Reviewerly/exHarmony huggingface dataset:
On the Utility Gain of Iterative Bayesian Update for Locally Differentially Private Mechanisms

This paper investigates the utility gain of using Iterative Bayesian Update (IBU) for private discrete distribution estimation using data obfuscated with Locally Differentially Private (LDP) mechanisms. We compare the performance of IBU to Matrix Inversion (MI), a standard estimation technique, for seven LDP mechanisms designed for one-time data collection and for other seven LDP mechanisms designed for multiple data collections (e.g., RAPPOR). To broaden the scope of our study, we also varied the utility metric, the number of users n, the domain size k, and the privacy parameter $$\epsilon $$ , using both synthetic and real-world data. Our results suggest that IBU can be a useful post-processing tool for improving the utility of LDP mechanisms in different scenarios without any additional privacy cost. For instance, our experiments show that IBU can provide better utility than MI, especially in high privacy regimes (i.e., when $$\epsilon $$ is small). Our paper provides insights for practitioners to use IBU in conjunction with existing LDP mechanisms for more accurate and privacy-preserving data analysis. Finally, we implemented IBU for all fourteen LDP mechanisms into the state-of-the-art multi-freq-ldpy Python package ( https://pypi.org/project/multi-freq-ldpy/ ) and open-sourced all our code used for the experiments as tutorials.
THE CONTENT OF EDUCATIONAL MATERIAL ON MECHANICAL SCIENCE IN THE TRAINING OF FUTURE LABOR AND TECHNOLOGY TEACHERS

The article deals with the solution to the problem of the low level of machine science knowledge of pre-service teachers of labor education and technology. It has been found out that it is based on a contradiction between the real content of mechanical training of students and the content of technological education of schoolchildren. The goal of the article is to reveal the peculiarities of students' knowledge of mechanical engineering, based on the study of the technology of transformation of mechanical energy of rotational movement. The methods of analysis and synthesis of achievements of machine science and scientific achievements of technological education have been used. It has been found that in the work of researchers of mechanical science, as well as researchers of technological education of schoolchildren, there are enough guidelines for a well-founded choice of the subject of study. It is described that it should meet a number of different level requirements, for example to contribute to the formation of the technical outlook of schoolchildren; correspond to the content of technological education of schoolchildren; have a polytechnic character; simultaneously belong to different types of working machines. Technical knowledge about it must be integrated with knowledge of mathematics and physics. It must be used in educational projects of schoolchildren being a model of implementation of natural and scientific knowledge in practice, and suitable for technical construction of schoolchildren. The machine drive as a subject of the study meets all the specified requirements. It has been revealed that the subject of study for the formation of students' general idea about machines should provide a large amount of knowledge about the types of working machines and at the same time a moderate content. It has been established that such contradictory requirements are met by the drive of the machine as a subject of study. It is described that the concept of drive has the property of fractality as far as it enables a free transition from the study of the drive of any mechanism to the study of the drive of any working machines. It is described that the condition for choosing the content of educational material for the formation of students' general idea about machines is the use of the mental operation of abstraction and the corresponding transition from the level of description of the morphology and functions of technical objects to the level of energy conversion technology. It has been substantiated that the didactic value of the basic technical phenomena of the machine drive is the transmission of mechanical motion to a distance, the change of the kinematic parameters of the mechanical motion and the change of the power parameters of the mechanical motion. There has been revealed the importance of the results of this study for the disclosure of approaches to the use of the project method, as well as the use of technical construction for the visual presentation of the basic technical phenomena
PROFESSIONAL DEVELOPMENT OF SUBJECT TEACHERS IN THE CONTEXT OF DIGITAL TRANSFORMATION OF EDUCATION

Digital transformation of education affects all levels of learning and requires subject teachers to undergo relevant professional development. The article discusses the current issue of professional development of subject teachers in the context of digital transformation of education. Challenges and opportunities that arise for subject teachers during the process of digital transformation of education, such as the use of digital technologies, virtual resources, online learning, individualized learning, etc., are analyzed. The importance of developing digital literacy and professional competencies of subject teachers for successful work in the digital environment is explored. Various strategies and approaches to professional development of subject teachers are also considered, such as pedagogical courses, trainings, professional collaboration networks, etc. The article concludes with conclusions and recommendations for further professional development of subject teachers in the context of digital transformation of education, including the development of digital literacy, adaptation to changes, and effective use of digital technologies in the educational process.
The Effect of Quantum Teaching Method on Motivation and Arabic Language Learning Outcomes (Literature Study)

