Reviewerly/exHarmony huggingface dataset:
Empirical Processing of Breast Cancer Prediction Strategies using DEFS Algorithm

Now-a-days an important threat to women over global manner is Breast-Cancer, which is the major disease cause drastic affection to female especially. Identification of Breast Cancer over earlier stages is must to save one's life and the significant affection range of Breast-Cancer is drastically improved day by day due to the improper food-habits, pollution-level and improper-life style as well as genetic-issues also. The main cause of this disease is the arising of breast-ample over the ‘breast-area, which develops the cancer to women in several cases. If the detection or prediction of such masses over earlier stage will helps to women to get more survival ratio as well as this leads a proportion to researchers to make an systematic process to detect such diseases on initial stages by using intelligent prediction methodologies with high accuracy rates. In this paper, the proposed system handles several stages of processing to make sure the prediction accuracy, such steps are as follows: Data acquisition, Feature vector formation by normalization, Feature Selection by using Differential Evolution based selection methodology, Classification using Subspace Ensemble Learning and different Performance Measures. By using these strategies the entire work assures the proposed system is perfect to predict or identify the breast cancer benign/malignant stages more accurately compare to the classical Margin-Based Feature-Selection process. Compared to the classical biopsy methodology, a systematic diagnosis attains more impact due to its prediction accuracy. This proposed system is powered by a powerful approach called Differential-Evolution Feature’-Selection (“DEFS”) with the association of Subspace Ensemble Learning Classification principle, which provides highest accuracy and prediction rates compare to the classical methodologies. This proposed paper assures effective and robust mining strategies in Breast Cancer identification/prediction as well as efficient decision-making norms. The proposed outcome proves the good accuracy and resulting levels by means of Precision-Recall, Sensitivity and Specificity, True Positive/True Negative, False Positive/False Negative, Accuracy and Time Consumption.
Linear Kernel with Weighted Least Square Regression Co-efficient for SVM Based Tamil Writer Identification

Tamil writer identification is the task of identifying writer based on their Tamil handwriting. Our earlier work of this research based on SVM implementation with linear, polynomial and RBF kernel showed that linear kernel attains very low accuracy compared to other two kernels. But the observation shows that linear kernel performs faster than the other kernels and also it shows very less computational complexity. Hence, a modified linear kernel is proposed to enrich the performance of the linear kernel in recognizing the Tamil writer. Weighted least square parameter estimation method is used to estimate the weights for the dot products of the linear kernel. SVM implementation with modified linear kernel is carried out on different text images of handwriting at character, word and paragraph levels. Comparing the performance with linear kernel, the modified kernel with weighted least square parameter reported promising results.
Statistical Distribution Functions for Daffodil Plants – Directions & Numbers

The daffodil plant (N.pseudo-Narcissus) typically makes its first appearance during March of each year, as early as March 1st following a warm winter, (Hanks, 2003; Greene et al. 2019).(Of course, these initial dates may occur 1 or 2 weeks later just 200 miles North to Boston, or 1 or 2 weeks earlier 200 miles South to Washington D.C.) Similar to the photo-sensitive responsibilities (also called heliotropic or phototropic responses) of sunflower plants (the Helianthus, Vandenbrink et al., 2014), daffodil plants also align and position their flower stems during development, with respect to sunrise, noontime, and sunset, so as to collect maximum solar radiation averaged throughout the day.The development phase, from ground level break-through to the appearance of flowers, usually takes 3 to 5 weeks, after that, the flowers last 3 or 4 weeks and then wilt.Remarkably, as shown in Fig. 1 below, for each plant, most of the flowers seem to "agree", concurring on the optimal direction, which is usually Eastward facing, but can sometimes be South, West, or North (listed in descending preferred order). Figure1. Normal growth of the daffodil plant, 3rd week of April Introduction contIn terms of plant mechanics, elastic modulus, stem bending, and buckling characteristics are measured by Greene & Greene (2015, 2016, 2017, 2019) for the Taraxacumofficinale and N. pseudo-Narcissus
A QoS-Latency Aware Event Stream Processing with Elastic-FaaS

