Reviewerly/exHarmony huggingface dataset:
Performance Improver for Block Generator in 1010! Using AND-OR Tree

1010! is a tile-matching game for Android and iOS.Players aim to fill a board's entire row or column using blocks from block holder to empty the board, thus create more space for the next blocks.These blocks are randomly-generated, thus occasionally block holders will hold blocks that cannot fit into the board by any combination and cause the game to end.This loss can be avoided using a two-stage performance improver consists of validator and unfit block changer.Validation begins by creating an AND-OR tree as a basis for validation's flow, taking block set's permutation and block's position to the board into account.If the block set is deemed unfit, block changer algorithm will calculate the heuristics for each block based on frequency and location of failure in the validation stage, then change the block with the highest heuristic with random block and redo the validation stage with new block set.After measuring performance on five gameplays, running only the validation stage results in an average of 3.95 ms, while doing both stages ran in 14.48 ms on average.
Grade Inflation Due to Selective Averaging

Summary. When assessing student performance, some educators choose to discard the worst tests written by the student. The mean of the remaining tests is taken as opposed to the mean of all tests written. Naturally, this process will result in some expected grade inflation. In our paper we provide a model for the expected grade inflation in the case when the student’s test-writing ability changes over time. Furthermore, we provide results on the grade inflation when the educator decides to use nested selective averaging processes.
Short Text Representation Model Construction Method Based on Novel Semantic Aggregation Technology

The semantic representation model of short texts has insufficient semantic representation ability, and the semantic representation method of short text based on the combination of word embedding and semantic weight is low in computational complexity and its performance is even better than that based on complex structure such as RNN and LSTM. This paper proposes a semantic representation model of short text based on ELMO (Embeddings from Language Models). The innovation of this model is: firstly, it is adopted the more advanced word embedding model ELMO; secondly, it is designed the semantic keyword extraction method of short text based on the topic model (Latent Dirichlet Allocation, LDA); thirdly, the stochastic gradient descent (SGD) is adopted, which is used to learn the semantic weights of semantic keywords in short texts. The experimental results show that compared with the existing short text semantic representation model, the representation model of short text, which is proposed in this paper, shows a high semantic representation ability of short text in specific domain and in the open domain.
The study on the effect of segmentising educational video towards students' knowledge acquisition and students' knowledge retention

This study was to investigate whether the segmentisation of educational video into different duration can affect students' knowledge acquisition and their knowledge retention. A total of one hundred and sixty students of first and second year students of Cognitive Science programme, divided into four groups, participated in the study. These groups experienced different durationof video segments. For example, group 1 watched a series of 4-minute segmented videos, group 2 watched a series of 6-minute segmented videos, group 3 watched a series of 12-minute segmented videos and group 4 watched a series of 24-minute segmented video. A first post-testto measure their knowledge acquisition was given after they finished watching all of the segmented videos while second post-test to measure their knowledge retention was given after two weeks later. Results of analysis of variance (ANOVA) show that 6-minute group significantly outperformed the 12-minute and 24-minute groups although there is no significant difference between the 6-minute group and the 4-minute group. As for knowledge retention, the 6-minute group has significantly outperformed the 24-minute group. There is no significant difference in knowledge retention between the 4-minute, 6-minute and 12-minute group.
Adaptive Fluorescence Pixels Control in Visibility Refinement through CSA

Visibility Impairment is a key area of concern in image processing and analysis. Brightest pixels, specially sky region in daytime, make some parts of image fluorescent resulting in artifact becoming unsuitable for computer-vision applications. Dehazing is carried out using optical model, masking high intensity pixels in each channel (RGB and gray) can reduce this artifact. Manual control of searching the exact high pixel values is time consuming and requires human intervention. This paper presents an efficient and simple method of optimizing fluorescent pixel intensity value by using Cuckoo Search Algorithm (CSA) with image quality and quantifying analysis through PSNR, CNR parameters. Objective functions PSNR, CNR are optimized by tuning fluorescent pixels using levy steps of CSA. CSA is used for faster convergence among other contemporary meta-heuristic optimizations.
A First Study of Compressive Sensing for Side-Channel Leakage Sampling