This study analyzes the effectiveness of the Quantum Teaching method in improving motivation and learning outcomes in Arabic. Researchers use descriptive qualitative research methods with a systematic approach to conduct data analysis in a simplified approach. Data was collected through database search tools and literature search stages using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) method. Article search strategies are carried out through international databases, such as Open Knowledge Maps, ResearchGate, and Google Scholar. The summary of this literature review is done using an analysis matrix. The results showed that applying the Quantum Teaching method significantly improved students' Arabic proficiency and learning outcomes. Quantum Teaching effectively improves student learning outcomes, motivation, and engagement. This method creates a comfortable, enjoyable learning environment and strengthens the interaction between teachers and students. In addition, Quantum Teaching also improves students' memory and learning potential.
Phylogenesis of gold in polymetallic volcanogenic-sedimentary massive sulfide ores

The Au concentrational level of the ores of polymetallic volcanogenic-sedimentary massive sulfide deposits is predetermined by the geodynamic setting of their formation. The ores formed in a mid-ocean ridge setting are characterized by low Au grades. The ores formed under the island arc conditions possess higher Au contents. In the course of the further existence of the ore deposit, its ores experience repeated external influences: underwater halmyrolysis, thermal and dynamic metamorphism, hydrothermal-metasomatic transformations, and exogenous oxidation. These processes lead to the transfer of gold from a micro- or nano-sized form in the sulfides to the free form and to redistribution of Au over the ore field of the deposit. The heterogeneity of the ores in terms of the Au content and existence forms must be taken into account when preparing a feasibility study. The work is intended for geologists conducting mining and geological modeling, designing techniques for the ore extraction, and proposing ore processing technologies.
Penerapan Aplikasi E-TRASH pada Program Bank Sampah Mendukung Ketahanan Ekonomi Rumah Tangga

The development of the era towards the era of society 5.0, allows every human being in his life to using modern technology such as AI and robots to meet needs and make life easier. With technology, it will be easier, because all humans are aware that getting work done quickly and easily will be better. Technological development has advantages and disadvantages, but the weakness is that it will be a concern for every human being that in Society 5.0, machines will replace all human tasks easily and which can improve the quality of human life in general. Many problems arise in life, in the form of problems in the fields of education, culture, society, economy, and other issues. One of them is the problem of garbage or waste which is increasing at this time. Seeing this situation, we innovated to create the E-TRASH application, where the application In practice, allows the process of disposing of previously useless waste, to be converted into something that has economic value, namely money/balances. This study aims to create a design for the E-TRASH application system using an Android-based operating system, this is because the use of smartphones is growing rapidly. The design of the E-TRASH application system aims to facilitate the community in minimizing the use of waste in the surrounding environment. The design of this garbage bank program system will utilize a technology called E-TRASH which will later be used for a transaction system. This design process produces a UML design which will later be used as the basis for making which includes the design containing the menus in the application. The application of E-TRASH application uses smartphone technology for customers, namely the general public, the E-TRASH mobile application implements the M-BANKING system, in this application, customers can find out the balance of transactions made, not only obtain balance information, but customers can also see the total debit and credit when transacting, this application also implements a transfer system, where customers can transfer their money to other banks if they don't want to withdraw cash.
Penentuan Uji Statistik pada Penelitian Bidang Kesehatan

The obstacle experienced by final year students was the difficulty in carrying out research, especially when processing and analysing statistical data and presenting the right information. Especially for students majoring in health, at the research data processing stage, it is often difficult to determine the appropriate statistical test. As a result, there are many misinterpretations of research results. This community service activity aims to provide an understanding of the determination of statistical tests in health research along with case examples using SPSS software. Service activities packaged through webinar via zoom were carried out by providing material and discussions which held on May 14, 2022. The webinar was filled by two presenters, each of whom delivered material on Parametric and Non-Parametric Statistics in Health Research. The participants who took part in the activity totalled 90 participants. Before the activity started, participants were given a pre-test to find out the extent of their knowledge of statistical tests in the health sector. Then, at the end of the activity, another post-test was given. Data analysis was carried out using the t-test, to test the hypothesis whether there were differences in participants’ understanding of statistical test in the health sector before and after the webinar. Based on the results, it can be concluded that there is a significant difference between the level of understanding of the participants before and after delivering the material related to determining the appropriate statistical test in health research, indicated by the value of t-test = 24.913 is greater than t-table = 2.279 (or p-value = 0.000 is smaller than 0.05 ).
ANALISIS OBSERVASI HASIL BELAJAR SISWA SD KELAS III DAN KELAS V PADA MATA PELAJARAN MATEMATIKA DI KOTA MEDAN, KABUPATEN DELI SERDANG DAN KABUPATEN LANGKAT

