Miracle-dz/UniFAR-FTUs huggingface dataset:
EBRA: Energy Balanced Routing Algorithm for Underwater Wireless Sensor Network

Summary Seabed is full of the application based information, which needs to explore for commercial purpose because at the bottom of the sea, the gold, silver, diamond, coal mines and valuable information is placed. To explore that information to the sea surface needs the designing of the routing protocols. The majority number of the routing protocols are designed for such kind of information retrieval but these routing protocols still faces some majority number of the challenges like: route broken issue between nodes due to the water pressure, depth controlling issue from sea surface to seabed, uncontrollable node mobility, water current issue, deployment issue and battery prolong issue. To maintain the link issue between nodes, control the depth of water, and prolong the battery power of nodes Energy Balance Routing Algorithm (EBRA) is proposed. In EBRA the water depth is controlled by formation of multiple layers from sea surface to seabed. To balance the battery power of nodes EBRA uses the powerful static relay nodes which have more power as compare to other sea water nodes. To control the node mobility the deployment of ordinary nodes at seabed level through multipath with Path Weight mechanism has been adapted for EBRA. The simulator NS2.30 with AquaSim is used for performance analysis. The EBRA is compared with EE-DBR and EMGGR and simulation response of EBRA is better than EE-DBR and EMGGR.
Cross-Sectional Analysis of Alcohol Intake and Serum Antibodies to Oral Microorganisms

The objective of this study was to evaluate the relation between alcohol intake and groups of periodontal antibody titers among individuals with normal glucose tolerance (NGT), prediabetes and diabetes. This was a cross-sectional analysis of the National Health and Nutrition Examination Survey III (NHANES III) 1988–1994 data, among individuals 40 y and older with information on alcohol intake and serum immunoglobulin G (IgG) antibody data against 19 oral microorganisms. Participants were excluded if they did not have teeth, reported that they were taking insulin, or having gestational diabetes. The sample size for this analysis was 3,219. Periodontal antibodies were grouped into four clusters using cluster analysis: Orange-Red, Red-Green, Yellow- Orange, and Orange-Blue. Cluster scores were computed for each individual by summing z-scores of standardized log-transformed IgG titers of antibodies against periodontal microorganisms making up each respective cluster. Each cluster score was modeled as an outcome. Alcohol consumption was assessed in g/day using self-reported number of days of drinking in the past 12 mo and the average number of drinks consumed per day on days when they drank. Overall, alcohol intake was positively associated with periodontal antibodies of the Orange-Red cluster (P. melaninogenica, P. intermedia, P. nigrescens, and P. gingivalis), and inversely associated with the Yellow-Orange cluster (S. intermedius, S. oralis, S. mutans, F. nucleatum, P. micra, C. ochracea) after multivariable adjustment. The association between alcohol intake and the Orange-Red cluster was strongest among individuals with diabetes; this relation was seen among individuals with and without periodontal damage. The Orange-Red cluster was positively associated with periodontal damage among individuals with diabetes. Alcohol intake was not associated with any antibody cluster among individuals with NGT or prediabetes. The effect of alcohol intake on periodontal disease may be greater among individuals with diabetes but this finding needs to be confirmed in prospective studies. Knowledge Transfer Statement: The results of this study can be used by clinicians when treating patients with periodontal disease and diabetes.
Microstrip Patch Antenna Design at 5.2GHz

The paper presents a broadband microstrip patch antenna for wireless communication. In its most basic form, a microstrip patc h antenna consists of a radiating patch on one side of a dielectric substrate which has a ground plane on the other side. The p atch is generally made of conducting material such as copper or gold and can take any possible shape. A rectangular patch is used as the main rad iator. There are several advantages of this type of broadband antenna, such as planar, small in size, simple in structure, low in cost, and easy to be fabricated, thus attractive for practical applications. This rectangular microstrip patch antenna is designed for wireless communicat ion application that works at 2.4 GHz with gain 11 dB for outdoor place. It also has a wide angle of beam in its radiation pattern. The results obtain that microstrip patch antenna can be used as client antenna in computer and workable antenna for wireless fidelity [10]
IMMUNOMODULATORY ACTIVITY OF AQUEOUS EXTRACT OF AMORPHOPHALLUS CAMPANULATUS TUBER

