Miracle-dz/UniFAR-FTUs huggingface dataset:
An Unmanned Ground Vehicle-aided Task Exchange System Of Small Air Vehicles For Remote Surveillance Missions

— Small/portable unmanned air vehicles which supply their energy from electric batteries have been successfully used in applications of intelligence, surveillance and reconnaissance-based missions gradually. Despite their increasing usage, studies which focus on S-UAVs limited battery capacities has not been completely dealt in the literature. This obstructs the usage of small unmanned air vehicles in long range and unremitting mission scenarios. In addition, small unmanned air vehicles have been supported with unmanned ground vehicles to carry out surveillance-based missions efficiently in recent researches. However, studies including collaborative teams with unmanned air and ground vehicle are limited in literature. In this paper, a surveillance system that is based on collaboration of two small unmanned air vehicles and a transporter unmanned ground vehicle was proposed. In order to provide the continuity of surveillance mission, an assigning and directing algorithm that considers battery charge level of the small unmanned air vehicles was developed within the proposed system. Developed algorithm assigns tasks to unmanned air vehicles and changes their role in surveillance mission by checking their battery levels. The proposed system was examined with tests in simulation and outdoor environment in a specified range and unmanned air vehicles completed surveillance mission by making a successful task exchange during their mission.
Analysis of Diabetic Patient’s Data Using Data Mining Clustering Techniques

: Data mining is Data mining is one of the knowledge discovery steps in database, in which modeling techniques are applied. In this research work, the analysis of K-Means method is applied for dealing with diabetic database for clustering. To increase the efficiency of mining process, some pre-processing needs to be done to the data. Diabetes data mining methods are used to analyze the diabetic data information resources. Diabetic data mining content mining and structure methods are used to analyze the medical data contents. The effort to develop knowledge and experience of frequent specialists and clinical selection data of patients collected in databases to facilitate the diagnosis process is considered a valuable option. Diagnose the Diabetes disease is a significant and tedious task in medicine. For detecting a disease number of tests should be required from the patient. But using data mining technique the number of test should be reduced. This reduced test plays an important role in time and performance. This technique has an advantages and disadvantages. This research work analyzes and study about how data mining technique is used for predicting the diabetes disease. This work reviewed the research papers which mainly concentrated on predicting Diabetes. Experimental results showed the good accuracy when applied to the adjust data.
New ICI Self-Cancellation Scheme for Orthogonal Frequency Division Multiplexing Systems

--Orthogonal Frequency Division Multiplexing (OFDM) is a well-known technique for the broadband wireless communication system. However, a main problem in OFDM is its vulnerability to frequency offset errors due to which the orthogonality is destroyed that result in Inter carrier Interference (ICI). ICI causes power leakage among subcarriers thus degrading the system performance. This paper studies ICI cancellation scheme which performs better than standard OFDM system. In this paper an effective Intercarrier Interference Self-Cancellation method to compensate the effects of multiple carrier frequency offsets for orthogonal frequency division multiplexing (OFDM) systems is presented.
Descriptive analysis of KRAS and BRAF mutations in senegalensis patients with colorectal cancer

Worldwide Colorectal cancer (CRC) is a leading cause to cancer mortality and morbidity. In many studies, mutations in the KRAS and BRAF genes are involved in colorectal cancer, and are associated with the primary resistance to the EGFR inhibitors. Objective of study is to investigate the prevalence of KRAS and BRAF mutations in first in Senegal and to correlate clinico-anatomical parameters according to genes mutation status in colorectal cancer. Genomic DNA from the tumor tissue was performed using the ReliaPrep gDNA Tissue kit from Promega on surgical specimens of twenty patients with colorectal cancer. The median age was 55 years and sex ratio was 0.82. Analysis of mutations in codons 12 and 13 of KRAS and in codon 600 of BRAF was assessed using High -resolution melting (HRM). Mutations were detected for KRAS in 45% and for BRAF in 55% of specimens and were not associated with clinico-anatomical parameters. Tumors harboring mutation in both KRAS and BRAF were observed in 15% of cases. The colon location of the tumor was the most recovered. Stage pT3 and pT4 were in more than 3⁄4 of the cases and liver metastases had in two cases.
SMART HUMAN BODY MONITORING AND MANAGEMENT USING IOT BASED ON MATLAB AND ARM11

