Reviewerly/exHarmony huggingface dataset:
Petrogenesis of ultramafic lamprophyres and carbonatites of the Alnö complex (central Sweden)

Central Iapetus Magmatic Province (CIMP) represents a large igneous province associated with the development of the Iapetus Ocean [1].In Baltica, some of the carbonatite complexes (Fen, Alnö) have been linked to extensional tectonics that followed the opening of Iapetus.Based on the results of the age dating, both Alnö and Fen appear to be contemporaneous with the second pulse within the CIMP at ~590 Ma [1].We investigated carbonatites and ultramafic lamprophyres (alnöites) from Alnö, their type locality [2].Here, several dyke generations are mainly found within the erosive section of a collapse structure.Using LA-ICPMS, the contents of transition metals in mica from alnöites are on average 20× (for Cr) and 35× (for Ni) higher compared to their contents in phlogopite from the associated carbonatites.Both the lamprophyres and carbonatites reveal whole-rock compositional characteristics similar to partial melting of metasomatically modified source characterised by anorogenic signature.The lamprophyres and carbonatites show comparable mantle ranges of δ 7 Li values (3.6-7.6‰) while having variable Li contents (2-4 ppm in carbonatites, 11-16 ppm in alnöites, 18-28 ppm in 'kimberlitic alnöites' -local name for olivine-rich variety).Overlapping ranges in Sr-Nd isotope compositions of uncontamined alnöites (Sr 590 = 0.70309-0.70317;εNd 590 = 2.6-2.7) and carbonatites (Sr 590 = 0.70309-0.70311;εNd 590 = 2.5-2.7)imply a depleted mantle to be involved in the petrogenesis of the Alnö rocks.Single-stage depleted-mantle Nd model ages of ~0.9 Ga can be linked with the evolution of the Rodinia supercontinent.Collectively, the origin of the ultramafic lamprophyres and associated rocks of the Alnö carbonatite complex can plausibly be explained by carbonated alkali-rich silicate melts derived in a plume-fed rift setting, and tapping melts from ancient metasomatised subcontinental lithospheric mantle.
A Survey On Privacy And Policy Aspects Of Blockchain Technology

from financial transactions to digital voting systems, identity management, and asset monitoring, blockchain technology is increasingly being developed for use in a wide range of applications. The problem of security and privacy in the blockchain ecosystem, which is now a hot topic in the blockchain community, is discussed in this study. The survey’s goal was to investigate this issue by considering several sorts of assaults on the blockchain network in relation to the algorithms offered. Following a preliminary literature assessment, it appears that some attention has been paid to the first use case; however the second use case, to the best of my knowledge, deserves more attention when blockchain is used to investigate it. However, due to the subsequent government mandated secrecy around the implementation of DES, and the distrust of the academic community because of this, a movement was spawned that put a premium on individual privacy and decentralized control. This movement brought together the top minds in encryption and spawned the technology we know of as blockchain today. This survey paper also explores the genesis of encryption, its early adoption, and the government meddling which eventually spawned a movement which gave birth to the ideas behind blockchain. It also closes with a demonstration of blockchain technology used in a novel way to refactor the traditional design paradigms of databases.
Research on the Construction of Regional “Cloud-Network-Client” Integrated Teacher Development Platform

Teacher professional development is the fundamental guarantee for promoting teaching reform, and there are two means to promote teachers' professional development: “internal promotion” and “external promotion”. At present, the teacher development platform at home and abroad is in a stage of vigorous development. This paper deeply analyzes seven representative domestic and foreign teacher development platforms, and finds that the existing platforms have problems such as system data dispersion, separation of system development and teacher development, and weak ease of use of the platform. Based on this, a teacher development platform with cloud-network integration is proposed, the connection between the cloud data layer, the system application layer and the teacher terminal layer is analyzed, and the design concept of the platform is proposed.
(Tentatively Named) Legislation Directions of Act on the Establishment and Support of Unification Experience Institution for Youth - Unification Education based on Democratic Citizenship -

