Data Sorting Research Articles

EDITORIAL SPECIAL ISSUE: PART IV-III-II-I SERIES

EDITORIAL SPECIAL ISSUE: PART IV-III-II-I SERIES

Replication Strategy with Comprehensive Data Center Selection Method in燙loud Environments

As the amount of data continues to grow rapidly, the variety of data produced by applications is becoming more affluent than ever. Cloud computing is the best technology evolving today to provide multi-services for the mass and variety of data. The cloud computing features are capable of processing, managing, and storing all sorts of data. Although data is stored in many high-end nodes, either in the same data centers or across many data centers in cloud, performance issues are still inevitable. The cloud replication strategy is one of best solutions to address risk of performance degradation in the cloud environment. The real challenge here is developing the right data replication strategy with minimal data movement that guarantees efficient network usage, low fault tolerance, and minimal replication frequency. The key problem discussed in this research is inefficient network usage discovered during selecting a suitable data center to store replica copies induced by inadequate data center selection criteria. Hence, to mitigate the issue, we proposed Replication Strategy with a comprehensive Data Center Selection Method (RS-DCSM), which can determine the appropriate data center to place replicas by considering three key factors: Popularity, space availability, and centrality. The proposed RS-DCSM was simulated using CloudSim and the results proved that data movement between data centers is significantly reduced by 14% reduction in overall replication frequency and 20% decrement in network usage, which outperformed the current replication strategy, known as Dynamic Popularity aware Replication Strategy (DPRS) algorithm.

A PERFORMANCE COMPARISON OF SORTING ALGORITHMS IN DIFFERENT PROGRAMMING LANGUAGES

Sorting, as one of the basic algorithms, has a wide range of applications in software development. As the amount of processed data grows, the need for fast and efficient data sorting increases significantly. There are many sorting algorithms and their extensions. However, choosing the best and most versatile among them is impossible. All these algorithms have their specifics, which determine the scope of their effective use. Therefore, the problem of deciding the optimal algorithm for certain specific conditions is relevant. This choice is often a non-trivial task, and an unsuccessful choice of algorithm can cause difficulties with data processing performance. To determine which algorithm will be the best in a particular situation, you need to analyse all the factors that affect the operation of algorithms: the size and structure of the data set, the range of element values, the form of access (random or sequential), the orderliness, the amount of additional memory required to execute the algorithm, etc. In addition, different algorithms have different performance in different programming languages. The study analyses the advantages and disadvantages of nine popular sorting algorithms (Bubble, Insertion, Selection, Shell, Merge, Quick, Counting, Radix, and Heap) due to their specifics and limitations on their possible use. The performance of these algorithms implemented in four popular programming languages (C++, C#, Java and JavaScript) is tested. We experimentally discovered that the performance of sorting algorithms differs depending on the programming language. The applied aspect of the study is that its conclusions and results will allow developers to choose the best algorithm for a particular programming language, depending on the size, range, structure, etc. of the data set to be sorted. Considering this is significant when we have to sort large amounts of data in search engines, scientific and engineering applications. After all, the sorting algorithm's efficiency significantly affects the system's overall performance.

A Multi-Criteria Optimisation Algorithm for the Evaluation of Scientific Activity

The article discusses a multi-criteria optimization algorithm, developed for the estimation of the quality of scientific activity. The presented solution is based on a modified knapsack algorithm, the novelty of the approach relies on extended data sorting – with splitting apparently equivalent data blocks. The criteria of the algorithm are based on the regulations in force in Poland, but it is possible to easily adapt the methodology to the requirements for scientists in other countries and for other tasks requiring multi-criteria optimization

