Reviewerly/exHarmony huggingface dataset:
Automatic and Intelligent Composition of Pervasive Applications

Opportunistic service composition is a novel and disruptive approach for building software in dynamic and open pervasive environments. It aims to tackle the growing complexity of software design in such environments by dynamically providing relevant applications in the absence of explicit user needs: an intelligent engine composes software components that are present in the pervasive environment in order to build user-tailored context-adapted applications, relying on reinforcement learning. This demonstration presents the current status of our opportunistic composition prototype: the intelligent engine builds pervasive applications in bottom-up mode from actual software components that are discovered via the UPnP (Universal Plug and Play) protocol, taking into account learned user preferences.
Research of active vibration control optimal disposition based on CMQPSO

The adaptive quantum particle swarm optimization algorithm based on cloud model and the multi-island genetic algorithm [15] have obvious advantages in convergence speed to solve the sensor optimization problem, and can effectively achieve global optimization. Due to the installation of sensors and actuators, the electromechanical coupling coefficient of intelligent structures is changed, which affects the vibration energy of structures. In this paper, the reserved energy index of structural vibration control system is taken as the objective optimization function. The position, number, length and control gain of sensors and actuators of active vibration control system are optimized. The adaptive Quantum-behaved Particle Swarm Optimization algorithm in cloud model(CMQPSO) is used as the optimization strategy, and the cantilever beam is taken as an example. This approach is verified its effectiveness and feasibility. It is found that excellent optimization results are obtained.
LVBERT - Latvian BERT

LVBERT is the first publicly available monolingual BERT language model pre-trained for Latvian. For training we used the original implementation of BERT on TensorFlow with the whole-word masking and the next sentence prediction objectives. We used BERT-BASE configuration with 12 layers, 768 hidden units, 12 heads, 128 sequence length, 128 mini-batch size and 32,000 token vocabulary.
The Bitcoin “Consensus” Problems

In discussion about blockchain, the term “consensus” is often used. For example, somebody might explain the blockchain’s function as follows: “It is a data-sharing mechanism where multiple computers form a ‘consensus’ on the validity of the data without relying on a central authority.” The contributors to this book also use the term “consensus;” in this chapter, we take a close look at what it means.
A Framework for Modeling the Semantics of Synchronous and Asynchronous Procedures with Abstract State Machines

We present a framework for modeling the semantics of frequent concepts in the context of procedures and functions. In particular, we consider the concepts of recursive and non-recursive procedures, parameter passing mechanisms, return values, procedures as values (with local and non-local procedures), synchronous and asynchronous procedures, and for the latter, synchronization mechanisms. The concepts are mostly modeled in a combinable manner. Hence the concepts for procedures for many popular programming languages are covered by the framework.
Innovative Instructional Methods Integrating 21st-Century Competencies

Innovative instructional methods integrating 21st century competencies need to be taught strategically by educators in virtual, hybrid, and traditional classroom settings. Several challenges with engaging students in virtual and hybrid environments have emerged. However, findings have indicated that implementing innovative technology tools and teaching methods can enhance student engagement. Addressing students' social-emotional needs before expecting them to master the 21st-century competencies is crucial; therefore, understanding synchronous and asynchronous instructional tools is necessary to enhance student engagement. Because the digital divide among students living in poverty continues to grow during the pandemic, developing global connections is critical. Therefore, high-quality professional development is essential to supporting teachers to become innovators.
Metodologia de formare a valorilor artistice la studenții pedagogi: validarea experimentală

The article addresses the issue of the formation of artistic values in students in the process of choreographic training from different perspectives: general-pedagogical, teleological and methodological. In general-pedagogical plan, the formation of value orientations is analyzed from the perspective of humanistic education, in teleological plan – from the perspective of educational finalities, in methodological plan – from the perspective of new educations and educational strategies: awareness formation, organization of educational action, stimulation. The level of manifestation of the artistic values of the research group indicated a significant difference from the initial testing to the final testing. Experimental validation is stipulated in tables and figures.
Integration Mechanism of Artificial Intelligence Technology Innovation and Commercialization

This paper combs the definition and classification of artificial intelligence. Based on the theory of dynamic capabilities of enterprises, the theory of excellent marketing, and the theory of consumers’ perception of products and value, combined with the characteristics of artificial intelligence technology, the mechanism of the integration of artificial intelligence technology and commercialization is constructed. The mechanism consists of five parts: organizational elements, technological innovation and commercialization integration activities, the results of integration, consumers’ perception of product service brand value and technical environment. This paper analyzes the relationship between the five parts and emphasizes the importance of mastering the market and consumer demand for integration. This paper expounds the management application of the mechanism, and discusses the limitations of the contribution of artificial intelligence to enterprises, as well as the possible privacy and ethical issues.
Calcu card: Developing augmented reality-based learning media on the three-dimensional shapes with curves lesson for junior high school student

