Reviewerly/exHarmony huggingface dataset:
OLFWA: A novel fireworks algorithm with new explosion operator and two stages information utilization

The Fireworks Algorithm (FWA) represents a relatively new algorithm that has demonstrated its competitiveness among other intelligent optimization algorithms. In most FWA variants, a simple random explosion generates sparks, accompanied by the guiding operator to explore promising search directions. However, this mechanism proves inefficient in exploiting the local landscape and effectively navigating the promising search directions. In this paper, we introduce a novel explosion technique based on orthogonal design (OD), wherein the orthogonal array is leveraged to regulate the distribution of sparks, thus enabling efficient analysis of spark information. Furthermore, we devise a two-stage mechanism for information utilization. In the initial stage, we propose an orthogonal learning (OL) prediction operator to capitalize on local optima by performing factor analysis on both the objective function value and the ranking feature information. Subsequently, in the second stage, an enhanced guiding method is deployed to determine the most promising search direction. The experimental results indicate that the proposed algorithm (OLFWA) showcases competitive performance compared to state-of-the-art FWA variants, various renowned OD-based algorithms, and other promising methods. Moreover, a comprehensive analysis of the effectiveness of each proposed strategy and their interactions has been conducted.
Solusi Semi Analitik Persamaan Burgers Menggunakan Metode Dekomposisi Adomian Laplace

Burgers equation is a partial differential equation which has important rule in fluid mechanics. Because it has nonlinear terms, the exact solution is complicated to find. Therefore many methods have been developed to find the approximate solution that can estimate the exact solution. In this research, the Laplace Adomian decomposition method is applied to calculate the approximate solution of Burgers equation. The method is a semi-analytical method to resolve nonlinear differential equation. By the numerical simulation, we obtained a result that the approximate solution by this method can estimate the exact solution with the sum of absolute and relative error less than those using approximate solution obtained by the Adomian decomposition method without the use of Laplace transform. Therefore the Laplace Adomian decomposition method is more accurate than the Adomian decomposition method in order to estimate the exact solution of the Burgers equation.
Data Visualization with matplotlib and Seaborn

The previous chapters covered the Python libraries that are responsible for data processing, and this chapter covers the libraries that take care of visualization. You first get a broad overview of the matplotlib library, and then the chapter concludes with the seaborn library, which extends matplotlib with the representation of statistical graphic elements.
Image Analysis and Computer Vision with OpenCV

In the previous chapters, the analysis of data was centered entirely on numerical and tabulated data, while in the previous chapter, you saw how to process and analyze data in textual form. This book rightfully closes by introducing the last aspect of data analysis: image analysis.
SECURE TEXT ENCRYPTION FOR IOT COMMUNICATION USING AFFINE CIPHER AND DIFFIE-HELLMAN KEY DISTRIBUTION ON ARDUINO ATMEGA2560 IOT DEVICES

In an Internet of Things (IoT) system, devices connected to the system exchange data. The data contains sensitive information about the connected devices in the system so it needs to be protected. Without security, the data in the IoT system can be easily retrieved. One way to prevent this is by implementing cryptography. Cryptography is a technique for protecting information by using encryption so that only the sender and receiver can see the contents of the information contained therein. The implementation of cryptography on IoT devices must consider the capabilities of IoT devices because in general IoT devices have limited processing capabilities compared to computer devices. Therefore, the selection of encryption algorithms needs to be adjusted to the computational capabilities of IoT devices. In this research, the affine cipher cryptography algorithm and Diffie-hellman key distribution algorithm are applied to the arduino atmega2560 IoT device. The purpose of this research is to increase the security of the IoT system by implementing cryptography. The method used in this research involves setting up a sequence of encryption and decryption steps using an affine cipher and diffie-hellman algorithms. Furthermore, these algorithms were implemented on an Arduino IoT device. Finally, the decryption time based on the number of characters and the avalanche test were tested. The results showed that on average, Arduino can perform decryption using affine cipher and diffie-hellman algorithms in 0.07 milliseconds per character. The avalanche test produced an average percentage of 45.51% from five trials.
IMPLEMENTATION OF CLUSTERING ON TWEET UPLOADING SIDE EFFECTS OF COVID-19 POST VACCINATION USING K-MEANS ALGORITHM

