Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic Range Enhancement of Images using Scalable Pyramids

—Dynamic range enhancement is a process of correctly reproducing the highlights and shadows of high contrast scene on monitors and printers. There are basically two ways to increase the dynamic range of digital photographs namely exposure blending and tone mapping, but most of the display devices have limited dynamic range (LDR). Therefore various techniques have been proposed for compressing the dynamic range while retaining the important visual information, so the information can be displayed effectively. It would also desirable to retrieve an HDR image from an LDR image with minimal degradation through ―companding‖. companding is a technique in which an HDR image is converted to an LDR image and later expanded back to high dynamic range. Hence in this paper we discuss a method to compand an image . The proposed technique preserves the features present in an image. Present technique is easy to implement and understand.
FPGA Implementation of Mutual Authentication Protocol Using Modular Arithmetic

— Radio-Frequency Identification (RFID) is a modern technology that utilize radio frequencies to locate the object. In this paper, we study the radio-frequency identification (RFID) tag–reader mutual authentication (TRMA)scheme. Two improved authentication protocols for generating the Pad Gen function are described. In this project, a protocol for RFID tag–reader mutual authentication scheme is proposed which is hardware efficient. Modified MOD scheme is implemented in protocol system to reduce the hardware cost. The proposed mutual authentication protocol with consumes less logic elements and also more secure from external attacks. The proposed protocol is described in Verilog HDL and simulated using Xilinx ISE design suite 14.2.
SIX MINUTE WALK DISTANCE IN A MULTICENTER STUDY OF HEALTHY SUBJECTS AGED 40-80 YEARS IN SPAIN AND SOUTH AMERICA

Background: The six-minute walk distance (6MWD) predicted values have been derived from small cohorts mostly from single countries. Objective: To investigate differences between countries and identify new reference values to improve 6MWD interpretation. Methods: We studied 444 subjects (238 males) from 7 countries (10 centers) ranging from 40 to 80 years old. We measured the 6MWD, height, weight, spirometry,, heart rate (HR), the maximum HR during the 6MWT/the predicted maximum HR (%PredMaxHR), Borg dyspnea and oxygen saturation. Results: The mean 6MWD was 571 (90) m (range 380-782). Males walked 30 m more than females (p <0.001). A multiple regression model for the 6MWD included age, gender, height, weight, and %PredMaxHR (Radj= 0.38, p <0.001), but there was variability across centers (Radj= 0.09-0.73) and its routine use is not recommended. Age had a great impact in 6MWD independent of the centers, declining significantly in the older population (p <0.001). Age-specific reference standards 6MWD were constructed for male and female adults. Conclusion: In healthy subjects, there are geographic variations in 6MWD and caution must be taken when using existing predictive equations. The present work provides new 6MWD standard curves that could be useful in the care of adult patients with chronic diseases. Word count: 200
REAL INTEREST RATE AND SAVINGS MOBILIZATION IN NIGERIA

This study empirically assessed the impact of real interest rate on savings mobilization in Nigeria. The VectorAuto Regressio n (VAR) was employed, using the time series data from 1980 to 2008. The study revea l d that real interest rate has negatively impacted on the level of savings mobiliz at on in Nigeria. The need for government in Nigeria to bridge the existing gap be tween the lending and savings rates and increase per capita income level of the populac e, to stimulate savings for investment and economic growth were revealed by the study. Therefore, efforts should be geared towards reducing domestic inflation rate to arrest its negative impact on real rates in Nigeria.
The Effect And Implications Of Work Stress And Workload On Job Satisfaction