STRENGTHENING THE DIMENSIONS OF PANCASILA STUDENT PROFILE IN SCHOOL MOVER IN THE ERA OF INDUSTRIAL REVOLUTION 4.0

The progressive era impacted the decline in the Pancasila values implementation in everyday life. The young generation behaves not according to the values and norms that apply in society. Based on this, it is necessary to strengthen character education in the era of the industrial revolution 4.0. In this era, science and technology developed rapidly. School mover is the school model of Kurikulum Merdeka implementation. One of the messages in the curriculum is strengthening character education. The character education implementation in the Kurikulum Merdeka is based on Pancasila values, called the Pancasila student profile.
 This research used qualitative methods, especially case studies. The researcher collected data by observation, in-depth interviews, and documentation; he tested the validity of the data by source triangulation and method triangulation. Data analysis included the stages of collecting data, identifying, sorting data, and concluding.
 Based on the research results, school movers, especially the Persatuan Umat Islam Elementary School, implemented strengthening character education by developing a religious basis, namely Islamic values. Educators trained students to implement the dimensions of the Pancasila student profile with a humanist approach and innovative strategies. They also used technology in various school activities because they educated the millennial generation; this generation is interested in technological developments.

A dataset of UAV multispectral images for the grassland-livestock balance

The grassland-livestock balance system plays an important role in reconciling the protection of grassland resources with the sustainable development of animal husbandry. The accurate estimation of the grassland-livestock balance is the basis for the implementation of the grassland-livestock balance system. In order to explore the accurate calculation method of the important parameter, i.e. livestock grass demand in the calculation system, in this study, we set up an experimental area in the natural grassland of Hulunbuir, Inner Mongolia, to simulate a real grazing scene, and conducted 4 grazing experiments controlling the sheep number and grazing time. We obtained multispectral images of the experimental area before and after grazing were with the help of the UAV remote sensing, and carried out a quadrat survey. After data sorting and preprocessing, we produced this dataset of high spatial resolution image data and accurate quadrat investigation data. It can be applied to the research on the daily grass demand of grazing sheep on Hulunbuir meadow steppe in autumn. This dataset provides data support for the accurate estimation of local grassland-livestock balance, and is of great significance for the adaptive dynamic management of grass and livestock.

Conceptualising adherence to exercise for musculoskeletal pain: A concept mapping study.

The concept of adherence to exercise for musculoskeletal (MSK) pain is poorly defined and inadequately measured. This study aimed to, (1) conceptualise adherence to exercise therapy for MSK pain, and (2) identify statements most representative of the new conceptualisation that could be developed into items for a new measurement tool. Concept mapping methodology was used, which is an integrated mixed methods approach. Focus groups with stakeholders generated statements describing adherence to exercise for MSK pain. Statements were grouped according to themes and rated for importance. Data analysis via multidimensional scaling and hierarchical cluster analysis produced a series of concept maps, which were refined during a further stakeholder workshop to produce the final conceptualisation of exercise adherence. Mean importance ratings established statements most suitable for future development. Twenty-eight participants produced 100 unique statements concerning adherence, which were sorted and rated. Analysis of the sort data with further participant refinement concluded that adherence to exercise consists of six domains: communication with experts; targets; how exercise is prescribed; patient knowledge and understanding; motivation and support; and psychological approach and attitudes. Fifty-six statements were rated with above average importance for inclusion in a new measure of adherence to exercise for MSK pain. Adherence to exercise for MSK pain is a complex and multi-dimensional construct represented by six distinct domains. Statements that best represent these domains have been identified by key stakeholders and will inform the development of a new measure of adherence to exercise for MSK pain.