Traditionally Amorphophallus campanulatus (AC) tuber is used for tumor, rheumatoid arthritis, carminative and liver tonic. It is also used in the treatment of piles and given as the restorative in dyspepsia debility, Anti-inflammatory, antihaemorrhoidal, haemostatic, expectorant, digrstaive and anthelmintic. In present study effect of aqueous extract of Amorphophallus campanulatus tuber on immunological function in mice was studied. The Aqueous extract (AE) of Amorphophallus campanulatus tuber, given orally at the doses of 250 and 500 mg/kg showed a significant results of test parameters viz., charcoal clearance, spleen index and delayed type hypersensitivity (DTH) response. In mice immunized with sheep RBC, aqueous extract of AC decreases the charcoal clearance rate and the cellular immunity by facilitating the footpad thickness response to sheep RBC in sensitized mice. Key word Amorphophallus campanulatus, Immunomodulatory activity Journal of Cell and Tissue Research Vol. 8(3) 1581-1584 (2008) ISSN: 09740910 (Available online at www.tcrjournals.com) Original Article
Study of Relationship between Psychological Capital and Social Capital among Women Teachers. J. Educ. Manage. Stud., 6(1): 09-12.;

This study is aimed at investigating the relationship between psychological capital and social capital among the women teachers Behbahan elementary schools. Research method is of descriptive type. The population of the research consists of women teachers Behbahan elementary schools (N= 230). The statistical sample (n=041) was specified by Morgan table and was selected through sampling method. To collect data, 2 questionnaires including Luthans (2007) psychological capital questionnaire and Abili (2011) social capital questionnaire were used. To analyze data, Pearson correlation coefficient and regression were used. The analysis of the data showed that there is a signification relationship between psychological capital and social capital. Therefore, it seems that the investment on psychological assets is practically an investment on the other capitals (human and social).
Matching method of partial shoeprint images based on PCA-SIFT algorithm

— To improve the accuracy of image matching shoeprint image feature matching method based on PCA-SIFT is proposed. Firstly, feature detection and pre-matching of images are done by using PCA-SIFT (principal component analysis-scale invariant feature transform) algorithm. And then, the correlation coefficient is used as similarity measurement, which can filter image interest points. By this method, the image matching pairs can be obtained. Finally, the RANSAC (random sample consensus) algorithm is used to eliminate the mismatching pairs. The simulation results demonstrate that the proposed algorithm is more robust while maintaining good registration accuracy when analyzing partial shoeprint images in the presence of geometric distortions such as scale and rotation distortions compared with conventional algorithms.
Implementation on Morphological Text Mining

: Text mining is extracting useful or relevant information from a textual file. The extraction of information works on search engine or through a tool. Text mining is used for text retrieval and categorization. This paper focus on every word of a textual document whose frequency or occurrence in a textual document is high and those words has its own meaning i.e. they are stand-alone words. So we have developed a tool which will extract the details of textual data for a user in summarized form and the information subsequently is sufficient to know about a textual file.
A Comparative Analysis of Delay Constrains In Mobile Ad Hoc Networks Using Max Weight Scheduling and Back Pressure Algorithms

In Wireless networks where the nodes routing and scheduling packets depend on queue overload differences, one can stabilize the queues for any feasible traffic. The delay analysis of throughput scheduling policies in such systems is extremely difficult due to complex correlations arising between the arrival, service and the queue length process. In this paper we give a regular evaluation of Back Pressure Routing algorithm and Max Weight Scheduling algorithm variants on an experimental testbed. This provides the first direct comparison of delay performance. Our result expose that even in simple network topologies these algorithms induce wide routing loops with connected high packet delay.
Survey on Image Processing Based Plant Leaf Disease Detection

