Reviewerly/exHarmony huggingface dataset:
K-NN SEMANTIC Inquiry on Scrambled Social Information BASE

In the present world of technology, the Data Mining has wide applications in different division, similar to bank segment, restorative field and different research focuses. Now in present days Distributed computing has most utilized as a part. Demand is one of the normally utilized works as a bit of the information. The Security is one of the fundamental pieces of the distributed computing and it is hard to deal with. So two fields daily has generally helpful. As a decade, in view of different confirmation some of issues and different hypothetical problems had been proposed below contrasting safety models. This paper will show center characterization has over an encoded information.AS we proposed K-NN classifier on encoded kind of information/details in the cloud. In the current framework security safeguarding information mining issue can’t tackle. Also, multi-party calculation not deal with legitimately. The proposed framework ensures that security of client’s data ask. What’s more, deal with DMED (Information mining over encoded information) display.
Research on Distributed Production and Publishing Technology of 3D Illustrated Part Catalog

In order to improve the timeliness and accuracy of construction machinery maintenance and spare parts service, a distributed production and publishing method for product illustrated part catalog based on service model hierarchical tree is proposed. According to the product information obtained by system integration, the product SBOM and service model are constructed; Drawing on the high-level architecture theory of distributed simulation standards, the publishing task is decomposed and collaboratively published by multiple computers. Compared with other methods, this method improves the efficiency of making and publishing illustrated part catalog and the accuracy of data, realizes the release of same-source data with multiple formats. The proposed method is illustrated by an example on a typical construction machinery grader.
Solving high dimensional multimodal continuous optimisation problems using hybridisation between particle swarm optimisation variants

This paper presents a comparison between three new hybridisations using three particle swarm optimisation (PSO) variants: The Barebones PSO (BPSO), the comprehensive learning PSO (CLPSO) and the cooperative learning PSO (CoLPSO). The goal of these hybridisations is to improve the exploration and the exploitation of the search space from these three variants and contributes to PSO on high scale continuous optimisation problems. The performance of these three new hybrids, named HCLBPSO-Half, HBPSO+CL and HCoCLPSO, are compared with the original methods on which they are based. The comparison is done using six classical continuous optimisation functions with dimensions set to 50, 100 and 200, and all 15 continuous optimisation functions from the CEC'15 benchmark with dimensions set to 10, 30, 50 and 100. The results are compared using the mean and median of executions.
Script Identification of South-East and South-West Asia: A Survey

The world population is 7.7 billion and the largest and most populous continent is Asia having 59.66% of the total world population. Southern Asia accounts for 39.49%, out of which South-East has 8.59% ranking third. Whereas, Western Asia is equivalent to 3.59% and ranks fourth in world population. This region hosts a variety of languages, playing a critical role in the polygraphia formation, sharing of one script by several languages which have applications in multilingual access to patents, business regulatory information for independently evaluating all regional market requirements. Ideographic languages in Southeast Asian scripts are left-to-right or vertically top-to-bottom is more flexible in their writing direction. This paper presents the challenges involved in analyzing handwritten and printed documents. The review work of popular scripts namely Chinese, Japanese, Thai, Sinhala, Balinese and Arabic using various methods of feature extraction and different classifiers are represented in this paper. It summarizes most of the existing methodologies in the papers published by various researchers.
Klasifikasi grade daun padi sebagai penentu pemupukan urea dengan metode ekstraksi fitur

