Reviewerly/exHarmony huggingface dataset:
An Adaptive Multi-channel Feature-fusion Model for Polyp Classification

Extracting effective texture features from computed tomographic colonography (CTC) and merging them to form a much powerful descriptor are two critical challenges in computer-aided detection (CADe) and diagnosis (CADx). In this paper, we introduce multi-scaling analysis into grey level co-occurrence matrix (GLCM) to construct texture features from different image domains, i.e. intensity, gradient and curvature. Thus, nine texture descriptors are generated and form a descriptor pool sorted by AUC (area under the curve of receiver operating characteristics) scores. Then an adaptive feature merging method is designed and implemented in a binary tree framework where every layer consists of two nodes, i.e. the baseline descriptor and its complement which are always the first two descriptors in the descriptor pool. Their merging will be performed using forward stepwise method where some complementary variables with gains in classification are preserved. After feature merging, the descriptor pool will be updated by removing the two candidates and adding the new baseline descriptor. This procedure will be performed iteratively until the final descriptor is obtained. Obviously, this is a greedy procedure which guarantees the monotonicity of the classification. Experimental outcomes testify the effectiveness of this method and the proposed method outperforms the pre-merging descriptor over 4% by AUC scores.
Facial expression recognition in videos

Facial expression recognition is considered as the most effective, naturally distinguished way for humans to communicate emotions, express their feelings, to clarify and emphasis and more generally to regulate interactions with other people. From the psychology point of view, remarkable effort have been made to realize how humans interpret and perceive facial expressions in term of mental models of emotions and effective states.Over the past decade, we have witnessed extensive progress in machine learning and human computer interactions. Those progresses and the importance of Facial Expression Recognition in a number of applications in areas such as human computer interaction, multimedia communication, robotics and video surveillance, draw a lot of attention in computer vision community to utilise existing massive calculation tools and technologies to design algorithms in which humans interact with computers in a novel way.As this domain is still a challenging problem due to the complexity of movements of face components and temporal variations of expressions, in this research, our goal is to present a model that is able to fully model the temporal information as well as appearance features for recognizing six basic emotions (happy, sadness, anger, fear, surprise, disgust). Since lack of data is major problem in the area of computer vision and machine learning, we study methods to overcome this challenge. We show how the large data requirements for deep learning can be alleviated using synthetic data focusing on facial expression recognition problem. We investigate the use of synthetic facial expression data to circumvent the large data requirements and report on the effects of this approach for deep learning based expression recognition.For efficient and effective learning process we have implemented and performed extensive experiments on different well-known algorithms and models including, LBP TOP, Support vector machines, 3D neural networks and Recurrent neural networks. We evaluate and compare our methods on different publicly available datasets where the performances, merits and demerits are discussed and showed.
Flocking based trust management for cloud security

- Experiencing cloud in distributed environment provides ease of access and also creates major challenge due to thelow down ratio of trust factors which includes three elements like Privacy, Confidentiality and Security[1]. Managing ofdistributed environment is highly challenging task for service level at consumer and provider end. The attraction towardscloud services as increased vibrantly around the globe to fume up guaranteed services. The establishment of service levelagreement between all the stakes of cloud management lack in communication due to aggregation knowledge ofheterogeneity between different entities. Quality of Service and Security usually depends on the adaptability of the system tothe heterogeneity which is a common factor in conventional system. This paper proposes the security management inheterogenic system scales up the trust factors by considering flock procedure ( idea driven by birds flock) technique as oneof the criteria which drives for consumer and provider related actions underneath to cloud management in positive factorsand integrating the K-factor at data sets for grouping similar sets. Later comparing the trust thresholds of consumer andproviders with the proposed procedure
PELATIHAN PEMBUATAN CLOUD STORAGE MENGGUNAKAN OWNCLOUD X DI UBUNTU SERVER PADA SISWA SMK MULTI KARYA MEDAN

The purpose of the Workshop on Creating Cloud Storage using OwnCloud X on Ubuntu Server is to increase insight and knowledge to participants who come from students of SMK Multi Karya Medan.Ubuntu Server and Cloud Computing is a discussion that is often discussed at this time. From the results of the training, participants have been able to install their own Ubuntu Server, Web Server, PHP and Create OwnCloud.
Internet Chat as ‘Jargon’