SISTEM SIMBOL DALAM LABUHAN SARANGAN DI KELURAHAN SARANGAN KECAMATAN PLAOSAN KABUPATEN MAGETAN

This study aims to describe and explain the symbol system contained in the Labuhan Sarangan. This research is a type of qualitative research based on an eclectic approach as an outcome of the collaboration of semiotics and hermeneutics theory. The researcher acts as a human instrument. The data of this research are verbal and nonverbal symbols. Verbal symbol data came from the speeches of the actors in the Labuhan Sarangan. Nonverbal symbol data came from the actions of the actors, equipment, and tools that support the implementation of the Labuhan Sarangan. Data collection was done by observing and interviewing Labuhan Sarangan. Data analysis is done in four stages, namely sorting data according to the range of problems, organizing data in formation and categorization, interpreting data based on empirical understanding, and evaluating data units to produce conclusions. The result of the study showed the findings on the shape, meaning, and function of the symbol. Findings in the form of symbols include verbal and nonverbal symbols. The verbal symbols findings include words or mantras or prayers and gamelan that is used as an accompaniment to the Labuhan Sarangan, which is spoken during the labuhan procession. Findings nonverbal symbols include the actions of the actors, equipment, and tools that support the implementation of the Labuhan Sarangan and the offerings used at the time of the Labuhan Sarangan. The findings on the meaning of symbols include religion, ethics, and philosophy. The function of symbols findings includes the purpose of knowledge, outlook on life, group solidarity, mediation, communication, and participation. Keyword: symbol of offerings, form, meaning, function Keyword: symbol of offerings, form, meaning, function

A Methodology for the Design and Engineering of Smart Product Service Systems: An Application in the Manufacturing Sector

The combination of servitization and digitalization is increasingly changing the economy and society at the global level towards sustainability goals. Companies are shifting their business models, typically oriented to selling products, towards providing bundles of products and services and integrating them with technologies enabling data collection and analysis, resulting in the so-called smart Product Service Systems (PSS). Different approaches and techniques have been put forth to design PSS and, more recently, smart PSS, but they continue to primarily concentrate on establishing value propositions and ignore the question of what sort of operational data can be gathered and used to deliver the PSS solution. Therefore, manufacturing companies willing to expand their portfolio with new advanced services nowadays still face multiple challenges. To address this gap, this study proposes the Service Engineering Methodology for the engineering of smart PSS (SEEM-Smart), which takes into account the trade-off between customer satisfaction and internal efficiency with a focus on data gathering and information flow. The methodology is then applied in a real-world setting. The case study shows the application of the SEEM-Smart for engineering a new data-driven service offering enabled by a cloud-based platform supporting the service provision.

“When people see me, they know me; they trust what I say”: characterizing the role of trusted sources for smoke risk communication in the Okanogan River Airshed Emphasis Area

IntroductionAs wildfire smoke events increase in intensity and frequency in the Pacific Northwest, there is a growing need for effective communication on the health risks of smoke exposure. Delivery through a trusted source or intermediary has been shown to improve reception of risk communication messages. This is especially salient in rural and tribal communities who may be hesitant to trust information from state and federal agency sources. This study aims to identify and characterize trusted sources for smoke risk information in the Okanogan River Airshed Emphasis Area (ORAEA), a rural region of North Central Washington state that is heavily impacted by smoke from wildfires and prescribed fire.MethodsThe research team conducted a qualitative study using data collected through key informant interviews and focus groups to assess the role of various sources and intermediaries in disseminating smoke risk information. We used a consensual coding approach in NVivo Qualitative Analysis Software to sort data into preliminary categories, which were grouped into themes using a thematic analysis approach. We used member checking and iterative feedback processes with local project partners throughout the project to ensure credibility of results.ResultsThrough the analysis, we identified three themes characterizing trusted sources for smoke risk communication in the ORAEA. These themes were: (1) local and tribal sources of information are perceived as more trustworthy than state and federal government sources, (2) trustworthiness is determined by an evaluation of multiple factors, in particular, perceived credibility, quality of information, and relationship with the source, and (3) conservative political ideology and perceived parallels with COVID-19 communication influence perception of trust. Within each theme, we identified several sub-themes, which contributed additional nuance to our analysis.ConclusionThis study provides insights into which sources of information are trusted by rural and tribal community members in the ORAEA and why. Results from our study emphasize the importance of relationships and collaboration with local and tribal partners in smoke risk communication. In this paper, we discuss implications for state and federal agency practitioners and present recommendations for how to work with local and tribal partners on smoke risk communication.

