Reviewerly/exHarmony huggingface dataset:
Initial Coin Offerings success factors

In these years’, from 2015 until now, cryptocurrencies (cryptos) and all the financial instruments and events linked to it has become very popular following a hype wave of excitement. These cryptos, like Bitcoin or Ether, are traded thanks to the existence of the blockchain technology, which is the concept of a distributed ledger (DL) system where all new transactions are added to the chain thanks to the due diligence of people who are part of the network. They are called ‘miners’ and assure the correctness of the code of the transaction and deliver security to the system, which is not based on a trusted centralized authority. Talking about entrepreneurial finance related to this technology, a very interesting financing tool for new businesses and start-ups in early stages are ICO’s (initial coins offerings), similar to IPOs (initial public offerings) where a young firm offers rewards or securities using specific crypto-tokens in exchange of cryptocurrencies to fund their business. A high number of studies have been conducted on these revolutionary and disruptive topics giving to the community more and more insights and revealing many interesting aspects, starting with research agendas about Blockchain, Bitcoin and ICOs, offering nontechnical explanations of the basics of blockchain and its applications, cryptocurrencies and ICOs. This Study focuses on the finding of the relevant success factors tha led ICOs success from 2016 to 2021.
Discussion of “A Gibbs Sampler for a Class of Random Convex Polytopes”

This very welcome article is a fascinating contribution to an important subject. Persistent questions about the lower and upper probabilities includeWhat does it do in simple problems?What does it ...
AN ANALYSIS OF STUDENTS ABILITY TO COMPREHEND DESCRIPTIVE TEXT AT THE TENTH GRADE STUDENTS OF SMA NEGERI 6 TANJUNGPINANG

This research aimed to know students ability to Comprehend Descriptive text. This research is intended to find out how students ability to comprehend Descriptive text. Population and sample of the study are grade X IPA1 SMAN 6 Tanjungpinang. The samples taken in one class to gather data. Researchers using multiple choice test that uses 8 descriptive text.The result of students ability to comprehend Descriptive text is in Moderate level. It can be seen from the mean score of the students which is 68.5 Among 22 students. There are 0 student (0%) is in Very good level, 1 students (4.54%) are in Good level , 21 students (95.45%) are in Moderate level, 0 students(0%) is in Very good level, 0 students(0%) is in failure level so, most of the students are in Moderate level.
Enabling Deep Neural Networks with Oversized Working Memory on Resource-Constrained MCUs

Deep neural networks (DNNs) have shown their great power in effectively extracting features and making predictions from noisy input data, which makes them the most widely used algorithm in machine learning applications. In the meantime, microcontroller units (MCUs) have become the most common processors in our daily life. Therefore, integrating DNNs into MCUs will definitely make a huge impact on the real world. Despite its importance, little attention has been paid to the deployment of DNNs onto MCUs yet. DNNs are usually resource-intensive while MCUs are resource-constrained, which often makes it infeasible to directly run DNNs on MCUs. Apart from the low frequency (1-16 MHz) and limited storage (e.g., 64KB to 256KB ROM), one of the biggest challenges is the small RAM size (e.g., 2KB to 16KB), which is needed to save the intermediate feature maps of a DNN in the runtime. Most existing DNN compression algorithms aim to reduce the model size so that the model can fit into limited storage. However, these algorithms do not reduce the size of intermediate feature maps significantly, which is referred to as working memory and might exceed the capacity of RAM. Therefore, it is possible that DNNs cannot run on MCUs even after compression. To address this problem, this work proposes a technique to dynamically prune the activation values of the output feature maps in the runtime if necessary, such that intermediate feature maps can fit into limited RAM. Experimental results on SVHN and CIFAR-10 have shown that the proposed algorithm could significantly reduce the working memory of a DNN to satisfy the hard constraint of RAM size while maintaining satisfactory accuracy with relatively low overhead on memory and run-time latency.
Application of Quizizz Educational Games and Rewards to Increase Students' Learning Motivation