: When plants and crops are affected by pests it affects the agricultural production of the country. Usually farmers or experts observe the plants with naked eye for detection and identification of disease. But this method can be time processing, expensive and inaccurate. Automatic detection using image processing techniques provide fast and accurate results. This survey paper discusses various methods for plant disease detection using image processing, neural networks and different algorithms.
Detection and Tracking of Faces in Videos: A Review of Related Work

- F ace detection and tracking in real-time is a inspiring problem in many application situations such as faces and gesture recognition in computer vision and robotics. The continuing work implements a robust method which is expected to localize multiple faces at same time under the changing environment of light brightness and complex background in real time by utilizing face detection and tracking in combination with depth information. To achieve robustness, the Kanade-Lucas-Tomasi point tracker is used and dedicated to work on facial features by embedding knowledge about the configuration and visual characteristics of the face. The resulting tracker is designed to recover from the loss of points caused by tracking drift or temporary occlusion. Performance assessment experiments is carried out on a set of video sequences of several facial expressions. The methods reviewed will are the state-of-the-art algorithms for this purpose.
 Improving Rating Predictions Using Domain-sensitive Recommendation Algorithm with Collaborative Filtering Algorithms

—Collaborative Filtering (CF) is one of the most successful recommendation approaches to cope with information overload in the real world. Typical CF methods equally treat every user and item, and cannot distinguish the variation of user’s interests across different domains. This violates the reality that user’s interests always center on some specific domains, and the users having similar tastes on one domain may have totally different tastes on another domain. This paper proposed an approach DsRec algorithm with the CF-based algorithms i
SVM Computer Aided Diagnosis for Anesthetic Doctors

— The application of machine learning tools has shown its advantages in medical aided decisions. The purpose of this study is to construct a medical decision support system based on support vector machines (SVM) with 30 physical features for helping the Doctors Specialized in Anesthesia (DSA) in pre-anesthetic DSA examination or preoperative consultation. For that, in this work, a new dataset has been obtained with the help of the DSA. The 898 patients in this database were selected from different private clinics and hospitals of western Algeria. The medical records collected from patients suffering from a variety of diseases ensure the generalization of the performance of the decision system. In this paper, the proposed system is composed of four parts where each one gives a different output. The first step is devoted to the automatic detection of some typical features corresponding to the American Society of Anesthesiologists scores (ASA scores). These characteristic are widely used by all DSA in pre-anesthetic examinations. In the second step, a decision making process is applied in order to accept or refuse the patient for surgery. The goal of the following step is to choose the best anesthetic technique for the patient, either general or local anesthesia. In the final step we examine if the patient's tracheal intubation is easy or hard. Moreover, the robustness of the proposed system was examined using a 6-fold cross-validation method and the results show the SVM-based decision support system can achieve an average classification accuracy of 87.52% for the first module, 91.42% for the second module, 93.31% for the third module and finally 94.76 % for the fourth module.
AN IMPROVED GRID CONNECTED INTERLEAVED FLYBACK INVERTER

This paper proposes a special type of grid-connected inverter system for photo voltaic applications. Here the inverter system is an interleaved high power flyback inverter, ie to implement an improved grid-connected interleaved flyback inverter based on photovoltaic. The existing micro inverter topology based on flyback converter. Therefore the main objective of this paper is to design a new flyback inverter system at high power with good performance. The flyback inverter system designed for 2 KW and it is achieved by interleaving of three flyback cell. The converter is operated in discontinuous current mode (DCM) for easy and stable generation of ac current at grid interface. The system simulation confirms the performance and design of the proposed system using MATLAB Simulink.
Ensembled Spectral Reweight Boost Clustering For Energy Aware Target Object Detection In Wsn