User experience and information architecture of the National Digital Library and archives of Iran: a usability investigation and card sorting

PurposeThis study aims to evaluate the usability and information architecture of the digital library (DL) website of the National Library and Archives of Iran (NLAI).Design/methodology/approachThis applied study used an exploratory mixed method, card sorting. Data were collected by interviewing, observation, usability test and card sorting. By interviewing users about problems of the DL, eight tasks were predefined and users’ problems in the path were identified. Their satisfaction of the tasks and the usability rates were measured via a questionnaire. Card sorting was done to inform on the information organization of the website elements. The study population included all users of the DL of the NLAI in two groups: ten initiator users (public users) and ten expert users (librarians). SPSS was used for analysing the usability test quantitative data. MaxQda was applied for analysing interview-driven qualitative data. Qualitative content analysis, categorization (data organization and grouping) and determining main and secondary codes were applied as well. The sort optimal application was used for analysing card sorting data in the form of similarity matrix and dendrogram. For validating qualitative findings, triangulation was used. The internal reliability of the used questionnaire amounted to a = 0.87FindingsRegarding the assigned tasks, new initiator users by consuming 367.67 s for registering and new expert users by consuming 403 s spent the most time. Task 2 ranked first in being incomplete among 40% of initiator users and Task 3 ranked first by 30% of incompleteness. Expert users had more unsuccessful attempts. Task 5 with the mean rate of 3.35 and Task 8 with the mean rate of 2.25 were the most difficult and the easiest tasks, respectively. Some usability components were rated lower than the moderate point. Only 30% of initiator users and 10% of expert users were satisfied with the website. A total of 12 categories and 452 codes were identified as main problems of the DL. The problems related to a vague perception of concepts and labels with 90 repetitions and digital source display with six repetitions ranked as the first and the last problems in working with the DL, respectively. The sort optimal package produced the card sorting results as a matrix similarity and a dendrogram. Card sorting reflected some changes in organizing information items. Interviews after card sorting emerged some new groups to be included, such as links to other digital libraries, shared databases in the organization and frequently asked questions.Originality/valueThe library’s website should be designed in a manner so that it can satisfy users with different traits. As the information technologies are increasingly developing, the importance of such a design increases for better service provision and effective competition.

Indexing with Excel, Part 2. Checking indexing data

The first article in this series showed how a Microsoft Excel table can be converted into a database. Excel’s database capabilities are a prerequisite for the program to be used meaningfully in indexing. Furthermore, it was shown that in order to sort data professionally, additional fields have to be created in Excel, which are used to prepare the sorting according to internationally recognised rules. After Excel has been set up in this way, checks can be made on indexes, among other things. In order to be able to carry out such checks, further fields must be included in Excel, which are filled with special check formulae. The current article in the series focuses on the topic of checks and how sensible formulae can be developed. Through detailed examples and illustrations it shows that Excel can be used for checks similar to those in DIPs (dedicated indexing programs), but that much more is also possible.

Identifying level and category shift in Legenda Pulau Senua bilingual storybook

to the TL. Adding occurs because TL has grammatical category which SL lacks. Omitting occurs because the TL has a grammatical category which exists in the SL.
 Purpose: This study is conducted to analyze translation shifts in Bilingual book story.
 Design and methods: This study used qualitative research method in the form of content analysis. Data analysis techniques is the process of organizing and sorting data into the patterns, categories and units of the basic description so that it can be determined the theme and can be formulated working hypothesis as based on the data.
 Results: there were 15 data that indicated translation shift in this book, and the category shift were dominantly used. Any shift in the process of translation is normal, as long as it does not change the meaning or the message of the text.

Packet Filtering Automation System Design Based on Data Synchronization on IP Profile Database Using Python

Data traffic on a dense network is a threat to cybercrime and a high vulnerability for technology companies so that the challenges to prevent it will be more diverse. Adding a strengthening of the boundary wall or firewall and sorting data through packet filtering plus writing firewall rules to prevent malware and attacks from outside at the network device level is an alternative to protect the traffic you have. When heavy traffic makes data exchange uncontrollable, this research will create an automation design so that the sorting of incoming data packets through selection based on the specified rules runs in real-time so that the prevention of crime that enters the network is more swiftly handled. The system is running successfully by connecting the MQTT Collector as a subscriber that uses the python programming language to retrieve profiling data from the IP Profile database. The system was tested on a mikrotik router RB951Ui-2HnD which then the blocking track record will be stored in the Dynamic Firewall Data database in MongoDB. Also added a tool for controlling data in storage in the form of a program release. The results of the test show that data with an average base score above 20 is blocked and then stored in the block list in checking the collection in the database every 30 seconds. In addition, the data in the database will be checked every day within 30 days which will then be released and recorded in the release log in MongoDB.