Stream processing systems need to be elastically scalable to process and respond the unpredictable massive load spike in real-time with high throughput and low latency. Though the modern cloud technologies can help in elastically provisioning the required computing resources on-the-fly, finding out the right point-in-time varies among systems based on their expected QoS characteristics. The latency sensitivity of the stream processing applications varies based on their nature and pre-set requirements. For few applications, even a little latency in the response will have huge impact, whereas for others the little latency will not have that much impact. For the former ones, the processing systems are expected to be highly available, elastically scalable, and fast enough to perform, whenever there is a spike. The time required to elasticity provision the systems under FaaS is very high, comparing to provisioning the Virtual Machines and Containers. However, the current FaaS systems have some limitations that need to be overcome to handle the unexpected spike in real-time. This paper proposes a new algorithm called Elastic-FaaS on top of the existing FaaS to overcome this QoS latency issue. Our proposed algorithm will provision required number of FaaS container instances than any typical FaaS can provision normally, whenever there is a demand to avoid the latency issue. We have experimented our algorithm with an event stream processing system and the result shows that our proposed Elastic-FaaS algorithm performs better than typical FaaS by improving the throughput that meets the high accuracy and low latency requirements.
On educational legislation of the Russian Federation in terms of training scientific and educational personnel in graduate school

Examined are changes in educational legislation of the Russian Federation in terms of training of scientific and educational personnel in postgraduate studies (adjunct). It is noted that as a result of the initial transformations of the “Bologna format” in accordance with FH-273, the effectiveness of the national graduate school has significantly decreased. The impact of the new changes in the educational legislation of the Russian Federation in terms of the training of scientific and educational personnel in graduate school on the quality of postgraduate programs and the nature of postgraduate training are discussed. Corrective measures have been proposed to improve the effectiveness of postgraduate studies at both the level of educational and scientific organizations and at the state level.
THE ROLE OF APPARENT DIFFUSION COEFFICIENT VALUE IN DIFFERENTIATING BENIGN FROM MALIGNANT SOFT TISSUE MASSES

ackground.Soft tissue masses are frequently referred for imaging assessment.Magnetic resonance imaging (MRI) is the technique of choice for detection of these masses and local staging of the malignant one.Purpose.The study is aimed to measure the apparent diffusion coefficient (ADC) values of different soft tissue masses and determine the cut-off value that can be helpful in differentiating between the benign and malignant histological types.Materials and methods.A prospective study was conducted in the Radiology Department of the Oncology Teaching Hospital.A total of 37 cases enrolled during the period from 12th July 2019 to 20th February 2020.Diffusion weighted images (DWI) were performed for all cases.The mean ADC value for the enhancing component of each mass was measured on the generated ADC map done at high b-value of 800 sec/mm2.Results.The benign soft tissue masses were recorded in 15 (40.5%), while malignant masses found in 22 (59.5%) of patients.The greatest ADC values (mean±SD) measured for the benign masses was (1.97 x10-3 mm2/s ±0.39) for hemangiomas.While the greatest ADC value results for the malignant masses was for myxoid liposarcoma (2.11 x10-3 mm2/s ±0.45).The lowest ADC values were observed in hematological tumors.In a selected group of masses which their enhancing componenet expressed low signal or intermediate hyperintense signal in T2-WI (n=26), the mean ADC value for the malignant masses (n=18) was lower than the mean ADC value of benign (n=8) (0.863±0.28 vs. 1.675±0.39),with statistically significant association (P-value=0.002)and the ADC cut-off value of 1.42 x10-3 mm2/s gives a high sensitivity of 94.44%, a high specificity of 87.5%, and accuracy of 92.31% for differentiating malignant from benign masses which was statistically significant (P-value <0.000).Conclusions.In a selected group of soft tissue masses which their enhancing componenet express low or intermediate hyperintense signal in T2-WI, the mean ADC value was lower in malignant soft tissue masses than that in benign masses with a cut off value of 1.42 x10-3 mm2/s gives a high sensitivity and a high specificity.
SECURE PRESERVING DATA IN INTERNET OF THINGS (IOT) USING CRYPTOGRAPHY AND STEGANOGRAPHY TECHNIQUES

Information is the contribution for different man-made reasoning (AI) calculations to mine important highlights, yet information in Internet is dissipated all over and constrained by various partners who can't put stock in one another, and use of the information in complex the internet is hard to approve or to approve. Accordingly, it is extremely hard to empower information partaking in the internet for the genuine enormous information, just as a genuine amazing AI. In this paper, we propose the SecNet, a design that can empower secure information putting away, processing, and partaking in the enormous scope Internet climate, focusing on a safer the internet with genuine huge information and hence improved AI with a lot of information source, by incorporating three key segments: 1) blockchain-based information offering to possession ensure, which empowers believed information partaking in the huge scope climate to shape genuine large information; 2) AI-based secure figuring stage to create more insightful security rules, which assists with building a more confided in the internet; 3) confided in esteem trade instrument for buying security administration, giving an approach to members to increase financial prizes when giving out their information or administration, which advances the information sharing and subsequently accomplishes better execution of AI. Besides, we examine the common use situation of SecNet just as its possibly elective approach to convey, just as break down its adequacy from the part of organization security and financial income.
Asymmetric Sigmoidal Activation Function for Feed-Forward Artificial Neural Networks