Most of Kalimantan lands are dominated by wetland such as rivers, swamps, and coasts. This wetland indirectly plays a role on hydrology processes in Kalimantan island. Kalimantan Selatan has 37.531 km2 wide area of land with 382.272 ha wide area of wetland.  One of wetland problems, generally, can be solved by planting wetland crops that can absorb nutrient on wetland. Rice is one of wetland crops which is suitable to be planted on wetland. Fertilizer requirement for rice to grow properly must be in accordance to the needs of the rice itself. Rice farmers usually use Leaf color chart tool (BWD) to estimate the fertilizer requirement for rice based on its leaf color. The result of this chart tool depends on human visual which is subjective. Therefore, this chart tool needs to be digitized and implements intelligent system so it can resolve problems caused by human vision. BWD can be build to work automatically by using Fuzzy Logic method. The determining parameters of rice leaf characteristics can be obtained from rice leaf two-dimension (2D) images by extracting the texture features based on Hue Saturation Intensity from the images. This research explains on how to determine the urea fertilizer requirement of rice based on its leaf images.
RelDenClu:A Relative Density based Biclustering Method for identifying non-linear feature relations with an Application to identify factors effecting spread of COVID-19

The existing biclustering algorithms for finding feature relation based biclusters often depend on assumptions like monotonicity or linearity. Though a few algorithms overcome this problem by using density-based methods, they tend to miss out many biclusters because they use global criteria for identifying dense regions. The proposed method, RelDenClu uses the local variations in marginal and joint densities for each pair of features to find the subset of observations, which forms the bases of the relation between them. It then finds the set of features connected by a common set of observations, resulting in a bicluster. To show the effectiveness of the proposed methodology, experimentation has been carried out on fifteen types of simulated data. It has been used for unsupervised learning using three real-life datasets. Applicability of the algorithm is also explored on three real-life datasets to see its utility as an aid to supervised learning. For all the cases the performance of the proposed method is compared with that of seven different state-of-the-art algorithms. The proposed algorithm produces better results. The efficacy of the algorithm is shown on COVID-19 dataset and found out that some features (genetic, demographics and others) are likely to affect the spread of COVID-19.
Integrated Big Data with Public Cloud: A Model for E-Commerce Retailer Market

Cloud computing is a robust platform to perform immense and complex data computing. It supports to maintain immoderate computing hardware, committed space and software. In present scenario, the amount of data continues to increase at an exponential rate in social media such as face book, twitter etc. Massive data is being generating by e-commerce retailers such as Amazon, walmart, snap deal etc. Addressing such big data and massive transactions is an extensive challenge and time-consuming task that needs a massive computational infrastructure to ensure successful data processing, data analysis and data analytics. This study, proposed a model to review the growth of big data with cloud computing in retailers market and it integrates the cloud computing with big data. This study proposes a model integrating Big Data as a Service (BDaaS) with Public Cloud referred to as an Integrated Big data with Cloud Model (IBCM) for realistic measurement of customer behaviour, predictive analytics and also supports operational analytics and supply chain analysis of e-commerce retailers in India. This study addresses the issues of big data processing in cloud through Hadoop and Cloudera tools.
Adversarial Attacks for Embodied Agents.

Adversarial attacks are valuable for providing insights into the blind-spots of deep learning models and help improve their robustness. Existing work on adversarial attacks have mainly focused on static scenes; however, it remains unclear whether such attacks are effective against embodied agents, which could navigate and interact with a dynamic environment. In this work, we take the first step to study adversarial attacks for embodied agents. In particular, we generate spatiotemporal perturbations to form 3D adversarial examples, which exploit the interaction history in both the temporal and spatial dimensions. Regarding the temporal dimension, since agents make predictions based on historical observations, we develop a trajectory attention module to explore scene view contributions, which further help localize 3D objects appeared with the highest stimuli. By conciliating with clues from the temporal dimension, along the spatial dimension, we adversarially perturb the physical properties (e.g., texture and 3D shape) of the contextual objects that appeared in the most important scene views. Extensive experiments on the EQA-v1 dataset for several embodied tasks in both the white-box and black-box settings have been conducted, which demonstrate that our perturbations have strong attack and generalization abilities.
A Study on Humanism in the Essay of Mok Seong-gyun

