Reviewerly/exHarmony huggingface dataset:
Simulation Analysis and Optimization of Lubricating Oil System

Abstract Based on the one-dimensional simulation model of lubricating oil system is established and analyzed by using FLOWMASTER software, this paper proposes a new method of optimizing lubricating oil system by PID technology. Ensure that the configuration requirements and control strategies of the relevant accessories of the simulation model are satisfied with the design requirements. Firstly, by simulating lubricating oil pressure fluctuation and lubricating oil flow distribution under Open/Close Valve in different opening and closing time, the optimal opening/closing time of Open/Close Valve is determined to be 0.2 s and 0.5 s respectively. Secondly, by writing the controller script file combined with a controller to realize automatic unloading relief valve simulation, determine the relief valve pressure regulating range of 0∼0.38 MPa, For precision of constant pressure valve of oil spill, the simulation results show that the average 10 m3/h flow caused by pressure changes of about 0.06 MPa. Under the flow sudden change signal of about 40 m3/h, the maximum pressure change is less than 0.1 MPa. Through the simulation results, it is found that most of the lubrication parts in the original design have the phenomenon of flow redundancy, which causes unnecessary pump power loss. The system is optimized by PID technology. By comparing the simulation results before and after optimization, it is found that the speed of constant displacement pump could be changed in time by PID controller, and the flow redundancy could be improved significantly, so the lubricating oil system could be lower consumption and achieve the purpose of optimization.
The Nexus Between Population and Economic Growth In Ethiopia: An Empirical Inquiry

Purpose: The link between population growth and economic growth has been becoming of most significant interest for researchers. However, there is no consensus among economists and researchers about the interaction between population and economic growth. Using time-series data spanning from the period 1981 to 2018, this study examined the population-economic growth nexus in the second most populous African nation-Ethiopia. Design/methodology/approach: The study used yearly time series data spanning from 1981 to 2018, Augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root tests, Autoregressive Distributed Lag (ARDL) co-integration approach and Toda-Yamamoto Causality tests. Finding: Population and economic growth (Proxied by GDP) have a long-run association, as confirmed by the bound test co-integration approach. From ARDL model estimates, population growth is found to have a negative and significant effect on economic growth, both in the short-run and in the long-run. Likewise, growth in GDP affects population growth positively and significantly—both in the short-run and long-run. The Toda-Yamamoto Granger-Causality test revealed that, there is a unidirectional causality running from population to economic growth. Research implications: The current (as of 2019) number of the total population of Ethiopia exceeds 110 million—making the country the second-most populous nation in Africa. With the prevalence of high fertility rate and mortality rate, unemployment, and poverty, the population is not expected to bring economic development in general and economic growth in particular. Hence, it is advised to the concerned body that anti-natal policies that discourage the fertility rate, need to be re-considered to supplement with economic growth policies. Originality/value: This paper provides an empirical study of population-economic growth nexus in Ethiopia—a low-income country with a rapidly growing economy but also a rapidly increasing population and labor force. An understanding of such an issue would provide a reliable input for formulating development policies. However, up to the best of my knowledge, there is limited empirical research about population-growth nexus growth for the case of Ethiopia.
Development of a Malaysian Sign Language interpreter using image recognition for the community to understand the deaf

In Malaysia, Person with Disabilities (PWD) with hearing problems or commonly known as the deaf, struggle to have a conversation with the communities who do not know or how to do sign language efficiently. The consequence is hearing PWD received unequal treatment in jobs and learning opportunities. This project aims to develop a Malaysian Sign Language interpreter to convert hand signs to texts, in order to facilitate the conversation between hearing PWD and the communities. The system would implement a camera and vision system to capture images of hand signs. Four hand signs have been selected. Stacks of these images were processed digitally using deep learning method, and eventually the trained network could recognize the hand signs successfully. This feasible study suggests that the proposed setup could be further implemented to train more hand signs and enrich the hand signs-to-text vocabulary.
IMPLEMENTASI PENDEKATAN WHOLE LANGUAGE DALAM PENGEMBANGAN KEMAMPUAN BERBAHASA ANAK USIA DINI DALAM ERA REVOLUSI 4.0

Early childhood education to develop moral potential and religious, social, emotional, independence, cognitive, language, motoric and artistic values for children's readiness connects elementary school level. Language development is one of the developments that need to be developed in early childhood. Through language that is permitted by children to translate experiences into symbols that can be used to communicate and think. Language development for kindergarten children based on reference to early childhood education standards No.58 of 2009, developed three aspects, namely accepting language, expressing language, and literacy. Whole language is a learning approach that teaches language in class or school in a whole and fun way. Learning to hear, speak, read and write is not carried out separately but is carried out together in an integrated manner in all areas of ability in kindergarten. Early childhood language development has a very close relationship with children's readiness in facing the 4.0 revolution era, because optimal child development will be able to stimulate all child development so that later when they are adults they will be ready to face the industrial revolution 4.0.
Mevzuat Verisetinde Soru Cevaplama Uygulamasi Question Answering Application on Legalisation Dataset