Investment in Learning Chinese by International Students Studying Chinese as a Second Language (CSL)

This study, drawing on the theoretical model of investment, explores what motivates and encourages international students studying Chinese as a second language (CSL) to invest in their Chinese learning using Q sorting and interview data collected from 15 international undergraduate students studying in mainland China. The results reveal that: (1) CSL students’ incentives for investment are intra-personally and inter-personally diverse and can be divided into three categories (multilingual posture and cultural capital-oriented, economic capital-oriented, and cultural capital and experience-oriented); (2) CSL students’ Chinese learning investment is dynamic, as they aim to enrich their learning and life experiences after studying Chinese for a period of time; (3) CSL students’ investment is apparently driven by multiple perceived benefits, in that utilitarian objectives (e.g., scholarships, employment opportunities, and educational qualifications) are characteristic of CSL students’ investment, but are also interwoven with some non-utilitarian objectives (e.g., enriching one’s experience and making friends). The findings have some implications for CSL education and future studies.

The practical ethics of repurposing health data: how to acknowledge invisible data work and the need for prioritization.

Throughout the Global North, policymakers invest in large-scale integration of health-data infrastructures to facilitate the reuse of clinical data for administration, research, and innovation. Debates about the ethical implications of data repurposing have focused extensively on issues of patient autonomy and privacy. We suggest that it is time to scrutinize also how the everyday work of healthcare staff is affected by political ambitions of data reuse for an increasing number of purposes, and how different purposes are prioritized. Our analysis builds on ethnographic studies within the Danish healthcare system, which is internationally known for its high degree of digitalization and well-connected data infrastructures. Although data repurposing ought to be relatively seamless in this context, we demonstrate how it involves costs and trade-offs for those who produce and use health data. Even when IT systems and automation strategies are introduced to enhance efficiency and reduce data work, they can end up generating new forms of data work and fragmentation of clinically relevant information. We identify five types of data work related to the production, completion, validation, sorting, and recontextualization of health data. Each of these requires medical expertise and clinical resources. We propose that the implications for these forms of data work should be considered early in the planning stages of initiatives for large-scale data sharing and reuse, such as the European Health Data Space. We believe that political awareness of clinical costs and trade-offs related to such data work can provide better and more informed decisions about data repurposing.

Secure word-level sorting based on fully homomorphic encryption

Fully homomorphic encryption enables to perform arbitrary computations over encrypted data opening a new avenue for the secure outsourced computation in cloud computing. Data sorting is a classical computational problem in computer science. Previously, all the secure sorting algorithms based on fully homomorphic encryption made use of the bit-level encryption, which requires that each bit of the input data is encrypted separately. However, the bit-level encryption incurs expensive computational overheads and a large ciphertext expansion. In this paper, we propose a secure word-level sorting scheme based on fully homomorphic encryption. We introduce a set of novel techniques to design an efficient word-level sorting algorithm. These include a new technique to compare two encrypted integers, a constant extraction technique to postprocess the output ciphertext of the comparison algorithm, an equality test method to check whether two ciphertexts encrypt the same integer and the single instruction multiple data technique to reduce the ciphertext sizes and improve the computational performance. The experimental results show that our word-level sorting algorithm outperforms the state-of-the-art bit-level sorting algorithm by more than 10 times.