— Each With the multiplication of Internet of Things (IOT) gadgets, for example, Smartphone's, sensors, cameras, it is conceivable to gather enormous measure of information for confinement and following of Health of the patient. This venture portrays the outline of a straightforward, ease controller based patient wellbeing checking framework. This instrument utilizes a basic Opto electronic sensor, helpfully strapped on the finger, to give nonstop sign of the beat digits. The Pulse screen works both on battery or mains supply. It is perfect for nonstop observing in operation theaters, I.C. units, biomedical/human designing studies and games pharmaceutical. This project utilizes managed 5V, 750mA power supply. 7805 three terminal voltage controller is utilized for voltage direction. Connect sort full wave rectifier is used to redress the ac yield of auxiliary of 230/12V stage down transformer. Lung Health analyzer will be shown on the LCD show which is associated with the Microcontroller.
Haematotoxicity of Cypermethrin (25% EC) to white carp

Copyright: © 2016 | Author(s), This is an open access article under the terms of the Creative Commons Attribution-Non-Commercial No Derivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is noncommercial and no modifications or adaptations are made. Cyperkill 25%EC is a synthetic pyrethroid pesticide widely used in Guntur district for pest control in agri ventures due to its effective control against different pest species in a definitive and constant way with low cost. Its presence in freshwater environs is very common in this area. Contamination of aquatic ecosystems with this toxicant affects all groups of aquatic fauna including fish which are non target biota. A static-renewal bioassay was conducted to assess the acute and sublethal toxicity of cypermethrin on some haematological parameters of white carp (Cirrhinus mrigala). Juveniles of experimental fish were exposed for lethal (96 h LC50 i.e. 4.23μg/L) and sublethal (1/10th of 96 h LC50 i.e. 0.423μg/L for 5, 10 and 15 days) concentrations of cypermethrin. Decreased tendency at both lethal and sublethal concentrations was evident in RBC count, Hb content and PCV. At the same time an increasing trend in WBC count and MCHC at sublethal and decreasing trend at lethal concentration. MCV and MCH values were elevated at both lethal and sublethal concentrations. Toxicity derived alterations observed in haematological indices during this study led to a conclusion that the cypermethrin has detrimental effect on the test fish and its presence in an aquatic environment may severely threaten the health of the ecosystem and its living component.
Modeling the impact of water and nutrient management in African agriculture

Africa has to adapt to the growing demand for agricultural commodities driven by growth in population, per capita income and new demands for biofuel. There is a wide agreement that African agriculture has enormous potential for growth and will shift towards a more productive farming. A systematic approach is needed to identify the main factors that explain observed yield gaps and to evaluate the impacts of a potential intensification on the environment. In this paper we presented a crop yield gap analysis for Africa using a newly developed tool linking a Geographic Information System and the biophysical model EPIC. We showed that in most African countries, the main limiting factor to crop production is nitrogen, while water limitation is more restricted to few countries. The predicted yield gap is much more marked in Sub-Saharan Africa than in North Africa. We predicted that a mining of soil resources, with nitrogen crop uptake exceeding the inputs through fertilization, is taking place in many countries in Africa. We also showed that even in water rich countries, appropriate water management including the development of irrigation infrastructure is needed to close the yield gap.
Performance Analysis and Comparison of Multiuser MIMO Broadcast Precoding Techniques for 5G Networks

