400 questionnaires from customers who used about three days of service from the Iranian hotel industry to test this model. After analyzing the data, all of the research hypotheses were strongly accepted in this population. Thereby providing crucial implications for managers of Iranian tourism and hotel service quality. Recommendations for marketing strategies were provided as well.
REDUCING THE SEARCH SPACE FOR INTERESTING PATTERNS FROM UNCERTAIN DATA

---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - Big data is a term for referring too large and complex data sets that are difficult to process and store with the existing technologies. Data in the world is growing so fast in such a way that it will never be the same. The noise in that data is also increasing in the same manner, this causes a big problem in the mining. When searching in uncertain data it consists of the existential probabilities. User are only interested in an tiny portion of data. There exists many techniques for working with big data algorithms to mine the uncertain data but they are not giving satisfiable results. So we propose an algorithm which will be using the map reduce model with the apriori algorithm to mine the uncertain big datasets.
Bacterial Meningitis in Navajo Indians

DESPITE THE AVAILABILITY OF ANTIBIOTICS, bacterial meningitis still results in appreciable morbidity and mortality (1,2). Bacterial meningitis due to Haemophilus influenzae has actually increased during the antibiotic era (3-5). The incidence of bacterial meningitis varies by age, sex, social class, ethnic origin, and other characteristics in different population groups (5-9). A national study based on death certificates suggested that American Indians are especially susceptible to H. influenzae meningitis (10). To test this observation, we examined the epidemiology of bacterial meningitis in one group of American Indians, the Navajo.
FAST SINGLE IMAGE HAZE REMOVAL AND DATA HIDING SYSTEM

Haze brings trouble to many computer vision and computer graphics applications. Single image haze removal is a challenging problem. In order to solve this problem a simple but powerful method to remove haze from single image is proposed. It uses a color attenuation prior model for haze removal. A linear model is created for modeling the depth of the scene and using depth map we can easily estimate transmission map and outlook radiance, thus effectively removing haze from single image. In the dehazed image some confidential data like time at which photos are taken and temperature of the place from where the photos are taken can be made hidden and this secret message can be recovered whenever necessary
Development and evaluation of in situ thermoresponsive nasal gel system for Nardostachys jatamansi

Nardostachys jatamansi is conventionally used indigenous plant as decoction for sedative effect. The purpose of present studies was to formulate and evaluate thermoresponsive nasal gel of N. Jatamansi extract. Cold method was used for formulation of gel containing pluronic PF 127 with dried ethanolic N. Jatamansi extract, PEG 400, PEG 4000 as gelling point modifiers and methyl paraben as preservatives. Most potent ethanolic extract used in the formulation was screened by assessing righting reflex using rat as animal model. 3 Factorial design was applied for factors of amount of Pluronic F 127 and PEG4000 and were evaluated for studying their effect on gelation temperature and p. Optimized batches showed gelation point at 34C and 37 C. p between 4.1-5.3, Spreadability between 0.35-0.8cm, Mucoadhesive strength was 1524.44 and 1720.44 dyne/cm across freshly excised sheep nasal mucosa. Rheological studies indicated viscous and Newtonian behavior signifies spreadability and increased residence time. The IR spectroscopic studies indicate possibility of jatamansone in the extract and formulation. HPTLC studies revealed the presence of jatamansone similar component. N. Jatamansi was successfully formulated into stable in situ thermoresponsive nasal gel system revealed by stability studies. It may enhance patient compliance by increasing bioavailability and reducing side effects.
Interactive Image Segmentation Using Combined MRF and Ant Colony Optimization

: Image segmentation is the process that partitions an image into region. Although many literatures studied automated image segmentation, it is still difficult to segment region-of-interest in any kind of images. Thus, manual delineation is important yet. [2] In order to shorten the processing time and to decrease the effort of users, this paper introduces the approaches of interactive image segmentation method based on MRF and Ant colony optimization. In this paper we proposed a segmentation algorithm combined MRF with ACS, which not only applied ACS as optimization algorithm but also introduced the neighborhood pheromone interaction rules into ACS under MRF model. Interactive segmentation aims to separate an object of interest from the rest of an image. This problem in computer vision is known to be hard, and very few fully automatic vision systems exist which have been shown to be accurate and robust under all sorts of challenging inputs. Most of the previous works require users to trace the whole boundary of the object. When the object has a complicated boundary, or the object is in a highly textured region, users have to put great effort into iteratively correcting the selection. [1] Dirichlet Process Multiple-View Learning (DPMVL) for image segmentation technique produces very effective segmentation results as compare to previously existing techniques. DPMVL use MRF model for smoothing the segmentation. This can be further improved by using MRF-based image segmentation using Ant Colony System which works effectively and provide an alternative computational algorithm for building interactive image editing tools. In this paper, we present an interactive segmentation framework that integrates image appearance and boundary constraints in a principled way using combined MRF and ant colony optimization. We have improved proposed technique by using modified technology which have more interactivity, user control of segmentation process, and reach a satisfied result among the noise restraint, edge preservation and computation complexity. Experimental results are provided to demonstrate the superior performance of the proposed approach. A comparison with other standard operators is also discussed and the proposed method produced acceptable results within reasonable amounts of time. It is shown that the proposed algorithm based on ant colony optimization and MRF achieves better performance compared to the typical interactive image segmentation methods without using ant colony optimization concept.
An Evaluation of Seismic Response Reduction Factor for Irregular Structures Using Non Linear Static Analysis