The Covid-19 Vaccination Program has become pros and cons among Indonesian people including Twitter social media users. When the program was running, Twitter users started uploading tweets regarding the side effects that occurred, ranging from mild to severe, both scientifically proven. or not. Of all uploaded tweets, by applying text mining, only tweets containing the queries "vaccine effect" and "post vaccine" in the period from January to June 2022 and Indonesian language tweets will be used and based on these parameters a total of 4800 tweets have been collected, of the total These tweets will be further processed using the clustering method, the k-means algorithm and the silhouette coefficient. The results of implementing the silhouette coefficient show that the best cluster is in cluster 2 with a score of 0.6228720387313319 and the results of the clustering algorithm k-means for 4800 tweets obtained 3917 members in cluster 0, and 883 members in cluster 1 placement. The feature is that cluster 0 contains tweets that state program effects explicitly or explicitly, while cluster 1 states program effects that arise implicitly.
Video Classification-Based Action Recognition with Enhanced Convolutional Neural Networks

The classification of videos has become increasingly important in the field of data science research, as it has numerous practical applications in modern society. Compared to image classification, video classification poses a significantly greater challenge. One of the most obvious difficulties is that video classification tasks require more powerful computers due to the large number of features that need to be computed. Additionally, conventional 2D Convolutional Neural Networks (2D CNNs) are not effective in handling such tasks. This paper proposes a novel 2-layer Convolutional Neural Network (CNN) architecture for action recognition that addresses these challenges. The proposed architecture achieved a high test accuracy of 79.66% for classifying large video clips. The results indicate the effectiveness of the proposed approach for video classification tasks.
Catalogue of Incunabula in the National Library of Poland. By Michał Spandowski

Journal Article Catalogue of Incunabula in the National Library of Poland. By Michał Spandowski Get access Catalogue of Incunabula in the National Library of Poland. By Michał Spandowski. 2 vols. Warsaw: National Library of Poland. 2020. 695 + 382 pp. 120 zł. ISBN 978 83 7009 833 9. Roczniki Biblioteczne (Library Annals: The Journal of the Book and Written Communication Culture). Available online at https://wuwr.pl/rbibl. Cristina Dondi Cristina Dondi Oxford christina.dondi@history.ox.ac.uk Search for other works by this author on: Oxford Academic Google Scholar The Library, Volume 24, Issue 2, June 2023, Pages 211–216, https://doi.org/10.1093/library/fpad015 Published: 02 September 2023
An Ensemble Load Balancing Algorithm to Process the Multiple Transactions Over Banking

The banking industry has been transformed by cloud computing, which has provided scalable and cost-effective solutions for managing large volumes of transactions. However, as the number of transactions grow, the need for efficient load-balancing algorithms to ensure optimal utilization of cloud resources and improve system performance becomes critical. This paper proposes an ensemble cloud load-balancing (ECBA) algorithm specifically designed to process multiple banking transactions. The proposed algorithm combines the strengths of several load-balancing techniques to achieve a balanced distribution of transaction loads in various cloud servers. It considers factors such as transaction types, server capacities, and network conditions to make intelligent load distribution decisions. The algorithm dynamically adapts to changing workload patterns and optimizes resource allocation by leveraging machine learning and predictive analytics. A simulation environment that mimics the banking system's transaction processing workflow is created to evaluate the performance of the ensemble load balancing algorithm. Extensive experiments with various workload scenarios are conducted to assess the algorithm's effectiveness in load balancing, response time, resource utilization, and overall system performance. The results show that the proposed ECBA outperforms traditional banking load-balancing approaches. It reduces response time, improves resource utilization, and ensures every server is adequately funded with a few transactions. The algorithm's adaptability and scalability make it well-suited for handling dynamic and fluctuating workloads, thus providing a robust solution for processing multiple transactions in the banking sector.
Cloud Computing Services Versus on-Premise Computing

This research paper offers the customer with an overview of the Cloud Services over conventional on premises computing. When exploring newly ranges for enterprise organizations, expert need to progressively weigh the assets of Cloud offerings. Vendors are offering appealing starting pricing to attract Cloud tenants as part of their battle to win customers and expand market share. Cloud Service providers offer a diverse set of cloud-based services around the world like data storage, analytics, databases, developer tools, computing, networking, Internet of Things, security, management tools, etc. On the other hand, the customer is responsible for the development, distribution, stacking, and a number of other server-related responsibilities in on-premise data centers. They are generally used to run private clouds, which have the same resources as a public cloud but are not accessible to the general public. Government agencies and major businesses that want to keep their sensitive data secret typically employ on-premise solutions. This data can contain bio-metric scans, employee compensation statements, company models, and other vital information. This research study lays out the foundations for determining whether to use Cloud or on-Premise Computing in the future.
A Least Significant Bit Steganographic Method Using Hough Transform Technique

