Reviewerly/exHarmony huggingface dataset:
РЕКОМЕНДАЦИИ МАГИСТРУ ПО СОЗДАНИЮ НАУЧНЫХ ПУБЛИКАЦИЙ

In order to write a scientific article that will cause a scientific interest, will be published and in demand in the professional circle, it is important to know the basics of creating a scientific publication. When writing an article, there are often difficulties associated with the publication process. The work should be original, contain the main part of the research, conclusions, have a clear structure and be based on a theoretical basis. Such a publication is unconditional to attract the attention of experts in their field, will benefit readers and the author. When publishing an article, you should remember that a lot decides the name of the publication. It should correspond to the topic of research, contain keywords on which it will be possible to easily find a job. The title should be weighty and compelling, to attract attention. The purpose of this article is to study the basics of creating scientific publications by masters in the learning process. This publication discusses the types of scientific articles, presents the principles for constructing the material, gives examples of the use of scientific style, and gives recommendations on writing headings on the example of existing works. The article discusses the algorithm for writing the main sections and the use of terminology. The article was prepared to help the researcher in the work on a scientific publication.
Neural Network Heuristic Functions for Classical Planning: Reinforcement Learning and Comparison to Other Methods

How can we train neural network (NN) heuristic functions for classical planning, using only states as the NN input? Prior work addressed this question by (a) supervised learning and/or (b) per-domain learning generalizing over problem in- stances. The former limits the approach to instances small enough for training data generation, the latter to domains and instance distributions where the necessary knowledge generalizes across instances. Clearly, reinforcement learning (RL) on large instances can potentially avoid both difficul- ties. We explore this here in terms of three methods drawing on previous ideas relating to bootstrapping and approximate value iteration, including a new bootstrapping variant that es- timates search effort instead of goal distance. We empirically compare these methods to (a) and (b), aligning three differ- ent NN heuristic function learning architectures for cross- comparison in an experiment of unprecedented breadth in this context. Key lessons from this experiment are that our meth- ods and supervised learning are highly complementary; that per-instance learning often yields stronger heuristics than per- domain learning; and that LAMA is still dominant but is out- performed by our methods in one benchmark domain .
Pengaruh Penggunaan Media Pembelajaran TIK terhadap Hasil Belajar Tematik Kelas IV SDN KIP Maccini

The current learning follows the pandemic situation that hit Indonesia. Any activity is required to follow the health protocol. The purpose of this study is to maximize the implementation of learning by using information and communication technology media in learning and to find the effect of using information and communication technology learning media on learning outcomes. Quantitative research approach, the type of experiment with a quasi-experimental design. This research is located at SDN KIP Maccini with a population of fourth grade students for the 2020/2021 academic year. The sampling technique used purposive sampling, so the sample was 20 students. Data collection techniques: tests, observations and documentation. Analysis technique: Descriptive and inferential statistics, hypothesis test dependent T-Test. The results showed that the use of information and communication technology media in fourth grade students of SDN KIP Maccini, its implementation using information and communication technology media could be said to be well implemented. This can be seen from the activeness of students during the learning process and the implementation of aspects observed through teacher and student observations. The use of information and communication technology media affects the learning outcomes of SDN KIP Maccini .
Making Use of More Reviews Skillfully in Explaninable Recommendation Gerneration

There are a lot of reviews in the Internet, and existing explainable recommendation techniques use them. However, how to use reviews has not been so far adequately addressed. This paper proposes a new exploiting method of reviews in explainable recommendation generation. Our new method makes use of not only reviews written but also those referred to by users. This paper adopts two state-of-the-art explainable recommendation approaches and shows how to apply our method to them. Moreover, our method in this paper considers the possibility of making use of reviews which do not provide detailed review utilization. Our proposal can be applied to different explainable recommendation approaches, which is shown by adopting the two approaches, with reviews that do not necessarily provide their detailed utilization data. The evaluation with using Amazon reviews shows an improvement of the two explainable recommendation approaches. Our proposal is the first attempt to make use of reviews which are written or referred to by users in generating explainable recommendation. Particularly, this study does not suppose that reviews provide their detailed utilization data.
Survey Report on Cloud Security

Cloud computing is an architecture. Cloud DBMS is a distributed database that provides computing service to a group of shared resources namely networks, storage, servers, services and applications through the internet on requirement and pay as you use access without physically acquiring them. For resources, software and information over a network the web infrastructure is shared. The database stored in the cloud can be accessed and computed from anywhere and it is used as a storage location. In this paper I have discussed some of the literature review of cloud, the cloud topics and the papers published by the authors in the appropriate years, the existing methodology used with its drawbacks and proposed methodology with its benefits in which we can improve it in future.
Multi-Instance Pose Networks: Rethinking Top-Down Pose Estimation

