Data Sorting Research Articles

A Review on Data Mining Technology

Presently days the method involved with removing significant principles from large and complex data are called data mining. Data mining has a rising fame in each field today. Data units are laid out in client situated enterprises, for example, showcasing, money and telecom to deal with the client beat and obtaining, specifically. Among the data mining techniques, order calculations are utilised in examinations led for client securing to anticipate the likely clients of the organization being referred to in the connected business. The idea of Data Mining has arisen to meet the prerequisite of speedy and exact data support for dynamic cycle. Data Mining is investigation of data to distinguish connection between various data components or substances. The course of data mining can likewise include connection or relationship between at least two data components, substances or occasions. They permit associations to make proactive, information-driven choices and answer questions that were already excessively tedious to determine. In this exploration we have zeroed in on the correlation of different Data Mining apparatuses which are useful and set apart as the significant field of data mining Technologies. As we know that numerous public and Multinational organisations and little or enormous associations are worked in better places of the various nations. Every activity might produce large data or unstructured. This sort of huge data is accessible as byte which has definitely changed in different regions. To examine, oversee and pursue a choice of such sort of colossal measure of data we really want strategies called the data mining which will changing in many fields. Bank advertising data set in UCI Machine Learning Data Set was utilised by making models with similar grouping calculations in various data mining programs. Exactness, accuracy and measure measures were utilised to test exhibitions of the characterisation models. While making the grouping models, the test and preparing data sets were arbitrarily separated by the holdout technique to assess the exhibition of the data set.

Cognitive Advantage of Bilingualism Over Monolingualism in Older Adults: A Meta-Analysis.

This study aimed to explore whether bilingual older adults had a cognitive advantage over their monolingual counterparts, and validate the influence of cognition-related (participants' cognitive condition, the cognitive domain assessed), and bilingualism-related factors (second language proficiency, frequency of use, acquisition time, and immigration status of participants)on the cognitive advantage of bilingualism. Through a systematic search of nine databases (Web of Science, PubMed, Elsevier Science Direct, Cochrane Library, Embase, PsycINFO, CNKI, VIP and Wanfang) from the inception to April 2021, observational studies with bilingual and monolingual older adults as participants and cognitive function scores as outcome measures were included. Two reviewers independently completed the selection and methodological quality assessment of studies using the JBI cross-sectional study quality evaluation tool and used a pre-designed table for data extraction and sorting. Fourteen studies with 51 tasks were included, involving 3737 participants (bilingual group: 1695, monolingual group: 2042). The overall results of the meta-analysis showed that bilingualism had a small cognitive advantage over monolingualism in older adults [SMD=0.23, 95%CI (0.07, 0.38), P=0.004]. In addition, the subgroup analyses indicated that factors such as participants' cognitive condition, the cognitive domain assessed, second language proficiency, acquisition time, and immigration status of participants impacted the cognitive advantage of bilingualism in older adults. Bilingualism had a mild cognitive advantage over monolingualism in older adults, which was more prominent in older adults with mild cognitive impairment than in cognitively healthy ones, more evident in global cognitive function and inhibitory control than in other individual cognitive domains, and might be influenced by the proficiency and acquisition time of second language as well as the immigration status of older adults.

Digitalised Information Security in Data Communication in Organizational Flow

Abstract: Understanding what cyber security is and how to successfully apply it in today's culture, which is driven by technology and network connections, is vital. Systems, essential information, data, and other important virtual goods are at risk if there is no security to protect them. Every business, whether it is an IT firm or not, requires equal protection. Similarly, attackers do not lag behind in terms of developing new cyber security technology. They've upgraded their hacking techniques and are concentrating on the weak places of several businesses. Cyber security is vital because military, political, financial, medical, and corporate entities gather, practise, and store large amounts of data on PCs and other devices. Financial data, intellectual property, personal information, and other sorts of data that could be harmed by unauthorised access or acquaintance can make up a major amount of the data

University Students’ Reflection on Chosen Characteristics of National Populism in Slovakia