Question Answering is a widely studied sub-field of Natural Language Processing (NLP). It studies information retrieval techniques that locate the answer in a corpus for a given query. Recently, deep learning techniques are widely employed in this field. This work uses a transfer learning method on Turkish Tax legislation documents. Experts in Tax-Law domain created 355 question-answer pairs in SQuAD 1.1 (Stanford Question Answering Dataset) format using law documents in UYAP (National Judiciary Informatics System). BERT (Bidirectional Encoder Representations from Transformers) contextual word embedding vectors are used to create a representation that can capture different meanings in word representations. Using both these embeddings and the model obtained from SQuAD 1.1 dataset, a system was deployed. Also, using the failing answers retrieved from the application of this model, a SQuAD 2.0 dataset were created that includes impossible-to-answer questions. New models were obtained by training with this dataset. Our observation is that the most successful model of SQuAD 2.0 dataset outperforms that of SQuAD 1.1 by 11% in exact matching measure and by 5% in F1.
Optimasi Port Knocking dan Honeypot Menggunakan IPTables Sebagai Keamanan Jaringan pada Server

Network security is the most important aspect of a system in maintaining data validation and integrity, as well as ensuring the availability of services for its users. The development of network security system demands a better security, especially in servers. However, there are still weaknesses in the server that controls incoming packet which results in more vulnerable it is to be stormed by Denial of Service and Brute Force attacks on the system. This study aims to improve network security performance using the Port Knocking and Honeypot methods which will be combined with the Iptables method. From the tests carried out with the addition of the IPTables method, an increase in performance of CPU usage (38.4%) and memory (44.2%) on servers and network security were obtained compared to those that only use the Port Knocking and Honeypot methods.
Fringe projection method for 3D shape measurement using linear LED device and cylindrical lens array

Recently, it is required to improve the fringe projection device to develop a compact and fast 3D shape measurement. In this study, a fringe projection method using a linear LED device and a cylindrical lens array to improve the LSSM is proposed. In the case of a conventional light-source-stepping method, the half of the emitted power is wasted at the grating plate. In contrast, in the case of the proposed method, almost emitted power can be used as the projected fringe pattern. It was confirmed with an experiment.
DaCy: A Unified Framework for Danish NLP.

Danish natural language processing (NLP) has in recent years obtained considerable improvements with the addition of multiple new datasets and models. However, at present, there is no coherent framework for applying state-of-the-art models for Danish. We present DaCy: a unified framework for Danish NLP built on SpaCy. DaCy uses efficient multitask models which obtain state-of-the-art performance on named entity recognition, part-of-speech tagging, and dependency parsing. DaCy contains tools for easy integration of existing models such as for polarity, emotion, or subjectivity detection. In addition, we conduct a series of tests for biases and robustness of Danish NLP pipelines through augmentation of the test set of DaNE. DaCy large compares favorably and is especially robust to long input lengths and spelling variations and errors. All models except DaCy large display significant biases related to ethnicity while only Polyglot shows a significant gender bias. We argue that for languages with limited benchmark sets, data augmentation can be particularly useful for obtaining more realistic and fine-grained performance estimates. We provide a series of augmenters as a first step towards a more thorough evaluation of language models for low and medium resource languages and encourage further development.
Parallel Model Counting with CUDA: Algorithm Engineering for Efficient Hardware Utilization

Propositional model counting (MC) and its extensions as well as applications in the area of probabilistic reasoning have received renewed attention in recent years. As a result, also the need for quickly solving counting-based problems with automated solvers is critical for certain areas. In this paper, we present experiments evaluating various techniques in order to improve the performance of parallel model counting on general purpose graphics processing units (GPGPUs). Thereby, we mainly consider engineering efficient algorithms for model counting on GPGPUs that utilize the treewidth of a propositional formula by means of dynamic programming. The combination of our techniques results in the solver GPUSAT3, which is based on the programming framework Cuda that -compared to other frameworks- shows superior extensibility and driver support. When combining all findings of this work, we show that GPUSAT3 not only solves more instances of the recent Model Counting Competition 2020 (MCC 2020) than existing GPGPU-based systems, but also solves those significantly faster. A portfolio with one of the best solvers of MCC 2020 and GPUSAT3 solves 19% more instances than the former alone in less than half of the runtime.
High Payload Qr-Based Data Hiding Using Secured Compressed Watermark in Polar Domain