A key assumption of top-down human pose estimation approaches is theirexpectation of having a single person/instance present in the input boundingbox. This often leads to failures in crowded scenes with occlusions. We proposea novel solution to overcome the limitations of this fundamental assumption.Our Multi-Instance Pose Network (MIPNet) allows for predicting multiple 2D poseinstances within a given bounding box. We introduce a Multi-Instance ModulationBlock (MIMB) that can adaptively modulate channel-wise feature responses foreach instance and is parameter efficient. We demonstrate the efficacy of ourapproach by evaluating on COCO, CrowdPose, and OCHuman datasets. Specifically,we achieve 70.0 AP on CrowdPose and 42.5 AP on OCHuman test sets, a significantimprovement of 2.4 AP and 6.5 AP over the prior art, respectively. When usingground truth bounding boxes for inference, MIPNet achieves an improvement of0.7 AP on COCO, 0.9 AP on CrowdPose, and 9.1 AP on OCHuman validation setscompared to HRNet. Interestingly, when fewer, high confidence bounding boxesare used, HRNet's performance degrades (by 5 AP) on OCHuman, whereas MIPNetmaintains a relatively stable performance (drop of 1 AP) for the same inputs.
Development of Interactive Learning Media inCharacter Formation Kindergarten

This study aims to determine: (1) The feasibility ofdeveloping interactive learning media with Adobe Flash CS6 onthe character building of Kindergarten. (2) The effectiveness ofusing interactive learning media based on Adobe Flash CS6 incharacter building for Kindergarten. The stages carried out inthis development are the needs analysis stage, the instructionalmedia planning stage and the design stage. This research is adevelopment research developed with the Dick and Careydevelopment model combined with Borg and Gall, involving 40participants who were randomly drawn from children aged 5-6years from two classes of Sint Xaverius Kabanjahe Kindergarten.Validation questionnaires from experts are used to explore thefeasibility of media and character building is developed andtested through the attitudes of children.Data analysis withdescriptive statistics to develop the state of the data. Needsanalysis and hypothesis testing were tested with inferentialstatistics. The analysis requirements with the lilliefors test weremet. The development stage and the testing or validation stage.The results showed (1) The material expert test was very good(92.05%). (2) The qualification of the instructional media experttest is very good (87.15%), (3) the learning design test is verygood (91.25%) (4) The individual test meets the requirements(93.60%), (5) The small group test meets the requirements verygood (92.50%), (6) The qualification of the field test is very good(90.60%). There are differences in character building learningoutcomes using stories and interactive multimedia based onAdobe Flash CS6, which are indicated by significant resultsbetween users of interactive multimedia based on Adobe FlashCS6 and storytelling models. Shown with results 30.05 > 24.50,α = 0.05. The results of hypothesis testing prove that thereis a significant difference, this is indicated by the results of dataprocessing t count = 3.53 at a significant rate = 0.05 t table = 2.57.It was concluded that the interactive multimedia based on AdobeFlash CS6 developed is feasible and effective to improvecharacter building in kindergarten age children
RANCANG BANGUN APLIKASI E-PROPERTI BERBASIS FRAMEWORK CODEIGNITER

The progress of the internet has become the best means to start a property business and it has been proven to be an effective and effective media of information from the internet to disseminate information that is fully accessible to anyone,anytime and anywhere. The great effect on the property business is caused through the internet because only by accessing it from smartphone device and computers at home or in the office of prospective buyers can see property add information.In today’s digital era property sales are mostly done on social media. Social media has many users. But social media has the disadvantages of having to pay if you want to advertise sales, consumers are only users of social media, sales posts quickly sink. In this research, a web-based property sales and leasing information system will be built to cover the shortage.
SOCIAL AND CULTURAL ASPECTS OF FORMING THE CREATIVE THINKING OF MILITARY SERVICES

The article reveals the socio-cultural aspects of the formation of the creative thinking of servicemen. He demonstrates the improvement, improvement and increase in the number of professionals who meet modern requirements and be creative in any field. Important ideas on the formation of the creative thinking of servicemen have been put forward.
Editorial Founding Issue

The Journal of Data Science, Statistics, and Visualisation (JDSSV) is an electronic journal which welcomes contributions to data science, statistics, and visualisation, and in particular, those aspects which link and integrate these subject areas. Articles can cover topics such as machine learning and statistical learning, the visualisation and verbalisation of data, visual analytics, big data infrastructures and analytics, interactive learning, and advanced computing. Articles thatdiscuss two or more research areas of the journal are favoured. Scientific contributions should be of a high standard. Articles should be oriented towards a wide scientific audience of statisticians, data scientists, computer scientists, data analysts, etc. The journal welcomes original contributions that are not being considered for publication elsewhere and contain a high level of novelty. Articles with a thorough but concise review of a certain topic with the potential to provide new insights are also welcome. Manuscripts submitted to the journal generally are accompanied by supplementary material containing software code, data, technical derivations or detailed explanations, additional examples, etc. All submitted material will be reviewed by the assigned associate editor and reviewers of the manuscript.
Kutatási adatkezelést támogató szolgáltatás a Szegedi Tudományegyetemen