The Unification Education Support Act prescribes a legal basis for unification education for schools and public officials. At the regional level, however, the National Institute for Unification Education provides education by designating a regional unification education center. Moreover, the institution is responsible for both social and school unification education. BR Unification Education at schools is a holistic effort of involved institutions such as the Ministry of Unification, the Ministry of Education, local governments, and the Office of Education. The Center for Unified Korean Future has enriched theoretical education by offering hands-on experiences of a unified Korea. Unfortunately, as of 2022, the center is the only place nationally that runs youth programs.BR Unification education for adults, on the other hand, is partially managed by the aforementioned regional institution. Learning opportunities are limited due to budgetary issues and compared to youth programs of the Center for Unified Korean Future, there is no public organization that conducts unification experience programs.BR This research suggests to extend the function of the Center for Unified Korean Future to cover adult programs and to establish an additional institution that offers a wide range of hands-on activities in the area of high demand. In addition, it proposes to make unification experience activities that are limited to students available to the general public. In the case of unification education for adults, the necessity of an experience-based education rather than a theory-centered education is emphasized. Regarding the theoretical basis, unification education based on fostering democratic citizenship is stressed.BR Moreover, compared to youth education, there are different aspects of education for the general population. Therefore, the Center for Unified Korean Future should tentatively offer unification programs for adults in the short term. For the medium and long term, the paper argues for an establishment of a new organization that promotes youth programs and a change in pedagogical methods regardless of age for the post-covid era.
An Analysis of Teachers' Strategies on Students' Reading Comprehension in Online Learning at Junior High School

This research discussed reading skills, especially students' reading comprehension in online learning. Reading is an important activity in the learning process. However, most students only read the text, which made them not understand the content of the text, so students’ reading comprehension was not appropriately achieved. There is a close interaction between the reader and the text. Readers not only read but also have to understand the content of the reading. Students need to focus when reading a text, but with the current situation (COVID-19 pandemic), which has changed the learning process into online learning where the process has the distraction that can occur during the learning process, so it is important to know the strategies used by English teachers on students’ reading comprehension. Regarding this matter, this research was conducted on teachers’ strategies for students’ reading comprehension, especially in the eighth-grade students in Junior High School, using the qualitative method with the descriptive design. The researcher used observation, interview, and questionnaire as the instruments of the research. This research aims to describe and obtain the analysis data of the teachers’ strategies for students’ reading comprehension in online learning, the problems teachers face in maintaining students’ reading comprehension, and students’ responses to teachers’ strategies during online learning. The researcher concludes that teachers use “finding difficult vocabulary”, previewing strategy, reviewing strategy, discussion strategy, and resuming strategy so that students’ understanding of a text can be achieved during online learning. The problems teachers face are that students have limited vocabulary and lack the willingness to learn English. During the online learning process, students understand the subject matter about the text explained by the teacher, and they also show a positive response to teachers’ strategies.
Early Detection of Breast Cancer Tumors Using Linear Discriminant Analysis Feature Selection with Different Classification Methods

Globally, the frequency of breast cancer and its morality speaks to a critical and developing risk for developing countries. In Asia, Pakistan has the biggest rate of breast cancer. It is evaluated that every year 83,000 cases were reported in Pakistan and over 40,000 deaths are caused by breast cancer. Many Early identifications of breast cancer can be achieved using data mining techniques, allowing preventative treatments to be done. Patients suffering from this malignancy have a better chance of surviving if they are diagnosed early. So, there is a need to develop a system to diagnose breast cancer tumors at an early stage. In this research WBCD and Duke Breast cancer datasets (DBDS) are used with Linear Discriminant Analysis (LDA) feature selection. Support Vector Machine (SVM), Decision Tree (DT), and Random Forest (RF) are classifiers to predict breast cancer tumors.
AN EFFECTIVE DEEP LEARNING MODEL FOR RECOGNITION OF ANIMALS AND PLANTS

This paper presents a deep learning model to address the problem of recognition of animals and plants. The context of this work is to make an effort in protection of rare species that are seriously faced to the risk of extinction in Vietnam such as Panthera pardus, Dalbergia cochinchinensis, Macaca mulatta. The proposed approach exploits the advanced learning ability of convolutional neural networks and Inception residual structures to design a lightweight model for classification task. We also apply the transfer learning technique to fine-tune the two state-of-the-art methods, MobileNetV2 and InceptionV3, specific to our own dataset. Experimental results demonstrate the superiority of our object predictor (e.g., 95.8% accuracy) in comparison with other methods. In addition, the proposed model works very efficiently with the inference speed of around 113 FPS on a CPU machine, enabling it for deployment on mobile environment.
A Multi-Agent Reinforcement Learning Approach for the Efficient Control of Mobile Robots

This paper presents a multi-agent control architecture for the efficient control of a multi-wheeled mobile platform.Such control architecture is based on the decomposition of a platform into a holonic, homogenous, multi-agent system.The multi-agent system incorporates multiple Q-learning agents, which permits them to effectively control every wheel relative to other wheels.The learning process was divided into two steps: module positioningwhere the agents learn to minimize the error of orientation, and cooperative movement -where the agents learn to adjust the desired velocity in order to conform to the desired position in formation.From this decomposition, every module agent will have two control policies for forward and angular velocity, respectively.Experiments were carried out with a simulation model and the real robot.Our results indicate a successful application of the purposed control architecture both in the simulation and in real robot.
Distribution-Based Single-Threshold PRA