Aim. The main aim of presented study is the exploration of university students´ reflection on chosen characteristics of national populism in Slovakia. Methods. For the main method of the study, a quantitative approach has been used. Students studying at universities in the Slovak Republic have been addressed via a questionnaire prepared in advance. Recorded answers of sixty-seven university students studying in the Slovak Republic have been analysed via first-degree data sorting. Results. The study has a theoretical-empirical character. In the theoretical part, there is a brief characteristic of national populism and characteristics of national-populistic tactics and strategies in Slovakia. In the empirical part, the analysis of surveyed university students´ opinions shows that most addressed university students studying at Slovak universities have not expressed a negative view of presenting the interests of the Slovak nation by political representatives. Conclusion. The addressed university students reflect on the issue of national populism on the Slovak political scene. On the other hand, respondents lack a relevant and expert view of the issue of national populism through the optics of a university educator who would (via his/her expert opinion) help students to identify undesired national-populistic tactics and strategies. A more detailed study of university students’ opinions related to their view of national populism and its manifestations in Slovakia should be supplemented by a qualitative study, using in-depth interviews.

People With Knee Osteoarthritis Attending Physical Therapy Have Broad Education Needs and Prioritize Information About Surgery and Exercise: A Concept Mapping Study.

To (1) identify the education priorities of people with knee osteoarthritis, including perceived importance and confidence that a health care professional can address each, and (2) match priorities to education-specific content recommendations in knee osteoarthritis management guidelines. Concept mapping methodology. Participants generated, sorted (based on themes), and rated (5-point Likert scales: importance and confidence) education priorities. Multidimensional scaling and hierarchical cluster analysis of sorting data produced a cluster map with overarching domains. Priorities were matched against education-specific content recommendations in knee osteoarthritis guidelines. Participants (brainstorming, n = 43; sorting and rating, n = 24) generated 76 priorities. A 4-domain, 11-cluster map was the most useful representation of sorting data: (i) understanding treatment options (relationship of education and exercise with surgery, adjunct options, treatment decision making); (ii) exercise therapy (how to exercise, why exercise); (iii) understanding and managing the condition (symptom management, understanding symptoms, understanding the condition); and (4) surgical, medical, and dietary management (surgery, medications, diet and supplements). The "relationship of education and exercise with surgery" (3.88/5), "surgery" (3.86/5), and "how to exercise" (3.78/5) clusters were rated highest for importance. Few priorities identified by participants were clearly recommended as education-specific content recommendations in the American College of Rheumatology (3%, n = 2/76), European Alliance of Associations for Rheumatology (12%, n = 9/76), National Institute for Health and Care Excellence (16%, n = 12/76), and Osteoarthritis Research Society International (1%, n = 1/76) guidelines. People with knee osteoarthritis presenting to physical therapists have broad education needs and prioritize information about surgery and exercise. J Orthop Sports Phys Ther 2022;52(9):595-606. Epub: 17 June 2022. doi:10.2519/jospt.2022.11089.

Semiotic analyses of actions on digital and analogue material when sorting data in primary school

This paper focuses on the actions of learners on digital and analogue materials while dealing with a statistical problem. To investigate the learners’ actions, a semiotic perspective of mathematical learning according to C. S. Peirce is used, since in this perspective learning mathematics is described as visible activities on diagrams. Through a qualitative semiotic analysis of the actions of two third-graders working with given data, the statistical diagram interpretations of the learners can be reconstructed. A comparison of the reconstructed diagram interpretations reveals whether different movements lead to similar diagram interpretations. In addition, it is of interest whether the diagram interpretations are the same when acting on digital and analogue diagrams because the same mathematical relationships have to be observed. Through this comparison, conclusions can be drawn about the similarities and differences in working with digital and analogue materials and how these materials may be used profitably in statistical learning.