Job satisfaction is very important for the work productivity of employees. This study aimed to empirically examine the effect of work stress and workload on job satisfaction of employees. The study sample was 40 educational support staff who were permanent employees at the University of X in Yogyakarta. This study used simple random sampling technique. Data collection was conducted using the job satisfaction scale, work stress scale, and workload scale with a semantic differential and Likert scale model. Data were analyzed using multiple linear regression analysis supported by assumption tests, which includes the normality test, linearity test, and multicollinearity test. The results of the data analysis show that work stress and workload simultaneously affect job satisfaction and obtained an F-value =12.274 and significance p=. 000 (p<.01). There is a very significant effect of work stress on job satisfaction with a t-value =4.307 and significance of p=. 000 (p <.01). There is also a very significant effect of workload on job satisfaction, which obtained a t-value = 4.656 and significance of p=. 000 (p <.01). Job stress and workload offer a contribution of 39.9% to job satisfaction with the remaining 61% being influenced by other variables.
Image Reconstruction Algorithm for Electrical Impedance Tomographic System

1ME Student at Government Engineering College, Gandhinagar 2Professor, Dept. of Biomedical Engineering, Government Engineering College, Gandhinagar, India 3Professor, Dept. of Biomedical Engineering, Government Engineering College, Gandhinagar, India ----------------------------------------------------------------------***--------------------------------------------------------------------Abstract Electrical Impedance Tomography (EIT) is a
Categorization of Web Content Based on Social Emotions Using Data Mining

: This paper is concerned with the problem of mining social emotions from text. Recently, with the fast development of web 2.0, more and more documents are assigned by social users with emotion labels such as happiness, sadness, and surprise. Such emotions can provide a new aspect for document categorization, and therefore help online users to select related documents based on their emotional preferences. Useful as it is, the ratio with manual emotion labels is still very tiny comparing to the huge amount of web enterprise documents. In this paper, we aim to discover the connections between social emotions and affective terms and based on which predict the social emotion from text content automatically. More specifically, we propose a joint emotion-topic model by augmenting Latent Dirichlet Allocation with an additional layer for emotion modeling. It first generates a set of latent topics from emotions, followed by generating affective terms from each topic. Experimental results on an online news collection show that the proposed model can effectively identify meaningful latent topics for each emotion. Evaluation on emotion prediction further verifies the effectiveness of the proposed model.
HIGH PERFORMANCE SPLIT RADIX FFT

— A high performance hardware FFT have various application in instrumentation and communication systems. It describes new parallel FFT architecture which come together the split-radix algorithm with a constant geometry interconnect structure. The split-radix algorithm knows to have lower multiplicative difficulty than both radix-2 as well as radix-4 algorithm. The split-radix algorithm maps onto a constant geometry interconnect structure in which the wiring in each FFT stage is the same, resulting in low multiplexing overhead. We are exploiting the lower arithmetic obscurity of split-radix to lower dynamic energy, by gating the multipliers during trivial multiplication. The proposed FFT accomplishes less power than a parallel radix-4 design when calculate at few point, the real-valued transform
The Structural Design and Control System of a Caudal Fin Robotic Fish

This article took the trevally crescent-shaped caudal fin mode fishes as bionic object, based on the biological observation and bionic research, established the fish swimming model of trevally crescentshaped caudal fin mode, and designed the three degrees of freedom, tailtail fins pectoral fin, robotic fish. It detailed focuses on the fish propulsion theory and robotic fish overall design, including mechanical design, tail design, pectoral design, hardware control system design, drive system design, software design, and the selection and application of steering gear, stepper motor, and microcontroller.
N-Nodeset Importance Representative based Outlier Detection for Categorical Data

The proportionate increase in the size of the data with increase in space implies that clustering and hence outlier detection a very large data set becomes difficult and is a time consuming process. Sampling is one important technique to scale down the size of dataset and to improve the efficiency of clustering. After sampling, allocating unlabeled objects into proper clusters is impossible in the categorical domain. To address the problem, Chen employed a method called MARDL to allocate each unlabeled data point to the appropriate cluster based on NIR (Node Importance Representative) and NNIR (N-Nodeset Importance Representative) algorithms. This paper took off from Chen’s investigation and analyzed and proposed a method for outlier detection using NNIR by finding the resemblance between an unlabeled data point and a cluster. The cluster at which the unlabeled data point gives maximal resemblance is compared with the outlier threshold values to identify the data point appropriate cluster label or an outlier. This paper also proposed a method to find outlier threshold values for all the exiting clusters.
“Fat-But-Active”: Does Physical Activity Play a Significant Role in Metabolic Syndrome Risk Among Children Of Different BMI Categories?