: WSN comprises a collection of sensor nodes (SNs) distributed with small in size. To monitor the presence or absence of a particular target within the communication range, the SNs are deployed in the network. Energy is a foremost resource in target detection since the SN has inadequate battery capacity. Energy limitation of SN leads to lessen the network lifetime (NL). The several methods are developed for target detection but it still not improving the detection accuracy with minimum energy consumption (EC). In order to improve target object detection with improved NL, an Ensembled Spectral Reweight Boost Clustering Based Target Object Detection (ESRBC-TOD) technique is introduced. At first, numbers of SNs are arbitrarily positioned in the network. Then, ensemble clustering is performed by measuring the initial energy and residual energy (RE) of SN. The ensemble clustering technique initially constructs the ‗n‘ weak learners. The spectral clustering algorithm is used as weak learner to cluster the SNs based on the RE level. The Reweight boosting technique combines the weak learners and converts a strong one. Then, the SNs are grouped into diverse clusters with higher accuracy and lesser error rate. For energy efficient target detection, the cluster head (CH) is chosen in WSN. The cluster comprises one CH and several member nodes. Cluster member identifies the target node within the cluster and transmits the information to CH. After that, CH gathers information of target object and transmit to sink node via the neighboring CH. Sink node sends the gathered information to base station (BS) for finding the target objects. This leads to increases the target object detection accuracy (TODA). Simulation is performed with different metrics namely EC, TODA, false alarm rate (FAR) and target object detection time (TODT). The observed results show that the ESRBC-TOD technique effectively improves the TODA and minimizes the EC, FAR as well as TODT than the state-of-the art methods.
Proteome Expression Database of Ewing Sarcoma: a Segment of the Genome Medicine Database of Japan Proteomics

Ewing sarcoma is the second most common primary malignant bone tumor in children and adolescents worldwide. Here, we report an open-access proteome expression database of eight Ewing sarcoma cases using proteome data obtained by two-dimensional difference gel electrophoresis (2D-DIGE) and mass spectrometry. Proteins extracted from primary tumor tissues were labeled with CyDye DIGE Fluor saturation dye, and separated using a large format electrophoresis device, generating 2431 protein spots. Mass spectrometry following in-gel digestion identified 330 protein spots corresponding to 220 proteins. Multiple proteins were observed from single protein spots, and single proteins generated multiple protein spots, suggesting diversity of the proteome observed by 2D-DIGE. The results of 2D-DIGE and protein identification by mass spectrometry, and part of the corresponding clinico-pathological data such as prognosis after treatments are freely accessible in the public proteome database Genome Medicine Database of Japan Proteomics (GeMDBJ Proteomics, https://gemdbj.nibio.go.jp/dgdb/DigeTop.do). *Corresponding author: Tadashi Kondo, MD, PhD, Proteome Bioinformatics Project, National Cancer Center Research Institute, 5-11 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan, Tel: +81-3-3542-2511 ext.3004; Fax: +81-3-3547-5298; E-mail: takondo@ncc.go.jp Received December 07, 2009; Accepted December 19, 2009; Published December 20, 2009 Citation: Kikuta K, Tsunehiro Y, Yoshida A, Tochigi N, Hirohahsi S, et al. (2009) Proteome Expression Database of Ewing sarcoma: a segment of the Genome Medicine Database of Japan Proteomics. J Proteomics Bioinform 2: 500-504. doi:10.4172/jpb.1000112 Copyright: © 2009 Kikuta K, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Proteome Expression Database of Ewing Sarcoma: a Segment of the Genome Medicine Database of Japan Proteomics Kazutaka Kikuta, Yukako Tsunehiro, Akihiko Yoshida, Naobumi Tochigi, Setsuo Hirohahsi, Akira Kawai, Tadashi Kondo* Proteome Bioinformatics Project, National Cancer Center Research Institute Orthopedics Division, National Cancer Center Hospital Clinical Laboratory Division, National Cancer Center Hospital Pathology Division, National Cancer Center Research Institute Journal of Proteomics & Bioinformatics Open Access JPB/Vol.2/December 2009
Utilization of Antenatal Care Services in a Rural Field Practice Area in Coastal Part of South India