Foredune responses to the impact of aggregate extraction in an arid aeolian sedimentary system

AbstractCoastal dunes have long suffered the effects of human interventions that have altered the landscape and operation of these ecosystems. Aggregate extractions have been shown to modify the biogeomorphological processes in aeolian sedimentary systems. The impacts associated to aggregate extraction include the reduction of available sediment and changes to the topography and vegetation patterns, thereby altering the sedimentary dynamics and limiting the recovery capacity of the dunefield. The aim of this article is to analyse the environmental effects produced by historical aggregate extraction in the foredune area of an arid aeolian sedimentary system (El Médano, Tenerife, Spain) through a study of the airflow dynamics and spatial distribution of vegetation, sediment and topographic changes. The methodology was designed with two temporal scales: (i) a long‐term approach which compares historical sources and current ones; (ii) a short‐term approach through experimental data collection to characterize the present functioning. For the latter, a field study was carried out in June 2021, collecting wind speed and direction data at a height of 0.50 m, sediment data (sand sheet thickness, grain size and sorting), and vegetation data (cover and species richness) at 40 sample points. The main results show that when the anthropic stress ceased the foredune did not follow a natural environmental pattern, and that the way it functions at the present time is determined by the changes induced by the aggregate extraction. Changes include alterations to the topography, the creation of a lagoon, and the generation of an aeolian deflation area and flow acceleration zones with the associated sand transport. This research contributes to an understanding of the environmental consequences of aggregate extractions on the foredunes of arid aeolian sedimentary systems and can enable the relevant authorities to make better‐informed decisions that help the management of these ecosystems.

RELIGIOUS MODERATION : AGAINST INTOLERANCE AND DERADICALIZATION

Conflict between religious communities is a sensitive matter that often occurs. This is due to truth claims about various practices that tend to be different from the teachings of the religion adhered to. Indonesia as a country that embraces pluralism does not escape the turmoil of religious conflicts that characterize the life of the nation, so that it has an impact on the loss of tolerance between people and tends to bring up radical principles and coercion of one belief. To produce valid and reliable data, this paper uses a qualitative writing style. In producing logical data, this paper performs several stages of data sorting in the form of: 1). Data reduction, 2). Display data, 3). Verifying data, and 4). Interpret research data. In its presentation, measurable analysis becomes the foundation in processing the data obtained. The perfection of this paper cannot be separated from the library technique carried out by exploring the existing literature in Google Scholar. Truth claims that are too radical tend to foster a sense of intolerance in a nation, this situation will be used by terrorist elements to build a division of the state through religious cloaks. This situation became the center of attention of the Indonesian government so that a program called "the house of religious moderation" was conceptualized to rebuild the dignity of tolerance between religious communities. The legalization of houses of religious moderation begins through educational institutions which in fact are neutral institutions in a country. It is hoped that intellectuals born in educational institutions will be able to provide a concrete understanding of the importance of maintaining tolerance through the values of Pancasila and religious values that are relevant to the situation and stability of the country.

Stakeholder insights into athlete attrition in the high-performance pathway

ObjectivesPrimary: To gain a system-wide perspective on factors leading to athlete attrition from a high-performance sport system (HPSS).Secondary: To identify what a sample of system-wide stakeholders and past athletes value as the most important and feasible attrition factors to address to retain talented athletes. DesignMixed-methods. MethodsConcept mapping was used for qualitative data collection and quantitative data analysis. Sixty-one participants including: (i) past athletes from an Australian state sporting institute; (ii) their families; and (iii) internal and external stakeholders to a HPSS who supported past athletes. ResultsParticipants brainstormed 83 unique statements (i.e. attrition factors) that were mapped into 13 clusters of attrition factors following multidimensional scaling and hierarchical cluster analysis performed on the participants sorting data: ‘abuse and mismanagement of health’; ‘athlete health’; ‘limited support/resourcing’; ‘coaching’; ‘inconsistent processes’; ‘financial and career support’; ‘pathway structure’; ‘organisational dynamics’; ‘competitive stress’; ‘performance potential’; ‘challenges with selection and transition’; ‘psychological state’; and ‘competing non-sport priorities’. ‘Abuse and mismanagement of health’ had the highest mean importance (3.76 out of 5) and feasibility (3.31) rating. The 13 clusters were further grouped into four overarching domains: ‘sport system policy, structure and processes’; ‘pathway structure, transition and support’; ‘individual athlete health and capability’; and ‘whole-of-life demands and priorities’. The domain ‘sport system policy, structure and processes’ contained the most important and feasible clusters. ConclusionsMacro (system-level) and micro (intrapersonal and interpersonal) level athlete attrition factors should be considered together. Athlete health was considered the most important athlete retention issue to address.