The response reduction factor R reflects the capacity of structure to dissipate energy through inelastic behavior. It is a combined effect of over strength, ductility and redundancy. Response modification factors play a key, but controversial role in the seismic design process. No other parameter in the design base shear equation impacts the design actions in a seismic framing system as does the value assigned to R. Despite the profound influence of R on the seismic design process, and ultimately on the seismic performance of buildings in India. No scientific basis exists for the values of R adopted in seismic design codes in India. Without such a basis, it will be difficult to advance the practice of force-based seismic design in its current form.In present work efforts has been made in estimating the actual value response reduction factor (R) of reinforced concrete medium rise special moment resisting frame (SRMF) having irregularity in elevation and as well as in plan by using non-linear static pushover analysis and compare it with codal values. The frames were designed as per guidelines of IS 456:2000.The lateral loads acting on the frames were obtained from the guidelines of IS 1893: 2002 (Part1).
A SURVEY ON FINGERPRINT INDEXING TECHNIQUES FOR BIOMETRIC DATABASE

: In biometric identification systems, the identity associated with the input data is determined by comparing it against every entry in the database. This exhaustive matching process increases the response time of the system and, potentially, the rate of erroneous identification. This paper presents a survey on the indexing methods that are currently available for fingerprint. Fingerprint indexing is based on the global feature, local ridge line orientation, minutiae and other features. An exhaustive survey is done on all the indexing techniques and some of them are presented.
Intelligent Tutor System for Learning Object Oriented Programming

- The author presents in the article the proposal of an intelligent tutor system, with the use of artificial intelligence techniques that extract and analyze the information of the interactions of the student with the platform in its teaching and learning process. In order to achieve this objective, the types of intelligence preponderant in each one are considered, since it will allow to reach more individualized solutions. The results show a positive impact on problem solving, which improves the learning process.
Incorporation of DCT and MSVQ to Enhance Image Compression Ratio of an image

------------------------------------------------------ Abstract – Image compression plays a vital role in research areas of image processing. The main objective of image compression is to reduce the image size, which leads to fast transferring of images. It is achieved by removing noisy and irrelevant data in the image. In this paper we propose Discrete Cosine Transform (DCT) and Multistage Vector Quantization (MSVQ) scheme to increase image compression ratio. DCT divides image into two frequencies where irrelevant frequencies are removed with the help of quantization and relevant frequencies are used while retrieving an image. Quantization is achieved by compressing a range of values into a single quantum. This is a hybrid method which uses vector quantization at each stage and Differential Pulse Code Modulator (DPCM). DPCM pre process the image after that cosine transformation applied on image. Compared to existing VQ and DCT our proposed DCT-MSVQ increases compression ratio (CR) and reduce storage size of images.
A Similarity Measure for Text Classification and Clustering

— Clustering is one of the necessary techniques in machine learning and data mining techniques. Similar data grouping is performed using clustering techniques. In document vector each component indicates the value of the corresponding feature in the document. The characteristic measure could be term frequency, are similar to relative term frequency. Similarity Measurement for Text Process (SMTP) is used to measure the similarity between two documents with respect to a feature. Presents and options of the features in both documents are used to estimate the similarity values. The SMTP is extended to estimate similarity between two set of documents. The SMTP scheme is used with text clustering and classification task. K means algorithm is used for the clustering techniques.
Review on image watermarking based on LBP transform technique

In this review paper, we describe a digital image watermarking technique applying local binary patterns (LBP). Local binary patterns are best known for their rugged texture defining capabilities and digital watermarking applied in proving the copyright of a multimedia content. In this work, we study an LBP synthesis or inverse LBP identical process and its suitability to the digital image watermarking. The LBP synthesis process varies the near pixels values so that the LBP measured from these pixels is the desired value that we want to synthesize. This procedure takes into account the requisition of a digital image watermarking such as robustness and imperceptibility to watermark removal attacks. Due to the character of LBP synthesis, it is necessary that only a few pixels of a provided block is changed to embed the watermark. The simulation output shows that the technique is rugged to the rotation, JPEG compression, and scaling attacks. This LBP synthesis procedure could also be utilized to watermark sensor data for justifying the ownership. We are positive that this work would progress to a new research direction invalidation of digital content. In this work, a binary watermark is embedded into the image blocks by changing the neighborhood pixels conferred to the LBP pattern. However, various image blocks can have the similar LBP pattern, which can lead to false detection in watermark extraction procedure. In different words, one can change the host image deliberately without affecting its watermark message. In addition, there is no encryption procedure before watermark embedding, which leads to another potential security issue. To explain its weakness, two special copy-paste attacks are suggested in this paper, and several experiments are organized to prove the effectiveness of these attacks. To solve these issues, an enhanced semi-fragile watermarking based on LBP operators is conferred.
Simulation of Dam Break Using Modified Incompressible Smoothed Particles Hydrodynamics (MPM-I-SPH)