The fifth generation of mobile networks (5G) aims to meet the high demand for mobile data that will exist from the year 2021, product of the development of new technologies, applications and services. Its main requirements are to achieve high data transmission rates, massive user capacity, low power consumption, high communication reliability and low latency. We propose ZF Precoding and ZF-DPC precoders’ scheme and algorithms that employ multiple transmit processing and ordering strategies along with a selection scheme to mitigate interference in MUMIMO systems. Both of the two proposed precoding algorithms can achieve a comparable sum-rate performance as, substantial bit error rate (BER) performance gains, and a simplified receiver structure, while requiring a much lower complexity.
Segment Segmentation in Lung CT Images - Preliminary Results

– Segmentation of lung anatomical parts like fissures and bronchopulmonary segments are of clinical importance in interpreting and assessing the pathologies present in the lungs. Segmentation of fissures still remains a challenging task as the selection of the segmentation algorithm decides the accuracy of the fissure segmentation. We conducted experiments on the existing segmentation methods and propose an automatic delineation method for fissure segmentation in High Resolution Computed Tomography images of the lungs. The method applies Gray Level Co-occurrence Matrix measures to enhance and detect the fissures. The feature set calculated from GLCM values are applied to a supervised enhancement filter. A KNN classifier is then trained to classify the pixels belonging to fissures by correlating the human observed and automated feature set calculated. A marker controlled watershed algorithm is applied to segment the bronchopulmonary segments as the next step using detected fissures. The method is experimented with 5 test images and the accuracy obtained is 57% comparable to the radiologist observation.
Kidney Segmentation in CT - Scan Image

-In this paper an effective approach for extracting kidney in abdominal CT scan (Computed Tomography) images has been proposed. It has been divided into two stages. In the first stage a template evaluation method has been developed for extracting the desired region in an image on the basis of properties of an organ, which helps in processing to a confined region and is an automated process. The second stage uses the concept of intensity values of a pixel and separates the desired region from the original image on the basis of a computed threshold range. In addition to this it uses a set of morphological operations for fine coarse kidney segmentation and various filters for removing noise from an image.
AN ENHANCEMENT OF COPY MOVE FORGERY DETECTION IN DIGITAL IMAGES USING HYBRID TECHNIQUE

Due to the technology advancement and availability of lots of sophisticated image editing tools, the digital images are losing authenticity. This has led to the proposal of different detection techniques to check whether the digital images are authentic or forged. Copy move forgery is a special type of forgery technique whose detection has become a widely used research topic under digital image forensics. In this paper an enhancement of copy move image forgery detection is done by implementing a hybrid of block based method DCT (Discrete Cosine Transform) and key-point based method SIFT (Scale-Invariant Feature Transform). The technique works by first applying DCT on an image and then SIFT on an resultant image obtained after applying DCT. Thus the features obtained using the hybrid technique DCT plus SIFT are found more robust against various types of attacks and show improvement in detection results also. The technique has shown quite significant results on multiple cloning, various attacks like against scaling, rotation, rotation plus scaling combined attack, noise, compression, blur and on real time images also.
A Model For Real Time Sign Language Recognition System

This paper proposes a real time approach to recognize gestures of sign language. The input video to a sign language recognition system is made independent of the environment in which signer is present. Active contours are used to segment and track the non-rigid hands and head of the signer. The energy minimization of active contours is accomplished by using object color, texture, boundary edge map and prior shape information. A feature matrix is designed from segmented and tracked hand and head portions. This feature matrix dimensions are minimized by temporal pooling creating a row vector for each gesture video. Pattern classification of gestures is achieved by implementing fuzzy inference system. The proposed system translates video signs into text and voice commands. The training and testing of Fuzzy Inference system is done using Indian Sign Language. Our data base has 351 gestures with gesture repeated 10 times by 10 different users. We achieved a recognition rate of 96% for gestures in all background environments.
Replacement of soyabean meal with dietary lablab bean meal ( Lablab purpureus ) in the diet of Clariid catfish ( Clarias gariepinus ) fingerlings