Abstract This study aims to: 1) produce Augmented Reality-based Calcu Card learning media on the Three-Dimensional Shapes with Curves lessons that are valid, practical, and effective, 2) test the suitability of applying the learning media to determine the application effect. The subjects of study were 9 th Grade Student of SMP Pesantren Guppi Samata. The development model was using the PIE development model or plan, implement, and evaluate. Meanwhile, the data to be collected were in the form of questionnaires and learning outcomes tests. This research was carried out in 2 ways, namely first a small-scale test for the 9 th Grade Student, then a large-scale test for 9 th Grade Student of SMP Pesantren Guppi Samata, they were 20 students. The results showed that the average validator’s assessment of the Calcu Card application was 3.25. Based on the student assessment, it can be obtained that the average response of students through a questionnaire to the Calcu Card application was 3.19. Furthermore, the percentage of students ‘completeness was 75% while the percentage of students’ incompleteness was 25%. Therefore, it can be concluded that the Augmented Reality-based Calcu Card learning media is suitable for 9 th Grade Student of SMP Guppi Samata by meeting the criteria of validity, practicality, and effectiveness.
Jaringan Syaraf Tiruan Memprediksi Kebutuhan Alat Suntik Medis di Rumah Sakit Menggunakan Metode Backpropagation

The hospital is an integral part of a social and health organization with the function of providing services, disease healing and disease prevention to the community. Predicting the number of medical devices is essential for managing a hospital, managing human and financial resources, and for properly distributing material resources. If the number of medical devices can be predicted accurately, this will become the basis for planning and making decisions for hospital managers. Based on these reasons, an electronic tool is needed that can determine the number of medical device needs with a high degree of accuracy and the display of the results for easy reading and data collection. From system testing, the need for medical devices in the following month will decrease in providing some medical devices because they still have a lot of stock in the previous month. The Backpropagation Algorithm can carry out the prediction process, but whether or not the error value and the output is very much influenced by the determination of parameters such as the amount of learning rate and the number of neurons in the hidden layer.
A Bottom-Up Approach for Feature Model Extraction from Business Process Models

Service-oriented architecture (SOA) enables the identification of services aligned with business process (BP) and the ability to address multiple execution environments. However, SOA lacks on support for high customization and systematic planned reuse. This problem prompted the search for combining SOA with software product lines (SPL). Therefore, SPL can be used to help SOA, more specially in business process model (BPM), to achieve benefits such as productivity gains, decreased development costs and effort and improved time to market segment needs. It helps to manage service component bundles dynamically according to identified commonalities and variabilities. In this paper, we present our approach to manage the variability in SOA by extracting feature model from different business process models.
Design and implementation of keycode encryption for electric door lock embedded system using cryptography algorithm

Abstract In this digital era the usage of locks is no longer only relies on traditional key systems, but also relies on usage of electronic sensors that can improve security system. Now the threat to keyless locking system does not only come from physical sources but also come from non-physical or digital sources. This treat can be prevented by using cryptography to hide digital data in the system. In this research utilizing a raspberry pi and a servo motor as a locking device, a web server as a data storage center, a mobile device software application as a user interface. Raspberry pi is a mini computer that can be used for various needs. The password will be sent over internet from mobile device to web server and raspberry pi will give a command to the servo to unlock and lock. This study will compare between combination of RSA, 3DES, AES 128 bit, and 256bit AES algorithms to obtain an algorithm that could be operated optimally on the system based on encryption and decryption speed. The final result of this study is a method to implement cryptographic algorithms on smart key systems to obtain better security.
Document Fragments Restoration via Similarity Measurement

The automatic restoration technology of shredded paper is an important branch in computer science. It plays an important role in judicial evidence restoration, the restoration of secret documents, and many other areas. In this article, we establish a similarity measurement model by data mining. This article mainly focuses on Chinese text files with regular cutting. The mathematic model is established and used for restoration, we provide several measurements to achieve the restoration and reduce the workload of manual intervention. At the same time, this article provides a way to restore two-side printing shredded documents. This paper gives experimental results that prove the effectiveness of the proposed method.
A Framework of Web Mining Algorithm-Based Hidden Pattern in India E-Government Application Using Blockchain Technology