IL-33 enhances Jagged1 mediated NOTCH1 intracellular domain (NICD) deubiquitination and pathological angiogenesis in proliferative retinopathy

Pathological retinal neovascularization (NV) is a clinical manifestation of various proliferative retinopathies, and treatment of NV using anti-VEGF therapies is not selective, as it also impairs normal retinal vascular growth and function. Here, we show that genetic deletion or siRNA-mediated downregulation of IL-33 reduces pathological NV in a murine model of oxygen-induced retinopathy (OIR) with no effect on the normal retinal repair. Furthermore, our fluorescent activated cell sorting (FACS) data reveals that the increase in IL-33 expression is in endothelial cells (ECs) of the hypoxic retina and conditional genetic deletion of IL-33 in retinal ECs reduces pathological NV. In vitro studies using human retinal microvascular endothelial cells (HRMVECs) show that IL-33 induces sprouting angiogenesis and requires NFkappaB-mediated Jagged1 expression and Notch1 activation. Our data also suggest that IL-33 enhances de-ubiquitination and stabilization of Notch1 intracellular domain via its interaction with BRCA1-associated protein 1 (BAP1) and Numb in HRMVECs and a murine model of OIR.

Detecting the Security Level of Various Cryptosystems Using Machine Learning Models

With recent advancements in multimedia technologies, the security of digital data has become a critical issue. To overcome the vulnerabilities of current security protocols, researchers tend to focus their efforts on modifying existing protocols. Over the last few decades, though, several proposed encryption algorithms have been proven insecure, leading to major threats against important data. Using the most appropriate encryption algorithm is a very important means of protection against such attacks, but which algorithm is most appropriate in any particular situation will also be dependent on what sort of data is being secured. However, testing potential cryptosystems one by one to find the best option can take up an important processing time. For a fast and accurate selection of appropriate encryption algorithms, we propose a security level detection approach for image encryption algorithms by incorporating a support vector machine (SVM). In this work, we also create a dataset using standard encryption security parameters, such as entropy, contrast, homogeneity, peak signal to noise ratio, mean square error, energy, and correlation. These parameters are taken as features extracted from different cipher images. Dataset labels are divided into three categories based on their security level: strong, acceptable, and weak. To evaluate the performance of our proposed model, we have performed different analyses (f1-score, recall, precision, and accuracy), and our results demonstrate the effectiveness of this SVM-supported system. INDEX TERMS Support vector machine (SVM), security analysis, image encryption, cryptosystem.

Challenges Faced by Dialysis Unit Staff During COVID-19 Times: A Qualitative Study

Background: The Coronavirus has caused an epidemic affecting the whole world for the last two years and has been spreading steadily. The hemodialysis patients are at high risk because of their lowered immunity status. The dialysis staff is also at higher risk of contracting COVID-19 as these patients come for twice/thrice weekly treatment sessions. Objectives: This study was done to study the hardships and problems afflicting the dialysis staff during the infections caused by COVID-19 in a rural hemodialysis unit. Methods: This study setting was the hemodialysis unit located in a rural hospital in Pondicherry, India. Free listing and pile sorting were done to study the structure and salient problems as felt in the cognitive domain by the dialysis team. Smith's S value was calculated for a free listing. Multidimensional scaling and cluster analysis were conducted to do pile sorting of data. Data were analyzed using Anthropac 4.983/X. Group interviews were carried out to get in-depth information and validate the findings obtained from the free list and pile sorting exercise. Results: Twelve salient items were obtained from the free list. Three broad domains emerged: the absence of personal safety, shortage of personal safety equipment, and presence of logistical and operational problems. Surprisingly, RT-PCR testing was not perceived to be of importance for them. Conclusions: Accepting the true feelings, fears, and needs of the dialysis staff, helping to tackle the impediments to personal safety, and the lack of personal safety equipment in a dialysis unit during COVID-19 outbreak are vital in ensuring personal safety and improving working dynamics.