This study examined the replacement of soyabean meal with lablab bean meal (LBM) in the practical diets of Clariid catfish ( Clarias gariepinus ). Five Iso-nitrogenous diets containing varying levels of ground toasted lablab bean were formulated accordingly; T 1 (10%LBM), T 2 (20%LBM); T 3 (30%LBM); T 4 (40%LBM) and T 5 (50% LBM) as a replacement for soyabean meal and were fed to three replicate of Clarias gariepinus fingerlings with an initial mean weight of 1.65±0.01g. T 1 (10%LBM) recorded the best growth rate (p<0.05) as it had the highest value of weight gain (1.79), feed intake(2.75), feed conversion ratio (1.54), relative weight gain of 7.29, specific growth rate of 1.69, protein efficiency ratio (57.61) and survival rate (97.33%). As the concentration of LBM in the diet increased, growth parameters decreased markedly, and this was attributed to the build-up of antinutrient factors which rendered the diet unpalatable and reduced its efficiency. Therefore, Lablab bean meal can partially replace soyabean and will be best at 10% level of replacement in diets of Clarias gariepinus without compromising the growth and carcass composition.
Smart Supervised Method for Blood Vessel and Optic Disc Segmentation from Fundus Images

Glaucoma is a condition of increased pressure within the eyeball, causing a gradual loss of sight. Normal eye pressure ranges from 12 – 22 mm Hg. Vision loss from glaucoma occurs when the eye pressure is too high for the specific individual and damages the optic nerve. Any resultant damage cannot be reversed. Therefore early detection through regular screening and timely interven tion will be highly beneficial in effectively controlling the progress of the disease. Various aspects and stage of glaucoma are a nalyzed by examining the colored retinal images. The bright circular region from where the blood vessels emanate are called the optic disk. Glaucoma patients require frequent, at least, six monthly screening of a vast number of patients and automating the process will go a long way in relieving the burden on the specialist and reducing the most common cause of preventable blindness. The main objective of this paper is to detect and segment the blood vessels and optic disc from the retinal images. For that in blood vessel segmentation, using CLAHE, OGF and LET followed by in Optic disc detection, two algorithms is used for selecting which method among the two is best fitted. The two methods such as CHT and super pixel, the brightness based is used for locating the optic disc. Finally, generate a report by calculating the average blood vessel and optic disc pixels.
A qualitative study of effectiveness of clinical teaching

Clinical experience has been always an integral part of nursing education. It prepares student nurses to be able of "doing" as well as "knowing" the clinical principles in practice. Clinical experience is one of the most anxiety producing components of the nursing program which has been identified by nursing students. The educational process is unique in the practice professions because being able to perform the activities of the profession in live situations as opposed to simply being able to express understanding of principles is a requisite competency of graduation. Despite a wealth of research on clinical teaching, the criteria for determining what constitutes effective clinical teaching remain poorly defined. Therefore, the aim of this study is to investigate the nursing students' and instructors' perception of clinical teaching effectiveness in critical care nursing courses. Material and Method; A descriptive qualitative research design was used. Setting: The study was conducted at the Critical Care & Emergency Nursing Department, Faculty of Nursing, Alexandria University. Subjects: consisted of two groups. The first group included nursing students and the second group consisted of critical care clinical instructors. Clinical Teaching opinionnaire tool was developed to elicit the nursing student's / clinical instructors' perception of clinical teaching effectiveness in critical care nursing courses. Results; Students had enough orientation. Students are under stress because of a lot of work and duties. The ratio of instructors to students (1:6) is adequate. The instructors' agreed with the students on the duration of clinical training is not enough. Students are well oriented with the intended learning outcomes (ILOs) of their clinical training. Students and instructors enjoyed OSCE. Students and instructors don't like portfolio and log book. Students like their clinical instructors they see them role models Conclusion; the findings of this study and the literature support the need to rethink about the clinical skills training in nursing education. Recommendation; Longitudinal studies to investigate the nursing students' and instructors' perception of clinical teaching effectiveness in randomly selected multiple faculties are recommended. [Hayam I. Asfour and Azza H. El-Soussi. A qualitative study of effectiveness of clinical teaching; Journal of American Science 2011;7(7):409-420]. (ISSN: 1545-1003). http://www.americanscience. org.
Indian diabetes risk score (IDRS), a strong predictor of diabetes mellitus: A cross sectional study among urban and rural population of Lucknow

