Reviewerly/exHarmony huggingface dataset:
Investigation and Research on the Development Level of Primary School Students' Information Literacy in Western China and its Development Strategy

In this study, the current situation of information literacy level of primary school students in western China, mainly in Lanzhou, Gansu Province, was investigated by Means of questionnaire and interview. The survey results show that there is a big gap between urban and rural primary school students' information literacy level, mainly because rural schools do not enjoy good resource allocation. In addition, it is found that there is no significant difference in information literacy level between genders, but there are still some gender stereotypes. On the whole, students' information literacy level is at a medium level, and information technology use behavior is mostly at a low level, while high-level behavior is less. The information literacy of primary school students in western China still needs further development.
청소년지도자 역량에 관한 연구 - 청소년지도자, 예비청소년지도자를 중심으로 -

The purpose of the present study is to analyze competency units and the level of performance – considered important by youth workers and prospective youth workers – with regards to competency unit elements in the field of youth activities based on the NCS. The study surveyed a total 331 subjects including 137 youth workers and 184 prospective youth workers to achieve such a purpose. The basic statistics of the subjects were analyzed, and an IPA analysis was conducted to figure out the general characteristics of the research subjects and the differences in importance and performance. The analysis results show, first, that the importance average by competency unit of youth activities for youth workers(incumbent) to be 4.19, while the performance average was at 3.56. Second, results indicate a 2nd quadrant(evaluating youth programs, operating youth self-government activities). Third, the importance average by competency unit of youth activities for prospective youth workers was 4.15, while the performance average was 2.92. Fourth, the results indicate a 2nd quadrant(planning youth projects, evaluating youth programs). Fifth, in the IPA analysis of youth workers and prospective youth workers, the results indicated a a 2nd quadrant(operating youth self-government activities, building and operating a collaboration system, supporting activities that promote youth rights)
AUTOMATIC CARVING TOOLS USING ARDUINO MICROCONTROLLER

In carving crafts, there are a lot of motifs or regional characteristics from which the carvings originated, making a carving work requires special skills, patience, thoroughness, and full concentration so that there are no mistakes in carving. In today's technological developments, the manufacture of wood carving crafts using a CNC (Computer Numeric Control) carving machine has begun to shift the role of traditional carving craftsmen who are currently out of business, because the results of the CNC carving machines are much better and more detailed in carving, because of that work is a machine so an operator only enters certain codes into the machine computer, in operation a CNC carving machine operator must have special skills
UNIVERSITIES AS LEARNING ORGANIZATIONS IN THE DIGITAL WORLD

The article reveals the features of the development of universities as learning organizations operating in the digital world. The discrepancy between the formal understanding of the university, fixed in regulatory legal acts, and the real functions of a modern university is revealed. The analysis of the coincidence of the semantic series of the concepts "university" and "learning organization" is carried out. The teacher functions of a university, which is a learning organization, have been identified. Awareness by universities of the need for the preservation, accumulation and development of knowledge leads to the translation of non-formalized knowledge of individual employees into formalized descriptions and procedures. The stages of development of the university as a learning organization are proposed. It is concluded that not only the knowledge itself should be used within the university, but also knowledge about knowledge and the ability to manage it, in this case the university can be considered a learning organization.
A Survey on Digital Forensic Investigation Practitioners Approach and Challenges

Digital crimes are taking place over the entire world. For any digital crime which commit at any part of world, computer or any electronic devices are used. The devices which are used to commit the crime are useful evidences which must be identified and protected for further use. The crimes involving electronic devices are called as cyber-crime. To investigate such crimes, a scientific procedures needs to be followed. The data collection, analysis, preservation and presentation of digital evidence is must in order investigate the cybercrime. This paper highlights the practices that are used worldwide in the investigation process of cyber-crime. Keywords: Digital Forensics, Analysis, Investigation, models of investigation.
MAN TGX Euro6 D2676 LF Sound [1.37-1.38OB]

Man tgx euro6 d2676 lf sound Hi guys this mod changes scs man tgx euro6 sound with real man D2676 LF sound All sounds are long range and smooth have
한국어 학습자의 어휘 추측 결과에 영향을 주는 요인들에 관한 구조적 연구

The purpose of this study is to examine the variables which could potentially contribute to vocabulary inference by learners of Korean. A total of 215 learners of Korean have been invited and among them 203 students were assessed in a questionnaire survey on vocabulary reasoning strategy, vocabulary learning attitude and vocabulary exposure experience. The results are as follows. First, according to factor analysis, three factors are found: vocabulary reasoning strategy, vocabulary learning attitude, and vocabulary exposure experience. In addition, based on structural equation modeling (SEM), vocabulary reasoning strategy and vocabulary learning attitude have a significant direct effect on vocabulary inference. Second, all of the three factors are positively correlated with one another. Third, vocabulary reasoning strategy and vocabulary learning attitude are strong predicators of vocabulary inference results.
Skin Disease Recognition using Texture Analysis