Seismic data IO and sorting optimization in HPC through ANNs prediction based auto-tuning for ExSeisDat

ExSeisDat is designed using standard message passing interface (MPI) library for seismic data processing on high-performance super-computing clusters. These clusters are generally designed for efficient execution of complex tasks including large size IO. The IO performance degradation issues arise when multiple processes try accessing data from parallel networked storage. These complications are caused by restrictive protocols running by a parallel file system (PFS) controlling the disks and due to less advancement in storage hardware itself as well. This requires and leads to the tuning of specific configuration parameters to optimize the IO performance, commonly not considered by users focused on writing parallel application. Despite its consideration, the changes in configuration parameters are required from case to case. It adds up to further degradation in IO performance for a large SEG-Y format seismic data file scaling to petabytes. The SEG-Y IO and file sorting operations are the two of the main features of ExSeisDat. This research paper proposes technique to optimize these SEG-Y operations based on artificial neural networks (ANNs). The optimization involves auto-tuning of the related configuration parameters, using IO bandwidth prediction by the trained ANN models through machine learning (ML) process. Furthermore, we discuss the impact on prediction accuracy and statistical analysis of auto-tuning bandwidth results, by the variation in hidden layers nodes configuration of the ANNs. The results have shown the overall improvement in bandwidth performance up to 108.8% and 237.4% in the combined SEG-Y IO and file sorting operations test cases, respectively. Therefore, this paper has demonstrated the significant gain in SEG-Y seismic data bandwidth performance by auto-tuning the parameters settings on runtime by using an ML approach.

Pengaruh Digitalisasi Al-Quran Terhadap Intensitas Pembacaan Al-Quran Pada Pelajar di Kota Bandung

The research conducted by the author aims to observe more broadly the impact of the emergence of various digital Al-Quran products as a product of digitalization in the field of religion. The impact in question is devoted to the intensity of the readings carried out and the usefulness obtained by the users. The research method used in this study is a qualitative descriptive analysis method. The questionnaire that has been made consists of several parts, namely, identity and questions. This questionnaire contains a total of 13 questions. This questionnaire consists of two types of questions, namely, fill-in questions (essays) and choice questions (yes/no. The data analysis of the survey results is processed by means of data collection, data sorting or filtering, data presentation, and data simplification. Then the data from the research analysis are summarized in the concept of and classified according to categories and poured in descriptive form and then the final conclusion is drawn. The results obtained are a decrease in the intensity of reading the Qur'an in respondents. In addition, overall the respondents prefer the conventional Al-Quran over the digital Al-Quran. This is reinforced by the preference for the conventional Al-Quran in several aspects such as the level of understanding in studying the Qur'an, the level of appreciation and practice of the Qur'an, and the level of increasing reading intensity. .Nevertheless, the majority respondents agree that the emergence of a digital Al-Quran can facilitate various aspects of life.

Analisis SWOT Sebagai Strategi Meningkatkan Daya Saing Pada Lim’s Cafe and Resto Tebing Tinggi

In determining the marketing strategy of a business requires the right tools/methods, one of which is using a SWOT analysis. SWOT analysis is an analysis of four elements consisting of strengths, weaknesses from the internal environment, opportunities and threats from the external environment. This study aims to determine the SWOT analysis strategy in increasing competitiveness at Lim's Cafe and Resto Tebing Tinggi. This type of research is descriptive qualitative with data obtained from both field data and literature processed through three stages, namely exposure of data based on the systematics that have been described (display), selecting and sorting data relevant to the discussion (reduction) and drawing conclusions (conclusion). ). The method used is Triangulation, namely Triangulation of Sources, Techniques and Theory. The results of the study, the internal factors of Lim's Cafe and Resto Tebing Tinggi have a value of 3.35 indicating the company's strategy in utilizing strengths and minimizing weaknesses is above average and internal conditions at this company tend to be strong and external factors of Lim's Cafe and Resto Tebing Tinggi have the value of 2.60 indicates the company's strategy in taking advantage of external opportunities and avoiding threats that will affect the company is above average and external conditions in this company tend to be strong. From the results of the comparison of the internal and external sectors, the company's ability to compete is in an aggressive growth strategy position, which is to make optimal use of the strengths and opportunities it has.