Audio Watermarking is a method to insert a copyright marker on audio. This method inserts a watermark in the information form and in a way that does not damage the audio. This technique is one of the ways to solve the problem of copyright infringement. The embedded watermark has to meet the condition of not damaging the audio and must have robustness, imperceptibility, and good capacity. The data hiding technique use the combined method of Lifting Wavelet Transform (LWT), Fast Fourier Transform (FFT), QR Decomposition and Reconstruction, and Cartesian-Polar Transformation (CPT) based on Quantization Index Modulation (QIM) with the secured and compressed watermark using Compressive Sampling (CS) technique. The proposed scheme is blind Audio Watermarking as it no needs for original audio in the detection process. The combination of methods overcomes multiple attacks with guaranteed quality watermarking and high capacity. Compared to the existing technique, the data hiding technique can withstand LPF attacks, Resampling, Linear speed change (LSC), and MP3 compression. This proposed technique is also secured due to the coded watermark by a particular random key using CS. Combining CS and Audio Watermarking techniques can perform well in capacity, imperceptibility, security, and attack resistance.
CRITICAL THINKING AS A MODERN PROBLEM OF PERSONALITY

The article is devoted to the problem of the formation of critical thinking in a modern personality.  Also, the article reveals the need to form and develop critical thinking in both pupils and students. The use of this tool can provide not only timely elimination of any arising problems, but also to find a new way to solve problems. The  critical thinking doesn’t occupy such a high position in lists of the best qualities of the students.
Dijkstra’s Algorithm-A Case Study to Understand How Algorithms are improved

In Graph Theory, Dijkstra’s Algorithm is one of the most well-known algorithms to calculate the Shortest Path. Many researchers have used its basic algorithm and attempted to improve its time complexity. This research is targeting the most famous works of such researchers. Few commonly known simple data structures like an array, link list, priority queues, and few advanced level data structures like binomial, Fibonacci are revisited and surveyed. The main target of this research/study is the evolutionary improvements in the time complexity of these algorithms. These improvements make it a suitable candidate to see how algorithms can run efficiently and the contributions of different researchers.
From Joe and Fred's complicated relationship to solving the condiment conundrum: Reliving the sights, sounds and spectacles of a 25-year lab road trip across the great white north

To cite the ever-quotable Grateful Dead, What a Long, Strange Trip it has Been (Garcia, J., et al., 1970). Although Garcia and colleagues' original characterization of their TRIP model is certainly accurate, additional data collected in the many years following the publication of this seminal work (i.e., Lyons et al. 1994-2021) strongly suggest that the descriptors inspiring, exciting, humbling, gratifying, and just plain all around awesome must now be added to this characterization as modifiers of their original Long/Strange hypothesis. As with any great journey, there are always detours from the original path. Some of these lead to the unexpected delight of discovery of new and fascinating places of great interest, whereas some lead to dead-end back alleys filled with rusting dumpsters. In this talk I will present an abridged summary of what was discovered along all of these roads well-travelled. In keeping with, and in honour of, Professor Wilberg's dedication to (and actual creation of) SCAPPS and his student-forward mentoring philosophy, I will constrain the content of this retrospective journey to only our lab's research that: a) first saw the public light of day at this wonderful conference, and b) has been driven, and often led, by the boundless imagination, creativity and industry of my graduate students over the past many years. This summary will include studies that span our collective interest in basic movement science (e.g., visual regulation of aiming and other movements, Inhibition of Return, etc.), to those that explore more abstract expressions of motor behaviour (e.g., Illusions of Control, gambling behaviours, etc.) to those that deal with issues of Human Factors and other Human-Environment interactions (e.g., Auditory tone-space relationships, End and Goal State comfort in applied settings, etc.). The outcomes of some of these studies were very fruitful, resulting in impactful publications and future research directions for our students, and some…well…not so much (see dumpster reference above). But regardless of the eventual outcome, all of these investigations were driven by the desire to better understand the incredible complexity of human behaviour and the motor control contributions that subserve these behaviours. My intention is not to dwell on any of these individual studies in great detail. Rather, the overarching goal of this talk is to provide an overview of this 25 year research road trip, back alleys and all, that I have taken with many, many true friends and respected colleagues (even if some of the more recent ones can't sing along to Truckin' in the car because they don't know the words, and even if I am now showing more than just a Touch of Grey).
Spatial-Scale Characteristics of a Three-Dimensional Cloud-Resolving Solar Radiation Budget Based on Monte Carlo Radiative Transfer Simulations