Skin is the primary part of our body, One of the major issues we are facing presently days that's skin illness due to high air pollution. In this research, we are trying to skin illness recognition by using Neural Network which is based on texture analysis. There are many skin infections like Eczema, Acne, Hives, rosacea, psoriasis, etc. In common, these diseases have similarities in the design of contamination and side effects such as redness and rash. Diagnosis and recognition of skin illness take a really long time to handle. The infection determination and recognition gets to be troublesome as the complexity and number of highlights of the infection increases. Thus, a computer helped diagnosis and recognition system is presented. Computer algorithm which contains few steps that are image processing, image feature extraction, segmentation, and classification .of information has been executed with the assistance of a Convolutional neural network (CNN). The CNN can learn designs of side effects of specific infections and makes it speedier.
NASTransfer: Analyzing Architecture Transferability in Large Scale Neural Architecture Search.

Neural Architecture Search (NAS) is an open and challenging problem in machine learning. While NAS offers great promise, the prohibitive computational demand of most of the existing NAS methods makes it difficult to directly search the architectures on large-scale tasks. The typical way of conducting large scale NAS is to search for an architectural building block on a small dataset (either using a proxy set from the large dataset or a completely different small scale dataset) and then transfer the block to a larger dataset. Despite a number of recent results that show the promise of transfer from proxy datasets, a comprehensive evaluation of different NAS methods studying the impact of different source datasets has not yet been addressed. In this work, we propose to analyze the architecture transferability of different NAS methods by performing a series of experiments on large scale benchmarks such as ImageNet1K and ImageNet22K. We find that: (i) The size and domain of the proxy set does not seem to influence architecture performance on the target dataset. On average, transfer performance of architectures searched using completely different small datasets (e.g., CIFAR10) perform similarly to the architectures searched directly on proxy target datasets. However, design of proxy sets has considerable impact on rankings of different NAS methods. (ii) While different NAS methods show similar performance on a source dataset (e.g., CIFAR10), they significantly differ on the transfer performance to a large dataset (e.g., ImageNet1K). (iii) Even on large datasets, random sampling baseline is very competitive, but the choice of the appropriate combination of proxy set and search strategy can provide significant improvement over it. We believe that our extensive empirical analysis will prove useful for future design of NAS algorithms.
Scania Nextgen Real V8 Sound V5.0 1.36

Competible 1.35-1.36 Hi guys this mod changes scs nextgen scania r and s v8 sound this mod changes what? Scania nextgen r and s v8 sound. Scania ...
Video Steganography Based on Shi-Tomasi Corner Detection and Least Significant Bit Algorithm

Today, the digital and social media platforms are extremely trending, leading a demand to transmit knowledge very firmly. The information that is exchanged daily becomes ‘a victim’ to hackers. To beat this downside, one of the effective solutions is Steganography or Cryptography. In this paper, the video Steganography and cryptography thoughts are employed, where a key text is hidden behind a ‘certain frame’ of the video using Shi-Tomasi corner point detection and Least Significant Bit (LSB) algorithmic rule. Shi-Tomasi algorithmic rule is employed to observe, the corner points of the frame. In the proposed work, a ‘certain frame’ with large number of corner points is chosen from the video. Then, the secret text is embedded within the detected corner points using LSB algorithmic rule and transmitted. At the receiver end, decryption process is employed, in the reverser order of encryption to retrieve the secret data. As a technical contribution, the average variation of Mean Squared Error, Peak Signal to Noise Ratio, Structural Similarity Index are analysed for original and embedded frames and found to be 0.002, 0.016 and 0.0018 respectively.
Quantum Computing for Artificial Intelligence Based Mobile Network Optimization

In this paper, we discuss how certain radio access network optimization problems can be modelled using the concept of constraint satisfaction problems in artificial intelligence, and solved at scale using a quantum computer. As a case study, we discuss root sequence index (RSI) assignment problem - an important LTE/NR physical random access channel configuration related automation use-case. We formulate RSI assignment as quadratic unconstrained binary optimization (QUBO) problem constructed using data ingested from a commercial mobile network, and solve it using a cloud-based commercially available quantum computing platform. Results show that quantum annealing solver can successfully assign conflict-free RSIs. Comparison with well-known heuristics reveals that some classic algorithms are even more effective in terms of solution quality and computation time. The non-quantum advantage is due to the fact that current implementation is a semi-quantum proof-of-concept algorithm. Also, the results depend on the type of quantum computer used. Nevertheless, the proposed framework is highly flexible and holds tremendous potential for harnessing the power of quantum computing in mobile network automation.
THE INTRODUCTION OF GRAMMIME: A NOVEL APPROACH IN TEACHING THE ENGLISH SENTENCE PATTERNS