Learning through online that does not do face-to-face certainly has various challenges. One of the challenges is the lack of student learning motivation. Efforts to create an interesting and fun learning atmosphere require several breakthroughs, both in curriculum development, learning media innovation and fulfilling educational infrastructure. This study aims to describe the application of the Quizizz educational game and the provision of rewards to increase the learning motivation of fifth grade students at SDN Tarokan 5 Kediri. The approach used in this research is a qualitative approach with the type of classroom action research. The research was carried out in two cycles. Each cycle consists of 4 stages, namely planning, implementation, observation, and reflection. The subjects of the research were the fifth grade students of SDN Tarokan 5, totaling 10 students consisting of 6 boys and 4 girls. The data in this study are the results of observations of teacher activities, student activities, and student learning motivation. Data collection techniques used by using observation, questionnaires, field notes and documentation. The results of the study by applying the Quizizz educational game and giving rewards can run well and have increased. In the first cycle the average value of teacher activity was 98% in the very good category, increasing to 100% with the very good category in the second cycle. The value of student activity is 83.5% in the good category, in the second cycle it increases to 91.5% in the very good category. Meanwhile, the result of students' learning motivation in the pre-action was 53% with a very low category. In the first cycle, the results of the observation of students' learning motivation increased to 77% in the high category. Furthermore, in the second cycle, the results of the observation of students' learning motivation increased to 82% with a very high category. The conclusion of this study is that the application of the Quizizz educational game and the giving of rewards to the fifth grade students of SDN Tarokan 5 Kediri, has been carried out by the teacher and students very well.
The Method for Generating Recommended Candidates through Prediction of Multi-Criteria Ratings Using CNN-BiLSTM

To improve the accuracy of the recommendation system, multi-criteria recommendation systems have been widely researched. However, it is highly complicated to extract the preferred features of users and items from the data. To this end, subjective indicators, which indicate a user’s priorities for personalized recommendations, should be derived. In this study, we propose a method for generating recommendation candidates by predicting multi-criteria ratings from reviews and using them to derive user priorities. Using a deep learning model based on convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM), multi-criteria prediction ratings were derived from reviews. These ratings were then aggregated to form a linear regression model to predict the overall rating. This model not only predicts the overall rating but also uses the training weights from the layers of the model as the user’s priority. Based on this, a new score matrix for recommendation is derived by calculating the similarity between the user and the item according to the criteria, and an item suitable for the user is proposed. The experiment was conducted by collecting the actual “TripAdvisor” dataset. For performance evaluation, the proposed method was compared with a general recommendation system based on singular value decomposition. The results of the experiments demonstrate the high performance of the proposed method.
Solar Tracker: An Essential Need of Solar Photovoltaic Energy Generation System

Climate change becomes a threat to the living bodies on the planet earth. A great concerned step to save the environment is replacement of fossil fuels by renewable energy resources.  Sun is a copious source of renewable energy. Solar cells tap the solar energy from sun. Solar cells convert the solar energy into plentiful utilizable form of energy. Solar cell provides more energy in response to normal fall of radiation otherwise less productive. To maximize the energy obtained from solar cell and increase the efficiency, solar tracking system tracks the movement of the sun. This scheme makes the energy more usable in domestic and commercial applications as a complementary source of power. The tracking system designed to respond in the normal direction of light in the shortest of time. Basics of solar tracking systems are discussed here for solar energy. Various Designs and components of solar tracker are technically mentioned in this paper. Keywords: Renewable Energy, Solar Energy, Solar Tracker
Pengetahuan tentang Pembelajaran Berbasis Mind Map QR-Code oleh Pendidik

This study aims to determine the extent of knowledge about teaching and learning, especially the QR-code mind map by educators. The research method used is an online survey method via google form. The survey method is a research method to obtain data about an existing symptom and seek factual information. The subjects of this study were 16 teachers or educators. The results showed that the educators of the respondents also strongly agreed and were interested in the use of the QR-Code Mind Map for the evaluation process through an IT-based quiz because it provided convenience during the teaching and learning process.
Using Mixture of Normal Distributions to Detect Treatment Effects when the Frequentist Method Fails

Background: Results from a clinical trial can either support the efficacy and safety of a new compound or fail to provide such evidence. One reason for ‘non[1]positive’ result is due to the underlying assumption of normality and homogeneity of variances, which are quite often violated when analyzing data from clinical trials, despite randomization. A question of interest is can we obtain more informative results when using mixture of normal distributions or linear models (MLMs) in such cases. Introduction: MLM can be used when traditional methods fail. MLMs “search” within the variability in data to identify components or subgroups of individuals (also known as latent classes) who have common intercepts and common slopes of change in a variable/endpoint of interest but whose intercepts and slopes are different from other subsets of patients. Thus, MLMs can be used to identify subgroups of patients exhibiting differential response to treatment within each treatment arm. The purpose of our study was to examine the usefulness of using MLM in such circumstances. Methods: Data of 155 subjects taken from a Multicenter, randomized, double blind, placebo controlled trial that evaluated the efficacy of Cpn10, administered twice weekly subcutaneously to treat Rheumatoid Arthritis was taken to evaluate the usefulness of MLM. The primary efficacy measure ACR20 was analyzed using a 3-step process: first, MLM was used to estimate RA duration using a 3-component model. The second step took the results of the first step to inform the logistic model and its analyses. Model was fitted with an intercept, MLM components, treatment arm, RA duration (linear and quadratic), dose response (modeled as an interaction effect), age and baseline weight. LOCF was used to impute for missing data. Data was analyzed using MLM and SAS v 9.0. Results: The model was a good fit to the data with a likelihood ratio significant at p=0.026, and a significant increase in the -2log L. We also observed low p-values for those variables that were non normal. Overall and for the 75 mg dose, Cpn 10 was efficacious relative to placebo, p&lt;0.050. We also observed that dose response was significant at p&gt;&lt;0.15 Conclusion: The use of MLM adds value because it can be used to understand the disease experience or the value of treatment when traditional statistical methods cannot. Key words: Mixture of linear models, normality, entropy.
A Study of Resource Utilization Improvement on Cloud Testing Platform