An important prerequisite for side-channel attacks (SCAs) is leakage sampling where the side-channel measurements (i.e., power traces) of the cryptographic device are collected for further analysis. However, as the operating frequency of cryptographic devices continues to increase due to advancing technology, leakage sampling will impose higher requirements on the sampling rate and storage capacity of the sampling equipment. This article undertakes the first study to show that effective leakage sampling can be achieved without relying on sophisticated equipments through compressive sensing (CS). As long as the information is leaked in the low-frequency component, CS can obtain low-dimensional samples by simply projecting the high-dimensional signals onto the observation matrix. The power traces can then be reconstructed in a workstation for further analysis and storage. With this approach, the sampling rate to obtain power traces is no longer limited by the operating frequency of the cryptographic device and the Nyquist sampling theorem. Instead, it depends on the sparsity of the leakage signal. As such, CS can employ a much lower sampling rate and yet obtain equivalent leakage sampling performance, which significantly lowers the requirement of sampling equipments. The feasibility of our approach is verified theoretically and through experiments.
Radar-based Near Field Environment Perception using Back Projection Algorithm

Radar-based high-resolution environment perception of close targets is facing challenges in terms of its bi-static antenna aperture configuration, where transmitting and receiving patches are separated. In the near field the different travel times occur at individual receive antennas. This time delay results in position errors of targets in the closer sensors’ environment using standard radar signal processing. Therefore the antenna configuration needs to be taken into account in raw data signal processing. This paper presents the application of a back projection algorithm to frequency-modulated continuous wave (FMCW) radar for increasing target localization in the automotive field. Therefore, multi-radar sensor measurements illuminating a real target vehicle equipped with an RTK-GPS reference sensor system were carried out on a test area. The standard radar signal processing give evidence of an increased localization error for targets illuminated under large azimuthal angles in the sensors’ near field. Applying the BPA approach has high relevance for the application of correction methods.
Isotope geochemistry of sulfur: implications for origin and distribution of sulfur in Isparta Angle of Western Taurus Belt, SW, Turkey

The study area is located between Isparta and Burdur cities in Turkey, in an area of 350 km2. According to sulfur isotope (δ34S) data of samples calculated δ34S (‰) values are between 0.0447-0.0449 and the variation range [Δ(δ34S)] is 7.7. These values suggest a genetic environment that suitable for shale formation. When it was examined the volcanic rocks in the region, it has shown that the rocks were quite poor in point of sulphide ores, it has been found Triassic bituminous shale, oil seepages in vicinity. Previous researchers asserted that the sulfur must have been originated from the volcanism. However, isotopic and geochemical analyses, detailed field surveys of volcanic rocks suggest that the sulfur has organic origin and may have occurred in shale environment. It is thought that the sulfur may have been thrusted to the surface by hydrothermal water and gas in the end of the volcanism.
MEDIA ADDICTIONS IN A SCHOOL ENVIRONMENT AND POSSIBILITIES OF PREVENTION

We are living in times where the media have become the main source of information, education and instruction for personal, family and social behaviour for many people. Different forms of media are competing for readers, listeners and viewers. They have growing influence on people’s consciousness, feelings, opinions, values, attitudes, actions and they contribute to versatile personality development. They are also source of information and entertainment. The system of mass media has a specific position in society. It contributes to the versatile personality development as a source of information, entertainment and it also acts as a tool of unification and coordination of educational influences in the whole society. The media includes not only negative aspects, but also many positive aspects that cannot be questioned. At the same time we have to be aware of the fact that children and young people belong to a “weaker” target group, which is more predisposed to addictions, because they are not able to distinguish what is right and what is wrong for them and what can result in negative or even fatal consequences. Media addictions in school environment have and unfortunately will have a rising tendency since the technology progresses much faster than in the past. Therefore it is important to pay attention to the prevention of media addictions at schools. Although the school cannot substitute a functioning family environment and upbringing, it can help to a large extent to prevent these addictions.
Learning of Medicinal Herbs Using QR Codes

Abstract Rapid development of information technology today has widened the use of computers as well as mobile phones. With more sophisticated devices is equipped with high resolution color, wireless access and high-speed processing. The current development has evolved with the creation of the portal since the mid-90‘s and given that the potential of the portal, it has been used by various firms regardless of body governmental or statutory bodies. Various advantages that can be utilized by the use of portals as it is has a dynamic source of information from a variety of sources and various formats. The current study aims to discover effects of QR codes implementation on medicinal herbs learning. The findings of students’ responses revealed that the QR Code facilitate the learning of medicinal herbs, whereby the mean from this analysis revealed that average majority of the students find the learning approach is easy to be employed.
The Integrity of Encryption Keys of European Train Control System Sessions During an Offline Loading