The process of net communication, which is internet dependent, takes place among millions of individual (private) or group of participants sharing the same room in order to comment, discuss, or pass time .While the communicators are of different countries, cultures, backgrounds, and languages they exchange their thoughts and linguistic messages throughout this experience which is termed as “Internet Chatting”. The researcher presents the definition of “Jargon” and “Chatting” in addition to the related terms .He submits the structure of morphemes / words, phrases , and sentences in chatting in addition to how the chatters manipulate parts of words, abbreviations, numerals, emoticons…etc. in order to carry out this experience. The researcher, after analyzing the presented examples in the obtained data, concludes that the chatting process can be regarded as a sort of ‘Jargon’. Thus the hypothesis of the study is affirmed.
Implementation of Data Stream Classification Neural Network Models Over Big Data Platforms

Streaming is being increasingly demanded because it helps in analyzing data in real-time and in decision making. Over time, the number of existing devices increases continuously, generating a huge amount of data. Processing this data with traditional algorithms is impractical, so it is necessary to apply distributed algorithms in a Big Data context. In this paper, Apache Spark is used to implement some distributed versions of algorithms based on Extreme Learning Machine (ELM). In addition, these algorithms are evaluated with different real and synthetic datasets by performing two experiments. The first one tries to demonstrate that the performance of the distributed algorithms is the same as that of the sequential versions. The second experiment is a study about the behaviour of the algorithms in the presence of concept drift, an important research area within streaming.
Building a Global Information Security System for the Future: New Angles

The year 2020 made it abundantly clear that the world is firmly and apparently immutably digitalized. All countries, regardless of their level of political, military, socioeconomic, and technological development, use information and communications technologies (ICTs) in various fields. But governments are certainly not the only users of ICTs. Companies, research and educational institutions, nongovernmental organizations, and civil society have swiftly adapted their work to the virtual format. It is convenient, accessible, and during the COVID-19 pandemic, often the only possible format. It would not be an exaggeration to say that the digital space has become a familiar habitat for most of the world's population. But due to the scale of their use, ICTs create global threats if they are abused. This makes information security a decisive factor in global social development and thus a key item on today's global agenda. Discussing international information security is not just a current trend but an urgent need in the new reality.
ТЕНДЕНЦИИ РАЗВИТИЯ ФОНДОВ БИБЛИОТЕК СИБИРСКОГО ОТДЕЛЕНИЯ РОССИЙСКОЙ АКАДЕМИИ НАУК В УСЛОВИЯХ ТРАНСФОРМАЦИИ СИСТЕМЫ УПРАВЛЕНИЯ НАУЧНЫМИ УЧРЕЖДЕНИЯМИ

Academic libraries in the region are organized according to the territorial and departmental principles as components of variously directed in their activities scientific centers of the Siberian Branch of the Russian Academy of Sciences (SB RAS). In the context of transformation of institutional management system, it is important to proceed with information and methodical support, rendered by SPSL SB RAS to SB RAS libraries. Besides, information support of educational and scientific interests of scholars and specialists needs higher level of integration of resources and service technologies for academic, university and regional scientific libraries, and this direction requires comprehension on the part of the library community.
Deep Learning Technology in Data Information System

With the development of data processing technology, data processing and analysis have become a problem that must be faced today.The deep learning technology is composed of a feedforward neural network, and the model nodes form a layer of association relationships.This paper studies the processing efficiency, accuracy and error of the network model based on deep learning technology.The segmentation statistics of language data by different models are studied separately, and the delay and total processing time of a large number of file data processing in the information system are studied.As the number of deep learning model node nodes increases, the data processing time will be greatly reduced.When processing the same amount of data, small data files will consume more time.With the expansion of the cluster, task allocation and data transmission will consume part of the system resources and time, but as the scale of data increases, the system processing capabilities gradually appear, and the average processing delay gradually decreases.
Wrist Dorsal Sensor Array for Finger Movement Recognition

Hu proposed a method that recognizes finger movements by detecting wrist muscles for human-computer interaction (HCI).Considering human habits and aesthetics, the sensor is placed on the back of the wrist.We first designed a polyvinylidene fluoride (PVDF) piezoelectric thin-film sensor unit with a planar elastic substrate.By studying the effects of the hardness and thickness of the substrate, we designed the sensor unit to have a Shore-A hardness of 23 and a thickness of 2 mm.Then we constructed a 4 × 2 sensor matrix with a size of 25 × 15 mm 2 .To build a finger movement dataset, we collected wrist dorsal movement signals when the fingers moved using the sensor matrix.Then we used a four-layer back-propagation (BP) neural network to recognize the finger movements.We experimentally demonstrated that even on the dorsal wrist side, finger movements could be recognized.The recognition rate of the general model using mixed personal data was 79%.In comparison, the recognition rate of the individual model using personal data was 94%.
Development And Construction Of Language Arts Module Based On Entertained Education Approach Using Method Fuzzy Delphi (Fdm)