A three-dimensional (3D) atmospheric radiative transfer (RT) model based on the Monte Carlo method was developed to evaluate the cloud-resolving radiation budget. The simulation data of stratocumulus (open and closed cell types) stimulated by a large eddy simulation model were used to obtain a detailed cloud field dataset at different spatial resolutions between 100 m and 1 km orders. By applying the 3D RT model offline to a multiscale cloud field dataset, the 3D distribution and magnitude of the solar radiative heating rate were estimated for each spatial resolution. The results showed that the magnitude of the local solar radiative heating effect significantly changes in the range of spatial resolution between 100 m and 1 km. The solar radiative heating rate can reach 6 K/hr locally in the case of the spatial resolution at 100-m order, whereas it is approximately 1 K/hr at most in the case of the spatial resolution at 1-km order. However, the domain-averaged values of the solar radiative heating rates were almost invariant at different spatial resolutions. The results indicate that a radiation scheme for the cloud-resolving model needs to be constructed while considering spatial resolutions, along with cloud parameterization.
ФОРМИРОВАНИЕ ВРЕМЕННЫХ ПРЕДСТАВЛЕНИЙ У УЧАЩИХСЯ С ЗПР НА УРОКАХ МАТЕМАТИКИ

The article deals with the problems and peculiarities of the formation of temporary representations in students with DSS at the lessons of mathematics in the classes of correction in the general education school in conditions of inclusive education. Special assignments are proposed for increasing the level of the formation of temporary representations for students with DSS.
Research of the Service Composition Optimization Model Based on Petri Net

Cloud service systems bring together a wide variety of flexible and scalable mass services. The service combination scheme which can meet the user&amp;rsquo;s needs is provided to the user through the flexible and changing service mode of service combination technology. However, service combination failures often occur. In view of the above problems, this paper establishes the cloud service combination optimization model. Firstly, it is proposed that the Service Combination Optimization Petri Net models and analyzes the service selection and combination. In order to avoid local convergence, combining Service Combination Optimization Petri Net with improved Genetic Algorithm, a service combination model based on Local Search Operator Genetic Algorithm is proposed, and the legitimacy of service combination sequence is verified by Petri net. The results of experiment show that the Petri net service composition model can effectively verify the constraints of service composition and the logical rationality of the system, the Local Search Operator Genetic Algorithm effectively reduces the search space and improves the convergence rate. Compared with other algorithms, the execution efficiency and accuracy of Local Search Operator Genetic Algorithm are improved.
Perancangan Aplikasi Kode Etik Profesi Dengan Menerapkan Algoritma Raita

Professional Code of Ethics is an ethical order that has been agreed upon by a certain community group. It can also be interpreted as a pattern of rules, procedures, signs, ethical guidelines in carrying out an activity or work. But in fact many professional actors do not know or care about the code of ethics of their own profession. The problem that occurs is that the professional code of ethics is generally written in a code of ethics book which is difficult to carry everywhere when compared to other books that are already application-based, either web-based or mobile-based. For this reason, with the application of this professional code of ethics, professional actors and the entire community can easily find out the desired professional code of ethics by searching for a professional code of ethics that has been determined according to the existing pattern. This professional code of ethics search application is designed using the string matching method. Application development uses the Unified Modeling Language (UML) planning method and is built on the android platform.
INFORMATION MODELING OF THE CONTENT QUALITY ASSESSMENT PROCESS DURING EXPERTISE OF TYPICAL LEARNING PLANS AND TYPICAL LEARNING PROGRAMS (CURRICULA)

This article discusses the information modeling process of the quality assessment of content in the expertise of typical learning plans and typical learning programs (typical curricula). The results of the study of linear-concentrically constructed traditional and updated standard curricula and logical and technological map of the process of expertise of typical learning plans and typical learning programs (typical curricula) are presented. The problems of implementation associated with the meta-subject orientation of typical curricula are shown. A new form has been proposed, which provides for planning for each individual subject. Among the main substantive differences of the updated standard curricula, the following are considered: the values ​​of secondary education, the construction of programs in accordance with the expected results, the spiral construction of subject curricula, the taxonomy of educational goals, functional literacy, the adequacy of the content of sections and topics of academic disciplines to modern trends and focus on development and the formation of socially significant competences, etc. The improvement of the technology with a new algorithm for evaluating typical learning plans and typical learning programs (typical curricula) and making expert decisions is proposed. This study was carried out within the framework of the scientific and technical program "Scientific bases of modernization of the education and science system" at the National Academy of Education named after Y.Altynsarin of the Ministry of Education and Science of the Republic of Kazakhstan.