Using AI to detect and classify malicious domain names

On the Internet and other IP networks, the Domain Name System (DNS) is used to identify machines. Resource entries in the DNS link domain names to various sorts of data. Commonly, it is used to transform domain names to IP addresses so that computers may locate services and devices utilizing the underlying network protocols. Due to a lack of security safeguards, cybercriminals use the Domain Name System (DNS) to launch attacks. So how to quickly locate and block possibilities? Finding rogue websites and their IP addresses has become a prominent research topic. Preventing unknown cyber-attacks is critical. This article advocated analysing enormous amounts of mobile web traffic to find dangerous domains. To classify, we used text and domain traffic statistics. Then we gave three typical classifiers to compare their impacts. The Spark framework is used to calculate huge amounts of DNS traffic. Our system's efficiency persuades us. It can be very useful in network security. The new features are tough to use and assist in identifying rogue domains. We tested MalPortrait using real-world big ISP networks' passive DNS traffic.

The Implementation of the Mind Mapping Model in Developing Children's Creativity in Thematic Lessons

Children's creativity is a potential that must be developed through the educational process. This study aims to describe the implementation of the mind mapping model in developing children's creativity in thematic lessons. This study uses a qualitative approach with a descriptive study method. The background of this research is in MIN Medan. Observation techniques, interviews, and document studies are three research data acquisition techniques. Then, the data were analyzed using an interactive analysis model, through the steps of data collection, data sorting, data presentation, and drawing conclusions. The results of this study indicate that the application of the mind mapping model makes it easier for educators during the thematic learning process, because it stimulates students to develop their creativity based on the spirit of group learning. Likewise, there are obstacles in implementing the learning model, namely the low focus of students in group activities, difficulties for teachers to control student learning behavior, and some students like to disturb their friends.

Application of Text Mining in Social Media.

Text mining or information discovery is that sub manner of information mining that is extensively being used to find out hidden styles and huge records from the massive amount of unstructured written fabric. Text mining allows accelerate know-how discovery by way of notably growing the amount records that can be analyzed. Rapid development in digital facts acquisition strategies have caused huge extent of facts. More than 80 percentages of these day’s statistics is composed of unstructured or semi-based information. This sort of data cannot be used until or unless particular records or pattern is determined. The discovery of appropriate patterns and trends to research the text documents from large quantity of records is a big issue. Social community applications create possibilities to set up interaction amongst people main reciprocal studying and exchanging of relevant understanding, chat, feedback, and discussion forums. Information in social media web sites is disorganized and fuzzy in character. In normal lifestyles conversations, people does not care about the spellings and correct grammatical creation of a sentence that could result in exceptional styles of ambivalence, such as syntactic, lexical and semantic. Large quantities of unstructured text information generated on the Internet, text mining is thought to have excessive business fee. We describe how textual content mining might also expand modern organizational studies with the aid of permitting the testing of present or new research questions with information which are likely to be rich.

Transgenic mice encoding modern imaging probes: Properties and applications.

SUMMARYModern biology is increasingly reliant on optical technologies, including visualization and longitudinal monitoring of cellular processes. The major limitation here is the availability of animal models to track the molecules and cells in their natural environment in vivo. Owing to the integrity of the studied tissue and the high stability of transgene expression throughout life, transgenic mice encoding fluorescent proteins and biosensors represent unique tools for in vivo studies in norm and pathology. We review the strategies for targeting probe expression in specific tissues, cell subtypes, or cellular compartments. We describe the application of transgenic mice expressing fluorescent proteins for tracking protein expression patterns, apoptotic events, tissue differentiation and regeneration, neurogenesis, tumorigenesis, and cell fate mapping. We overview the possibilities of functional imaging of secondary messengers, neurotransmitters, and ion fluxes. Finally, we provide the rationale and perspectives for the use of transgenic imaging probes in translational research and drug discovery.