One of the main challenges of transport research is to achieve the highest possible level of cyber security against significant threats to signaling and telecommunications systems.In European Rail Traffic Management System (ERTMS), the potential vulnerability comes from two primary factors: the vulnerability of the key material distribution and the weakness of the cryptographic algorithms used.This article aims to provide a security analysis of ERTMS offline key management system by evaluating a risk analysis of the encryption keys distribution process and designing a matrix for the assessment of this type of risk, and studying the weaknesses of the cryptographic algorithm used.
History and Philosophy of Science as a Field of philosophical Researh. Stadler, F. (Ed.). (2017). Integrated History and Philosophy of Science: Problems, Perspectives, and Case Studies. (Vienna Circle Institute Yearbook, vol. 20). Vienna: Springer

Review of the&nbsp; book Stadler, F. (Ed.). (2017). Integrated History and Philosophy of Science: Problems, Perspectives, and Case Studies. (Vienna Circle Institute Yearbook, vol. 20). Vienna: Springer. &nbsp
Help communities solve real-world problems with AI

Join other AI professionals as a mentor in Technovation's AI program for families. Share your expertise with adults and children who are curious about artificial intelligence and how it can be used to address real issues in their communities. Help people all around the world learn to not only use AI, but to create solutions with AI that improve their lives and their communities.
Safety Mechanisms in Relational Database as Part of the IT System of the Enterprise

Abstract The work examines the effectiveness of the replication mechanism of the X production company database. In order to extend the functionality of the computer database of the enterprise, a model of its resource flow was created and an intensional and extensional part was created for a test database based on real enterprise resources. The model has been simplified to 3-rd normal form. The implementation was done in the MySQL database system. Two different operating systems were selected for testing: Windows and Linux. The database management system (DBMS) is working under the GPL license. MySQL DBMS offers many security mechanisms, and to secure the database, system of users permissions to objects have been selected and also an encryption of access passwords for users and connections to servers was used. A replication engine based on the binary log and the model “main server and backup server” was used to create a copy of the enterprise data.
A study on noise reduction and automatic P-phase onset time picking technology of weak micro-seismic signals from underground mines

The frequency range of the microseismic signal is wide, with contamination of noise including human disturbance, power frequency interference and other signals from underground mines, which greatly reduce the signal to noise ratio and raise a great challenge to accurate detection and picking of the P-phase onset time in noisy micro-seismic data from underground mines. Reliable P phase onset time picking plays a key role in accurate source location. Facing this situation, in this paper, synchrosqueezing wavelet transform (SST) is used to filter the micro-seismic signal in time-frequency domain, and the short-term to long-term average (STA/LTA) ratio combined with AIC method is used to finish P phase onset time picking. The objectives of this method are to improve the signal to noise ratio and provide an automatic means of P phase onset time picking. Firstly, the synchronous squeeze wavelet transform is used to filter the signal over several scales, and then the automatic P-phase onset is achieved by using the short-term to long-term average (STA/LTA) ratio combined with AIC method. Finally, the actual mine data are processed in this method, and the result of automatic P-phase onset time picking is compared with manual picking. The results show that the method provides a more reliable means of the P phase onset arrival and accurate matching the manual picking for low signal to noise ratio data.
Fuzzy Logic Applications to Predict Total Production of PKO (Palm Kernel Oil)

Abstract The purpose of this study is to apply fuzzy logic to predict the amount of Palm Kernel Oil (PKO) production at PT. Web-based AAI. This study uses the Tsukamoto method to anticipate the instability of palm oil production based on the existing demand and supply. The results showed that with the implementation of the fuzzy logic, the Tsukamoto method can affect the rate of more stable production and reduce the production of which is not in accordance with the market demand. The conclusion of this study is to apply the result of the predicted number of production PKO (Palm Kernel Oil) at PT AAI, in order to know the budget supply and demand thereafter.
Overview of Search Engine Optimization

Search Engine Optimization aims to draw the greatest amount of traffic possible to a website by bringing it to the top of a search engine's results. Search engine optimization is used by businesses and individuals to maximize the visibility of their websites and content in order to boost traffic and therefore business. Search engine optimization involves a number of adjustments to the HTML of individual Web pages to achieve a high search engine ranking. Search engine optimization is the umbrella term for all the methods you can use to ensure the visibility of your website and its content on search engine results pages.
Research on Evaluation Method of First-class City Distribution Network