Artificial neural networks of the feed – forward kind, are an established technique under the supervised learning paradigm for the solution of learning tasks. The mathematical result that allows one to assert the usefulness of this technique is that these networks can approximate any continuous function to the desired degree. The requirement imposed on these networks is to have non-linear functions of a specific kind at the hidden nodes of the network. In general, sigmoidal non-linearities, called activation functions, are generally used. In this paper we propose an asymmetric activation function. The networks using the proposed activation function are compared against those using the generally used logistic and the hyperbolic tangent activation function for the solution of 12 function approximation problems. The results obtained allow us to infer that the proposed activation function, in general, reaches deeper minima of the error measures and has better generalization error values.
Retraction Note to: Multi-label Text Classification: Select Distinct Semantic Understanding for Different Labels

The authors have retracted this conference paper [1] because of significant overlap with a previously published conference paper by Lin et al. [2]. All authors agree with this retraction.
Enhanced Auction Based Scheduling in Cloud Computing

In distributed computing different cloud clients could demand number about cloud benefits all the while. Provisioning remains completed so that every resource was completed accessible in the direction of client's solicitation within an effective way toward fulfil their requirements. The present contribute dependent on interest because resources were planned based on specific arrangements. So as to battle as well as settle Virtual Machine (VM) planning issue during distributed computing, Novel Unique Tabu Search (NUTS) resource supported booking method while have its premise up auction sale method remains appeared via remembering numerous components incorporating the band with along with due date considering system as well as sale. The offers about customers were initially ordered inside the challenge due date. Besides, a displaying about the customer gathering remains completed as well as the VM resource such compares toward it remains arranged in understanding towards insignificant expense about the service suppliers. Ultimately, instalment cost remains settled via accepting normal instalment just as instalment completed via contenders into reflection in this way empowering auspicious finishing about VM resource job. The after-effects about reenactment examinations demonstrate the present method suggestion that was ready remains equipped for improving proficiently QoS otherwise Quality of Service about cloud context, and furthermore guarantee the present benefits about suppliers of cloud management as well as charge about resource usage of VMs were productively finished.
Pengaruh Aplikasi Pembelajaran Pengenal Aksara Bali Terhadap Prestasi Belajar Siswa Kelas III pada Mata Pelajaran Bahasa Bali di SD Negeri 1 Kawan

This study aims to, 1) determine the effect of the learning application identifier Balinese script towards student achievement in Balinese subjects in SDN 1 Kawan. 2) describe the students' responses regarding the learning of Wianjana scripts using the learning media of the introduction of Balinese script. As an application for learning Balinese alphabet recognition, a template matching technique is used. This type of research is quasi-experimental research (quasi-experimental) with a post-test-only control group design. The population of this study was all students of class III of SD Negeri 1 Kawan, totaling 42 students. The sampling technique in this study is used the saturated sampling technique because all members of the population are members of the sample. The sample consisted of class III-A of 21 students as the experimental group and class III B of 21 students as a control group. Data were collected using a multiple-choice test method and a questionnaire method. A multiple-choice test is given about 20 items. The research questionnaire used was a questionnaire with a gutter scale, where respondents answered questions about the number of answer choices provided. The data analysis method uses descriptive qualitative and quantitative data analysis. Hypotheses test using correlated sample t-tests. The results showed that 1) The application of learning the introduction of Balinese Script teaches students' learning achievement in the Balinese subject at SD Negeri 1 Kawan elementary school. This can be seen from the approval of the average score of students' learning achievement tests in the study group is greater than the control group. 2) The students' responses about the learning of Wianjana scripts using the learning media for the introduction of Balinese script were very positive. Can be seen from the results of the questionnaire which shows the figure of 88.57% with a very positive category.
Implementation of Advanced Security System using QR Code for Catching Stolen Vehicle

In India, which is a developing country ,it always needs a significant improvement in infrastructure such as Roads or Highways. These constructions' of highways is costly, which can't be done by the government alone. Normally Public personal partnerships square measure made to construct such an enormous projects. The money spent on these projects can be regained by collecting toll from the passengers who uses the roads. The toll collection system, particularly in developing country like India faces some issues such as long queue lines, escaping from toll plazas etc. These systems can service only 300 vehicles per hour, and if more than that number of vehicles arrive at that plaza, server traffic jams may occur. Number of crimes involving vehicle stealing has increased with the increase in number of vehicles. Although there are many strict laws being in place, thieves can still get a way to stay one step ahead and vehicle theft is still among one of the most reportable crimes worldwide.To solve these problems, we propose QRCode based toll collection system.In our proposed system at the time of vehicle registration, QRcode is generated.We collect toll and identify vehicle is stolen or not at the toll collection booth.
Smart Classrooms and E-learning