Purpose: The Indian Government should be analyzing these problems and organized a special team who has responsibility for all inquiry and reduced these types of problem and India’s Government should be informed about new health projects to people by public relations or advertising. Now, with the advent of data analysis techniques and tools, this process of finding patterns in the behavior of applications can be taken to a next higher level. The methods and algorithms used exclusively in data mining for medical purposes are known as Medical Data Mining. Many studies in the fields of e-government implementation in developed countries are available, but there are not many studies available in India. There is no underlying explanation why considerations apply to the electronic government's introduction, which contributes to a hole in the written audit. The knowledge is hidden among government data set and it is extractable through data mining techniques. The relevant and unchanging design of blockchain technologies could be used to accelerate constant progress to open and distributed energy frameworks and to tackle some problems facing the company. Design/Methodology/Approach: Design &amp; Implementing the theoretical concept of blockchain is an increasing technology which is seen by many inhabitants as a fundamental weakness because of the general obscurity of the complexities and chances of its execution. Findings/Result: Although the study being conducted on the thorough analysis of e-government results, various questions relating to data collection and methodologies for analyzing these data are yet to be addressed by the potential researchers. Originality/Value: Huge data analysis will open up options for developing market intelligence to increase the usage and personalization of e-governments. Paper Type: Conceptual Research Review.
Structure-Oriented Progressive Low-Rank Image Restoration for Defending Adversarial Attacks

Deep neural networks recognize objects by analyzing local image details and summarizing their information along the inference layers to derive the final decision. Because of this, they are prone to adversarial attacks. On the other hand, human eyes recognize objects based on their global structures and semantic cues, instead of local image textures. In this work, we propose to develop a structure-oriented progressive low-rank image completion method to remove unneeded texture details from the input images and shift the bias of deep neural networks towards global object structures and semantic cues. We formulate the problem into a low-rank matrix completion problem with progressively smoothed rank functions to avoid local minimums. Our experimental results demonstrate the proposed method is able to successfully remove the insignificant local image details while preserving important global object structures.
A White-Box Implementation of IDEA

IDEA is a classic symmetric encryption algorithm proposed in 1991 and widely used in many applications. However, there is little research into white-box IDEA. In traditional white-box implementations of existing block ciphers, S-boxes are always converted into encoded lookup tables. However, the algebraic operations of IDEA without S-boxes, make the implementation not straight forward and challenging. We propose a white-box implementation of IDEA by applying a splitting symmetric encryption method, and verify its security against algebraic analysis and BGE-like attacks. Our white-box implementation requires an average of about 2800 ms to encrypt a 64-bit plaintext, about 60 times more than the original algorithm would take, which is acceptable for practical applications. Its storage requirements are only about 10 MB. To our knowledge, this is the first public white-box IDEA solution, and its design by splitting can be applied to similar algebraic encryption structures.
Changes in the Operation Mode of Real Estate Investment Trusts in the Era of Big Data

With the continuous maturity of big data technology, the application field of big data has also been greatly expanded. In recent years, the technical advantages of big data technology in the real estate investment trust industry have been gradually demonstrated, which not only optimizes the traditional operation mode, but also strengthens the operation ability of enterprises. However, the mode is still in the primary stage of development, and there are still many deficiencies. Therefore, this paper puts forward the research on the change of real estate investment trust operation mode in the era of big data. This paper makes an in-depth investigation on the operation mode of real estate investment trust under the background of big data, analyzes the main problems existing in the current mode and the advantages and disadvantages of different types of REITs operation mode. In view of these problems and deficiencies, this paper further puts forward the optimization and improvement measures, and combined with the needs of enterprises, makes the path selection analysis of the development of REITs operation mode in China. In order to further investigate the actual effect of real estate investment trust operation mode based on big data technology in the actual operation of enterprises; this paper takes enterprise A as an example for investigation and research. Through the analysis of the survey results, we can see that the operation mode based on big data technology effectively broadens the financing channels of enterprises and avoids the problems such as performance decline.
LODQuMa: A Free-ontology process for Linked (Open) Data quality management