Equation ( 1.3 ) shows that the key probability distributions for basic PRA are p[z|x < thr] and p[z|x ≥ thr].
KETERAMPILAN GURU DALAM PENGGUNAAN MEDIA PEMBELAJARAN DIGITAL TERHADAP PEMBELAJARAN TEMATIK

KELAS IV, This study aims to find out how the skills of teachers in using digital learning media during the covid-19 period on thematic learning at SDN 03 Pontianak City. This research is a qualitative research in which the research was conducted by conducting interviews with the homeroom teacher of class IVA at SDN 03 Pontianak City. Procedures for collecting data by means of interviews and documentation. The data that has been collected is then processed and analyzed by means of data reduction, namely summarizing, selecting the main things, focusing on the important things, looking for themes and patterns. In the implementation process, the researcher reduced the data from the interview results from the informants, then selected important things to be used as data related to the research. After that, the researcher presented the data and finally drew conclusions. Based on the results of the research that has been carried out, it shows that the skills of teachers in using digital learning media are very good, varied, interesting, and innovative by the teachers. smartphones and laptops as well as applications that support digital learning media, namely WhatsApp, Youtube, and Google Meet.
A New Error Model Based on Adjustable Exponential Basis for Image-Based Visual Servoing

Error model has a great effect on the performance of image-based visual servoing scheme, such as convergence rate, smoothness of control inputs (e.g. velocity commands), etc. For a long time, the classical first-order error model dominates the design of the visual servoing control law, and the second-order error model is not employed to design the control law until recent years, both of which guarantee that the error decreases exponentially. In this paper, by adding an adjustable exponential basis to the feature errors, a new error model for the image-based visual servoing scheme is proposed. To the best of our knowledge, this is the first time that such an error model is developed. Compared with the existing first-order error model and second-order error model, the proposed error model has comprehensive advantages in computational efficiency, convergence rate and depth errors robustness, although it has a disadvantage in velocity smoothness. Comparative numerical simulations and real experiments conducted on a six-axis industrial robot confirm the performance of the proposed error model.
Comparative Analysis of Multinomial Naïve Bayes and Logistic Regression Models for Prediction of SMS Spam

This research was conducted based on a report from the United States Federal Trade Commission regarding fraud through electronic text messages via SMS that fraudsters use to manipulate potential victims. Usually, scammers spread SMS spam as an intermediary for the crime. The development of a supervised learning algorithm is applied to predict SMS spam into three categories, such as SMS spam, SMS fraud, and promotional SMS. The prediction system is dividing into several stages in the development process, including data labelling, data preprocessing, modelling, and model validation. The known accuracy based on modelling using Logistic Regression using a test size of 15% is 99%, using a test size of 20% is 99%, and using a test size of 25% is 98%. The Multinomial Naïve Bayes algorithm's accuracy with a test size of 15%, 20%, 25% is 97%. So, the SMS spam prediction approach uses the logistic regression method, which has the highest accuracy.
Optimizing Near-Data Processing for Spark

Resource disaggregation (RD) is an emerging paradigm for data center computing whereby resource-optimized servers are employed to minimize resource fragmentation and improve resource utilization. Apache Spark deployed under the RD paradigm employs a cluster of compute-optimized servers to run executors and a cluster of storage-optimized servers to host the data on HDFS. However, the network transfer from storage to compute cluster becomes a severe bottleneck for big data processing. Near-data processing (NDP) is a concept that aims to alleviate network load in such cases by offloading (or "pushing down") some of the compute tasks to the storage cluster. Employing NDP for Spark under the RD paradigm is challenging because storage-optimized servers have limited computational resources and cannot host the entire Spark processing stack. Further, even if such a lightweight stack could be developed and deployed on the storage cluster, it is not entirely obvious which Spark queries would benefit from pushdown, and which tasks of a given query should be pushed down to storage.This paper presents the design and implementation of a near-data processing system for Spark, SparkNDP, that aims to address the aforementioned challenges. SparkNDP works by implementing novel NDP Spark capabilities on the storage cluster using a lightweight library of SQL operators and then developing an analytical model to help determine which Spark tasks should be pushed down to storage based on the current network and system state. Simulation and prototype implementation results show that SparkNDP can help reduce Spark query execution times when compared to both the default approach of not pushing down any tasks to storage and the outright NDP approach of pushing all tasks to storage.
The Shift of Addressing Terms of Mandailingnese Society in Panyabungan