The awareness of communicative way of teaching English comes in different forms. This paper discusses the grammime, a new form of TPR which is mainly designed for eight parts of speech. It is used in some English training schools in China and is seen effective because it helps young learners to be acquainted with grammatical structure of sentences thus helping them to construct well-structured sentences with the help of different hand gestures which represent a structural rule. Incorporating oral drill with hand movements can augment the opportunity of memorizing the words, their meanings, and structural rule which makes learning much easier, interactive, and fun. The results which were obtained through experimental approach and self-made assessment instrument for pretest and posttest were used to assess grammime’s influence and impact on young learner’s learning process and outcomes. It is explored that the intervention using grammime really has an impact on young learners’ learning outcomes. Most specifically, the results suggest that when young learners are exposed to grammime and they practice it, the acquisition of knowledge and the learning process and outcomes increase.&#x0D; &#x0D; &lt;p&gt; &lt;/p&gt;&lt;p&gt;&lt;strong&gt; Article visualizations:&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;img src="/-counters-/edu_01/0745/a.php" alt="Hit counter" /&gt;&lt;/p&gt;
Determination of the Soil Sounding Depth for the Earthing Resistance Calculation of Substations 35 kV

Purpose. Determination of the minimum required sounding depth for calculation of the earthing resistance for substations with a voltage class of 35 kV. Methodology. For each ratio of electrical resistivity values of soil layers, earthing resistance was calculated with changing of the layers separation depth from 0.4 m to hmax, where hmax is the layers separation depth in a two-layer soil at which the earthing resistance value becomes the same as in a uniform soil. Results. In the experiments carried out, a family of curves was obtained that describes the effect of separation depth of soil layers for various combinations of soil electrical resistivities and geometric dimensions of the earthing arrangement. The accumulated statistical data for substations with a voltage class of 35 kV made it possible to determine the required sounding depth depending on the maximum size of the earthing arrangement and the probability of the relative resistivity falling into the corresponding range of values. An algorithm is proposed for determining the required investigation depth by Wenner method as part of the electromagnetic diagnostics of the earthing arrangement of existing substations with a voltage class of 35 kV. Originality. For the first time, a probabilistic relationship was established between the ratio of the electrical resistivity of soil layers, the size of the earthing arrangement, and the necessary depth investigation of the geological medium. As a result it has been proven that there are substations for which the required sounding depth does not exceed the maximum size of the earthing arrangement. Practical value. The use of the algorithm developed in this work allows increasing the accuracy of the earthing resistance calculation of electrical installations with voltages above 1 kV operating in a network with isolated neutral.
ASK: Adversarial Soft k-Nearest Neighbor Attack and Defense

K-Nearest Neighbor (kNN)-based deep learning methods have been applied to many applications due to their simplicity and geometric interpretability. However, the robustness of kNN-based classification models has not been thoroughly explored and kNN attack strategies are underdeveloped. In this paper, we propose an Adversarial Soft kNN (ASK) loss to both design more effective kNN attack strategies and to develop better defenses against them. Our ASK loss approach has two advantages. First, ASK loss can better approximate the kNN's probability of classification error than objectives proposed in previous works. Second, the ASK loss is interpretable: it preserves the mutual information between the perturbed input and the in-class-reference data. We use the ASK loss to generate a novel attack method called the ASK-Attack (ASK-Atk), which shows superior attack efficiency and accuracy degradation relative to previous kNN attacks. Based on the ASK-Atk, we then derive an ASK-\underline{Def}ense (ASK-Def) method that optimizes the worst-case training loss induced by ASK-Atk. Experiments on CIFAR-10 (ImageNet) show that (i) ASK-Atk achieves $\geq 13\%$ ($\geq 13\%$) improvement in attack success rate over previous kNN attacks, and (ii) ASK-Def outperforms the conventional adversarial training method by $\geq 6.9\%$ ($\geq 3.5\%$) in terms of robustness improvement.
Quick Response Code (QR Code) Data Security and Solution

Quick Response (QR) codes seem to appear everywhere these days. We can see them on posters, magazine ads, websites, product packaging and so on. Using the QR codes is one of the most intriguing ways of digitally connecting consumers to the internet via mobile phones since the mobile phones have become a basic necessity thing of everyone. Information about QR codes and their types get examine in the paper. Identification of objects and places in the real world is very important, and QR (2-D printing) code is useful to store identifiers of them. At the point when a barcode contains useful information or security data, the danger of security turns into an important issue. Because QR codes essentially highlight a square barcode with a special pattern, individuals have no clue whether the code will take them to legitimate data or a site loaded with malware. In recent year’s security of information have become big concern in the internet, so the information hiding has become an important issue. In steganography, Steganography hides the data in a medium such as text file, image, audio, video etc., and restrain the very existence of the message in the medium from a third party. In this paper, we present a methodology for creating QR codes and how they can be used to attack human interaction and automated systems and their different data types. Latest approach is proposed for secret communication by combining the concept of steganography and QR codes.
A study on the On-line Teaching system for Linux-based Programming Language