For many years, data quality is among the most commonly discussed issue in Linked Open Data (LOD) due to the huge volume of integrated datasets that are usually heterogeneous. Several ontology-based approaches dealing with quality problems have been proposed. However, when datasets lack a well-defined schema, these approaches become ineffective because of the lack of metadata. Moreover, the detection of quality problems based on an analysis between RDF (Resource Description Framework) triples without requiring ontology statistical and semantical information is not addressed. Keeping in mind that ontologies are not always available and they may be incomplete or misused. In this paper, a novel free-ontology process called LODQuMa is proposed to assess and improve the quality of LOD. It is mainly based on profiling statistics, synonym relationships between predicates, QVCs (Quality Verification Cases), and SPARQL (SPARQL Protocol and RDF Query Language) query templates. Experiments on the DBpedia dataset demonstrate that the proposed process is effective for increasing the intrinsic quality dimensions, resulting in correct and compact datasets.
Analysis of Students’ Responses in PBL Class with Design Thinking

Project Based Learning has a good compatibility with manufacturing courses, and increase the range of degrees of completion that can be achieved and the sense of accomplishment of the students by incorporating a problem-finding element. Thus, we considered and implemented a PBL course to learn the product development process incorporating design thinking. In the first report, the educational effects were confirmed by the results of the implementation and the analysis of the students’ responses. In this paper, we checked how the students’ attitude toward the project changed over throughout a year by questionnaires. Three types of questionnaires were used, one is a signed questionnaire, an anonymous questionnaire, and a psychological test. From these analyses, it was confirmed that success and failure experiences in exercises lead to motivation. On the other hand, negative emotions were also found to be caused by environmental factors.
Research on the Construction of College English Teaching Platform and Teaching Mode Based on Demand Analysis

In modern college English teaching, we usually use a top-down teaching model. This neglects the feelings and needs of college students in learning English, which makes them less motivated or unable to apply what they have learned. Because of this, the construction of a college English teaching platform based on needs analysis can give full play to its role, based on the combination of its teaching platform and its traditional teaching methods, and seek new teaching models. This article is based on demand analysis theory. The test was conducted with 300 English majors from two applied technology-based universities in the east coast and used questionnaires to investigate their English needs. This study uses questionnaires to investigate the needs of English curriculum settings and English learning goals. , English learning extracurricular needs, English learning tools, English learning strategies, English classroom teaching models and methods, English curriculum evaluation system needs, etc. The results show that it is necessary to set up college English courses, but the teaching method is single, student participation is low, and the courses cannot meet their needs. The demand for professional English is significantly higher than academic English.
The validation of traditional knowledge to harvest sustainably the Udono reed materials for rozetsu of hichiriki

The objective of this study is to validate the traditional knowledge of reeds for the hichiriki (traditional Japanese oboe) harvested from the Udono reed field. Hichiriki is one of main instruments in gagaku (Japanese imperial court music). The reeds at the Udono reed field in Osaka is used for high quality rozetsu (vibrating plate) for hichiriki. The reeds for hichiriki was selected not in the water area but in the land area for larger stem diameter and thicker flesh. It was found the area, for harvesting the reeds for hichiriki, has soft soil and can develop rhizomes to deep underground in comparison to other land area. It is shown that harvesters, with their long time experiences and skills, can select the most efficient places to harvest the best reeds. Therefore, it seems passing down the skill of harvesters contributing to the cultural continuation of gagaku which is an important intangible cultural property.
Teacher and Student Perceptions: Do Students Have Good Reading Motivation?

Reading requires students’ efforts: they may choose not to do this activity, so motivation has an important role. Motivation and attitudes toward reading are central to reading performance. Therefore, this study aims to analyze the perceptions of students and teachers on reading motivation at the elementary school level. A quantitative approach with the survey method was employed. The survey was conducted during learning in the Bahasa class. The data were collected from 106 third-grade students and 4 Bahasa teachers in Bandar Lampung, Indonesia, using the Motivations for Reading Questionnaire and Teacher Questionnaire on Student Motivation to Read (3 rd Ed.). The data were then analyzed using descriptive and quantitative intercorrelation techniques. It is known that, in general, the students are interested in reading activities where the most influential aspects are awareness of the importance of reading and competition among students when the teacher gives reading tasks. Teachers' perceptions regarding the dimensions of reading motivation show that the individual dimension is the most crucial factor to be improved. This factor is directly related to each student's intrinsic motivation, positively correlated with reading achievement. Appropriate environmental conditioning and learning strategies can be carried out to stimulate students' intrinsic motivation in reading, such as carrying out a hands-on activity related to the student's real-life before working on reading tasks. It is implied that the findings of this study can be a reference for teachers to create a teaching system that can foster students' reading interest. Keywords: reading motivation, intrinsic motivation, teachers’ perception, elementary students.