Following the national and international trends in mid-2020 the Klebelsberg Kuno Library of the University of Szeged has also started to deal with the issue of research data management. After thorough self-training the library staff studied the Hungarian and international best practices of managing research data. We tried to assess the needs of the institutional research data management habits and the opinion of the researchers of SZTE with a comprehensive questionnaire. We compiled a comprehensive questionnaire to assess the needs of our researchers, learn what they’re thinking about RDM and what kind of practices regarding RDM already exist in the research community. By evaluating the questionnaire we have determined the areas in which the library could provide professional assistance where there was a real need among researchers. Keeping in mind the needs of the research community of University of Szeged we have decided to develop the following services: copyright consulting, RDM trainings for PhD students, theoretical and methodological assistance for RDM, write institutional FAIR data management recommendations. The last four services have been successfully implemented. We also wrote a feasibility study to assess the possibilities of developing our own institutional data repository.
AN ERROR ANALYSIS IN WRITING CAUSE AND EFFECT ESSAY OF THE FOURTH SEMESTER STUDENTS IN PGRI WIRANEGARA UNIVERSITY

Writing is one of the important aspects of language learning. Through writing, students can share much information and idea in the written text. It can help them to think critically and to clarify their thought.Many of the students commonly make grammar mistakes in their learning especially in writing. Because of that the researcher wants to know the frequency of errors found in the writing of cause and effect essay. In analyzing the error, the researcher conducts in Hewings’ theory. The data was analyzed into seven categories, they are errors in using verb groups, in agreement between subject and verb, in article, in preposition, in pluralization, in pronoun, in conjunction. The design of this research is descriptive qualitative. The subjects were the fourth semester students and 37 writings participated to be the subject of this research. The data were documentation of the students’ writing assignment . As a result, the researcher found the total number of errors were 604 items. This study is important to educators who should become aware of the kind of errors. For learners, error analysis is important as it shows the mistakes in their writing.
Behavioral and psychological symptoms in dementia, often reversibile conditions

In the later stages of dementia some people with develops what's known as behavioural and psycological sympotoms of dementia, BSPD. Sympotoms of BPSD can include increased agitation, agression, delusions, hallucinations, sleep disturbance and night-time waking. Behaviour changes could be caused by brain-related issues or from changes to someone's environment, health or medication.
Research on online to offline Mixed Teaching Mode based on rehabilitation Function assessment -- Taking muscle tension assessment as an example

With the development of the Internet, multimedia teaching technology and mature, compared with traditional teaching mode,Online to offline mixed teaching is more suitable for the training needs of rehabilitation therapeutics professionals, therefore, this paper will take the core course "rehabilitation function assessment" offered by the rehabilitation therapeutics specialty of Xi'an Fanyi College as an example,to explore the application of online to offline mixed teaching mode in rehabilitation function assessment.
Absence of Society and Cultivation of Moral Individual——Re-examining Durkheim’s Moral Education

Durkheim attributed French social anomie to a deficiency of collective consciousness. In his view, individuals gained more and more opportunities for free development in the society with the acceleration of social division of labor, making it possible for individuals to achieve free development apart from the society.The key to solve the problem of social anomie is to establish a new moral system to arouse people’s collective consciousness, guide individuals to discard extreme individualism, and cultivate individuals with moral consciousness.Durkheim believed that individuals should have moral consciousness in the general sense: the spirit of discipline, the sense of group attachment and the spirit of autonomy. Durkheim firmly believed that school education was the most effective way to cultivate moral individuals, and teacher authority and school punishment could cultivate children’s respect and obedience to discipline. School environment and teaching content can cultivate students’ attachment to the group, and then rise to the attachment to the society. Science teaching can guide children to use reason to understand society and morality, and eventually train children to be moral individuals who abide by norms and attach to groups and realize rational freedom.
Determining Journal Rank by Applying Particle Swarm Optimization-Naive Bayes Classifier