Generally, hydrodynamic problems can be analyzed using the three different views of Lagrange, Euler and a combination of Lagrange and Euler views. Choosing any of these methods depends on the nature of the problem and its characteristics. Using the existing numerical methods, which are based on network production, for the analysis of such problems can be time consuming and problematic, also numerical propagation error in Euler's methods which may arise through discretization of transfer terms in Navier-Stokes equations, could have a negative impact on the accuracy of results. Considering these problems, it seems that only Lagrangian numerical methods without grid are suitable for the analysis of hydrodynamic problems. This study aims at simulation of dam break using MPM-I-SPH. This approach has been primarily based on integral interpolation theory. In this method, various fluid parameters such as density, velocity and pressure are specified, and the value of a dependent variable is calculated by summing over neighboring particles. Differential equations can be converted to integral equations using an interpolation function. In this paper, the governing equations for free surface flows are described based on the Lagrangian SPH method . Gradient and Laplacian terms modeling, execution of boundary conditions and the predictor corrector standard method for the solution of dam break equations were presented The good accordance between modeling results and experimental results proved the capability of the resultant numerical model for simulation of complex phenomena.
EFFECTIVE AES IMPLEMENTATION

The importance of cryptography knuckle down to the security in electronic data transmissions has gained an essential relevance during past years. Cryptography security mechanisms uses some algorithms to muddle the data into unreadable text with a key which can only be decoded/decrypted by one who has that associated key for the locked data. Cryptography techniques are of two types: Symmetric & Asymmetric. In this paper we’ve used symmetric cryptography method-Advance Encryption Standard algorithm with 200 bit block size as well as 200 bit key size. We’ve used 5*5 matrix to implement same 128 bit conventional AES algorithm for 200 bit block size. After implementing the algorithm, the proposed work is compared with 128,192 & 256 bits AES techniques in context with Encryption and Decryption Time & Throughput at both Encryption and Decryption ends.
Longitudinal Study on Change in CD4 Cell Counts On HIV Positive Patients in Nigeria

The purpose of this study is to examine and compare the utility of the GLMM models for modeling longitudinal data, with particular focus on the change in CD4 cell count in HIV patients started on Antiretroviral therapy(ART) in University of Abuja Teaching Hospital (UATH) Abuja-Nigeria. The determinants of CD4 cell counts as well as the effect of the factors studied on patients CD4+ cell count were shown in the study. The GLMM full model and the GLMM reduced model with the response variable CD4 counts at 36 month with the following predictor variables; time on ART, regimen, BMI, age and baseline CD4 count up to 33 month were fitted and analysis done with correlated data and specified variance components that represent within-subject variance in outcomes and between-subject variation. A comparison between the two models for Goodness of fit using Akaike’s Information Criterion (AIC) showed that the full model has the best fit for CD4 count and it hold promise when used with empirical variance estimates. The optimal approach will depend on study design and management goals. The importance of early treatment was evident from this study. The Initial CD4+ cell count was shown to significantly determine a patient‘s current CD4+ cell count following initiation on ART. A higher initial CD4+ cell count would result in a better rate of recovery of patients on ART. This agrees with findings of Viviane et al (2009) and Kulkarni et al (2011). This study did not show any age differentials. However, the BMI was shown to significantly determine a patient‘s current CD4 cell count hence a higher baseline BMI predicts greater gains in CD4 cell counts. This finding is in contrast to the results in the CrumCianflone et al study, which showed that obese patients have smaller CD4 cell count gains
On Developing the Translation Competence: A Case of EFL Learners

The purpose of this research paper is to report a study, which has been conducted very recently. The study aimed at examining the feasibility of the direct teaching of translation in developing the translation competences of the Yemeni EFL students. The study is quantitative and qualitative investigation, so it adopted a quasiexperimental design as a method for data collection and analysis. A purposive sample of 40 subjects was selected from the students who registered at the department of English language, college of education in Seiyun of Hadhramout University in Yemen. Prior to the commencement of the classroom intervention, all the subjects were given a pre-test after which they were subject to classroom training sessions lasted for an academic semester, and then the subjects were given a posttest. In order to test the effectiveness of the direct instruction and classroom training sessions on the students’ translation competence, the two tests were analyzed and their analyses were compared using descriptive statistics such as mean and standard deviation. The results show very significant points, which are contextspecific, so their generalization is questionable. Finally, in the light of the findings, the study recommended some suggestions concerning syllabus updating, teaching methodologies, learning facilities and staff professional development.