This study uses a qualitative descriptive method that aims to understand the phenomena of elementary mathematics learning outcomes. The resulting data is presented in the form of numbers described in the description. Research using the observation method was conducted on mathematics learning outcomes in grades III and grade V of elementary schools spread across three districts/cities in North Sumatra Province. To understand students' errors and misconceptions is essential for the effective teaching and learning of mathematics. It is important for teachers to approach student mistakes in a constructive way, helping students understand their mistakes and learn from them. Research has been conducted to investigate patterns of student misunderstandings, errors, and misunderstandings across educational systems, grade levels, gender, and time. Several case studies of mathematics subjects in elementary schools in North Sumatra Province became the main focus of the North Sumatra Education Office so that they held improvement and development activities for Chemistry, Biology, Physics and Mathematics subjects in 2022. The conclusion showed that only three grades III fulfilled and 1 class V that meets above the value of 70.
Kesalahan Penggunaan Kata-Baku Pada Salindia-Salindia Presentasi Mahasiswa Semester 3 UNINDRA

This study-aims to obtain a-clear picture of information on errors in-the use of standard words in the presentation slides of Unindra's 3rd semester students. Suwito1 (1983: 3159) states that the standard language is one that must be used as a standard because it is seen as fulfilling the criteria of a number of good and correct languages. This shows that it is appropriate that the-use of standard-language in Indonesian society, especially for the scope of students is very important. Therefore, we made this research to-find out-how-high the-level-of standard words used by students is. The steps for analyzing the data are 1) Analyzing the data set, this analysis includes: noting which data are non-standard words and entering non-standard word data into the justification table. 2) After the analysis of the stages above, the researcher counted the occurrence of non-standard words, namely from the non-standard number. With this result, we can find out how many times the non-standard word is used.
Cloud Server in Academic Knowledge Centers

Today, we are living in the age of modern scientific inventions and technologies. In the present day, all organizations, business sectors, and institutions are adopting cloud computing technology for their future development. Especially in libraries, the current scenario of resource sharing with the customers is much different than in older days. So, the libraries must adapt and execute modern technologies like cloud computing for rapid resource sharing for customers and it helps to access the library resources in remote mode by the customers. That helps to save their valuable time and they can access and refer to the resources online made with the help of the internet. In academic libraries, most of the utilizers cannot able to find or gather relevant information via books. On such occasions, the library cloud plays an effective part in resource sharing with our utilizers. This research paper clearly deals with cloud computing and its benefits for libraries and information centers in academic.
Automatic Hyper-Heuristic to Generate Heuristic-based Adaptive Sliding Mode Controller Tuners for Buck-Boost Converters

Metaheuristics are commonly used to solve complex and challenging problems, particularly in electrical system applications. Nevertheless, there is a colorful palette of metaheuristics to select from, which can be overwhelming for a practitioner with solid experience in controlling electrical systems. Still, it is well-known that empirical or analytical tuning of controllers is no trivial labor. This work implements a methodology to address the Metaheuristic Composition Optimization Problem to coin a heuristic-based technique that guides an initially random population of individuals to find the optimal set of parameters of an Adaptive Sliding Mode Controller in the search space. As a case study, we implement this methodology for controlling the dynamic response of a DC-DC Buck-Boost converter under different conditions, including nonlinear perturbations. The objective is clear: find the optimal heuristic-based solver to determine the control parameters satisfying a predefined performance. Our experimental results reveal the reliability and potential of the proposed methodology when finding suitable solutions for control system design applications. We also support our findings with statistical analyses performed on the results obtained by the tailored metaheuristic against other classical heuristic-based methods.
Retracted: Effect of Different Doses of Propofol on Pulmonary Function and Inflammatory Response in Patients with Lung Ischemia Reperfusion Injury Induced by One-Lung Ventilation Based on Big Data Analysis

[This retracts the article DOI: 10.1155/2022/7677266.].
Exploring the tractability of data fusion models for detecting anomalies in IoT-based dataset