SCImago Journal Rank (SJR) is one indicator of a journal's reputation. The value is calculated based on several published journals, such as scholarly journals' scientific impact, representing the number of quotes sent to a journal and the relevance or reputation of journals from which the quotations originate. High SJR value means that the corresponding journal has a high reputation. This study aims to approach the SJR classification by implementing a machine learning approach. A simple yet powerful method Naive Bayes Classifier (NBC) is selected. NBC utilizes probability calculations based on Bayes' theorem. However, NBC has an assumption that the attribute values do not depend on each other. This method is optimized using Particle Swarm Optimization (PSO) to overcome this weakness. This study used SJR data of the computer science domain from 2014 to 2017. Publication withaout Q rank is filtered for better performance. As a result, the accuracy of the proposed method is higher than the baseline. The use of PSO significantly improves the NBC performance based on the performed T-test. The PSO-NBC selects four of eight features: H index, Cites/ Doc (2 Years), and Ref. / Doc. Overall results show that using PSO-NBC is closer to SJR rather than using mere NBC.
An Extended Mondrian Algorithm – XMondrian to Protect Identity Disclosure

In recent days, Privacy Preserving Data Publishing (PPDP) is considered as vital research area due to rapid increasing rate of data being published in the Internet day by day. Many Organizations often need to publish their data in internet for research and analysis purpose, but there is no guarantee that those data would be used only for ethical purposes. Hence data anonymization comes into picture and play a vital role in preventing identity disclosure, also it restricts the amount of data that can be seen or used by the external users. It is an extensively used PPDP technique among data encryption, data anonymization and data perturbation methods. Mondrian is considered as one such data anonymization technique that has outperformed compare to many anonymization algorithms, because of its fast and scalable nature. However, the algorithm insists to encode the categorical values into numerical values and decode it, to generalize the data. To overcome this problem, a new extended version of Mondrian algorithm is proposed, and it is called XMondrian algorithm. The proposed algorithm can handle both numerical and categorical attributes without encoding or decoding the categorical values.The effectiveness of the proposed algorithm has been analysed through experimental study and observed that the proposed XMondrian algorithm outshine the existing Mondrian algorithm in terms of anonymization time and Cavg. Cavg is one of the metric used to quantify the utility of data.
Federated Learning approach for SpectralClustering

Spectral clustering is a clustering paradigm that has been shown to be more effective in finding clusters with non-convex shapes than some traditional algorithms such as k-means.However, this algorithm is not directly applicable when the data is naturally distributed in different locations, as it happens in many Internet of Things scenarios.In this work, we propose a distributed spectral clustering to create a cooperative federated model to deal with those cases in which the data is distributed in different sites and with data privacy concerns.We demonstrate that sharing a minimal amount of information allows this distributed version of the spectral clustering to achieve good behavior for clustering several synthetic data sets.
Towards Computational Assessment of Idea Novelty

In crowdsourcing ideation websites, companies can easily collect large amount of ideas. Screening through such volume of ideas is very costly and challenging, necessitating automatic approaches. It would be particularly useful to automatically evaluate idea novelty since companies commonly seek novel ideas. Three computational approaches were tested, based on Latent Semantic Analysis (LSA), Latent Dirichlet Allocation (LDA) and term frequency–inverse document frequency (TF-IDF), respectively. These three approaches were used on three set of ideas and the computed idea novelty was compared with human expert evaluation. TF-IDF based measure correlated better with expert evaluation than the other two measures. However, our results show that these approaches do not match human judgement well enough to replace it.
An application of artificial intelligence for investigating the effect of COVID-19 lockdown on three-dimensional temperature variation in equatorial Africa

We present interesting application of artificial intelligence for investigating effect of the COVID-19 lockdown on 3-dimensional temperature variation across Nigeria (2°-15° E, 4°-14° N), in equatorial Africa. Artificial neural networks were trained to learn time-series temperature variation patterns using radio occultation measurements of atmospheric temperature from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC). Data used for training, validation and testing of the neural networks covered period prior to the lockdown. There was also an investigation into the viability of solar activity indicator (represented by the sunspot number) as an input for the process. The results indicated that including the sunspot number as an input for the training did not improve the network prediction accuracy. The trained network was then used to predict values for the lockdown period. Since the network was trained using pre-lockdown dataset, predictions from the network are regarded as expected temperatures, should there have been no lockdown. By comparing with the actual COSMIC measurements during the lockdown period, effects of the lockdown on atmospheric temperatures were deduced. In overall, the mean altitudinal temperatures rose by about 1.1 °C above expected values during the lockdown. An altitudinal breakdown, at 1 km resolution, reveals that the values were typically below 0.5 °C at most of the altitudes, but exceeded 1 °C at 28 and 29 km altitudes. The temperatures were also observed to drop below expected values at altitudes of 0-2 km, and 17-20 km.
Nighttime image dehazing with a new light segmentation method and a linear image depth estimation model

The predecessor of China Optics was China Optics and Applied Optics Digest, which was founded in 1985. At that time, it was the only retrieval journal in the field of optics in China. At the end of 2008, China Optics and Applied Optics Digest was renamed