Background: The prevalence of Diabetes Mellitus is growing rapidly worldwide and is reaching epidemic proportions. Globally around 366 million people have Diabetes in 2011 and by 2030 this will have risen to 552 million. IDRS is a cost effective & simple method for identifying undiagnosed diabetic subject at community level. Objectives: To estimate prevalence of Diabetes Mellitus and to identify high risk subjects by using Indian diabetes risk score for detecting undiagnosed Diabetes in urban and rural areas of Lucknow. Material and Methods: It was a community based cross-sectional study done in the urban and rural areas of Lucknow, under Department of Community Medicine, Era’s Lucknow Medical College and Hospital in subjects aged 20 years and above from August 2013-July 2014. Results and Observations: 555 (67.7%) of subjects were in moderate risk IDRS category while 143 (17.4%) were in low risk and only 122 (14.9%) were in high risk IDRS category. Prevalence of Diabetes Mellitus was highest in high risk IDRS category (47.5%) followed by moderate risk (9.2%) and low risk (2.8%) IDRS category. The sensitivity of IDRS was 81.40% in the present study and a high specificity of 72.0%. Present study also showed a Positive Predictive value of IDRS as 31.7% and a Diagnostic accuracy of 73.3%. Conclusion: This study provides a use of Indian Diabetes Risk Score for identifying undiagnosed high risk for patients with Diabetes in Indian population. It is essential to implement the simple IDRS tool in the community for mass screening so that proper intervention can be carried out to reduce the burden of Diabetes.
Fault Diagnosis Based On Wavelet Fuzzy Feature Extraction and Information Fusion

With increasing demand for efficiency and product quality and progressing integration of automatic control systems in high cost and safety –critical process the field of supervision or monitoring, fault detection and diagnosis plays important rules. The Fault diagnosis task consist of the determination of the fault type with as many details as possible such as the fault size, location and time of detection. Today, fault diagnosis is main research in world. We exposure new algorithm in this paper, this algorithm have 3 steps. In the First step used wavelet packet and fuzzy set for make wavelet tree with coefficient in each node. In second step using wavelet tree and fuzzy set fused data with maximum Entropy coefficient in wavelet tree and in step three with output of fusion function we classification this fusion data. This algorithm have best time study because the time of search algorithms is 2 D ,D is depth of wavelet tree. Our proposed fusion strategies take into account that a Wavelet-Fuzzy by finding the optimal hyper plane with maximal margin. Then a Support Vector Machine classifier is trained. In the distributed schemes, the individual data sources are processed separately and modeled by using the Support Vector Machine.
Landmark Recognition Using Image Processing With MQTT Protocol

: The most important necessity for any user visiting an unknown or known establishment is true information. Even using Google and other searches wastes a lot of time. Asking around to people often confuses and misleads visitors. Hence, to bridge this user – information gap, a system providing complete true information to any naïve user needs to be formed. Our system takes an image as input from user and provides detailed real-time information. The image from the user will be processed and compared with the images in the database using Homograph. If match found, the information related to that image will be fetched and transferred using MQTT protocol. A client side will also be provided for small entrepreneurs to update information independently. There are various reasons why MQTT can be preferred over HTPP. MQTT is much faster and more flexible. Also, it works on various levels to provide security depending on user preferences. The image can be tested against various conditions according to camera quality and environmental conditions. Further, we will be explaining the system in detail along with its future scope in the world of computer vision.