수필가 목성균은 십여 년이라는 짧은 작품 활동에도 불구하고 사후 뜨거운 조명을 받는다는 점에서 ‘수필계의 기형도’라 불린다. 목성균 수필전집 『누비처네』는 “수필은 필자의 품성, 인성과 삶의 철학이 담겨야한다”는 작가의 수필관이 고스란히 응집되어 있다. 이 글은 목성균 수필전집 『누비처네』를 대상으로 그의 수필세계의 인간애를 레비나스의 타자윤리로 읽어 보았다. 실존적 연민과 인간으로서의 도리가 근간이 된 그의 수필은 레비나스의 타자의 윤리학으로 읽을 때 작가의 삶의 가치관, 인간애를 더욱 깊이 해석할 수 있기 때문이다. 이를 통해 따뜻한 정과 인간적 도리로 살아가는 삶의 가치와 통찰을 이끌어내는 수필문학의 본질을 만나고자 하는 데 있었다. 최근 수필계의 뜨거운 한 기류로 주목받는 그의 수필은 내밀한 정서와 섬세한 필력으로 ‘수필의 보고’로 자리매김하고 있다. 온몸으로 느낀 다양한 체험의 진정성과 문학적 형상의 감동으로 수필문학의 정수를 간직하고 있기 때문이다. 수필문학의 본질이란 일상 체험의 해석과 의미 부여를 통한 삶의 통찰이다. 목성균 수필세계는 인간에 대한 정을 바탕으로 삶의 보편적인 가치와 의미를 끌어낸다는 점에서 그 탁월함을 인정받고 있다. 이 연구를 통해 작가의 삶이 보여준 타자와의 따뜻한 교감과 윤리적 책임, 그 인간애가 우리들에게 얼마나 소중한 의미인지 돌아볼 수 있을 것이다. 또한 ‘어떻게 살아야 하는가’하는 근원적 질문에 대한 답을 감동으로 제시해줄 것이다.Despite essayist Mok Seong-gyun’s short ten-year period of writing activity, he is known as “Gi Hyung-do of the Essay World” and has posthumously attracted enthusiastic attention. Mok Seong-gyun’s collection of essays titled Nu-bi-cheo-ne condenses his essay-writing philosophy in one succinct statement: “An essay must contain the writer’s moral character, personality, and life philosophy.” With a focus on Nu-bi-cheo-ne, this paper aims to consider humanism in Mok Seong-gyun’s essay world from the perspective of Levinas’ ethics of the Other. Such a perspective allows us to understand Mok Seong-gyun’s life values and humanity as expressed in his essays based on human beings’ existential sympathy and duty at a much deeper level, since we encounter the essence of essay literature, especially as it pertains to life values such as warm affection, human duty, and insight. Recently, Mok Seong-gyun has received considerable attention as a hot trend in the essay world. His work is being established as a “repository of essays” that showcases his intimate emotions and elaborate writing skills. His essays preserve the essence of essay literature by providing a diverse array of sincere personal experiences and impressions of literary figuration. The essence of essay literature refers to insight into life through the interpretation of daily experiences and semantic assignment. Mok Seong-gyun’s essay world is recognized for its excellence because it extracts universal values and meanings from life based on human-to-human affection. It is anticipated that this study could make a contribution to looking back on the precious meanings that Mok Seong-gyun has revealed in his life, namely engaging in warm communion with others, ethical responsibility, and humanity. Moreover, the study intends to provide an answer to the fundamental question “How should we live?” with respect to emotion.
Modified Gabor Filter (MGF) Image Enhancement Approach for Early Detection of Lung Cancer