Introduction: Utilization of services during pregnancy will lead to further utilization of additional maternal services. The utilization of these services is not universal which was reflected during National Family Health Survey 3. Objective: To evaluate the utilization of antenatal care services among mothers in south India. Methods: The present community based cross sectional study was conducted among rural mothers who had delivered one year back and accompanied their children for immunization at the rural health centres. A semi-structured Proforma was used and detailed information regarding sociodemographic details and utilization of antenatal services was collected. Results: The study included a total of 300 antenatal mothers. Majority of the antenatal mothers had their antenatal checkups in private set-ups (n=257, 85.7%) and had their first antenatal check up in the first trimester (n=262, 85.3%). Around 95% of the study subjects had consumed more than 100 Iron and Folic Acid tablets. Conclusion: Utilization of antenatal care is much higher in the present study as compared to other available literature for the entire country. Consistent and focused efforts are needed to sustain and consolidate the good coverage and utilization of antenatal services.
Membrane Computing and Its Applications

— There are two types of computing; one is conventional and another is unconventional. Turing machine is a hypothetical device and a conventional model, model of computation; it is not a random access machine, so to simulate current day’s basis systems; in a exact manner register machine had been defined, so they are conventional model of computing. Paradigms like DNA computing, Quantum computing, Membrane Computing, they are model of unconventional computing. These have comes an existence in their resent times and we have found a certain problems can tackle in a very efficient manner using this. The practical use of this is still a question and it’s being exploded. Membrane computing which biologically inspired and mathematically motivated. Membrane structure is an essential ingredient of a membrane computing, having hierarchical arrangement of membranes, like a cell or tree. This mainly deals with distributed and parallel computing models. Parallelism is restricted in classical computers bounded by ‘n’ (16/64) number of processors. But when size of problems increases, then the number of processors can’t increases. Unbounded parallelism is exists in DNA, Membrane computing. Because of unbounded parallelism, you can have DNA strands and they can exist within one cubic centimeter of a solution; millions of DNA strands can exists. Because of that the action state place parallel and you can have a number of operations performed simultaneously. The basic features are evolution rules and evolving objects encapsulated in compartments of membranes. These evolution rules are applied on multisets. It is a framework to reflecting a limb of a system model.
Contribution to Vibriosis in Cultured Eels (Anguilla Anguill)

One hundred and twenty cultured eels (Anguilla anguilla L.) were collected from Behera Governorate were investigated for the isolation of Vibrio species. The isolation of Vibrio spp. was achieved from the ulcers, blood, liver, kidneys and spleen of naturally infected eels (alive and freshly dead). The recovered bacteria were studied for the virulence, pathogenicity and antimicrobial sensitivity. Blood samples were collected for determination of serum AST and ALT, total protein , albumin , globulin , cholesterol , cortisone , Glucose , direct and indirect bilirubin . Forty eight isolates of Vibrio species were identified as V.anguillarum (22) ,V.ordalii (12) , V. parahaemolyticus (7), V.vulnificus (4) and V.algnolyticus(3). The results of LD50 in eels A. anguilla injected with V.anguillarum was 10 cfu / ml , while the sublethal dose 1/10 X LD50 equal 10 cfu/ml . The experimentally infected eels showed severe hemorrhages over the body and congestion of the head. Internally, enlargement of spleen which became cherry red and loss of its sharp edges as well as severe congestion of kidney. The histopathological alterations revealed hepatic cell necrosis and hyperactivation of the melanomacrophage centers of kidneys in acute phase while in thrombus formation in the branchial artery of gills and severe glycogen deposition in liver in chronic stage. The five recorded isolates of the Vibrio species were sensitive to Ampicillin, Doxycycline, Colistin sulphate and Amoxicillin, but totally resistant to Oxytetracycline and Nalidixic acid. The Antibody titers in A. anguilla injected with booster dose of bacterin of V.anguillarum were higher than in group injected by one dose of bacterin. Asignificant increase in enzymatic activity, hypoproteinaemia ,hypoalbuminaenia and hypoglobulinaemia. Also significant increase level of adrenocorticotrophic hormone,glucose and cholesterol in chronic infection(1/10LD50) [Khalil, R. H. ; Hana R. El-hofy and Nadia. B.mahfouz Contribution to Vibriosis in Cultured Eels (Anguilla Anguill)]. Journal of American Science 2011; 7(12): 101-110]. (ISSN: 1545-1003). http://www.americanscience. org.