Thayse Natacha Gomes1, Fernanda Karina dos Santos1,2, Daniel Santos1, Raquel Nichele Chaves3, Michele Souza1,2, Peter Todd Katzmarzyk4 and José Maia1* 1CIFI2D, Kinanthropometry Lab, Faculty of Sport, University of Porto, Rua Dr Plácido Costa, 91, 4200-450, Porto, Portugal 2CAPES Foundation, Ministry of Education of Brazil, Brasília – DF, Brazil 3Federal University of Technology – Paraná (UTFPR), Campus Curitibat, Brazil 4Pennington Biomedical Research Center, 6400 Perkins Road, Baton Rouge, LA 70808-4124, USA
Personalized Movie Recommender System using Rank Boosting Approach on Hadoop

Today we are living in an era of Big Data. Large numbers of services are available to customers; from these services it is difficult for them to choose those that are most appropriate for them. In this scenario a wide variety of service recommender systems will guide the user in selecting the most appropriate one. But these traditional service recommender systems will not work well with Big Data environment; they will experience scalability and efficiency problems as it has to work on huge amount of data. Most of the existing recommender system will provide same rating and ranking of services to different customers. As a solution to this we propose service recommender systems that operate on MapReduce Framework on Hadoop platform. Our service recommender system uses keywords to indicate user preferences and a variation of collaborative filtering algorithm called user based collaborative filtering is used to provide recommendation to customers. It also uses rank boosting approach for combined preferences, which will help to rank the results according to the preference of the current user and produce the recommendation list accordingly.
Brown Rice as a Healthy Food and Lowering Blood Sugar in Rats

This investigation was carried out to evaluate and compared between brown and white rice high and low amylose. Chemical composition, total dietary fiber fractions, minerals content and total phenolic compounds were determined in brown and white rice. Biological experimental was determined in diabetic rats fed on brown and white rice high and low amylase for four weeks (30 days). Glucose blood level, total lipid, triglycerides, total cholesterol, high density lipoprotein (HDL) and low density lipoprotein (LDL) were evaluated after end of the biological experimental period four weeks. The results showed that the brown rice high and low amylose had contained the highest amount from crude protein, fat, ash and crude fiber content (8.85, 1.65, 1.9 and 1.25 % in high amylose and 8.42, 1.38, 1.83 and 1.24% in low amylose, respectively) compared with white rice. Brown rice contained a large amount of total dietary fiber soluble and insoluble dietary fiber. This is due to the fact that the whole grain contains all three components: bran, germ and endosperm. Minerals content (magnesium, potassium and calcium) and total phenolic compounds were significant increased in brown rice compared with white rice. The results after the end of biological experimental period showed that the rats fed on brown rice high and low amylose significantly decreased in serum glucose blood level (160.3 and 166.0 mg/dl), followed by rats fed on white rice high amylose (171.5 mg/dl). It is clear that feeding on rice high amylose reducing serum glucose level than white rice low amylose. The rats fed on brown rice high and low amylose significantly lowered in total cholesterol (150.0 and 160.0 mg/dl, respectively) than white rice high and low amylose (163.0 and 172.5 mg/dl, respectively). The results from HDLcholesterol, LDL-cholesterol, total lipids and triglycerides were paralleled for total cholesterol. From this study it could be recommended that the brown rice is reach in protein, fiber, minerals and phenolic compound and it is more beneficial food for lowering glucose blood level and lipid parameters than white rice. Therefore, the brown rice is a benefit healthy food and alternative for white rice. [Fizah Mosaed Mohamad Al-Subhi and Maha A. Hejazi. Brown Rice as a Healthy Food and Lowering Blood Sugar in Rats. J Am Sci 2013;9(4):21-28]. (ISSN: 1545-1003). http://www.jofamericanscience. org. 3
IMPROVED FEATURE EXTRACTION USING BOX FILTER COMBINATION IN IMAGE DATA