Steganography is a data-hiding scientific branch that aims to hide secret data in an image, video, or audio. Image steganography methods try to embed a large amount of data into images with high imperceptibility. However, increasing the number of embedded data in the image decreases its quality. Therefore, in this paper, a new method based on Least Significant Bit (LSB) using Hough Transform is proposed to improve the stego image quality with increasing the amount of embedded data. The LSB is the common embedding steganography method due to its simplicity of implementation and low complexity. The proposed method inverts the LSBs of image pixels to enhance the quality of stego image. First, improved edge detection filter is used to detect edges areas. Then, we invert LSBs for the pixel in edge area pixels. Finally, the LSBs smooth area pixels of the cover image are inverted. The performance of the presented method is evaluated for the stego image quality and the amount of embedded data. The results show that the new method has better performance in comparison with the current methods in terms of Peak Signal-to-Noise Ratio (PSNR) and capacity.
PREDIKSI JUMLAH PRODUKSI GENTENG DI KEBUMEN BERDASARKAN FUZZY INFERENCE SYSTEM MAMDANI

Tile is one product that is in demand by many people. This is a trigger for producers to improve their management. One of the efforts made is to predict the production that can be done to get the optimal amount obtained, so as to get a big profit. In this study, to predict the amount of tile production, computerized calculations were carried out using the Mamdani fuzzy logic method. This method uses the concept of monotonous rules, which are then re-selected by experts in tile production by choosing rules that match the actual situation in the agency. This study proves that predictions made with monotonous rules, then re-selection by experts are able to handle the process of predicting tile production. The results of the comparison of predictions with actual production have an error percentage of 28.45%, with a truth of 71.55% (based on the calculation of the Average Forecasting Error Rate (AFER)). Therefore, when implemented in the Fuzzy Inference System, Mamdani can produce optimal tile production predictions.
A Real-Time Algorithm for Searching for Substrings of a Pattern in Online Text Stream: An Alternative to Suffix Trees and Finite Automaton

In the field of similarity search, very little effort has been made to process the text without using suffix trees or automata. Most of the algorithms developed in the past use data structures and methods outlined above to accelerate the search process. However, their costly maintenance has always been a cause of concern. Let, T be a text of size N, and P be a pattern of size M. We present highly practical algorithms to process a real-time stream of text characters. The algorithm reports all substrings of pattern P in the text stream T as they appear in the stream. This is highly useful in detecting patterns in the data stream in real-time, for example, viruses and malware can be detected as they appear in the data stream. Additionally, the algorithm can be used to find the longest common substring(s) between two given strings. We achieved the stated goals without using any sophisticated data structure such as a suffix tree or finite automaton. For an alphabet size σ the algorithm runs in O(M) space, and O (MN/σ) expected time, which simplifies to O(N) for M ≤ σ. We also provide experimental results to support our claim.
Native English teachers (NETs) strategies in teaching English to non-native learners

Students prefer learning English with native English teachers (NETs) compared to non-native English teachers (NNETs). Knowing how the NETs teach in the class, like their learning activities, would be very interesting. The purpose of this research is to find out the strategies used by NETs in teaching English to non-native learners. Five NETs were chosen based on the demographic information questionnaires and to be interviewed to describe the strategies that they used in teaching English, especially speaking skills, to non-native learners. This is the qualitative design with the case study tradition. Three themes were found as the result of this study: NETs’ strategies in teaching English (how to begin the class, the activities during the class, and how to end the class), media used in teaching English, and games used during teaching. The various fun activities provided by the NETs in teaching English could be useful information for other NETs, fresh graduate English teaching students, and English teachers who want to teach English in non-native English countries.
The role of digitalization in innovation: Investigating the environmental sustainability in the context of circular economy in UAE

The study aimed to evaluate the role of digitalization in innovation in terms of circular economy. For the attainment of this goal, the researcher collected data using qualitative methods such as semi-structured interviews with managers and experts from different organizations in the UAE. Further, the qualitatively gathered data was analyzed using thematic analysis to summarize research outcomes. The outcomes disclosed that digitalization such as AI applications, 3D printing, and big data analytics are some of the factors that contribute significantly to bringing innovations and help reduce waste of time, money and other resources. Though digitalization brings multiple benefits some challenges are also there such as skill shortage, lack of infrastructure, waste generation from the disposal of new technologies, and data privacy and security. However, these challenges can be overcome by training and developing employees (T&amp;D), developing equal infrastructure, recycling systems, adopting advanced technologies, and complying with data privacy laws and regulations.
Study of Image Resolution in Virtual Reality Panorama Technology 360 In Comfort of Interior Visualization