UNCERTAINTY REDUCTION PADA MAHASISWA TAHUN PERTAMA DI MASA PANDEMI COVID-19

This research aims to reveal the forms of uncertainty experienced by first-year students during the pandemic as well as to describe the uncertainty reduction strategies that have been carried out. The method used is a qualitative research method with a case study approach. Data analysis was carried out by selecting and sorting data, both primary and secondary according to the focus of this research and tested for its validity level using triangulation of sources and methods. The results showed that the interaction process of first-year students during the pandemic took place more virtually. As a result, informants experience three forms of uncertainty at the same time, namely cognitive uncertainty, behavioral uncertainty, and relationship uncertainty. One of the things that creates uncertainty for first-year students during this pandemic is the concealment of faces and identities by not turning on the camera during virtual interactions. This then causes individual confusion in behaving to other individuals. The strategy taken to reduce this uncertainty is in the form of planning and seeking information, while hedging measures are not found in this research.

Comparison Analysis of Bubble Sort Algorithm with Tim Sort Algorithm Sorting Against the Amount of Data

The role of algorithms in software or programming is so important that you need to understand the basic concepts behind them. In most of our daily life, we often face problems that need to be solved by entering the data sorting process. A lot of programming logic has been created, both in the general case and in the special case. In this study, the authors carried out the sorting process with two methods, namely bubble sort and tim sort. Sorting application is built using C++ program. Algorithms are needed in order to be able to solve a problem more effectively and efficiently in a shorter time using only a few resources. The preparation of this research uses data collection methods that aim to obtain the necessary data so that it can be extracted to be used as information. It is hoped that from this information it can be seen that the comparison of the bubble sort algorithm with the tim sort is getting better in the data sorting process, if the number of inputted data is greater than n.

Visualization and Analysis Model of Industrial Economy Status and Development Based on Knowledge Graph and Deep Neural Network.

This paper adopts knowledge mapping combined with a deep neural network algorithm to conduct in-depth research and analysis on the current situation and development of the industrial economy and designs a visual analysis model of economic development based on knowledge mapping combined with a deep neural network algorithm. Cultivate the concept of coordinated development and legal system of the subject, improve the awareness of network security and integrity self-discipline of the subject, improve the level of network hardware equipment manufacturing, improve the level of network platform construction, build a network security technology prevention system, improve the repair system of network information alienation, set up a specialized agency setting for the coordinated development of network ecology and industrial economy, and increase the capital investment in network infrastructure and network information technology research and development. A framework of breadth and depth recommendation ranking based on a knowledge graph is proposed and implemented. This paper provides a visual analysis method to sort and classify multivariate data. The method first determines users' preferences through their interactive operations, calculates the weights of each attribute according to the users' preference model, then uses the obtained attribute weight sets to sort the whole data set, and finally completes the category classification according to the sorting results and the users' markings on some data. The visual display allows users to intuitively perform data sorting and classification operations and quickly understand the characteristics and category features of the data. The framework achieves modeling and integration of knowledge graph neighborhood information from breadth dimension and depth dimension to realize personalized recommendation sorting and improves the F1 metrics by 8.59%, 14.36%, and 15.22% on the public datasets Amazon-book, Yelp2018, and ILast-FM compared with the previous optimal model.

The Role of TPD Pay Al Ma'ruf on Education of Orphans and Dhuafa Around The Al Ma'ruf Mosque

The cost of education is a common problem for students, especially in the era of the Covid-19 pandemic. In addition, the free time that parents use to earn a living for the family during the Covid-19 pandemic has made a minimal role in social education and character guidance for children at home. For this reason, the role of the community is needed in helping to finance education and character building for underprivileged families. This study attempts to describe the role of the Al Ma'ruf Orphans Education Fund Management Team (TPD PAY) in the education of orphans and poor people around the al-Ma'ruf mosque. This type of research is based on a qualitative approach paradigm with a case study method. Data were obtained through interviews, observation, and document review. Then, it is analyzed through data sorting techniques, data presentation, and drawing conclusions. The results of this study indicate that the role of TPD PAY Al Ma'ruf for orphans and poor people around the al Ma'ruf mosque is very beneficial. This is marked by 3 aspects, namely (1) providing educational scholarships for orphans and poor people around the al Ma'ruf mosque, (2) fostering children's character based on the Koran, and (3) supporting children's talents and creativity.