This paper developed the software testing factory-cloud testing platform (STF-CTP) to address the software compatible issues in various smart devices.Software developers who only require uploading the application under test (AUT) and test script can test plenty of smart devices in STF-CTP.The challenge for the cloud test platform is how to optimize the resource and increase the performance in the limited resource.This paper proposed a new scheduling mechanism and a new process of the system operation which is based on the OpenStack platform.We decrease about 40% memory usage of OpenStack server, increase 3% to 10% Android device usage of STF-CTP, enhance about 80% test job throughput and reduces about 40% test job average waiting time.
PERANCANGAN INTERIOR RUANG PERPUSTAKAAN PERGURUAN TINGGI DI JAKARTA (STUDI KASUS PERPUSTAKAAN UNIVERSITAS MERCU BUANA)

Generally the library is a place to read books and add references about science and to add data to the task literature. Reading books or literature is a very important source of reference for students. But it is unfortunate that the interest in reading among students looks very minimal at this time. One of the low interest in reading is among students, it can be seen from the number of visitors in each college library. The library will look very crowded when just before the exam because many students are looking for books for reference sources of assignments, other than when not before the exam the library tends to be very quiet visitors, who visit the library are usually only a few final-year students who are working on thesis. the presence of a library with a comfortable room is very necessary to attract interest, especially students and the general public so they want to visit the library. The design method used is a qualitative analysis method whose data collection techniques are by means of observation, interviews, literature studies, comparative studies, documentation. The result of this design is the Modern style and the theme Wonderful green and local culture of Betawi in the interior of the College Library, by creating a functional atmosphere, ergonomic, and has a good aesthetic value, so that it can make the place become more convenient for visitors and also for employees on duty.
Restitution to Africa Unjust Enrichment and Damages from Imperial, Colonial, and Post Colonial Abuse of Dominance

Most of Africa struggles to improve daily life, and reduce or eliminate deep poverty. Household income and wealth are stuck at low levels. Public policies are unable to accelerate investment and growth, employment creation, and food production and security, housing, health care, and educational access and success, for the majority. The Fundamental, underlying reason for these lagging conditions is 500 years of unjust enrichment by Western, Northern, and lately, Asian actors. They abused their dominance, and captured excess benefits from trade, investment and other activities. The author proposes the orderly, disciplined, targeted return of the $20–$40 trillion of unjust enrichment, in grants to sectors identified as key to economic development.
AN ANALYSIS OF STUDENTS’ SKILL IN READING ANALYTICAL EXPOSITION TEXTS OF THE ELEVENTH GRADE STUDENTS OF MANTANJUNGPINANG

The purpose of this reseaarch is to find out the students skills in reading analytycal exposition and what factors that influence the students skill in reading and understanding analytical exposition text. This research belongs to decriptive qualitative research. There are no population and samples. Therefore, this study has participants as research subjects. The participants were eleventh students of MAN Tanjungpinang selected using purposive sampling technique. Participants were asked to read and answer the question about analytical exposition text and answer the quetionniare provided by the researcher. To analyze the data, the data were described and then displayed according to each answer. This research shows that students skill in reading analytical exposition text is in good category. It can be concluded that based on the total score, the eleventh students got 40% in excellent category, 60% in good category and no students in average and poor category
LibGuides: Omeka: Technology: Signing Up

An introductory guide to building online exhibits with Omeka.net, the web-based version of Omeka.
Tailoring personalized breathing rhythms of a Sleep Robot: An interactive data loop design