— A feature of the image is the point that can represent better the characteristic of the image other than points. Therefore, a feature of the image data must be detected regardless of the change of scale, rotate and viewpoint, etc. For feature extraction of existing research, feature point is extracted compare to normal image and abnormal image, otherwise method has been developed to extract edge points. In particular, SIFT(Scale Invariant Feature Transform) applies the filter and uses DoG(Difference of Gaussian)to extract the edge points. In this case, Gaussian filter is used. The reason is known that the best filter to extract the feature of image is Gaussian filter. However, Gaussian filter blur objects in image. So, using Gaussian filter prevents to extraction exact feature point. Therefore, the purpose of this study is to solve the problem by developing a filter with linear combination of box filters. The proposed filter extracts feature that located the boundary between the object in image more sensitive. In addition, through experiments,the proposed filter is confirmed to be better than Gaussian filter in specific image.
A Method Based on K-Center Problem for Efficient Client-Server Assignment in Internet Distributed Systems

—The internet is a modern collection of interconnected networks of various systems that share resources. Such a system consists of various nodes communicating with each other directly or indirectly. The client server assignment takes part in optimizing the overall performance of these systems. The optimal client server assignment can be done on internet distributed system based on some pre-specified metric on communication cost and load balancing. When we use heuristic via relaxed convex optimization for finding the approximate solution to the client-server assignment problem, inter server communication become increases, while making an average traffic equal in all groups. So in this paper an algorithmic solution based on the k - center problem is introduced to solve the client-server assignment problem for optimizing the performance of a class of distributed systems over the Internet. This algorithm gives better results and done a performance comparison of this algorithm with heuristic via relaxed convex optimization.
Mesh Based Peer to Peer Live Video Streaming using ANT Algorithm

-Data distribution and data retrieval has always been an integral part of the Internet. In particular, video streaming has been gaining popularity over the last few decades. Though there has been no shortage of innovations and Experimentations, no single system has been able to deliver highly scalable and reduce congestion to the requesting users. The development of p2p technologies brings unprecedented new momentum to Internet video streaming. This work proves that p2p is indeed more efficient by taking into account the factors of scalability, response time and reliability of serving the request. This work is broadly and logically divided into joining the network group, requesting, retrieving and video playing segments. The Requester takes care of receiving the file and storing it in the buffer. The video receiver takes care of sensing the user connections and playing the appropriate video on the requesting peer side. To provide video in efficient manner, this work use ACO (Ant Colony Optimization) algorithm and bandwidth for choosing optimized peer. From that optimized peer, user can get video. We also take care of scheduling and scalability issues.
Complexity of seismic process: a mini–review

At present, there are two major concepts, adopted for description of seismic process. The simplest of them, namely, Poissonian model, now dominant, is a basis of widely accepted modern methods of Probabilistic Seismic Hazard Assessment. According to this model, the seismic events are independent of each other, i.e. the long-term correlations are absent in seismic process, which means that it can be described in terms of classic Boltzman-Gibbs (B-G) thermodynamics. Last decades, application of modern methods of complexity analysis revealed undeniable arguments in favour of existence of long-term correlations in temporal, spatial and energy distributions of seismic events, leading to power-law distributions in all three domains. As a result, nonlinear (hidden) structures were discovered in seismic data sets and their characteristics were calculated: it turned out that they vary with time, which is in contradiction with memoryless purely Poissonian approach. There is a hope that the analysis of temporal variations of complexity (seismic) measures offer a challenge of more well founded forecasting strong earthquakes.
WATERMARKING WITH DENOISING USING SOURCE CODING TECHNIQUE

