Adversaries always eager to take advantage of flaws in emerging healthcare digital solutions. Very few authors discussed durable application security. Therefore there is a need for a durable security mechanism that must be adequately efficient, is reliable, and defend critical data in an emergency situation. It ensures that the application can be serviced and meet the needs of users over an extended period of time. This paper presents the fuzzy TOPSIS based method to evaluate the behavioural impact for durable security in the context of the Digital India initiative. This paper also presents novel DURASec blueprints for trustworthy and quality healthcare application development.. Even though the advantages of such technologies may outweigh the dangers, hospitals, drugstores, clinics, practitioners, the drug industry as well as medical device manufacturers, should be prepared to identify and minimize security threats in order to protect sensitive healthcare data.

Image denoising is very important in image preprocessing. In order to introduce the priori information of external clean image into the denoising process, a non-local clustering image denoising algorithm is proposed. A sparse representation dictionary is obtained by combining the image blocks of external clean image and internal noise image. The sparse coefficient estimation of ideal image is obtained by global similar block matching. Based on the class dictionary and the estimated sparse coefficient, a sparse reconstruction method based on compressed sensing technology is used to denoise the image. Experimental results show that compared with traditional image denoising methods, the proposed algorithm can significantly reduce the denoising block effect and preserve more details while transitioning more naturally in the flat area of the image.

In this paper, we propose an automatic scoring method for Chinese-English spoken translation based on attention LSTM. We select semantic keywords, sentence drift and spoken fluency as the main parameters of scoring. In order to improve the accuracy of keyword scoring, this paper uses synonym discrimination method to identify the synonyms in the examinees' answer keywords. At the sentence level, attention LSTM model is used to analyze examinees' translation of sentence general idea. Finally, spoken fluency is scored based on tempo/rate and speech distribution. The final translation quality score is obtained by combining the weighted scores of the three parameters. The experimental results show that the proposed method is in good agreement with the result of manual grading, and achieves the expected design goal compared with other methods.

Characterizing the topology of MANETs provides the means for packet routing protocols to perform adaptively and efficiently in the particular environments. We show that the geographic routing’s greedy packet forwarding distance dissimilarity distributions in relation to node size characterizes MANET topologies and supports efficient multi-greedy forwarding. The models we described, based on the average greedy packet forwarding distance measures, showed distinct distribution patterns of the dissimilarity indices when applied to the example multi-greedy routing environment consisting of the ELLIPSOID and the GREEDY forwarding metrics. The scheme demonstrates the potential for adaptive forwarding performance to improve successful packets delivery in environments of high node-size variations such as VANETs.

INTRODUCTION: Breast cancer is the most hazardous disease among women worldwide. A simple, cost-effective, and efficient screening called mammographic imaging is used to find the breast abnormalities to detect breast cancer in the early stages so that the patient’s health can be improved.

OBJECTIVES: The main challenge is to extract the features by using a novel technique called Advanced Gray-Level Co-occurrence Matrix (AGLCM) from pre-processed images and to classify the images using machine learning algorithms.

METHODS: To achieve this, we proposed a four-step process: image acquisition, pre-processing, feature extraction, and classification. Initially, a pre-processing technique called Contrast Limited Advanced Histogram Equalization (CLAHE) is used to increase the contrast of images and the features are retrieved using AGLCM which extracts texture, intensity and shape-based features as these are important to identify the abnormality.

RESULTS: In our framework, a classifier called eXtreme Gradient Boosting (XGBoost) is applied on mammograms and the results are compared with other classifiers such as Random Forest (RF), K-Nearest Neighbor (KNN), Artificial Neural Networks (ANN), and Support Vector Machine (SVM). The experiments are done on the Mammographic Image Analysis Society (MIAS) dataset.

CONCLUSION: The outcome achieved with CLAHE+ AGLCM+ XGBoost classifier is better than the existing methods. In future, we experiment on large datasets and also concentrate on optimal features selection to increase the classification.

In this proposed method, iMCS can detect and prevent fake sensing activities of mobile users using machine learning techniques. Our iMCS solution uses behavioral analysis based on participants' reliability scores to detect variation in behavior of users and introduces a new role in a distributed system of MCS architecture to validate the collected data. To evaluate the incentive based on the participant's sensory data and data quality, to properly distribute profit among the participants, we employ the Shapley Value approach. The evaluation results demonstrate that our method is effective in both quality estimations and incentive sharing.

The Maritime Society of the Riau Islands Province has various forms and varieties of folklore, for instance the Legend of the Alut Island. This legend has the value of local wisdom that is appropriate for character education media at the primary and secondary education levels. The purpose of this study is (1) to describe the educational value of Alut Island folklore characters, (2) assist teachers in providing literary teaching materials (folklore), (3) help the availability of learning materials about folklore, and to (4) introduce students about the folklore of Alut Island. This research includes qualitative research. The research method uses content analysis method. Data collection techniques using document techniques and the data analysis using structural techniques. The result of the research is that the Legend of Alut Island contains character education values, for instance religious values, hard work, and responsibility values.

One form of literary learning that can be applied to members of Generation Z is the adoption of a digital-based learning model, which involves designing an application that contains literary materials and content. The use of such applications in literary learning is optional, as teachers can employ this digital device as an alternative or in combination with conventional learning. Hence, literary learning with this digital device should cover a larger portion during lessons based on the characteristics of current Generation Z students, who are generally more interested in learning with electronic visual forms. This will allow teachers to only serve as facilitators to direct the teaching of all elements of instructional materials that have been incorporated into the digital application. Therefore, teachers' position becomes less central because the learning is more student-centered. The design of literature learning using this digital device is one of the efforts of innovation to answer the challenge of science and technology in education.

The purpose of this study is to reveal about the symbols and meanings of the symbols contained in the poetry structure of Junewal Muchtar's poetry. The theory used in this research is symbol theory which analyzes an object representing a symbol. The method used in analyzing this poem is descriptive and qualitative methods. The source of the data was obtained from the collection of poetry Retak Looking for Belah by Jenewal Mucthar. The results of this study indicate that the symbols contained in 46 poems by Jenewal Muchtar are living things and objects. Symbols of living things include humans, animals and plants which have the meaning of piety, faith, honor, power, loyalty, stength, peace and so on. as well as objects including anchors, bottles, glasses, and others which have the meaning of being transparent, and easily cracked.

Teachers need to have good inquisitive techniques because they help to train students cognitively. Therefore, this study aims to examine teacher's questioning skills to facilitate students in thinking at higher levels. A total of 150 teachers from the elementary school that partakes in online training activities were selected as participants. The results showed that the teacher's questioning skills through the HOTS were in a suitable category, while the evaluating and creating aspects were in the lower level.