Lung cancer continues to be the foremost cause of death in both women and men. Worldwide, lung cancer kills over 1 million peoples a year. The major cause of lung cancer is smoking. In India each year it is estimated that about 80% of male lung cancer deaths and 70% of lung cancer deaths are caused by smoking. Undoubtedly, lung cancer is a major threat to human beings and also a widespread disease which constitutes a major public health problem. Other possible factors for lung cancer are increased air pollution by dusts and gases released by industry, automobile traffic etc. Hence, lung cancer detection is one of the major needs of the day. Several researchers developed Image Processing Techniques (IPT) for the detection of Lung Cancer [, , , , , , , ]. Earlier researchers employed the methods like Discrete Cosine Transform (DCT), Auto Enhancement Algorithm (AEA), Fast Fourier Transform (FFT), for image enhancement. These approaches are time consuming and less accurate. Some of the researchers are also used Kalman Filters, Hessian Based Filters (HBF), but these filters have drawbacks like, varying contrast; poor and non-uniform response for images of varying sizes [, ]. Some of other researchers used interpolation techniques, which is complex and time consuming []. So, to overcome the drawbacks of these earlier approaches, a new image enhancement technique is proposed with modifications in Gabor Filters which will help in early and efficient detection of lung cancer. This Modified Gabor Filter (MGF) approach has been validated using CT (Computer Tomography) and X-ray lung images which are collected from a hospital and they are analysed. The results obtained are comparable with real time analysis of medical practitioners. Hence, this new technique for Image Enhancement using MGF Approach can be employed for early detection of lung cancer and this technique is also suitable for development of new medical equipment’s for better detection of lung cancer.
Implementation of Code Cleanup and Code Standard Refactoring with PMD and UCD Tool

Software refactoring is the procedure that requires alteration in the source code to keep away from unused variable or duplicated variable, unused method and deprecated method. In this paper, work is done for implementation of CCACSR with PMD and UCD tool, which is useful for software refactoring. This paper focuses on CCACSR that includes mainly three modules, first to detect and then remove unused or duplicate variable from source code, second to detect and then remove or comment unused method from source code and third module is to find out the method which will be replaced by its equivalent new method of source code, so that method can be changed but its external behavior should not be changed. Other than this a comparison of developed system result with PMD and UCD tools is also performed. For this a program of 15–430 lines of code is developed. This code is checked with available platform and found results very effective. And same code is checked with PMD and UCD tools. Finally, the comparison of the results is performed with these tools. The detection of cloned variable or unused variable can be done by the concept of method and classes of AST parser and JAVA parser of eclipse from the existing source code, after removing the cloned or unused variable from source code and save the associated information in file for further used purpose. Similarly to detect the unused method from existing source code prepared by the concept of method and classes of AST parser and JAVA parser of eclipse and store related file after comment or removing particular method from source code. For Refactoring swing API is used, which is to find out the old method of older version and will be replaced by new method of newer version of Java. We compare our IDE CCACSR with PMD&UC Detector, which detects only unnecessary code but in our IDE and we determine as well as remove it from Java source file.
The Development of Classroom Climate Study in Indonesia (A Historical Perspective)

Improving the micro-scale education quality through classroom climate improvement can be conducted, either by the teacher or school principal according to the each capacity. These efforts have been widely implemented abroad. Nevertheless, it is still rare in Indonesia because of the lack of adequate instruments or measurement tools, or even the lack of teacher capacity and principals in conducting the improvement. In America or Australia, classroom climate improvement has become an integral part of the learning process and the education process in schools. In Indonesia, the improvements need to be pursued in order to become a good habit. The author has started that effort by developing standardized, valid and reliable classroom climate instruments starting from primary education, secondary and higher education. The instruments have been used for classroom action research in order to improve the classroom climate. These efforts still need to be strengthened and disseminated to education providers, teachers and school principal to stimulate them and other researchers to use the classroom climate instrument in order to improve the learning and education quality in schools.
Dimensional Insight to Innovations in Security Aspects of Cloud Computing

Computing remotely also brings with it the most sensitive and significant aspect of data security. Data being resident on server and infrastructure that are opaque to users bring with it the huge advantage of ridding users of all the infrastructure operational liabilities. But this also means the data owned by users navigates through routes either unknown or no control territory. This glaringly brings security of data on cloud with high vulnerability. This paper explores dimensionally various such vulnerabilities, and related strategies to circumvent them does involve a sensitive disection of modern technology in today’s world of computing. An insights through various levels of infrastructure, application, data and network architecture gives this research enough evidence that complexities involved in solutioning the security problems of cloud computing is nevertheless a path most discussed and debated. Further much attention is needed to all the vulnerabilities discussed and solutioning them comprehensively.
Definiteness across Languages: from German to Mandarin