Abstract The first-class urban distribution network is the key content of our country’s current construction. In order to obtain accurate evaluation results, a first-class urban distribution network evaluation index system is constructed from four aspects of reliability, economy, low carbon and intelligence, and a decision-making method based on cloud model and probability analysis is pro-posed. The cloud model is used to express and process the linguistic evaluation information of qualitative attributes given by experts. The 3En criterion is utilized to convert the cloud model to the interval value, thereby reducing the impact of randomness on distribution network evaluation results. The probability method is used to process the interval value and obtain the comprehensive evaluation results. The proposed method can effectively solve the randomness and fuzziness of qualitative indicators in the evaluation process. Finally, the method is used to evaluate and sort 11 regional distribution networks in xi ‘an jurisdiction, and the effectiveness of the proposed method is demonstrated according to the actual situation.
Approximation Method for the Periodic Signal RMS Measuring in the Presence of Random Noise

The article describes an approximation method for the periodic signal RMS measuring in the presence of random noise. To solve this problem, the processing of a periodic signal is used only for half of its period, which allows you to quickly define its effective value. A preliminary parabolic spline - approximation of periodic signal discrete samples at half its period is used. The error of the spline - approximation of signal discrete samples, as well as the error in the presence of random noise is defined. It is shown that the use of spline approximation reduces the effect of random noise. The analysis of the error of the considered method caused by the presence of random additive noise is given. The characteristics of the considered method when analyzing signals from industrial circuits are determined. Signals in industrial circuits have a non-harmonic form, which is caused by the presence of the third harmonic in most cases. The structure of the system that implements the described method of spline - approximation of signal samples is presented. It is proposed to use the considered approximation method of powerful electrical equipment voltage and current RMS measuring in order to rapid determines its emergency situations.
Consistent Kalman Filter for Distributed Target Tracking with Polar Measurements

This paper deals with a distributed target tracking problem for multiple autonomous vehicles sharing the polar measurements obtained from heterogeneous sensors. To enhance the unsatisfactory convergence property of the existing filtering techniques, a linear consistent Kalman filter (CKF) is proposed. The key idea of our approach is to model the relation between the target state and the polar measurements as a linear uncertain measurement equation. This model has a distinctive form because the uncertain coordinate transform matrix is multiplied, and correlated, to the available measurement matrix. The design objective of the proposed CKF is set to achieve the optimal performance in the sense of estimation error mean even when the coordinate transform uncertainty exists. Different from the previous methods, it provides the consistent target state estimates and makes the heterogeneous sensor fusion easy. Through the simulations, the effectiveness of the proposed method is verified.
Preventing Routing Loop in Routing Distance Vector Protocol using Destination Sequence Distance Vector (DS-DV) Method)

Abstract Count to infinity is a problem that appear in the vector routing protocol. This is because, there is a routing loop caused by the nodes structure in the networking that create loop. The destination sequence – distance vector method can be a solution to prevent the routing loop, so that the count to infinity problem can be solved in the protocol routing distance vector.
Application of improved Multiscale normalization

Abstract In this paper, a method based on neighborhood information is proposed, which adjusts the parameters by using a method of chi square with Gauss weighted distance and the self-adaptability of shared neighbor weighting. And by integrating the nearest neighbor weighted adaptive method, each pixel is automatically given a scale parameter to reduce the need to adjust the parameters. Gauss weighted local neighborhood information is introduced in this paper, to construct the similarity matrix directly on the original image. At the same time, based on the existing graph-cut image segmentation method is necessary to construct a better network graph by using the maximum flow minimum cut. So, a method is applicated, NJW algorithm is replaced by a improved Graph cut which combines the multi-scale analysis method, to improve the efficiency of the original segmentation method and enhance the clinical usability.
Zero-Shot Transfer Learning Based on Visual and Textual Resemblance

Existing image search engines, whose ranking functions are built based on labeled images or wrap texts, have poor results on queries in new, or low-frequency keywords. In this paper, we put forward the zero-shot transfer learning (ZSTL), which aims to transfer networks from given classifiers to new zero-shot classifiers with little cost, and helps image searching perform better on new or low-frequency words. Content-based queries (i.e., ranking images was not only based on their visual looks but also depended on their contents) can also be enhanced by ZSTL. ZSTL was proposed after we found the resemblance between photographic composition and the description of objects in natural language. Both composition and description highlight the object by stressing the particularity, so we consider that there exists a resemblance between visual and textual space. We provide several ways to transfer from visual features into textual ones. The method of applying deep learning and Word2Vec models to Wikipedia yielded impressive results. Our experiments present evidence to support the existence of resemblance between composition and description and show the feasibility and effectiveness of transferring zero-shot classifiers. With these transferred zero-shot classifiers, problems of image ranking query with low-frequency or new words can be solved. The image search engine proposed adopts cosine distance ranking as the ranking algorithm. Experiments on image searching show the superior performance of ZSTL.