The thesis aims to investigate how the Sleep Robot system (a Sleep Robot, its application, and servers) can adopt a data-enabled loop to make optimal use. The research has three main objectives: (1)understanding the needs and concerns of using the Sleep Robot system in different user profiles, (2)building a data loop of the Sleep Robot system with subjective and objective data, and (3) identifying the design principles of long-term engagement in a data loop. To answer the research question and fulfil the objectives, the thesis adopted a four-diamond design process. In the discovery phase, the research reviewed the literature on personal informatics and sleep solutions, then plotted the Somnox data ecosystem. In the refining phase, the user research was performed to obtain profound insights, create a journey map, and user profiles by using a sensitizing diary, fetching data from servers, creating data visualization, and conducting interviews. The user research found that users stick to standardized breathing settings without engaging themselves in self-experimenting with breathing settings due to the lack of guidance and support. Thus, the project’s design goal is to let users feel guided and at ease during self-experimenting different breathing settings. By going through creative sessions and user testing in the developing phase, the research found out four essential design elements to achieve design goal: (1) step by step learning experience, (2) dynamics of breathing rate, (3) growing together through empowering the breathing recommendation system, and (4) breathing with a specific goal which reflects causes of poor sleep. Eventually, the proposed design integrated these four elements into three levels of personalized breathing rhythms, including customized breathing, optimized breathing, and contextualized breathing. In the evaluation phase, the proposed design was evaluated through user scenarios and high-fidelity prototypes. The results showed that users highly appreciated the guidance and ease through measuring personal conditions to tailor three-level breathing rhythms. This study emphasizes the transition role of the proposed concept from three-level of personalized breathing with a data loop and, ultimately, toward the adaptively synthesized breathing.
Implementing Accreditation Approach in Agricultural and Natural Resources Research Centers of Iran

Providing an appropriate model for accreditation of Agricultural and Natutal Recources Research Centers is a heavy duty for  monitoring and evaluation of these centers. An accreditation is a process of validation in which academic institutions are evaluated. To do this, an accreditation council must first be formed which its focus is reflected in its belief, vision, mission and values. The standards for accreditation are set by a peer review board whose members include faculty members from the accredited institute and the other  accredited centers. Therefore, research centers, with their own evaluation of accreditation program, may be able to develop a model for their ongoing performance monitoring. To this end, they must first form different agents or working groups according to their tasks and missions. Each working group defines the tables of  objectives and indicators including main objectives, sub-main objectives, evaluation criteria, measurement indices, and achievement criteria. Measurement tool for the evaluation is a specialized questionnaire relevant to each working group together with the registered data of the evaluated institute. The questionnaire is filled by relevant target groups in the National Agricultural Research Centers in the country. The questionnaires are then collected and analyzed. One of the important outcomes of the evaluation is the motivation of the staff of evaluated center in attention to the importance and quality of research in the center and showing its current situation. In addition, the current status of the center will be determined in terms of its possible distance to the level of utility and standards.
Geochemistry of Sedimentary Iron Ore in Shendi-Atbara Basin, River Nile State, Sudan

This paper emphasized on the geochemistry of sedimentary iron ore of Shendi-Atbara Basin, River Nile State, Sudan. The main geological units in the study area are composed of Basement Complex (Pre-Cambrian), Nubian Sandstone Formation (upper Cretaceous), Hudi Chert (Oligocene) and Quaternary superficial deposit in ascending chrono logical order. The aim of this study is to investigate the geochemical behavior and geochemical conditions affecting precipitation of sedimentary iron ore. The methodologies have been used to realize the objectives of this study included; fieldwork, geochemical data analyses. Geochemical investigation of studied samples includes chemical analysis such as major oxide analysis (Fe2O3, SiO2, Al2O3, CaO, K2O and Na2O) and trace element analysis (Cr, Co, Cu, Zn, Mnand Ni) using Atomic Absorption Spectrometry (AAS). The results showed that the origin of iron ore is formed by chemical precipitation during chemical weathering of the rocks from surrounding areas. The study of iron ore showed that, the environmental conditions under which iron ore are formed were lacustrine environment and warm temperature. Concentration of Fe2O3 in the study area ranges between maximum 79.52% in Goz Alhaj area to minimum 27.22% in Alkarbican area and the average is 53.37% indicate that the quality of iron ore is good according to int ernational standards. All these results have been to construct isoconcentration maps of the iron ore distribution in study areaand potentiality for future mining works.
Design Directions for Supporting Implicit Interactions in a Market Surveillance System

Enterprise systems are built for companies and used by the employees to complete work tasks. Focus on userdriven designs for consumer technology has led to expectations of user-friendly designs. En ...
Pseudo-data generation for the extraction of Problems, Treatments and Tests.

One of the primary challenges for clinical Named Entity Recognition (NER) is the availability of annotated training data. Technical and legal hurdles prevent the creation and release of corpora related to electronic health records (EHRs). In this work, we look at the impact of pseudo-data generation on clinical NER using gazetteering utilizing a neural network model. We report that gazetteers can result in the inclusion of proper terms with the exclusion of determiners and pronouns in preceding and middle positions. Gazetteers that had higher numbers of terms inclusive to the original dataset had a higher impact.