A Search Based Face Annotation (SBFA) Algorithm for Annotating Frail Labeled Images

Data mining is the method of extracting valuable data from an over-sized information supply. Currently a day’s web has gained additional attention of users with its wealthy interfaces and surplus quantity of knowledge on the market on web. This has earned plenty of user’s interest in extracting plenty of helpful data but it’s still restricted with a number of the resources extraction like frail labeled facial pictures. This paper mainly investigates a novel framework of search-based face annotation by mining frail tagged facial pictures that are freely available on the web. One major limitation is how effectively we can perform annotation by exploiting the list of most similar facial pictures and their weak labels that are usually vague and incomplete. To resolve this drawback, we have a tendency to propose a unsupervised label refinement (ULR) approach for refining the labels of web facial pictures. A clustering-based approximation algorithmic rule which might improve the quantifiable significantly is implemented. In this paper we've enforced a replacement search supported image search i.e. Image is taken as input instead of text keyword and also the output is additionally retrieved within the sorted list of image, If the input image is matched with any of the of pictures in image sound unit. Also ranking is given to images based on user views

INTELIGENT HOME AUTOMATION CONTROL USING BLUETOOTH AND GSM

The home automation improves the approach to life of the management of home devices. Technology advancements have created the implementation of embedded systems within home appliances. the talents and advantages are inflated by the house automation. The worth of our lives may be improved by automating numerous instruments or electrical appliances. There's continuously a stipulation for home automation through mobile phones. Our main objectives are to assist recent aged people and incapacitated and to regulate the house appliances from overseas. Our major focus is on dominant the house appliances from each indoor and outdoor. The mobile application is formed and interfaced with the device to control home appliances through Bluetooth and GSM for indoor and out of doors controlling severally

Determination, Development and Validation of Method for Simultaneous AXITINIB Pharmaceutical Dosage form by a Reverse Phase HPLC

A simple and selective LC method is described for the determination of AXITINIB dosage forms. Chromatographic separation is observed on a c18 packing column using mobile phase with a mixture of TEA -Acetonitrile (50:50) with detected at 254nm. Linearity was observed in the range 15-45 µg /ml for AXITINIB (r2 =0.997) for drug estimated by the proposed methods was in good agreement with the label claim. The proposed method was validated. The accuracy of the methods was assessed by recovery studies at three different levels. The current study indicated the absence of interference of commonly encountered pharmaceutical additives. The method was precise to be indicated by the repeatability analysis, by showing %RSD > 2. All statistical data proved the validity of the methods and used for routine analysis of pharmaceutical dosage form

Study of safety and efficacy of autologous platelet rich plasma combined with fractional CO2 laser in the treatment of post acne scars: a comparative simultaneous split-face study

Background: Many treatments are available for treating post acne scars but optimized treatment does not exist still. Hence, this study was conducted with the aim to evaluate the safety and efficacy of autologous platelet rich plasma combined with fractional CO2 laser for treatment of acne scars when used in Indian skin.Methods: Thirty patients attended to the Dermatology OPD were enrolled in the study after meeting inclusion criteria. They underwent split-face therapy. They received ablative fractional carbon dioxide (CO2) laser combined with autologous platelet-rich plasma (PRP) treatment on one half of their face and ablative fractional CO2 laser with intradermal normal saline on the other half. The injections were administered immediately after laser therapy. Each participant received 4 treatments spaced by 1 month and were followed up for a period of 4 months.Results: The outcome among the study subjects were assessed using Goodman and Baron Scale at different time intervals. Significant reduction in acne scars was observed in both PRP injection site and normal saline injection site but better reduction of acne scars was noted at the PRP site. The blinded physician’s assessment and patient satisfaction was better at PRP injected side as compared to the normal saline injected side. The incidence of adverse effects and pain during the procedure was significantly lower in PRP injected side compared normal saline injected side.Conclusions: This study demonstrated that PRP should be considered as an adjuvant therapeutic option for dermatologic procedures such as fractional CO2 laser resurfacing for treatment of post acne scars as it might have additional benefit of reducing the adverse effects such as persistent erythema and edema

Enhancing the Performance of Automated Grade Prediction in MOOC using Graph Representation Learning

In recent years, Massive Open Online Courses (MOOCs) have gained significant traction as a rapidly growing phenomenon in online learning. Unlike traditional classrooms, MOOCs offer a unique opportunity to cater to a diverse audience from different backgrounds and geographical locations. Renowned universities and MOOC-specific providers, such as Coursera, offer MOOC courses on various subjects. Automated assessment tasks like grade and early dropout predictions are necessary due to the high enrollment and limited direct interaction between teachers and learners. However, current automated assessment approaches overlook the structural links between different entities involved in the downstream tasks, such as the students and courses. Our hypothesis suggests that these structural relationships, manifested through an interaction graph, contain valuable information that can enhance the performance of the task at hand. To validate this, we construct a unique knowledge graph for a large MOOC dataset, which will be publicly available to the research community. Furthermore, we utilize graph embedding techniques to extract latent structural information encoded in the interactions between entities in the dataset. These techniques do not require ground truth labels and can be utilized for various tasks. Finally, by combining entity-specific features, behavioral features, and extracted structural features, we enhance the performance of predictive machine learning models in student assignment grade prediction. Our experiments demonstrate that structural features can significantly improve the predictive performance of downstream assessment tasks. The code and data are available in \url{https://github.com/DSAatUSU/MOOPer_grade_prediction