In this paper, a system configuration method that can practice Linux-based programming language online is presented.The proposed system utilizes the web-server function, which is the biggest feature of the Linux operating system, and simulates the telnet and FTP functions without firewalls or other security restrictions, so that it is possible to practice similar to the actual Linux console.To do this, we analyzed the functional elements that a programming tool should have on the web and established an algorithm to implement it.In particular, a method was implemented in which an error message caused by a user's mistake can appear in the same form as the actual telnet screen.As a result of using the implemented learning system in the class for students, it is possible to practice the Linux programming language online, as well as the instructor can directly check and guide all the learners, so the learner's satisfaction is similar to that of the offline class was confirmed.
Multiword Expressions lexicon extracted from the Gigafida 2.1 corpus

The MWE lexicon was extracted from the Gigafida 2.1 Corpus of Written Standard Slovene (https://www.clarin.si/noske/run.cgi/corp_info?corpname=gfida21) using specialized scripts for extracting data from corpora containing syntactic dependency annotations. The lexicon contains 5,242 Multiword Expressions with 12,358 examples from Gigafida 2.1. Each MWE entry (or sense) contains at least one and up to three extracted examples.MWEs were analysed using the JOS dependency parser system (http://nl.ijs.si/jos/bib/jos-skladnja-navodila.pdf) and were assigned matching syntactic structure IDs. The corpus sentences containing the MWE components and matching syntactic structure features were identified in the corpus and assigned to the corresponding headword or sense.MWEs variants (or variant senses) are linked with the senseKey attribute values, forming a MWE cluster of related variants or variant senses. A sample of MWE headwords also contains manually created sense division with descriptions of meaning for each sense.
Software Defect Prediction by Strong Machine Learning Classifier

Ensemble learning algorithm works on the approach, which utilized several learning algorithms to solve the problem. It shows the enhanced generalizability than that of a single learner; thus, ensemble algorithms are very useful. AdaBoost is one of the ensemble algorithms, which is very popular because of its simplicity and effectiveness. However, it may suffer from an overfitting problem. To reduce this problem in this paper, we proposed a new approach called AdaBoost.ET. In this approach, we develop bagging and bosting-based strong base learners using an ensemble of Adaboost based on an extra tree as a base algorithm. This approach improves the prediction rate of the AdaBoost algorithm by avoiding overfitting of the learner. The performance of AdaBoost.ET has been evaluated on benchmark open-source software defect data sets and compared with distinct state-of-the-art variation of AdaBoost algorithms.
Large-scale quantum hybrid solution for linear systems of equations

State-of-the-art noisy intermediate-scale quantum devices (NISQ), although imperfect, enable computational tasks that are manifestly beyond the capabilities of modern classical supercomputers. However, present quantum computations are restricted to exploring specific simplified protocols, whereas the implementation of full-scale quantum algorithms aimed at solving concrete large scale problems arising in data analysis and numerical modelling remains a challenge. Here we introduce and implement a hybrid quantum algorithm for solving linear systems of equations with exponential speedup, utilizing quantum phase estimation, one of the exemplary core protocols for quantum computing. We introduce theoretically classes of linear systems that are suitable for current generation quantum machines and solve experimentally a $2^{17}$-dimensional problem on superconducting IBMQ devices, a record for linear system solution on quantum computers. The considered large-scale algorithm shows superiority over conventional solutions, demonstrates advantages of quantum data processing via phase estimation and holds high promise for meeting practically relevant challenges.
Application Biplot and K-Medians Clustering to Group Export Destination Countries of Indonesia’s Product

A good increasing export will yield foreign exchange to a country, and subsequently funding its country growth. In Indonesia, export is one of the biggest foreign contributors. As we can see that the countries Indonesia export to are more than 100, it is a must to group them based on their similarity. Biplot and cluster analysis are statistic methods which are used as tool to classify data based on variable explanatory. There are outliers in data acquired. Outliers are observation data which is appeared to be extremely different to the other data. Those data are identified by leverage method. in summary, this research applies K-Medians Clustering Method using Manhattan Distance to resolve outliers while grouping the countries based on their export data. The data contains export data of 182 countries in the year of 2017. R 3.5.1 software was used to calculate in this analysis. The clustering shows us that each continent form difference clusters. Asia has 4 clusters while the rest each has 3 clusters. In addition, we can conclude that several clusters have high value export of Indonesia for certain variables.