Utilizing virtual reality technology is used as a method of interacting virtually. With the many uses of virtual reality today, it certainly affects the lives of users of these technologies. In the field of interior design itself, virtual reality technology is also often used, the application of VR technology for design interior are often used as a means of design presentation. This study is aimed at testing the visual comfort of virtual reality panorama 360 which is used as a medium for virtual interaction of interior design to interior design users. The analysis process in taking data by questionnaire and followed by several stages of observation and the last stage is the experimental stage to take research data related to case studies. The results obtained from this study are knowing visual comfort when interacting directly using virtual reality technology. It is hoped that with the testing of the visual resolution used in interior virtual reality, it can later be used as a reference in the selection of visual media in the future.
Compatibility of Clique Clustering Algorithm with Dimensionality Reduction

In our previous work, we introduced a clustering algorithm based on clique formation. Cliques, the obtained clusters, are constructed by choosing the most dense complete subgraphs by using similarity values between instances. The clique algorithm successfully reduces the number of instances in a data set without substantially changing the accuracy rate. In this current work, we focused on reducing the number of features. For this purpose, the effect of the clique clustering algorithm on dimensionality reduction has been analyzed. We propose a novel algorithm for support vector machine classification by combining these two techniques and applying different strategies by differentiating the clique structures. The results obtained from well known data sets confirm the compatibility of clique clustering algorithm with dimensionality reduction.
Вплив педагогічної комунікації на ефективність освітнього процесу в закладах загальної середньої освіти

Teachers' communication skills are one of the key factors that influence the quality of learning and student development. Teacher-student interaction can influence students' attitudes to learning, motivation, ability to cooperate and learn independently. Effective communication is a key factor in learning success. It not only helps to ensure that the material is learned correctly, but also keeps students motivated and creates a favourable emotional climate in the classroom. This can only be achieved through good communication techniques, such as listening and speaking, using positive and supportive language, and presenting material in a clear, understandable and engaging way. Its impact on learning effectiveness depends on the quality of communication itself, which includes various forms and methods of communication, such as verbal and non-verbal communication.&#x0D; The study of the impact of pedagogical communication on the effectiveness of the educational process involves the study of various aspects, such as the emotional side of communication, interaction between teacher and student, the use of different methods of interaction, and others. In a world of profound social and economic changes, the reform of the education system should promote the establishment of a person as the highest social value.&#x0D; Therefore, understanding how pedagogical communication affects the effectiveness of the educational process is very important for improving the quality of education in secondary schools.&#x0D; The article analyses the current state of pedagogical communication in general secondary education institutions and its impact on the effectiveness of educational and management processes in these institutions. Therefore, we see the study of technologies focused on the personal influence of participants in the educational process on the development of communication competencies of teachers and managers as a prospect for further research in this area.
The Mediating Effect of COVID 19 - Pandemic on the Nexus between Accounting Information Systems Reliability and E-Commerce: From the Perception of Documentary Credit Employees

In this paper, we discuss the mediating effect of COVID 19 - pandemic on the nexus between accounting information systems reliability and e-commerce: from the perception of documentary credit employees. To test this nexus, a 38-item questionnaire was developed and sent to respondents who are working in the documentary credit department at Jordanian commercial banks. Only 230 questionnaires were returned. The findings show a positive and significant nexus between Accounting Information System Reliability (Security, Availability, Processing Integrity, Privacy, and Confidentiality) and e-commerce. And also, the results of regression illustrated that COVID 19 has a mediating effect in the nexus between Accounting Information System Reliability and E-Commerce.
Assessments of Guest Technologies in Five Stars Hotel at Aqaba Special Economic Zone Authority (ASEZA)

The purpose of this study is to look at the effects of website management, technology level, and innovation on customer satisfaction in five-star hotels in Aqaba, Jordan. Among the 450 surveys distributed to hotel guests, 235 were filled out completely and returned. To investigate the connections between the variables, an (Smart PLS 4) analysis was used. Website management was shown to have a positive and statistically significant link (T = 2.909, p = 0.004) with customer satisfaction. There was a significant positive link between the hotel technology level and customer happiness (T = 10.160, p 0.001). The research found a statistically significant positive link between innovation and consumer happiness (T = 2.160, p = 0.031). In terms of the moderating effects of innovation, the research discovered that innovation did not substantially modify the link between website management and customer satisfaction (T = 0.636, p = 0.525). The research revealed a substantial moderating effect (T = 2.822, p = 0.005), however innovation was shown to reduce the influence of technology level on consumer satisfaction. In light of these results, it is suggested that the management of five-star hotels in Aqaba place a greater emphasis on better website management techniques and the enhancement of technical services. Furthermore, encouraging innovation should be approached cautiously due to the lack of data on the impact it has on the link between technology and consumer happiness. The findings of this study provide Aqaba hotel managers with useful information for improving guests experiences, which should result in happier visitors who are more likely to return and spread the good news about their stay.