The entertaining educator approach introduced in language arts skills is aimed at creating a teaching and learning environment that is entertaining, fun, addictive and able to attract students to follow the learning. Thus, the study of the development of language arts modules based on the entertainment education approach in primary schools aims to diversify methods and strategies in teaching and learning to create a fun learning climate for students. The development of this language arts module is based on Jean Piaget's Theory of Cognitive Constructivism and Lev Vygotsky's Theory of Social Constructivism. The research methodology used is to combine descriptive qualitative method and Fuzzy Delphi Method (FDM) to obtain expert consensus (agreement). Information was collected through interviews, observations, questionnaires and document analysis. Study participants consisted of five students in three and 10 teachers specializing in the subject of Bahasa Melayu in SK A as the main respondents in the study. The findings of the study analyzed by FDM show that the language arts module based on entertainment education has a positive impact on teachers' teaching as well as student learning and is suitable for use. Pupils are more interested and enjoy learning in the classroom. The implication of this study is that students become more fun and interested in learning, understanding, expressing and appreciating language through fun learning through acting, storytelling, singing, poetry and language games. In conclusion, this language arts module successfully creates an atmosphere and learning style. which relaxes and entertains students in the classroom as well as being a guide to teachers in diversifying fun PdP methods and techniques.
Estilos de Aprendizaje en Ingeniería Como Apoyo en la (Estrategia de) Planificación de Clases Virtuales [Not available in English]

Learning styles are crucial during the whole process of teaching learning and especially for the curricula. In the case of teachers of engineering it could be common to notice that the student’s profile differs with the professional’s profile and for this reason, it is very important to know the learning styles of the group. So, teachers should take into account the different learning styles and mostly, apply it in their strategies in order to achieve their goal. In this sense, it is required that teachers plan and design active and modern methodologies in order to motivate students during their professional path.During 2020, the career Ingenieria en Sistemas de Informacion from Universidad de la Cuenca del Plata have been working with his students to know their learning styles in order to help the planification of the teachers. This paper shows the first results in relation with the predominant styles of the students in each level of the career.
PENGEMBANGAN MEDIA PEMBELAJARAN INTERAKTIF BERBASIS ANDROID MATERI SEJARAH PERGERAKAN SMA DI LAMPUNG

The purpose of this development is to develop an Android-based intractive learning media using iSpring Suite 8 which is feasible and practical when used. The method used in this research is 4-D which consists of the define stage, the design stage, the development stage and the dissemination stage. The datacollection instrument was in the form of a questionnaire, consisting of an expert validation questionnaire and a student response questionnaire. Data analysis techniques used in this study included several steps, namely data analysis, data tabulation, and interpreting the percentage of the questionnaire. The validationresults obtained from the development of the developed learning media are stated to be very feasible with a percentage. The validation of media experts got 86% results and material expert validations got 84% results, and the average was 85%. The results of the small group trial were stated to be practical with a result of 80%. Based on the predetermined criteria, the development of androd-based intractive learning media is declared feasible and practical.Keywords: instructional media, interactive media, history of movement in Lampung.
Initial Coin Offerings, Corporate Finance and Financial Regulation

Initial Coin Offerings (ICOs) have grown substantially in recent years. They involve issuing coins that are recorded on a block-chain. These can be used to purchase the service or good that the firm they finance produces. The coins can be exchanged for currency on cryptocurrency exchanges. Although many ICOs are fraudulent, most studies find positive average and median returns. Theoretical analyses suggest they can have several advantages compared to Initial Public Offerings (IPOs). They are regulated in widely differing ways with the UK, Switzerland and Singapore having regimes that make them easier to undertake than other countries.
The rediscovery hypothesis: Language models need to meet linguistics