This study deals with the shift of addressing term of Mandailingnese society in Panyabungan. It employs qualitative research design with a case study. This study aims to describe: (1) the types of shift occur in the use of addressing terms by Mandailingnese speaker in Panyabungan, (2) the pattern of the shift of addressing term and (3) Reasons of Mandailingnese shift the addressing term in Panyabungan. The subjects were 20 respondent from second generation of parents group. The instruments used in this study were questionnaire and interview. The data was analyzed by Miles and Hubermans’ data analysis. There are fourteen respondent (70%) shif completely the addressing term in core family, two respondent (10%) shift partly the addressing term and four respondent (20%) maintain the addressing term. The shift of ddressing terms cover three types; ten respondents (50%) do not participate actively in the life of minority language, three respondents (15%) are not fluent in Mandailing language and seven respondents (35%) those are influenced by their parents to shift the addressing term. There are five patterns of the shift of addressing terms and three reasons why Mandailingnese society shift the addressing term; status of Indonesian language, social success and family tradition.&#x0D; Keyword : shift, addressing term, mandailingnese society
Removal of noise in Poisson image based on minimum risk wavelet shrinkage operator

Image Denoising is the procedure of getting rid of noise from images. The pixel value of pix engaged via image sensors are supposed tainted by using Poisson noise. Multiscale Poisson image denoising strategies have treated Haar body and wavelet constants. The modeling of those constants is allowed through Skellam distribution evaluation and increasing those consequences through resolving for reduction operator that reduces the danger useful inside the multiscale putting. The minimal threat reduction operative of this type efficiently creates denoised wavelet constants with least manageable blunders. To stunned the inadequacy of little difference in Bivariate Minimum Risk Shrinkage Operator (BMRSO), Hybrid Minimum Risk Shrinkage Operator (HMRSO) that syndicates BMRSO and Univariate Minimum Risk Shrinkage Operator (UMRSO) is used. UMRSOcan preserve contrast, but can’t preserve fine details in the image. HMRSO will preserve contrast fine particulars in the images.
Towards Early Distribution of Container-Based Microservices in Cloud Computing Environment

Microservices gained the popularity for use in scalable cloud application. The application based on microservices uses intensive network communication to call other microservices or to pass on the messages to hundreds of microservices running inside the cloud/edge nodes. This study addressed the early distribution of container-based microservices and proposed two distribution strategies named as Random Distribution and Design Pattern Distribution. In random distribution approach the microservices are assigned arbitrarily to the available data centers. While in design pattern distribution the microservices are grouped together on the basis of behavioral design patterns which identifies common communication patterns among objects. The proposed solution was tested using custom built simulation environment and the results showed that the early distribution of microservices according to the design pattern of the application resulted in significant reduction of network calls to the microservices hosted at other network nodes or data centers.
Analysis Of The Value Of Character Education In Women Author's Novels In 2000's

Character education is the most important learning experience in human life.Character education provides an understanding of humans about reason and behavior.One of the media to learn about character education is literature, because literature contains various commendable values.This study aims to describe and explain the values of character education in the novels of female authors in the 2000s.This research uses qualitative methods, documentation and interview data collection techniques, data analysis techniques using interactive models, data validation triangulation theory and data sources.The results of the research on the value of character education in the novels of female authors consist of love for the homeland, communicative, social care and responsibility.Learning to understand the value of character education aims to become a better person, in terms of thought and behavior
The Effect of Smart (Self Monitoring Approach to Read And Think) Strategy In Students’ Reading Comprehension at SMAN 4 Kota Bengkulu

The objective of the research was to find out the effect students reading comprehension after being trough SMART (Self Monitoring Approach to Read and Think) strategy in reading comprehension. The design of this research was experimental research. The instrument of the research was reading comprehension test. The result showed SMART (Self Monitoring Approach to Read and Think) was effective to be used to students’ ability in reading comprehension because there was a significant difference between the progresses in writing of the students who were studying through SMART strategy and those are not. By SMART strategy was effective to improve students’ comprehension in the aspect of finding main idea and identifying specific information. It is suggested for English teacher: it is expected for the teacher to use this strategy to make students enjoy their time to read the text in the classroom. Afterthat, in order to increase the students scores reading comprehension, the teachers are expected use the variation strategy and choose the best strategy, like SMART or another strategy that can help improvement of students ability and the students do not feel bored to learn.&#x0D; &#x0D; Key words: Reading Comprehension, SMART Strategy, Desscriptive Text