- Watermarking is a widely used technique for image security and authentication. An important application in watermarking is image protection against tampering. This paper proposes an efficient watermarking algorithm that detects the tampered zones and recovers the information lost in those zones. The original image is source coded in the watermark embedding scheme and the output bit stream is protected using appropriate channel encoder. For image recovery, erasure locations that can be detected by check bits help channel erasure decoder to retrieve the original image. The watermarked image quality gain is achieved through spending less bit-budget on watermark. The image recovery quality is being improved well as a consequence of consistent performance of designed source and channel codes. The design is used to protect and provide self recovery for image security applications and can remove the noise in case of noisy image during the recovery. Experimental results show that the proposed scheme outperforms other similar methods in terms of image quality before and after watermarking.
Performance Analysis and comparison of Recurrent Network for Pattern Storage and Recalling of Static Images

Pattern storage and recalling is a problem of interest in field of pattern recognition till now, which is used to mimic the human brain. Auto associative memory is an extensively used network for pattern storage and recalling of patterns. Recurrent network like Hopfield is popularly known auto associative memory networks. In this paper we present performance analysis and comparison analysis in term of storage and recalling efficiency of Hopfield network. Our analysis is based on the storage capacity and recalled efficiency of the pattern storage network for original images as well as distorted form of these images. For storage and recalling, edge Dilation and SOM are the methods for feature extraction used here to evaluate the performance of pattern storage network.
Plagiarism Detection Based on Neural Network

Being a developing issue, plagiarism is commonly described as literature theft and academic dishonest nature in the writing, and it must be avoided and adhere to the moral standards. Plagiarism occur in scholastics, paper publication, music, work of art developing quickly, so the recognizing plagiarism is essential. While the most recent couple of year’s plagiarism detection tools have been utilized predominantly in research conditions, refined plagiarism programming and instruments are presently quickly rising. In this paper, we give an outline of various plagiarism programming and apparatuses to take care of the plagiarism issue. We propose an element classification conspire that can be utilized to examine plagiarism discovery programming and plagiarism recognition instruments. This plan depends on the product's general qualities, devices qualities, and apparatuses property.
A comparison between gray and white mineral trioxide aggregate (MTA) and calcium enriched mixture (CEM) cytotoxicity in L929 and Saos-2 cell lines

The purpose was to compare the cytotoxic effects of two commonly used mineral trioxide aggregate (MTA) (gray & white) with the recently introduced calcium enriched mixture (CEM) in L929 and Saos-2 cell lines and to determine the oxidative stressinduced by each cement. Sterile discs of each cement were submerged and incubated in complete media for 24, 48 and 72-h. The cell lines were exposed to two fold serial dilutions (1, 0.5, 0.25 X) of each extract. In addition to trypan blue (TB) dye exclusion test, MTT assay was carried out after 24-h. To determine the oxidative stress mediated cell toxicity, malondialdehyde (MDA) concentration and total ferric reduction activity potential (FRAP) were measured in the media.The MTT and TB results with 48-h and 72-h CEM extracts showed that both extracts are cytotoxic in L929 cell line at 1 X and 0.5 X dilutions, while neither white MTA (WMTA) nor gray MTA (GMTA) showed any toxic effects in this cell line. On the other hand all three cements (undiluted 48-h and 72-h extracts) were cytotoxic against Saos-2 cell line. The oxidative stress marker (MDA) was proportionate to the cytotoxic effects of CEM while there was no significant changes in reductive capacity of the media measured by FRAP in both cell lines.The cytotoxic effects of CEM on L929 and Saos-2 cell lines seems to be higher than WMTA and GMTA and it is increased by the time of extraction up to 72-h. However, CEM, WMTA and GMTA showed similar toxic effect in Saos-2 cell line proportionate to the oxidative stress measured by TBARS. It seems that while all three cements extracts don't change the antioxidant activity of the media, they could significantly increase lipid peroxidation, especially CEM with Saos-2 cell line which elucidate triggering oxidative stress mechanisms without having direct oxidative activity.