In recent years Internet of Things (IoT) devices have made their way into many different industries. Deep learning and machine learning methodologies have been applied to many IoT-related tasks<sup>123</sup> such as intrusion detection systems or anomaly detection. The efficiency of IoT systems is often hindered by anomalies in data present within the system, often leading to undesirable behavior or possibly a full system shutdown. Due to this, the detection of these anomalies is of the utmost importance. Over the years, various traditional and neural network-based machine learning models have emerged for anomaly detection and classification of corrupted IoT data. However, many of these models fail to capture important features in the data which can lead to false anomaly detection or none at all. In this paper we investigate the applicability of using data fusion to improve the detection of data anomalies. This method uses many different models, such as VGG16, Inception, Xception, and ResNet, to extract features from the data. These extracted features are then fused together, to see if the use of multiple models is better than relying on a single model. This paper also provides a detailed analysis of the efficacy of this fusion-based classification method compared to simpler classification methods. This work investigates the applicability of various machine learning and deep learning models, for anomaly detection in various IoT datasets<sup>45</sup>.
Learned image compression with transformers

Recent years have witnessed great advances in deep learning-based image compression, also known as learned image compression. An accurate entropy model is essential in learned image compression, since it can compress high-quality images with a lower bit rate. Current learned image compression schemes developed entropy models using context models and hyperpriors. Context models utilize local correlations within latent representations for better probability distribution approximation, while hyperpriors provide side information to estimate distribution parameters. Most recently, several transformer-based learned image compression algorithms have emerged and achieved state-of-the-art rate distortion performances, surpassing existing convolutional neural network (CNN)- based learned image compression and traditional image compression. Transformers are better at modeling long-distance dependencies and extracting global features than CNNs. However, the research of transformer-based image compression is still in its early stage. In this work, we propose a novel transformer-based learned image compression model. It adopts transformer structures in the main image encoder and decoder and in the context model. In particular, we propose a transformer-based spatial-channel auto-regressive context model. Encoded latent-space features are split into spatial-channel chunks, which are entropy encoded sequentially in a channelfirst order, followed by a 2D zigzag spatial order, conditioned on previously decoded feature chunks. To reduce the computational complexity, we also adopt a sliding window to restrict the number of chunks participating in the entropy model. Experimental studies on public image compression datasets demonstrate that our proposed transformer-based learned image codec outperforms traditional image compression and existing learned image compression models visually and quantitatively.
Retracted: Observation on the Effect of Rehabilitative Physical Training on Sports Injuries under Ultrasound Image Examination

[This retracts the article DOI: 10.1155/2022/9998265.].
A non-intrusive load identification method considering unknown loads

The current non-intrusive recognition model has complex input features and model structure. In addition, it usually can only identify known loads in training dataset and cannot identify unknown loads that are outside the training dataset, which makes it difficult to be applied to dynamic user-side monitoring environment. To this end, we propose a non-intrusive load identification method considering unknown loads—One Class Load Identification Network(OC-LIN), which can accurately identify both known and unknown loads. The proposed method consists of two main parts: (1) a load identification network that accurately identify loads using fusion V-I trajectory feature and odd harmonic amplitude feature; (2) an one class method in deep support vector data description (DSVDD) to identify unknown loads. Through the validation of the PLAID 2018 dataset, the proposed method not only identifies the unknown loads efficiently, but also improves the identification precision among the known loads.
Non-BPS non-Abelian strings

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PERANCANGAN SISTEM INFORMASI PENILAIAN KINERJA KARYAWAN HOUSEKEEPING PT FAJAR MEKAR INDAH BERBASIS WEB MENGGUNAKAN METODE SAW (Simple Additive Weighting) (Studi Kasus: Menara Bidakara)

Employee performance appraisal activities are a way of measuring the involvement of individuals in the organization, the important value of performance appraisal involves determining the level of individual involvement in the performance carried out in completing the tasks for which they are responsible. The process of evaluating the performance of housekeeping employees at PT. Fajar Mekar Indah (FMI) in Bidakara is still using a manual calculation system, namely still using calculators and Microsoft Excel in its calculations, ledgers with lines, and sheets of paper, so that the resulting information is sometimes found to have errors in calculations and recording, often losing data to less accurate in making reports. To assist and support the needs of processing employee performance appraisal data at PT FMI, it can be done by designing an online (web) based application system. While the method used by researchers in designing employee performance appraisals is by applying the SAW (Simple Additive Weighting) method. With the design of an employee performance appraisal information system, it is hoped that it can overcome problems and provide convenience in processing housekeeping employee performance appraisal data at PT FMI Biadakara, so that the resulting information becomes faster, effective, efficient, and accurate.