There is an ongoing debate in the NLP community whether modern language models contain linguistic knowledge, recovered through so-called \textit{probes}. In this paper we study whether linguistic knowledge is a necessary condition for good performance of modern language models, which we call the \textit{rediscovery hypothesis}. In the first place we show that language models that are significantly compressed but perform well on their pretraining objectives retain good scores when probed for linguistic structures. This result supports the rediscovery hypothesis and leads to the second contribution of our paper: an information-theoretic framework that relates language modeling objective with linguistic information. This framework also provides a metric to measure the impact of linguistic information on the word prediction task. We reinforce our analytical results with various experiments, both on synthetic and on real tasks.
Differences in Conventional Learning with E-learning: Muhamad Sholeh muhamadsholeh@unesa.ac.id Lecturer in Education Management Department, Faculty of Education, Universitas Negeri Surabaya

Educational management, also sometimes known as educational administration, is commonly associated with elementary and secondary schools as well as institutes of higher learning like colleges and universities. Education management professionals can also be found working in governmental agencies, private companies, and not-for-profit organizations.Those working in educational management might develop education policy, conduct research, or consult to help evaluate and develop ways to enrich and enhance the educational system at all levels. Most educational management professionals have earned at least a master's degree and many are licensed teachers or principals.To improve a quality education, we need to manage the education system from conventional learning to e-learning, which can provide convenience in educating students, so that independent learning can create innovation and creativities.Learning is basically the process of adding information and abilities, when thinking about what information and competencies are meant by students, then at that moment we should think about what strategies should be done so that all of them can be achieved effectively and efficiently.This is very important for every teacher to understand, because what must be achieved will determine how to achieve it. A teacher is required to master the learning methods that he does will be able to provide added value for his students. If so far the method of learning is done face to face directly (conventional), but in an era of globalization like this requires educators to use methods that are more effective and efficient. This method is then called the online learning method.
More Linear Models in R!

Abstract Chapter 6 continues exploring the world of statistics that are covered within the linear model, namely two-way and three-way ANOVA, linear regression and analysis of covariance (ANCOVA). In each type of model, a detailed description of how to interpret the summary output is undertaken, including understanding how to interpret and plot interactions. Conducting post-hoc analyses and using the predict() function are also covered. The chapter ends by reinforcing earlier plotting skills in ggplot2 by walking through an example of making a professional looking figure with multiple non-linear regression curves and confidence intervals.
Pengaruh Kecerdasan Emosional terhadap Prestasi Belajar pada Mata Pelajaran Ilmu Pengetahuan Sosial Siswa Kelas VIII SMPN 17 Kota Bekasi

The corona virus disease pandemic has not only had an impact on the world of health and the economy, but also the world of education. Face-to-face learning activities in schools have been temporarily suspended and replaced with School from home (SFH). This has an impact on the emotional intelligence of students during learning at home (Shool From Home). This research has a function to determine whether there is Emotional Intelligence in the learning achievement of 8th graders (Eighth) in social science subjects at SMPN 17 Bekasi. The research method used in this study is descriptive regression, which is a solution model that seeks the influence of one or more variables. With its variable characteristics, namely the independent variable and the dependent variable. Problem solving in this study uses a quantitative approach that uses statistical tests with the steps of data collection, classification, analysis and data management and making these conclusions. Emotional Intelligence (EQ) is so important in the world of education today, because it affects the achievement and progress of student achievement. Emotional intelligence is a person's ability to manage his emotional life with intelligence (to manage our emotional life with intelligence) maintain emotional harmony and express (the appropriateness of emotion and its pression) through mental awareness skills, mental motivation, empathy, and social skills. Based on the results of research using SPSS (Statistical Product Service Solution) it is known that the multiple linear regression equation is: Y = 59.474 + 0.325 X, so it can be concluded that the hypothesis (Ha) is accepted, the evidence is that there is an influence of emotional intelligence on learning achievement. From the regression equation, it can be interpreted that the regression of 59.474 student achievement (Y) is influenced by an increase in emotional intelligence (X) of 0.325.
Sistem Pendukung Keputusan Pemilihan Konten Lokal Terbaik Menerapkan Metode Moosra (Studi Kasus: Komisi Penyiaran Indonesia)

Decision support system as a computer-based system consisting of components including language system components, knowledge system components and problem processing system components that interact with one another, which helps decision making through the use of data and decision models to solve semi-structured and unstructured problems. This study uses the Moosra Method in Selecting the Best Local Content based on criteria by using a formula which results are more accurate and right on target. In it also all data are combined into one with the weight of the assessment that has been obtained through an assessment of the test results. The research conducted is to create a system that can provide consideration in making decisions for the selection of the best local content.