Reachability problems for PAMs

Piecewise affine maps (PAMs) are frequently used as a reference model to show the openness of the reachability questions in other systems. The reachability problem for one-dimentional PAM is still open even if we define it with only two intervals. As the main contribution of this paper we introduce new techniques for solving reachability problems based on p-adic norms and weights as well as showing decidability for two classes of maps. Then we show the connections between topological properties for PAM's orbits, reachability problems and representation of numbers in a rational base system. Finally we show a particular instance where the uniform distribution of the original orbit may not remain uniform or even dense after making regular shifts and taking a fractional part in that sequence.Comment: 16 page

ERROR ANALYSIS ON PRONOUN MADE BY THE ELEVENTH GRADE STUDENTS OF SMA KATOLIK CINTA KASIH TEBING TINGGI IN ACADEMIC YEAR OF 2020/2021

The Research was aimed to analyze the error on pronoun made by the eleventh grade students of SMA Katolik Cinta Kasih Tebing Tinggi in Academic Year of  2020/2021. The subject of this research consists of 30 students in XI-MIPA-1. The objectives of the study were (1) To find out the types of error made by students in using pronoun. (2) To find out what causes the students made such error in using pronoun. This research used qualitative approach with descriptive research. The errors were collected, identified, and classified based on the Surface Structure Taxonomy by Dulay. It was specified by four types of errors namely omission, addition, misordering, and misformation.The result showed (1) The most common errors made by the students were misformation (52,0%) or 88 errors. The second was error in addition with the frequency (35,5%) or 60 errors. The third error was omission (11,2%) or 19 errors. The lowest frequency of error was misordering (1,1%) or 2 errors. (2) The students made such errors in using pronouns because of their less motivation of learning, lack of knowledge about grammar and English language, and minimal use of media by the teacher during teaching learning process. The teacher should create an interesting teaching, so it that can increase the students’ interest in learning English

Learning from Prior Designs for Facility Layout Optimization

Peer reviewe

Indigenous Knowledge and Long-term Ecological Change: Detection, Interpretation, and Responses to Changing Ecological Conditions in Pacific Island Communities

When local resource users detect, understand, and respond to environmental change they can more effectively manage environmental resources. This article assesses these abilities among artisanal fishers in Roviana Lagoon, Solomon Islands. In a comparison of two villages, it documents local resource users’ abilities to monitor long-term ecological change occurring to seagrass meadows near their communities, their understandings of the drivers of change, and their conceptualizations of seagrass ecology. Local observations of ecological change are compared with historical aerial photography and IKONOS satellite images that show 56 years of actual changes in seagrass meadows from 1947 to 2003. Results suggest that villagers detect long-term changes in the spatial cover of rapidly expanding seagrass meadows. However, for seagrass meadows that showed no long-term expansion or contraction in spatial cover over one-third of respondents incorrectly assumed changes had occurred. Examples from a community-based management initiative designed around indigenous ecological knowledge and customary sea tenure governance show how local observations of ecological change shape marine resource use and practices which, in turn, can increase the management adaptability of indigenous or hybrid governance systems

Nonparametric identification of regulatory interactions from spatial and temporal gene expression data

<p>Abstract</p> <p>Background</p> <p>The correlation between the expression levels of transcription factors and their target genes can be used to infer interactions within animal regulatory networks, but current methods are limited in their ability to make correct predictions.</p> <p>Results</p> <p>Here we describe a novel approach which uses nonparametric statistics to generate ordinary differential equation (ODE) models from expression data. Compared to other dynamical methods, our approach requires minimal information about the mathematical structure of the ODE; it does not use qualitative descriptions of interactions within the network; and it employs new statistics to protect against over-fitting. It generates spatio-temporal maps of factor activity, highlighting the times and spatial locations at which different regulators might affect target gene expression levels. We identify an ODE model for <it>eve </it>mRNA pattern formation in the <it>Drosophila melanogaster </it>blastoderm and show that this reproduces the experimental patterns well. Compared to a non-dynamic, spatial-correlation model, our ODE gives 59% better agreement to the experimentally measured pattern. Our model suggests that protein factors frequently have the potential to behave as both an activator and inhibitor for the same <it>cis</it>-regulatory module depending on the factors' concentration, and implies different modes of activation and repression.</p> <p>Conclusions</p> <p>Our method provides an objective quantification of the regulatory potential of transcription factors in a network, is suitable for both low- and moderate-dimensional gene expression datasets, and includes improvements over existing dynamic and static models.</p