Smart classroom is technology-enhanced classrooms that foster opportunities for teaching and learning by integrating learning technology, such as computers, specialized software, audience response technology, assistive listening devices, networking, and audio/visual capabilities. Smart classroom allows students and teachers to personalize their environment according to their likes and needs.&lt;br/&gt; A learning system based on formalised teaching but with the help of electronic resources is known as Elearning. E-learning can also be termed as a network enabled transfer of skills and knowledge, and the delivery of education is made to a large number of recipients at the same or different times.&lt;br/&gt; Learning is not how much one can cramp up. It's rather the knowledge that remains after one forgets what he/she learned in schools. Thus we emphasize on learning the concepts with the help visuals and activities. To keep such view the smart learning was introduced. The Smart Learning approach provides learners of all ages and walks of life with a framework and a host of Smart Thinking Tools that motivate higher levels of understanding. Through the process learners activate and build background knowledge, process information, transform their learning into a product that shows what they know, and reflect on their learning. Structured talk and assessment as and for learning are carefully woven into the process to build a thoughtful context for learning and to advance the thinking of all learners.
Perancangan Prototype Sistem Informasi Monitoring Stok Barang pada PT XYZ

Monitoring is one of the important stages that must be carried out regularly, especially on the stock of goods. With the continuous monitoring process, it is hoped that all goods will always be under supervision so that stock management becomes easier and more accurate. PT XYZ at this time, in monitoring the stock of goods, they still use general applications that are devoted to calculating numbers, resulting in the current stock of monitoring system having several shortcomings, namely the unavailability of the login function and reports that must be reprocessed with the different application. Based on these problems, the authors conducted a research entitled designing a prototype monitoring stock of goods information system at PT XYZ. The information system that built in this study will be defined using the waterfall modeling and use case diagrams. The final result of this research is a prototype of an stock of monitoring information system that allows system users to carry out various functions such as functions to change their own passwords, perform CRUD management of user data, item data, category data, brand data, unit data, vehicles data, supplier data, incoming goods data, outgoing goods data and processing reports that related to the stock of goods at PT XYZ.
Detecting Spam Vietnamese Email

Spam messages have been causing much impact on email users. There are many different techniques and measures applied to detect and classify spam messages with other emails. Filters have been installed and configured to detect spam emails based on their identifying characteristics. However, relying only on filters is very easy to miss spam emails because spammers often try to use techniques to bypass the filter's control. The most effective approach in spam detection today is to find ways to analyze the content of emails. However, it is recognized that each natural language will have different analytical and identification characteristics, so it is not possible to use the same technique or method for all languages. In this paper, we will present a method to detect Vietnamese email based on the process of analyzing email content in both HTML and image formats.
Mathematical Formula of Performance of Watermarking System with Repetition of Bits of Watermark

The performance of a watermarking system depends on all of its factors, such as watermark embedding strength, size of watermark and repetition of watermark bits. In this paper, a mathematical formula is designed, that governs the relation of performance of watermarking system with amount of the repetition of watermark bits. Performance of the watermarking system is measured by using the extracted watermark bit accuracy rate. The designed formula is verified experimentally. A spatial domain watermarking scheme is used for experimental verification. Further, verification is done for different kind of attacks such as cropping, Gaussian filter, Gaussian noise and salt &amp; pepper noise. Accuracy rate by using the mathematical formula and experimental observations are very near. This supports that the designed mathematical formula is reliable.
Using Data Mining Techniques to Analyze the Customers Reaction towards Social Media Advertisements

As social media is in boom, it is becoming very easier for customers to share their views and comments and express their feelings regarding any products which are present in online social media. . If these data can be analyzed efficiently different suggestions can be provided to the company regarding to improvise their products sale. It becomes easier for the company to understand the customer’s reaction after seeing the advertisements of the products posted on social media. This research focuses on analyzing the sentiments of customers based on the comments and reviews of products available in Facebook. Sentimental Analysis is performed to analyze the customer comments as positive, negative and neutral and later they are labeled as 0 or 1. After the labeling process, a comparative analysis is performed using different classification algorithms. The classification algorithms used are K Nearest Neighbors (KNN), Support Vector Machine (SVM) and Naïve Bayes Classifier. The classification algorithm with the highest accuracy is identified to predict the sales of online products.