We showcase the potential of a data-driven methodology for cross-linguistic research: Translation Mining. We introduce the technique and put it to use in the domain of definiteness. We show how Translation Mining confirms existing insights about definiteness in English, German (Schwarz 2009) and Mandarin (Jenks 2018) while at the same time leading to novel insights for Mandarin.
A Neural Network Approach to Automated Classification of Elementary Mathematics Instructional Activities

Automated analysis of classroom video for teaching evaluation has eluded current solutions. A few types of neural networks have recently proven effective for video classification: convolutional neural networks (CNNs), long short-term memory (LSTM) neural networks, and hybrid CNN-LSTMs. We use classification accuracy to evaluate the efficacy of each approach while taking account of practical considerations such as the computational burden of each method as well as the training set required.
Outlying Info Integrity-Checking Protocol with Augmented Stability to Secure Storage in Cloud

Outlying information stability monitoring permits a web server to prove to a reviewer the respectability of missing reports. The innovation is so valuable for isolated storing. Distributed storage is taken as example in this regard. The inspector could be a person other than the data administrator, in this manner, a RDIC can be termed even as OOIC whose evidence depends generally on freely accessible details. To record the interest of data security against an unconvicted inspector, Hao et al. determined officially “the outsiders against personal protection are deputed for verification” as safety requests and a method is recommended for fulfilling this delineation. Nonetheless, do notify that every current technique with open undeniable nature associate facts refresh, a recommendation call for the data proprietor to distribute some meta-data identified with the spared info. We disclose that checker could inform a customer that he has spared a clear-cut data and typical parts of records depends information that is discharged in Hao et al’s convention. At the end of the day, the idea “personal security against outsider verifiers” isn’t sufficient in shielding data personal protection, and also in this way, we present “zero-information personal protection” to guarantee the verifier who don’t discover any info concerning data related to client from all promptly accessible details. We help the security of Hao et al’s methodology, build up model to audit the execution, furthermore execute investigation to make evident the practicality of above recommendation.
PENGGUNAAN METODE PROMETHEE PADA APLIKASI PEMBELIAN SMARTPHONE

Along with developments, mobile phones are one of the most important communicationtools today. The use of communication devices in the form of mobile phones that are filled withcriteria and specifications often makes people confused in the selection of suitable mobile phones.Therefore, the public is given the ease in the matter of selecting the handphone. This study aimsto create an application to provide recommendations for purchasing Android-based smartphones.This study uses the Promethe method to produce a smartphone purchase recommendation tocustomers. The results of this study are in the form of an application that can provide smartphonepurchase recommendations to customers. It is expected that the application can help the Intercellular shop in providing advice to buyers who want to buy a cellphone or smartphone withcertain criteria.Keywords— Promethee, Smartphone, Android
LibGuides: Cataloging Toolbox for International Government Information: Reference Shelf for Cataloging & Authority Work

Cataloging, classification and subject vocabularies used in creating metadata description for International Governmental Organizations.
A Survey on Reversible Data Hiding Techniques

Data hiding is a technique for carrying data in a suitable carrier for secure communication. Data hiding technique provides authentication and secure communication but there may be a chance of loss of carrier during communication. Data hiding techniques are mainly used for authentication, media registration, copyright protection, etc. But in the field of medicine and military distortion of the original image is not allowed. So it needs high secure data hiding techniques. To overcome the problem faced during extracting the carrier with distortion was removed by RDH (Reversible Data Hiding) techniques. RDH technique gets the original data after extracting the secret encrypted data. RDH techniques are classified based on implementing method. In this paper we discussed about different techniques based on histogram shifting, compression embedding and different expansion for RDH are discussed.